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Intro Data Analysis Project: baseball database
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.gridspec as gridspec # figure layout for multiple plots\n",
"import statsmodels.formula.api as sm # statistical package\n",
"from __future__ import division # assume division is always boolean, handy as lots of baseball stats are integers\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"master = pd.read_csv('Master.csv') # contains all data for all players.\n",
"batting = pd.read_csv('Batting.csv') # contains batting data\n",
"pitching = pd.read_csv('Pitching.csv')\n",
"fielding = pd.read_csv('Fielding.csv')\n",
"teams = pd.read_csv('Teams.csv') # contains team data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Baseball Analysis\n",
"The [Sean Lahman database](http://www.seanlahman.com/baseball-archive/statistics/) is a very extensive baseball database that has statistics on players, team, and much more ranging from 1871 to 2015. In total there are 24 databases linked by various IDs: playerID, teamID, yearID, lgID, franchiseID, etc. You can think of countless ideas to look into with this database. I will come back later to my choices. All the data comes from MLB.\n",
"\n",
"This project is to show introductory level data analysis using python. Only the datasets are provided, and general guidelines for the project (contact me if you want to know more). The questions and research topics discussed are of my own choice. A rough outline of the guidelines is to provide show code functionality, datawrangling (cleaning & extracting data), analysis (research question, computations), exploration (multiple angles, 1 and 2 variables), conclusion (discussing results, limitations, statistics).\n",
"\n",
"To run the notebook yourself, download it, as well as the .csv version of the Lahman database. Run the notebook in the same folder. To be able to run Ipython notebooks, the easiest way is to go to download Anaconda from [continuum.io](https://www.continuum.io/). \n",
"\n",
"For data analysis I'll be using python, specifically pandas. Pandas is a module that gives the ability to work with large datasets, merge tables, and especially to efficiently do complicated calculations by combining grouping and applying functions. Pandas has series (1D data) and dataframes (2D data) objects that also profit from versatile indexing and filtering options that you can get from python lists and dictionaries. For older records, not all data is present, pandas has great functionality to handle incomplete data. For example plotting ignores any NaN values as well as many build in functions either ignore missing values, or you can specify how it deals with these values. In short pandas is the way to go.\n",
"\n",
"As I come from Europe, my knowledge about baseball is non-existant, so the statistical side of baseball is quite daunting to start with if you barely even know how the game is played. So I started with some more general exploration of the data, calculating the career length of baseball players (comparing different methods) and studying team size (more technical use of pandas functionality). Afterward I dip my toe into some team statistics, batting specifically, to understand what statistics correlate well with offensive capability of a team (exploring two variables at the same time, linear regression)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Career Length"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Professional sports careers are usually of quite short duration due to high competitiveness and high physical demands (you might argue otherwise nowadays compared to 10 years ago though). So how long do baseball career last? Below I discuss two methods to calculate the career length.\n",
"\n",
"#### Using debut and final Game\n",
"To calculate the career length we take the finalGame data and subtract the debut date. As these dates are the first and last game the player played in MLB it gives an estimate of his professional career. \n",
"\n",
"But, as it only takes into account first and final appearance, this can include long periods of not playing full-time. As is the case for the maximum of a bit over 35 years from [Nick Altrock](http://www.baseball-reference.com/players/a/altroni01.shtml).\n",
"\n",
"#### Using seasons played\n",
"One could also look at the number of seasons played. This can be done by looking at the batting table (contains player, team, season ID data). By grouping the records per player and counting the number of records one gets the amount of seasons played.\n",
"\n",
"However, players can switch teams mid season, this will lead in counting one season played as 2 seasons (due to 2 records for the player for that year). Removing these records can be done by finding the duplicated records of (playerID and yearID).\n",
"\n",
"#### cleaning the data\n",
"For the first method only the master table is needed. This one contains all player information: ID, name, brithdate, debutgame, and final game (and more).\n",
"- Change string data to datetime object.\n",
"- Correct record of [Theodore Charles Menze](http://www.baseball-reference.com/players/m/menzete01.shtml): final and debut date were mixed up.\n",
"- Account for 193 records of players without final and debut game.\n",
"\n",
"The datetime object allows easy use of dates doing computations, for instance to find the difference in days you just subtract the two dates. \n",
"\n",
"To check why some players did not have a debut and final game listed I looked at [Manuel Elias Acta](https://en.wikipedia.org/wiki/Manny_Acta). He did not play any MLB matches, but was a coach. All the records miss both dates, so a good explanation is that these people played a role in MLB, but not as players (either coaches or managers for example). "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" nameLast nameGiven birthYear debut finalGame\n",
"11360 Menze Theodore Charles 1897 1918-04-27 1918-04-23\n",
"corrected record:\n",
"nameLast Menze\n",
"nameGiven Theodore Charles\n",
"birthYear 1897\n",
"debut 1918-04-23 00:00:00\n",
"finalGame 1918-04-27 00:00:00\n",
"Name: 11360, dtype: object\n",
"total missing debut:193\n",
"total missing finalGame:193\n",
"193\n",
" playerID birthYear birthMonth birthDay birthCountry \\\n",
"55 actama99 1969 1 11 D.R. \n",
"\n",
" birthState birthCity deathYear deathMonth \\\n",
"55 San Pedro de Macoris San Pedro de Macoris NaN NaN \n",
"\n",
" deathDay ... nameLast nameGiven weight height bats throws \\\n",
"55 NaN ... Acta Manuel Elias 172 74 R R \n",
"\n",
" debut finalGame retroID bbrefID \n",
"55 NaT NaT actam801 actama99 \n",
"\n",
"[1 rows x 24 columns]\n"
]
}
],
"source": [
"# cast date strings to datetime objects\n",
"master['debut'] = pd.to_datetime(master['debut'])\n",
"master['finalGame'] = pd.to_datetime(master['finalGame'])\n",
"\n",
"# apparently one person has debut and finalGame interchanged! If statement to make sure don't accidentally undo change\n",
"if (master.debut > master.finalGame).sum() > 0:\n",
" print master[['nameLast','nameGiven','birthYear','debut', 'finalGame']][(master.debut > master.finalGame)] \n",
" master.ix[11360,['debut','finalGame']] = master.finalGame[11360], master.debut[11360]\n",
" print \"corrected record:\"\n",
" print master.ix[11360,['nameLast','nameGiven','birthYear','debut', 'finalGame']]\n",
"else:\n",
" print 'correction already done'\n",
"\n",
"# accounting for missing records of debut and final game:\n",
"print 'total missing debut:{}'.format(len(master.debut)- master.debut.count())\n",
"print 'total missing finalGame:{}'.format(len(master.finalGame) - master.finalGame.count())\n",
"# Same number of records, also of the same index:\n",
"print (master.finalGame[~pd.notnull(master.finalGame)].index == master.debut[~pd.notnull(master.debut)].index).sum()\n",
"# Example: Manuel Elias Acta, coach, but has no machted in MLB\n",
"print master.ix[~pd.notnull(master.debut)].head(1) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Why use only batting table?\n",
"The batting table contains all the playerIDs that are also in the pitching and fielding table, so looking at the batting table will at least include all players. I checked this by looking at total playerIDs, unique playerIDs, and overlapping playerIDs between tables (see below). It could still possible that some records are missing between the tables that would count for some additional seasons for players (I did not look into this, but it is something to keep in mind: you could check all combination of yearID+playerID).\n",
"\n",
"Below you can see the numbers of playerIDs for the different tables:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"18846\n",
"18659 101332\n",
"18465 170526\n",
"9126 44139\n",
"170526 44139\n",
"101128 48554\n"
]
}
],
"source": [
"print len(master.playerID) # total number of different players in database\n",
"print len(batting.playerID.unique()), len(batting.playerID) # batting: unique players, number of records \n",
"print len(fielding.playerID.unique()), len(fielding.playerID) # fielding: unique players, number of records \n",
"print len(pitching.playerID.unique()), len(pitching.playerID) # pitching: unique players, number of records \n",
"print fielding.playerID.isin(batting.playerID).sum(), pitching.playerID.isin(batting.playerID).sum() # overlap with batting\n",
"print batting.playerID.isin(fielding.playerID).sum(), batting.playerID.isin(pitching.playerID).sum() # overlap other way"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Calculations and bit more cleaning up the data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"nameFirst Nick\n",
"nameLast Altrock\n",
"debut 1898-07-14 00:00:00\n",
"finalGame 1933-10-01 00:00:00\n",
"Name: 261, dtype: object\n",
"max career length: 35.2142368241 years\n",
"min career length: 0.0 years\n"
]
}
],
"source": [
"career_length = (master.finalGame - master.debut) # pandas series of career_length in days\n",
"career_length = career_length[pd.notnull(career_length)] # drop NaT values from data not available\n",
"# 'technically' you can't get the exact number of years if you just know the number of days, as it depends on the starting \n",
"# and end date. To get a good estimate for career length we do not need to be so exact, so dividing by average number of days\n",
"# per year is accurate enough.\n",
"career_length = career_length.astype('timedelta64[D]').astype(int) / 365.25 # panda series of careerlength in years \n",
"\n",
"# Checking max and min career length, checked Nick Altrock, has 35 years between first and last game. \n",
"max_length = career_length.argmax()\n",
"print master.ix[max_length,['nameFirst', 'nameLast', 'debut', 'finalGame']]\n",
"print 'max career length: {} years'.format(career_length.max())\n",
"print 'min career length: {} years'.format(career_length.min())"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# number of seasons played per player get rid of multiple entries per year (mid season change, so that it only counts for 1 year)\n",
"# this only shifts few higher counts to some lower counts (the effect is not dramatic)\n",
"nseasons = batting[~batting.duplicated(['playerID', 'yearID'])].groupby('playerID').count()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that I discussed both methods, as well as some considerations to take into account, it is time to compare the methods."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
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zuaamhssvv7zD9tcey5m2uMRTzHJuLlHHU8zytGnTGDVqVGziKcW/h6THn5G0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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x8a65a50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# figure layout:\n",
"fig = plt.figure(figsize = (7, 7))\n",
"gs = gridspec.GridSpec(4, 1)\n",
"plt1 = plt.subplot(gs[:3, 0])\n",
"plt2 = plt.subplot(gs[-1,0])\n",
"\n",
"# histogram of career lengths:\n",
"binsmax = np.ceil(career_length.max()).astype(int) + 1\n",
"#bins2 = np.linspace(0,binsmax, binsmax*2) # bin width half a year, use if want to see difference within a year\n",
"bins = range(0, binsmax, 1) # bin width is 1 year\n",
"plt1.hist(career_length, bins = bins, label = 'career length')\n",
"\n",
"# histogram number on seasons:\n",
"nseasons.yearID.hist(bins = bins, color = 'black', alpha = 0.5, ax = plt1, label = 'nseasons')\n",
"\n",
"plt1.set_title('histogram of career lengths, N={}'.format(len(career_length)))\n",
"plt1.set_ylabel('frequency')\n",
"plt.setp(plt1.get_xticklabels(), visible=False) # share x-axis with bottom figure\n",
"plt1.legend()\n",
"\n",
"# boxplot with statistical info distribution career lentgh:\n",
"plt2.boxplot([[career_length], [nseasons.yearID]], vert = False)\n",
"\n",
"plt2.set_yticklabels(['career length', 'nseasons'])\n",
"plt2.set_xlabel('years / seasons')\n",
"\n",
"fig.savefig('careerlengths.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"From the above figure one can see almost 1/3 of all careers are shorter than 1 year. After the first year the drop in career length is a lot slower. The figure below shows the boxplot of the same data, it is clear that the median for baseball careers is just above 3 years, while 75% of the careers are shorter than 8 years. Any career longer than ~19 years is an outlier. The lower 25% all finished there career well before the end of the 1st season they played. 50% of careers range from half a year to 7 years.\n",
"\n",
"The number or seasons played shows a quite similar trend. In order to compare the two graphs you need to take into account that whenever a player is on a team for a given year it counts as a season played. For the career length calculation above however, a player can have its debut and final game anywhere within a season (like the peak at zero discussed above). As the first bin contains 0 >= to < 1, number of seasons played will start at 1, containing all records with 1 seasons played.\n",
"\n",
"For number of seasons played, the median career lasts 3 seasons. The minimum career lasts 1 season, but as we see compared to the career length (blue) this could be seen as a quite optimistic view (due to its first quartile being ~half a year, can also check bins2 with a binsize of half a year). \n",
"\n",
"If you want to investigate more about the general career of players, it would be informative to look at total games played per season, age at which players start their career, amount of times players switch teams, or player games/seasons played for a team. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### quick intermission: Weight vs. Height\n",
"For fun I wanted to see the distribution of baseball players length and height in a scatter plot. Pandas works great even though some players have no data available to them and ignores the points when plotting (If you need to do specific computations these values might be removed beforehand in order for your function to work)."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xbd0f6d0>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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pHdJHEKkYJF86DAYDwWADd989r4/922IZj9ut8tBDT9HcbESv93PxxSOBIA8+uIZ4vAiT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\nUiU0MCillCqhgUEppVSJ/w+xiv3G8JYMKQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xbad0310>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"master[['weight','height']].plot(x='weight',y='height', kind='scatter', alpha = 0.2)\n",
"plt.xlabel('weight (lbs)')\n",
"plt.ylabel('height (Inch)')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The outlier in the bottom right is actually [Eddie Gaedel](https://en.wikipedia.org/wiki/Eddie_Gaedel), some fun baseball trivia."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"nameLast Gaedel\n",
"nameFirst Eddie\n",
"height 43\n",
"weight 65\n",
"Name: 5761, dtype: object"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" master.ix[master.height.argmin(),['nameLast','nameFirst','height','weight']]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Team size"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When I was checking teams compositions in the data set I noticed that the team size of baseball teams is quite large (from 2015, New York Yankees had 56 players). This led to the idea to see how team size changes over years. As a second question I wanted to know how many of the same players stayed compared to their last season.\n",
"\n",
"#### Data wrangling\n",
"To be able to get the full team names and player names the batting table is merged with the master and teams table. In the end the results in this section could be able to be obtained just from the batting table, but while exploring the datasets it was invaluable to get the full names for teams and players in order to check if what I was doing was right. It has been useful for various other investigations of the data that did not make it to this notebook."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# add player info in master to batting table\n",
"battingmaster = batting.merge(master, on = 'playerID', how = 'inner')\n",
"# adding team data to batting master\n",
"battingcomplete = battingmaster.merge(teams, on = ['yearID', 'teamID', 'lgID'], how = 'inner')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Total number of players per team\n",
"The first question is easily answered by grouping the data per year and team, and counting the number of records. In total we will have one data point per team per year, as there is some 30 some teams per year in MLB (at least currently), it is informative to know the median and quartile ranges to get a better comparison between years."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# count number of players per team, per year\n",
"players_per_team_year = battingcomplete.groupby(['yearID','teamID'], as_index = False).count()\n",
"\n",
"ppty_median = players_per_team_year.groupby('yearID').describe() # get statistics"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Number of players same as last year per team\n",
"In order to find what players are the same as last year one needs to compare the players. To do this I found out that applying the list() function to the playerID column when the data is grouped by year and teamID. As a result we get a nice column containing lists of all players in the team. After I add a new column which is a shifted version of the last one. This allows us to efficiently apply a lambda function to the *rows* that compares the lists. \n",
"\n",
"For the function to work the NaN values introduced by the shifting of the column before need to be taken care of though, as NaN is seen as a boolean and the for loop will give an error. Instead I filled the NaN column values with an empty list. The NaN values correspond to the first year the team started in MLB, so there is no group to compare it to. As a result the first value of a team will always be a zero."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# get a list of players for each team for each year (also possible: add to teams data as another row)\n",
"teams_comp = battingcomplete.groupby(['yearID','teamID'])['playerID'].apply(list).reset_index()\n",
"\n",
"# to compare it to last years players we add a shifted row to the table with list of last years players at the current year\n",
"teams_comp['shift_playerID'] = teams_comp.groupby('teamID').playerID.shift(1) # shift(1), on data grouped by team\n",
"\n",
"# need to fill NaN with empty lists or apply function won't work, fillna does not work with lists\n",
"for row in teams_comp.loc[teams_comp.shift_playerID.isnull(), 'shift_playerID'].index:\n",
" teams_comp.at[row, 'shift_playerID'] = []\n",
"\n",
"# compare the lists from current and last year, using sort_values seems to work as I grouped by year and team before, this apply \n",
"# function does not work on groupby DF and I don't get why.\n",
"teams_comp['same'] = teams_comp.sort_values('teamID').apply(lambda row: sum(i in row.playerID for i in row.shift_playerID), axis = 1)\n",
"\n",
"teams_comp_stats = teams_comp.groupby('yearID').describe() # statistics"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### total players and mid season transfers\n",
"It is informative for the question I want to answer to know how many players switch teams mid season. In the above calculations, these players will be counted in two teams for a given year. By looking at the duplicate records of playerID for a given year and summing them up you get the total mid season transfers for the year (later I found out the stint column actually provides you with the info if the player appeared in first or second half of a season, alternatively you could count the number of records that have stint == 2 per year). To see the size of this group compared to the total number of players per year the two function nunique and count are used. An example of player with mid season tranfer is given below too."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# statistics about total number of players in database per year \n",
"players_per_year = battingcomplete.groupby(['yearID'])['playerID'].aggregate({'nunique players': pd.Series.nunique, \\\n",
" 'total records': pd.Series.count, \\\n",
" 'difference': lambda x: x.duplicated().sum()})"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>playerID</th>\n",
" <th>yearID</th>\n",
" <th>stint</th>\n",
" <th>teamID</th>\n",
" <th>lgID</th>\n",
" <th>G_x</th>\n",
" <th>AB_x</th>\n",
" <th>R_x</th>\n",
" <th>H_x</th>\n",
" <th>2B_x</th>\n",
" <th>...</th>\n",
" <th>DP</th>\n",
" <th>FP</th>\n",
" <th>name</th>\n",
" <th>park</th>\n",
" <th>attendance</th>\n",
" <th>BPF</th>\n",
" <th>PPF</th>\n",
" <th>teamIDBR</th>\n",
" <th>teamIDlahman45</th>\n",
" <th>teamIDretro</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>93677</th>\n",
" <td>ackledu01</td>\n",
" <td>2015</td>\n",
" <td>2</td>\n",
" <td>NYA</td>\n",
" <td>AL</td>\n",
" <td>23</td>\n",
" <td>52</td>\n",
" <td>6</td>\n",
" <td>15</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>135</td>\n",
" <td>0.985</td>\n",
" <td>New York Yankees</td>\n",
" <td>Yankee Stadium III</td>\n",
" <td>3193795</td>\n",
" <td>99</td>\n",
" <td>101</td>\n",
" <td>NYY</td>\n",
" <td>NYA</td>\n",
" <td>NYA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95635</th>\n",
" <td>ackledu01</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>SEA</td>\n",
" <td>AL</td>\n",
" <td>113</td>\n",
" <td>384</td>\n",
" <td>40</td>\n",
" <td>97</td>\n",
" <td>18</td>\n",
" <td>...</td>\n",
" <td>149</td>\n",
" <td>0.986</td>\n",
" <td>Seattle Mariners</td>\n",
" <td>Safeco Field</td>\n",
" <td>1761546</td>\n",
" <td>92</td>\n",
" <td>92</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95988</th>\n",
" <td>ackledu01</td>\n",
" <td>2011</td>\n",
" <td>1</td>\n",
" <td>SEA</td>\n",
" <td>AL</td>\n",
" <td>90</td>\n",
" <td>333</td>\n",
" <td>39</td>\n",
" <td>91</td>\n",
" <td>16</td>\n",
" <td>...</td>\n",
" <td>152</td>\n",
" <td>0.982</td>\n",
" <td>Seattle Mariners</td>\n",
" <td>Safeco Field</td>\n",
" <td>1939421</td>\n",
" <td>94</td>\n",
" <td>95</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97083</th>\n",
" <td>ackledu01</td>\n",
" <td>2012</td>\n",
" <td>1</td>\n",
" <td>SEA</td>\n",
" <td>AL</td>\n",
" <td>153</td>\n",
" <td>607</td>\n",
" <td>84</td>\n",
" <td>137</td>\n",
" <td>22</td>\n",
" <td>...</td>\n",
" <td>155</td>\n",
" <td>0.988</td>\n",
" <td>Seattle Mariners</td>\n",
" <td>Safeco Field</td>\n",
" <td>1721920</td>\n",
" <td>90</td>\n",
" <td>91</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>100238</th>\n",
" <td>ackledu01</td>\n",
" <td>2014</td>\n",
" <td>1</td>\n",
" <td>SEA</td>\n",
" <td>AL</td>\n",
" <td>143</td>\n",
" <td>502</td>\n",
" <td>64</td>\n",
" <td>123</td>\n",
" <td>27</td>\n",
" <td>...</td>\n",
" <td>139</td>\n",
" <td>0.986</td>\n",
" <td>Seattle Mariners</td>\n",
" <td>Safeco Field</td>\n",
" <td>2064334</td>\n",
" <td>95</td>\n",
" <td>95</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>100282</th>\n",
" <td>ackledu01</td>\n",
" <td>2015</td>\n",
" <td>1</td>\n",
" <td>SEA</td>\n",
" <td>AL</td>\n",
" <td>85</td>\n",
" <td>186</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>8</td>\n",
" <td>...</td>\n",
" <td>155</td>\n",
" <td>0.985</td>\n",
" <td>Seattle Mariners</td>\n",
" <td>Safeco Field</td>\n",
" <td>2193581</td>\n",
" <td>92</td>\n",
" <td>94</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" <td>SEA</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>6 rows × 90 columns</p>\n",
"</div>"
],
"text/plain": [
" playerID yearID stint teamID lgID G_x AB_x R_x H_x 2B_x \\\n",
"93677 ackledu01 2015 2 NYA AL 23 52 6 15 3 \n",
"95635 ackledu01 2013 1 SEA AL 113 384 40 97 18 \n",
"95988 ackledu01 2011 1 SEA AL 90 333 39 91 16 \n",
"97083 ackledu01 2012 1 SEA AL 153 607 84 137 22 \n",
"100238 ackledu01 2014 1 SEA AL 143 502 64 123 27 \n",
"100282 ackledu01 2015 1 SEA AL 85 186 22 40 8 \n",
"\n",
" ... DP FP name park \\\n",
"93677 ... 135 0.985 New York Yankees Yankee Stadium III \n",
"95635 ... 149 0.986 Seattle Mariners Safeco Field \n",
"95988 ... 152 0.982 Seattle Mariners Safeco Field \n",
"97083 ... 155 0.988 Seattle Mariners Safeco Field \n",
"100238 ... 139 0.986 Seattle Mariners Safeco Field \n",
"100282 ... 155 0.985 Seattle Mariners Safeco Field \n",
"\n",
" attendance BPF PPF teamIDBR teamIDlahman45 teamIDretro \n",
"93677 3193795 99 101 NYY NYA NYA \n",
"95635 1761546 92 92 SEA SEA SEA \n",
"95988 1939421 94 95 SEA SEA SEA \n",
"97083 1721920 90 91 SEA SEA SEA \n",
"100238 2064334 95 95 SEA SEA SEA \n",
"100282 2193581 92 94 SEA SEA SEA \n",
"\n",
"[6 rows x 90 columns]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Showing example mid season transition:\n",
"battingcomplete[battingcomplete.playerID == 'ackledu01']"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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JaiaQ9Y2DrO/2Va/Zs0FR4Lbb6t3U/v0tiK+dSQIphBBCiB5Hr9djsVik5zFA7Nmzh9Gj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TBNlJPoG4j1x15oPdKTVZl/GxVq6WPZo1JQo4d4FzTo4lje9yoAei56Bu3h3QQ0eg4lWCJAmlAo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38dCcvsZZb8/3Ve7ZTBsNt4kH4QzEdt3Be+ReUMhDoCe5HLlX+jx8P35M9zb/qXw+tOEYonI5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\naDT9womSxW63M2rUKBoanGRl1TF+/ByysupS4CxASl2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5+SJBdLwZPjMB1wI5wKfuQEJv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smtW6P3hz+SrLwhJQWFScVCUSLyTt6mJ16l5iqfZMGvj2+lw27vumYymbRXAXmkHafLxXXF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\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Vl0+SJOFua0OXloats5PnHngg+uNL8XXXoQi3dVZKCkNnzIj+2JDYR2ebGzu2bmX9woU9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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x8f78610>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# create subplots:\n",
"fig2 = plt.figure(figsize = (15, 6))\n",
"gs = gridspec.GridSpec(1, 3)\n",
"plt1 = plt.subplot(gs[0, :2])\n",
"plt2 = plt.subplot(gs[0, -1])\n",
"\n",
"# plot players per team as function of year:\n",
"players_per_team_year.plot(x = 'yearID', y = 'playerID', kind = 'scatter', alpha = 0.2, ax = plt1)\n",
"plt1.plot(ppty_median.playerID.loc[:, '25%'], 'red'\\\n",
" ,ppty_median.playerID.loc[:, '50%'], 'green' \\\n",
" ,ppty_median.playerID.loc[:, '75%'], 'red', linewidth = 2)\n",
"\n",
"# plot number of players same as last year:\n",
"teams_comp.plot(x = 'yearID', y = 'same', kind = 'scatter', color = 'red', alpha = 0.2, ax = plt1)\n",
"plt1.plot(teams_comp_stats.same.loc[:, '25%'], 'red'\\\n",
" ,teams_comp_stats.same.loc[:, '50%'], 'green' \\\n",
" ,teams_comp_stats.same.loc[:, '75%'], 'red', linewidth = 2)\n",
"\n",
"# Brushing up figure a bit:\n",
"plt1.set_ylabel('Number of Players')\n",
"plt1.set_xlabel('year')\n",
"plt1.set_ylim([0, 70])\n",
"plt1.set_xlim([battingcomplete.yearID.min(), battingcomplete.yearID.max()])\n",
"\n",
"# Second figure:\n",
"players_per_year.plot(linewidth = 2, ax = plt2)\n",
"plt.locator_params(nbins = 6)\n",
"plt2.yaxis.tick_right()\n",
"plt2.yaxis.set_label_position(\"right\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Above the number of players per team over time is given. The blue dots represent total team size of the teams for a given year, while the red dots are the player numbers similar to last years composition. The spread of team size is quite large, to make overlapping points more visible the opacity of the points has been set to 0.1 so that you can recognize the overlap by darker colors. As discussed above the record of a team for its first year will give 0 for same players. The green lines show the median and the red lines the quartile ranges.\n",
"\n",
"The total number of players per team has for the most part been in an upward trend all the way from the first records. While slowing down considerable around 1915 (after an initial spike, if anyone knows why this is the case let me know) to 1980. From 1980 the teamsize has been on a rise again. But the players that stayed the same since last year does not show this trend. Actually since 1920 it seems that the mean amount has been roughly the same. As a consequence the number of new or transfered players in a team has increased since 1980. \n",
"\n",
"The right graph shows total number of players each year (blue), transfers (green), and their sum (red). A relatively small amount of players is transfered between teams mid season, as example for 2015 it amounts to just below 10% of total players in MLB. Looking back at the other graph, the large change in team size (above 50% in last few years) is mostly because of changes between seasons. \n",
"\n",
"For individual players this change could be an indication of increasing competition inside a team. But more factors have to be taken into account as changes in teams come from many different situations. A part comes from new talent, retiring players, and mid-season transfers as mentioned before, as well as many other factors. Of course, not only a players accomplishments determine if he will stay on a team. Economics plays a role too (both a players earnings as well as team economics). To investigate competition one needs to take into account a broad range of factors.\n",
"\n",
"As a last comment, the graph on the left contains a lot of data and could also take some more polishing. For example the zero points could be removed (or in a more interactive plot using plot.ly for example it could point to where new teams enter MLB). The strange peaks to zero at the start of the graph could be due to [different MLB assocations](https://en.wikipedia.org/wiki/Major_League_Baseball_schedule) around that time, the peak around 1914 would also be explained by that."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Team batting statistics"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As I mentioned before, I know nothing of baseball, but in order to learn something about how the game is played I have calculated some statistics used in baseball to measure performance of teams and players. There is however a boatload of statistics that is recorded for each player and team, even if you just look at batting and disregard fielding and pitching. Here I just look at batting stats to find out which one determines offensive capabilities for teams the best.\n",
"\n",
"In baseball the offensive team scores whenever a player makes a run, so a good measure of offensive capability is a statistic that correlates very well with the amount of runs earned by the team. When you know what statistics correlate with runs for team statistics, you can look at individual players to determine their contribution to the team.\n",
"\n",
"Below are some functions that calculate different statistics from the data\n",
"\n",
"- [OBP](https://en.wikipedia.org/wiki/On-base_percentage): on-base percentage: measure of how often a batter reaches base by any means but not including certain errors.\n",
"- [AVG](https://en.wikipedia.org/wiki/Batting_average): Batting average: measures offensive capability of batters by hits devided by at bats.\n",
"- [SLG](https://en.wikipedia.org/wiki/Slugging_percentage): slugging rate: measures offensive capability of batters similar to AVG, but with more weight on 2base, 3base, and HR hits. (it seems the factors are given by the amount of bases covered in the hit)\n",
"- [SBP](https://en.wikipedia.org/wiki/Stolen_base): successful stolen base percentage: ratio of how many stolen bases a team has performed successfully. CSP: caught stealing percentage is the ratio of how many times a player has been caught stealing.\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# these functions could also be useful to calculate statistics for individual players\n",
"\n",
"def OBP(data):\n",
" # this function works for team and player data (unless merged in a single file)\n",
" return (data.H + data.BB + data.HBP) / (data.AB + data.BB +data.HBP + data.SF)\n",
"\n",
"def AVG(data):\n",
" # this function works for team and player data (unless merged in a single file)\n",
" return data.H / data.AB \n",
"\n",
"def SLG(data):\n",
" # H = 1B + 2B + 3B + HR\n",
" return ( data.H + data['2B'] +2*data['3B'] + 3*data.HR) / data.AB\n",
"\n",
"def CSP(data):\n",
" return data.CS / (data.CS + data.SB)\n",
"\n",
"def SBP(data):\n",
" return data.SB / (data.CS + data.SB)\n",
"\n",
"def babip(data):\n",
" # calculate batting average on balls in play\n",
" return (data.H - data.HR) / (data.AB - data.SO - data.HR + data.SF)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"teams['AVG'] = AVG(teams)\n",
"teams['SLG'] = SLG(teams)\n",
"teams['Wrate'] = teams.W / teams.G\n",
"teams['SBP'] = SBP(teams)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### missing values\n",
"I noticed that many records for HBP and SF are missing in the database for teams, this means that OBP cannot be calculated. In fact no statistics are given from before 2000. Although HBP and SF seem to be recorded since a later time than other statistics, it seems that both have been measured well before 2000. I could not find a sasifactory answer why these records are missing (wikipedia still mentions the dates the stats were 'officially' measured, which is way before the year 2000 too). Here I made the decision to just look at the data from 2000 and on, which will give a clear state of how the stats measure for todays baseball. \n",
"\n",
"There could be more info for individual players inside the batting table, I did not check this. Or you could use a value of zero for HBP and SF for the missing records, but this might give a skewed result (if someone has an explanation using baseball rules why this might be valid, let me know). You could investigate this by comparing the OBP after the year 2000 with a function not taking HBP and SF into account (basically set them zero in the above function). To be able to graph the data below I implemented this method for the missing data, if you want to investigate records before 2000, you can adjust the year1 value."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2325\n",
"2805 480\n",
"2325\n",
" yearID teamID lgID HBP SF\n",
"2320 1999 SFN NL NaN NaN\n",
"2321 1999 SLN NL NaN NaN\n",
"2322 1999 TBA AL NaN NaN\n",
"2323 1999 TEX AL NaN NaN\n",
"2324 1999 TOR AL NaN NaN\n",
"480\n"
]
}
],
"source": [
"# OBP has only a few records, this is because sacrifice flies have not been recorded for long.\n",
"print teams[teams.SF.isnull()]['yearID'].count()\n",
"print len(teams.SF), teams.SF.count()\n",
"print teams[teams.HBP.isnull()]['yearID'].count()\n",
"\n",
"print teams[teams.HBP.isnull()][['yearID', 'teamID', 'lgID', 'HBP', 'SF']].tail(5)\n",
"print len(teams[teams.yearID >= 2000])\n",
"\n",
"# calculate OBP with HBP and SF = 0\n",
"teams['OBP'] = OBP(teams.fillna(0))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I have extended the teams table with data on OBP, AVG, SLG, CSP, SBP, and babip. To calculate these statistics the data of a team per season is used, so every team has a datapoint each year. Below I plotted the correlation of runs with: AVG, SBP, SLG, and OBP."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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QhBQZgn7//YFrrwVWrcIenw9n1un4lTEtoztmqbty1hpeUi5uEZktCIUzng39WLsdF8zL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lzleu9bSmsI9gGeT/p5i//cPsALSc+/4D8nIiIiIlKuSubet6aQb14MzjkrdhlEREbKzNJ7kAJN\nMVtEyllQYnYpjRBsAfZL+nlf/7lsz2dlZmV/XHzxxUUvg65F11IOR1Cuw6xy74uL/XfXf7O6Zl2z\nrnckRx7k7d53tMaiQeAYOGcq+XdxdwKnO+fCzrmJwAFAp5m9DGx1zh3hL7Q4A7ijoCUWERERERmZ\nsrv3LeiUIefcSmAOsJtz7jngYryFFj8A/gG42zn3RzP7sJl1Oed+BnQBfcC51t/8Og9YDkSBX5nZ\nvYUst4iIiIjIcJXrvW9BGwRm9sksv7o9y/mXAZdleP5hYHoei1by5syZU+wi5I2upTQF5VqCch1S\nOSrxv1ldc/BV2vVmU673vi5Pc6BKhnPOgnZNIlIZnHNYQBao5UoxW0TKVZBidiktKhYRERERkTGm\nBoGIiIiISAVTg0BEREREpIKpQSAiIiIiUsHUIBARERERqWBqEIiIiIiIVDA1CEREREREKpgaBCIi\nIiIiFUwNAhERERGRCqYGgYiIiIhIBVODQERERESkgqlBICIiIiJSwdQgEBERERGpYGoQiIiIiIhU\nMDUIREREREQqmBoEIiIiIiIVTA0CEREREZEKpgaBiIiIiEgFU4NARERERKSCqUEgIiIiIlLB1CAQ\nEREREalgahCIiIiIiFQwNQhERERERCqYGgQiIiIiIhVMDQIRERERkQqmBoGIiIiISAVTg0BERERE\npIKpQSAiIiIiUsHUIBARERERqWBqEIiIiIiIVDA1CEREREREKpgaBCIiIiIiFUwNAhERERGRCqYG\ngYiIiIhIBStog8A5t8w594pz7tGk51qcc/c55550zrU755qSfnehc+4p59xG59wJSc/Pcs496pz7\ns3Pu+4Uss4iIiIjISJTrvW+hRwh+DHww7blFwP1mdiDwG+BCAOfcQcA/A9OADwPXOeec/5rrgflm\nNgWY4pxLf08RERERkWIry3vfgjYIzGwd8Fra06cAP/Ef/wQ41X98MrDazHaa2SbgKeAI59yeQIOZ\nrffPuyXpNSIiIiIiJaFc732LsYZgdzN7BcDMXgZ295/fB3g+6bwt/nP7AC8kPf+C/5yIiIiISKkr\n+XvfmkK+eY4s3294ySWXJB7PmTOHOXPm5PsjRERGbe3ataxdu7bYxRARkRzkMWbn/d53tJxZYcvk\nnJsA3GVmM/yfNwJzzOwVf0ikw8ymOecWAWZmV/jn3QtcDGyOn+M/fzpwjJl9IcvnWaGvSUSkEJxz\nmJkb+szgUMwWkXKVLWaP9b1vPozFlCHnH3F3Ap/xH58J3JH0/OnOubBzbiJwANDpD61sdc4d4S+0\nOCPpNSIiIiIipaTs7n0LOmXIObcSmAPs5px7Dq/Vczlwq3PuLLwW0D8DmFmXc+5nQBfQB5yb1G10\nHrAciAK/MrN7C1luEREREZHhKtd734JPGRprGn4WkXKlKUMiIuUjSDFbOxWLiIiIiFQwNQhEiqSn\np4f169fT09NT7KKIiIgAqpsqlRoEIkWwatUaJkyYyvHHn8OECVNZtWpNsYskIiIVTnVT5dIaApEx\n1tPTw4QJU+nt7QBmAI8Six3L5s1P0NraWuziSREFaT5qrhSzRUqD6qbhC1LM1giByBjbtGkT4XAb\nXsAFmEEoNIFNmzYVr1AiIlLRVDdVNjUIRMZYW1sbO3ZsAh71n3mUvr7NtLW1Fa9QIiJS0VQ3VTY1\nCEQY20VUra2tLFt2HbHYsTQ2ziIWO5Zly64bMCSrhV0iIjJWcq2bhmM49ZjqvOLSGgKpeKtWrWH+\n/HMJh73ekWXLrmPevLkF/9yenh42bdpEW1vbgIBbrDJJcQVpPmquFLNFSstgddNwDKceK9c6L0gx\nWw0CqWiluIiqFMskYyNIlUuuFLNFgmc49Vg513lBitmaMiQVLZ+LqPI13KmFXSIiUi4y1X3DqcdU\n55UGNQikouVrEVU+czdrYZeIiJSDbHXfcOox1XmlQQ0CqWj5WETV09PD/Pnn0tvbwdatD9Pb28H8\n+eeOeKSgEAu7RERE8mmwum849ZjqvNKgNQQijG4R1fr16zn++HPYuvXhxHONjbO4//4bmD17dlHK\nJOUpSPNRc6WYLVKecqn7hlOPlWOdF6SYrQaByCiV84IoKS1BqlxypZgtUp5U9wUrZmvKkMggclko\nXIzhTuVrFhGRYkqu++rrpxOJ/CPf+97lea37VNeNHTUIRLIYzkLhefPmsnnzE9x//w1s3vxESv7k\nfAe0fC5gFhERGal58+byrW99nR07nicU2p8vf3lR3uok1XVjS1OGRDLI11Bovjdb0RBtsAVp+DlX\nitki5euGG27inHPOBx4kn3VSudR1QYrZGiEQySAfeZHznX0oX+USEREZrZ6eHs4//9+AKSTXSTU1\n40ddJ6muG3tqEIhkkI+8yIUIaMrXLCIipcCr4yYAz5NcJ+3YsWnUdVK8rtuPdpp5DdV1hacGgUiS\n+Hx/YNQLhQtx8658zSIiUgra2trYuXMLcAFwLHAocCRf/vIXRv3era2t3HPefP7Ih7mlZiKx6BzV\ndQWmNQQivkzz/Y877v2jyoscf89QaAJ9fZtHvYYgrhzzNcvQgjQfNVeK2SLlK17HVVfvzfbtfwGg\nru7A0a2Z6+uDiy6C734XgL8fdRR9K1bQOmFCPoueF0GK2WoQiFDYBUy6eZdcBalyyZVitkh56+np\nYcOGDZxyyly2b3+AUdWhzz0Hc+fCgw9CdTVcdhl85StQVZoTWoIUs0vzLywyxgq5gKm1tZXZs2eX\nTGNAeZ1FRCRfWltbaWlpIRLZn8Hq0CHrnrvvhsMO8xoD++4LDzwAX/1qyTYGgkZ/ZREqZ7Gu8jqL\niEi+DVWHDlr39PXB174GJ50Er70GJ54IGzbAUUeN8VVUNk0ZEvEVar5/qcg2Ler221cxc+bMkhnB\nqGRBGn7OlWK2SPnr6enhhhtuYsmSqwiHJ6bUoYNOyd2+HU4/HX73O2+K0He+A//2b2UzKhCkmF0e\nf3GRPBhquHKw3YZH+p6lJNO0qN7eFj72sYUaLRARqUD5qMPivf/f/e4vcK6Kr37144k6tKenh1/9\n6lfU1EwgfTrRaytWeFOEfvc72GcfWLvWGykok8ZA4JhZoA7vkkRSrVy52mKxcdbUNMtisXG2cuXq\nknzPQuru7rZYbJzBnwzM/7fFoNvgTxaLjbPu7u5iF7Oi+fGr6HF0LA/FbJHiyEcdlqleidcl8fdv\naJhuEEucU8Mf7KqaqPkvMPvQh8x6egpwhYUXpJitKUMSeIXIIFQu26qni0+LqqralzfffBq4GfBG\nQhobZ3H//Tcwe/bsopaxkgVp+DlXitkiYy9fddj69es5/vhz2Lr14cRzjY2zuPXWyzn11HlJ738l\ncAlT6yayrPfPvHfXTm+K0Le/XdajAkGK2eX5DYgMQyEyCJXrturxaVG33XYV0WgYmOb/JpiLqEVE\nZKB81WHZFhMDae//NT4W3Z0N7jmvMbDPPtDRAYsWlW1jIGj0LUjgFSKDULlnJWppaeH7379SOx6L\niFSgfNVhra2tLFt23YC6ZObMmf77r6WG33MZn+QX2zcT3bYNPvhBL4vQP/5jXq9JRqem2AUQKbR4\nwJo//9iUDEKjufktxHuOhfTdmL/3vcuZNeswbZomIlJB8lmHzZs3l+OOe/+ADTjnz/80v/zhh1kN\nvI/tvOMc1d/5TllPEQoyrSGQilGIHYNLfRfi5PIBZbnuoZIEaT5qrhSzRYpnqDpspHVcT08PZ++7\nPz/aUcM/8He20MpnwttZ+cIzgapvghSz1USTijHUjsEjSb9WyF2IR5sOLn0jmBtuuKks1z2IiEhm\no60nBqvDRryR5c6dvPHFL3L7jm38A3/nXj7IYTxOZ/QA1TclTA0CEUpvB9/Rlqenp4f588+lt7eD\nrVsfpre3gyVLrirrdQ8iItKvkPVWpjpk/vxzh254bNlC9/Tp7L9mDe8AF/FFTuRXvMpLqm9KXNEa\nBM65851zj/nHQv+5Fufcfc65J51z7c65pqTzL3TOPeWc2+icO6FY5ZbgGXHgK+HyZMogEQ5P5KKL\nvqKFxCIiZa7Q9daIshC1t7Pr0EPZ/YkneJFWjuViLuOnGFMqrr4px3vcojQInHMHA/OBdwGHAf/k\nnJsELALuN7MD/z973x4nV1mf/93ZObe57exKuAiEhE2WQDabLK2XemmRImqtKaIUQQXKRbCuwdYq\nIQpBtmuNaVoNVdbF6lrNsuvdUi+Dl6W61XZQUdEBvFS0FnVSRETJDwg8vz/e951ze8+ZMzNn9sye\nfZ/P5/0kuzlzzvuezT7f9/1eni8RfYmIrubXn0JEf05MI/EFRPTuvr6+VORsKSSPXpMQDZrPHXfc\nETk0HKQgcfnll7XcjVlBQUFBobcQh90KSzdqSYXo8GGiN72J6PnPp8z999MXs0XaRt+lr9B1RHQP\n5fP99MlP3rxq7M1K3eMmFSE4mYj+C8AjAB4noi8T0dlEtJ2IPsCv+QARncX/vp2I5gEcBnAvEf2A\niJ66vFNWSCt6TUJUNp9Dh35IZ511XuTQcJAU3Jo1a7pa96CgoKCg0H10areapRuF2RAX7ruP6I//\nmOitbyXKZOh3O3fS9myWDtIv+AU/pyee+D8aHx/vYLUrDitzj5tEe2Qi2kREdxPRIBHliOirRLSf\niH7lue5X/M8biOh8x/ffS0RnB9wbCgr1eh3VahX1ej3S9aLFeqk03nYLd+9zW51D0HxMswxdH5C2\nhm9lPgq9D85fibewX86hOFtBoT147db09Ewkvq/VajCMssumGEYZtVrNd22oDalUgDVrACLgmGOA\n226Tzqtde7oSIOPsbu5xuzkS6UMA4O6+vr49RPR5IvotEd1BRI/LLm3n/tddd13j76eddhqddtpp\n7dxGoUMkJcnp1dr/539+d9NQZZCOcrvPPXToRwQ8TrncSOQ5BM3ngQceoD//86vp0Uf9oeFm8xQR\nAYXexG233Ua33XZb0tNQUFBYgTjvvHNp27YxqlardPDg/fRXf7Wzqd27+eYF+ou/eBU98sjR5Ew3\neuSRNTQ+/nR6//tnXJ+T2pDDh4muu45FBQCi5z6X6EMfIjryyMa8OrWnvYoonN3tPW7XsNwnENkg\noikiuoKI7iKio/j3jiaiu/jfdxLRVY7rP0dETwu4V4vnO4VuQHgIBgZOXVYPQb1eh2UNteVNj/u5\nRIMgqnc8hzjWtNIiBSttvnGBVIRAQWFFYzm5S9jZYnEcRBaI9oTaCNuWLILIa6/Y95valv/9X+AP\n/xAgAjIZYHISePzxLq+0dxGFs+Pc43ZzJGkE1vA/1xJRjYhKRLRHvBQiuoqI3sb/fgqxE5ZOROuJ\n6IfEm6pJ7tvGj1QhTiS1KQeAarWKgYFT+XPZKJXGUa1Wl/25ROMgqrY8B5lB6SQEm9ThrF2stPnG\nCXUgUFBYueiEu1o9SMidUEPcCSW3OW47tYMfIjbwP3c0t1XOFKGjjwYWFyOvL60I4uxu7XG7OZI0\nAl8mou/yl3Aa/94QEX2BiO4holuJqOy4/mr+ku4iojND7tveT1UhNsS5KY+DJFdShMBrUJw5oUHv\nIuwdJXk4awcrbb5xQx0IFBRWJjrhLifvm2YZk5NTTT8nd0KNcSdU1AjBIr9efH0jTLPc+FzDttx3\nH/DmNwN9fexBZ5wB/OIX7b+sFCHkQNCVPW43R+LGIPYFKeOSOOLa1LXrbelWQVOzw4nzubo+AE0r\ntDQH/3vbAyILxWLwPZq9o6QiJu1ipc03bqgDgYLCykS73OXm/XnuSNoA0xwMPRjInVAWCoXRUJsz\nNzcPwyiBaMRzmBgG0XHQ9QHMzc03bMtJxVH8eyaLRorQ9dcDhw93/L7SgjRxduITiH1Byrj0BDrd\nlHd6qIg7j9PO1dwCwyhhenqm6XNbnYPboNThzfH0rj/KO1ppHveVNt+4kSbjEnUozlZIA9rlLpv3\n/ZxPlINplkM3916VoUqlgkqlEvpcmcqQN6JtmmWcQdP4JbEUoZ9THx74+Mc7ejBb8CUAACAASURB\nVEdpRJo4O/EJxL4gZVx6Bp1synvJU2wT/R5O2FtBZAUeCjp/zrd5GHdr6PqjvqOVJgG30uYbJ9Jk\nXKIOxdkKaUE73GXz/gEQyerQDoQeLJx2tpWourg2nx8DUY5HJ9hzi7kt+DvtSXicWIrQrXQGhguj\nqyZS2wrSxNmJTyD2BSnjkgr0kqe4Wq2iWNzi894YRjnW+dTrdUxOTsE0yygURsEKveLx/q801Z6V\nNt+4kCbjEnUozlZIE9rhrrm5eZhmmW/M/UXCXkeP7Bnt2Mx6vY5KpcKfzT53NH0BizxF6HHqwzX0\nRmTog67aAgUbaeLsxCcQ+4KUcUkNesVTXK/Xec6l22Ofz49idna2pSLfIHg9O5OTU5ienmm6/okJ\noRSxEUQWJiZ2dLxeheSQJuMSdSjOVlBwOoQGeT7/IPfauzf2QcITlUql7ai6uOf23DB+waMCDw8M\n4Ln9Fj+kbGjUFii4kSbOTnwCsS9IGZdUoVc8xdPTMx6Pvbzgt51C6DDPTjQFoUUIpYjVlG+fRqTJ\nuEQdirMVFGw4I8VeZ1Az4Yn+fneEQdcHotmDw4fx29e/Hk8IFaHTT8fBO+/smSh9LyNNnJ34BGJf\nkDIuCk3Q7iFjenoGhlFGPr9Zms5Tq9U6LCpDqGfHO+9eqrNQiAdpMi5Rh+JsBQU/ZHaqmfAEs0sD\nvPZgEJpWaC5wcd99eORZzwKI2IHguuuAw4eVfYmINHF2hhQUUoiDBw/S7bffTgcPHnR9/+abF+iE\nEzbRc597BZ1wwia6+eaFyPe8/PLL6J3vfDs9+ui9RHQ8Odu+a9oJVK1WSdfX+b5/7733ht533bp1\n/J7f4d/5Dj322E9o3bp1ofOO8jkFBQUFhd5BkG3yYs2aNfSUpzyF1qxZ0/iem/PvJaJjyGlviI4l\nog8T0XuI6B6yrI30nvfcFGzzvvhFOnTyyaQvLdEv+7L0Qq1AN49sIurvV/ZlNSLpE0ncg5S3adUj\nKG0nDinToLbvnUQInHOW1QvU63Ve9HUA3kZn7dZZ9EoqloIblCJvU9ShOFthtUBmm1rlYlsdaJMv\nUs2+/kTja9Msy23Sz38O7N7dSBH6Ij0FR9N9gfUKndTxpd3WpImzE59A7AtSxqVnERcxtNuZt9MQ\nqPvz8/xQsBGGUfbVELRDoEHrmpyc4oVdp/Jnzrvm3WoH4yh1Dmkn8V5FmoxL1KE4WyFutMJfy8V1\nMtukacWWas7EXGu1GmZnZ2EY67hNGAfREDTteBhGqWF/JienfDZvvXUy/m/bNogUobcZRyNDhwNt\nYifvp93moisJaeLsxCcQ+4KUcelJxEUMnXTmjS9CID6/CMMooVar+a4TpN2poZF3oxxsKgHXSZRk\nNZB4ryJNxiXqUJytECfa0eLvNtfV63XMzs6iWBx32KY6vDKjYfZIpi4kE5Vw2h0v3z+HZvBzPoFD\npQE88JGPdK1wuJekw7uJNHF24hOIfUHKuPQc4iKGODrzdhoCjfr5qIammfdFdsAhGsbk5FTgPTqJ\nkqwWEu9VpMm4RB2KsxXiQqu9WZaD65xd7t0pPgdAtCHQeRWF073S1EKC1OvgyZuDuJYG8Th/0Jfo\n97GeO5WYWEYJhcJorIei1VKUnCbOTnwCsS9IGZeeQyfE4CTGKPeZm5uHphW452VYqp3caYi42eej\nGpqoqTv+CIHdJVl2j06iJKuFxHsVaTIuUYfibIW4UK1WYVlbXPxlWfIOu8vBdcEyodtgmmXo+kDg\nJr8VTq9Wq9LPAcDBO+/ET0dGAGKNxq6ja5GhwyiVxjE5OcUPK+MwjHLDrnRn7el0LqWJsxOfQOwL\nUsal59AuMQSHSOX3cT+nDqIDsXdXdB4Ggg4GlUoF+fxJfA5yQ9PKO2E9EEzuTSqDaE9oEXOz4uZm\nBcyrgcR7FWkyLlGH4myFuFCr1SArtPWmdQLxiEw0q92SbeQLBbuhpZeL9+7dx5tgLrbE6UFr+dfX\n/XWj0dgviXAGXdL4d3fBcXfsZa80F+0m0sTZiU8g9gUp49KTaJUYooZInffptsfHeUDR9QFoWsHn\njRHXsM27vNNkq3O1i4q3wllUPDs7G3iPZu87LMqxXCSuCpf9SJNxiToUZyvEBRYhWA9noa1prgu0\nAe1yXVB0t1UnFmDz4N69+3jEYKTB81E5vVqt8pSkKojqyNBh/K1+NA5zw7BIf4Rj6PMgshqpQXbB\nsRDIOBVEOVc6ahxIO8+nibMTn0DsC1LGpWfRCjGwTXC0/Epx70ql0hXvdtC92YbflgGVeXGIcjDN\nsnRDHmWuYUXFUbxG7RJxt0lcFS7LkSbjEnUozlaICzZfLiJq9/ZWuS6Iu4P4WHj9w3L0WRTYG9kY\n8s0/aK7257fiSCrjVtoAEOFxIlxPb0Y/PQYioFjc1ohO1OtCznowks1M+8a+XaSJsxOfQOwLUsYl\nNnS6oaxUKqhUKm0VD7dCVM7NpaYVoOsDsXm3bc3nk3wHFOaBqjYOKzKPfT4/hkqlEnrvsLk2Kype\niSFZlZYUjDQZl6hDcbZCnOgmJ9pqQe46hSD+t6xRGEYpNEe/Xq/zNKGtHp7fCMMo+VI6Zc4wwaen\n0ZdwHx0BEOF3+QL+VC+G8myY4032TpUDx480cXbiE4h9Qcq4xIJOCIAV9hbB0lw2SAt7w2BvgkUo\nczwwlCnbXJpmua2DSPi9674DSpQIQafeqSibZ6FJLcuT7UWowuVgpMm4RB2KsxXiRje82bZa0Dj3\nxu9pGiFg1y2G2gM73cf9WV0fcHF6kE2uVqsYLI3jzXQ9DlMGIMJX+vO449OfxtzcPE9DGgZRDppW\naLlmzH+NXG57tSJNnJ34BGJfkDIuHaMTD26r3v3mzw8udrK9NU5t5/g2l/6N6zyIcsjnxxo1BF4v\nVDe8U2H3XImeGxUhCEaajEvUoThbodcRpPZWKIzCNMuYnJzyFQkbRpnXM4TbJvvee/ihYAxOJbmg\n5wvOPPi97+HzmSxATEVoki5DwRz0pAX5u9wLNLNZ8oacI66GnKsZaeLsxCcQ+4KUcekYnXhwq9Uq\nT6/xp860sklvRlLB2s7dbazijD4IL5S3AVk3vFPNQsVx1xB0Gysx1Wk5kCbjEnUozlbodchsYrG4\nDZdf/mqfQ8ZpF6I6PuzU1E3QtDz27t3XVK2oVBrHXdPTwDHHAESoUx9enBv2RQ+i2PIwW+Guy1CO\nHC/SxNmJTyD2BSnj0jGSjhA47xUk6+aen63tHPfmMurBJAkPfRjZr4TIQS8fWJJCmoxL1KE4W6HX\nEWQTma1r3vU9iuODNQgro1gch6YVoesDgWpFfXQHdmctPJFhKUL4wz/E/3372y07jaJibm6e1zmM\ndCUav5KRJs5OfAKxL0gZl1jQiQc3SnOwTtBM2zluRD+YtE62UWoImntuWutDoNC7SJNxiToUZyus\nBNgb9m0e2U6EbpCj1Hg1q1dzHgpOLIziVp4iBCLgTW8CHnss8N5xRWNrtRoMI/wAtBqRJs5OfAKx\nL0gZl9iQlMpQlHt3c8Mbdd2dFsc28+JH8fLLyL7VeSlPfe8gTcYl6lCcrdBr8HKiM0XVMEqYnp6J\nVOsWNVLr5uyqL+VW8PcDn/oUHlmzhn3ziCOAz32urfW0C5Xq6UeaODvxCcS+IGVcuoJe2zR2i5ha\nSbXpNLWqWf5/1Ht7fzatfHYlpBatJqTJuEQdirMVegmtNBcLU9RrlcPDIgQ5cxC/3bULEClCz342\n8LOfLferacy1l/YCSSNNnJ34BGJfkDIusaNXN41xE1OrG/x6vY7JySmYZrnlg0kzL35c0YeweSm1\nn95DmoxL1KE4W6FXIONElibk7zsgbE8Qh3q7BzfjcCdnZzIWmFjGRhxBJmrHr7UfvnNnaIqQwvIi\nTZydIQWFEBw8eJAuueQv6dChRXrwwW/QoUOLdMklf0kHDx5c1jncfvvtvmeuWbOGnvKUp9CaNWti\nec69995Lur6OiMb4d8ZI006ge++913ftzTcv0AknbKK///uPUV9fht7whpfST35yN5133rmRnrVu\n3Tp69NF7ieg7/Dvfocce+wmtW7cu0r83w3nnnUs/+cnd9IUvvCdwXq2sV0FBQSHtkHGirq+jRx/9\nCdlcfBs98siPqFAohHLoN7/5LXrooR8S0WVEtImI3h7K4YKzP/KRt5FhWET0GXoW/Q19iwp08v/8\nlJ4YGiL67GeJ/u7viLLZ7rwAhdWNpE8kcQ9S3qZYkXQTqeWMTkT1mEdt5tKshiKqglG38jVVhKD3\nQCnyNkUdirMVuoVWo8hBnCjShkxzPYgsWNaW0HSioCZl3k7FsvlVq1WUS+PYSW/FY9QPEOE/+vO4\n45ZbYn03CvEgTZyd+ARiX5AyLrGi001jp4XJy71h9SpJyDbhQYekSqWCarWK6ekZ3h1yA2TdIb1r\nbFdlKA6oIrHeQpqMS9ShOFshLjj5sl1nUhAnBqnsiENBM2GHYnGby5HGbE0JxeIW13PuWVrC5/r6\nGx98K13caDSm0HtIE2cnPoHYF6SMS+xod9PYqXe/G9GJsA223Rzm5EZzmKB7eA8quj4A0yx72toz\n5QmiAWmn5U7nGxe6qQil0BrSZFyiDsXZCnHAa2+Y9HV7gg8yPgyzR97PNHNmTU/PcDuxFazZ1x5Y\n1hA++TdvwM+oDyDCQSJs144MtZ3NZKlV8W/3kSbOTnwCsS9IGZeuIK7Qa6sa/e0q7cj+fXJyKvCA\nYj9LtI/fKg3xCngPSV7jQzQAojKItoDIgKYd2fJBppvpUnF40hTiR5qMS9ShOFuhU8hsBVP+qbfk\nTArjwjB7JJMlnZjY0SgMJrJw8cWXNe7jjTT00SCu0dbgMT7Zr9BTcSzdCsMoY2lpSWrbwuaqOH35\nkCbOTnwCsS9IGZeeQFze/SjRiSh6/qyjZC7wcGErQvgVJpql81QqFd9aiYZB9FrX4SIo4hB071YP\nVFEPbXF50hTiR5qMS9ShOFuhU1QqFeTzJ7kOAIyDD7TEn804V2aPgpxJjFcXwVSGFhsOJmZrxhvz\nfBIdxGeo2DAeb6WjkKVBEM3DskZhGCWfbQubq6oNW16kibMTn0DsC1LGpScQV4SgWq2iVqu13K3X\nr8l/AEHNXsR1rDX7Vtc13rxP2aZb7p2yWjpceNHqgSqqR0iWB9uOJ02hO0iTcYk6FGcrtAPBxXZh\n7wYQ30g70zijprpG5VyvDahWq8jnR3187+VVolHoesFVcPxM+gr+h44EiHCQ+vAC+ifH5wdBZPLD\nhNu2hdWxzc7Oug4citO7izRxduITiH1Byrj0DDopWJVtcIMUGcJI3PYc1XyE7T2g2Hmd8muihGhL\npXFoWglE2aaHizC039Qm+Nq5uXl+6BlxzatVT5pC95Am4xJ1KM5WaBXOFB0vZxPlYJrlQJsh0ElD\nRyeY3TB8fO/lVXZAsDA5OYW5D83hTVmrkSL0/TVHYlN+s+/zhvFkqW0Lr2PzvxPF6d1Dmjg78QnE\nviBlXHoK7RQ2ychO04rSzXizvE7THOSeozKIdnCvyzBMs4zJyalGiFXMMUhlqBWpUZaedE3HpBz1\nQBXFs2XPf9F3MGrVk6bQPaTJuEQdirMVWoGbi6u+jXg+P4ZKpRJ6jyCHU6uNJu25+PmeOYZMfjCw\nIxfHmWX8vz/+48aE92VNDBZGfZ83zUFuS4IdVKZZRj4/AtMse1I/94DIClXLU4gHaeLsxCcQ+4KU\ncUkMcaka+De4dYTl/wfldTLpT7fnyDBKOOeclzWMga4PQNMKHUci5NfN8IPIBhBZmJjY0ZV3GuWw\n4p7XPD8UbIRh2J40pTSUPNJkXKIOxdkKrcDNZXWfg6OdWgGvw0k4i1qbywyISvwAwOSmt2//MxAd\nB5E69Axaws/6NIAIjw8O4mw9fBM/NzfPDxb2PcXmXji8LGsUuj4Ay1rvsk+FwihmZ2cVn3cZaeLs\nxCcQ+4KUcUkEcaoa+An7AN9U22Qn84A7N84LCwsuIhYh2JtuukmS7z/Ir7Obyng34Sz3vgRZPmf4\n3D8BojyIZluSvWtV0amZZ8s/r0UYRgm1Wg2AOwQvVDIUlh9pMi5Rh+JshVbg57LWvOGtOpycz/XW\ntLkjrwuc6w+47IlpltFHd+ANtKfRaOx327bhI/v2IZ8/GSzKUZdu4lk6kgmmVFSGkCet1WoSh5fV\n1D4pxI80cXaSRuCviOi7xPqBHyAinYgGiehWIrqHiCpENOC4/moi+gER3UVEZ4bcN/IPUiEedEPV\nwOn1N82yj/zC7s9y5cvwhmqJcti/f79EEWickzKkqg5iLpbFcjNNc50r5Sj4+cdwkh4FURmGcXxo\nDUG9XsfOnbug6wVfs5qgQ4L3ICZLg5K9U3k6VDTJVYXuIU3GJepQnK3QKrxcJtR7grjPCb+9utHn\ncCIaxuTklO95lnUinJ2K5+bmMTFxJef5YX6wmHc5rv5+5y58NqM1bv7JkzahaA5C19eC1R6cBGcv\nAmdNg1sAYhFEJeTzm7B//37pnHW9oFI/lxlBnN2tPW43R1IG4MlE9N9EpPOvF4joQiLaQ0Rv5N+7\niojexv9+ChHdQURZIlpHRD8kor6Ae7f7c1WIgE7SaTp5VtR8+mA9apYaJG8pb0cIvF4W0yzzOgT7\n+v7+PExzMDQasrS0BH+xW7D0KAsNF/lcN4D1MdjTMHat1E/Irg9TbGpHcjXKz0yhdagDgYJCNIQ5\nPZpFqkX+va4/mXvgc/DaBNFMMqz+SkQAguzJaXoBDxSZpOj91Ic/pSx/lqg5sBuTeZ0wbnlSkeY5\nAiILO3ZcKZlzDgsLC4p/lxkyzu7mHrebIykD8GQi+gk/LWWJ6F+J6AwiupuIjuLXHE1Ed/O/7ySi\nqxyf/ywRPS3g3u3+XBWaIIhsl0v3OMpmU3Y4IdoAXXfnXlrWEAqFrZyU82BRgkHusbHTjHT9RI8n\nJlp4uVqtwjRHPfMYg2GUpKFoZlTcBw+iIeTzm7iXaBFCzzpMeq5Y3MZTm/xFw0FGMqrkajOoZjid\nQx0IFBTaQyt2yN+bZh5CcIJtvOcb/GfzbBVe6ep8fgymudHD88Poo2Pxhj6toSL0VerH8ZQDSyfa\nApb+4+Z6onWuYuhmB5FsNs/nzGyXphXUQSABhBwIurLH7eZI0gjsIKKHiOiXRPRB/r0HPNf8iv95\nAxGd7/j+e4no7ID7tvEjVWiGZmTbicRoK3Nop8DWMMqNXHmB6ekZaFoeRCfyTb7I4/RKxZke8m5e\nzyDm4df7LyOf3yQtRM7lRnzGhmgUmpaHYaznBuFUEA3BNNcFSs8xhaQtPgPVTFa0meRqlJ/NchwK\n0w51IFBQaA+t9BFgXCU25+L6OojWg6gCEdGdnp5pOUIwRCXcQpnGJN5Of4MsfZ0fPmpghcdjHo4e\nA5GBhYUF11zn5uah6wUQrYW3V4yoGxMqQ8oBkwxCUoa6ssft5kjKAJSJ6ItENERE/UT0cSJ6uXg5\njuvub/VlERF2797dGIuLi63+fBUkiEK2tVoNs7Ozvs13HGjF++xtGe9V9/ET/CKE913TSjDNMnI5\noeV8Auxw7ThYB0q3Bz5o42tvsk9x3Mufm28XjnkjBBZ2736Lb6NOZPmKgZ25tPKUqeaNx4IkV6Og\nW2ljacfi4qKLr9SBQEGhPUR1SthcVZNyK0vLcef0C57NZo/02Za5uXlks0UQDePpZOAn1AcQ4X7K\n4EX0KYljxu98YV/rvo29WzrbrocT81IpmsuPKJzdzT1uN0dSBuClRHST4+tXEtG7iBVTOMMpd/G/\ne8Mpn1MpQ8uLqBGCbqSLyLrrBm3C3Zt9d4qNgHvzKgrCNvJNuYb+/hxMcy33yog110F0ALpeamy6\nZQVtXrANvYEg9Qd3QW+Bb96Hkc0WsXfvPszOzvpSjyxrNFRhyXtIcOtTh3vu2zUwKkIQD9SBQEGh\nfTSLVAt5ZTtCIKKv4/zPo0E0yw8LVRQKow0+XFhYkKZvTk/PQNfy+GvK4FEeGfganYy1ZEg2/SaY\nyEQO7kJkDaxPjnuzL3PuqGhAbyHgQNC1PW43R1IG4KlEdCcRmUTUR0SzRPQaYgUXV/FrZAUXOhGt\nJ1VUnAiaq9TEvxkM6q4b5H1uv0mXyCHdwIl6H/9aKO+MQRQFO4tzgwp+o87dr6ldgWmegAsvvKij\nrpPtFGR3iuV6TpqhDgQKCq3DyXdRFNk0reAQcVhsbPAZ114Dp9raxRe/iqcGbYQ3XbRY3IYjMhY+\nRbaK0N9TDrlsEaxbvcjxL4Oov+FsymTE4cCWKGXPrDfsg8yWRWm6prC8CDgQdG2P282RpBHYzU9L\n3yGiDxCRxsMrXyAmyXQrEZUd11/NX5KSHU0Qy60yFJa7KSP/KIcTodvPcjNHIGtuwwh8BkQ55HKn\nwDBKDcMgNv/T0zM8f9StO12r1Rwdi4PnLubillTdw42SM0TcedfJ5QotqxB2Z1AHAgWF1hAlOi2z\nC6ZZxgUXXMQPBSJCcJnHAbPo+LoOb1rns7I53MtThH5FA9hO7wBRDldeeSWIngRWLzDC/2SHkFxu\nDHYKKRxjHEQHQiMEKuraewji7G7tcbs5EjcGsS9IGZdlR7eIq1l33SBDEOapZnnyJRSLW2CaZZ77\neQD+gt5tIDoA0yyjUqlI5Ur7+/PcmJwKoUxhmuthGGXk81tha1L75+58dyylZxAslOzNLWVeo3y+\nedfJdjbjagPfW1AHAoU0odv80nrdACBEJAqFUYfjRjh1vKIRVbB0UvH1PHMSWaO4KmvhMX4Y+E/K\n4QQa4P9+NHfybOCOpXPBZKS9fXHcEtciHcjZ30ZFXXsfaeLsxCcQ+4KUcUkE3SAuP9nb3XWbGQKZ\nIbKLfG3tZ00rIJsVufvBuZpRulsy8jc93xOa1IvQ9QIWFhYCoit1sNzVcbgPJuPcSIU3CmunhkPJ\nhPYe0mRcog7F2enEcvBL68pC/uaLQoI0nx+BYZQ8EVvRL8CuIxskA/ds2tR44D56BTR6hF8zIHHq\nWGDNz9ypQUxsQigOWdi+/cVSeWjltOltpImzE59A7AtSxiUxdIO4gg4a8n4D7u6S3rxSvwzoUMNL\ntHPn1Q2lCKIc+vvzDck5UTPgPoBM8Gvdz9e0E33fy+dHoGlF6PpAkx4O/pA0O3TYLevDC6mjR2hU\nOLo3kSbjEnUozk4flrM3TdTnBEkrizqwfH4rLGsIExM7wPrUiIjtHhCxeoOn0rGOFKEMttPRHr4/\nFpp2ss8G2N2I511OHtZnpoS9e/dJ1yFrJBnlnagDxPIhTZyd+ARiX5AyLqmDjODkCgx2d0mvd2py\ncsrR9VEMu1GY3RzMrgfQtKLrHm5DIZcJlRmchYWFSApNpdI4NK0AXR9APj/GDwNTEJKhnRRSyz7D\nCparTe+vsHxIk3GJOhRnpw9x1pU12+BGjU67O/+KMcwbfPk34rOzs/x65qh5Hf0NHqUsQIT/pH6c\nQJ+X2ADT19ne2bmY/d2CaZZd6nSy9yXST1XUt7eRJs5OfAKxL0gZl1WDyckpuAvC5kE0jJ07d0kL\nyPwHCDsNJ0pKkDAU+/fvB8sPdfYnyIHoEjg7XgpCDjKOlUpFqowhpPG8DW/ijBDI0qdUhCB5pMm4\nRB2Ks9OHuCIEUTe4UbziMvlqluKzXnpwEWso0ww+QQONC/6BXgeNtnJnyjznfqZOJ/oSWNYQLEvI\ni867DiCXX/5q3zxl6bGtqsupqG8ySBNnJz6B2BekjEusaEa0SYYnZV59okHoesHnCRKdHVl+6DCI\nLPT32wcCZixKsIu8gjsSVyoVx2FBFKJZIFrgRqKGfH6kIQ8XJfog08uenJyKXJfRSg2HPLoSXqMQ\ndi8Vno4PaTIuUYfi7HQiCieF8UccG1xxf5EWpGnHw24WWQaTl3Y7fpyd7T93/d82UoQeoCLOoo/D\n7/W38PrXv75R2zY5OQXDKME018FbUxY2f+f7MowSLMvdcT5K1Fc1h1x+pImzE59A7AtSxiU2NPPO\n9EJ4UhYlKBRGpY3MarUa35i/Fm6d6cscqhAWiI5q5PwHSZ0yZaAyWEFYGUQ69zadCqJBaFrBlRLE\nuhtvAFEO2Ww+8N7e9+pVnQhD1M25zHAUi9taNhy98PNPG9JkXKIOxdnpRRgnNeOPKJHVMIj7271c\nREHx8WDNIjeBqIy+Ph2mOcg9+hYsaz0scxDfeOUFgMb6C1Qpi3W8aSS7V57bHJvrxfMYzxe4PTgB\nogGZrg805cjgmjUVIehVpImzE59A7AtSxqUjRCWkXiEfmffdWSjm9E7ZefN+77hb/m0AhuHvSOwk\n84mJK7n3Zy2ITPT1ubtS6voA6vU6arUaz1G175/NFvk84BjDjY1/O4aglShOXJ63Xvj5pw1pMi5R\nh+Ls1Yco/CG7RtNKXBFoFJpWwN69+yLcvwqizZz3F7kDxxlVzsEwSujvZ3agTL/Cx+k5DXK+od+A\n1jgITID1pxkA0bENJbpwcYhFEOVd9WqtHGhaUe5TMqXLjzRxduITiH1Byri0DafHxjDKsCx5biXQ\nW+HJsA7K3o0wSwva6tmMb+RGQ3w9jnx+xFXwFWyonClD9cY9CoVRXHHFX/JIwEbYNQ4A0TDvYeAv\niK5UKi2913ajOBMTO/icN0LkvraCXvr5pwlpMi5Rh+Ls1Yeo/DE3N+9I88yBRWLd0qEXX3yZ9P62\naEINTN5zK5hIg7t3jK36k8NTaB4/pmMAIjxAGbw065WWFpKhdeRyJ2L//v0NG2Gn+FQh62uTz480\n0kCjRlVVb5neR5o4O/EJxL4gZVzaQlBeudOzHTVCkAQhRX3m3r37INeJXoR3cx50L9uYiaLiU2EX\nFVfBtKtN+PsUCA9VDn19OrypTsXiNlQqlcie92ZetqB/t6M/i3y+iypC0CNIk3GJOhRnrz7IimhF\njxnvdXYEuAKW+++3U97P+UUTXsI52VtUPMi/90vsoCIe4Tv4KvVjOGPwzWT1lwAAIABJREFUrsJw\njDHOmaJ7PHNCue2KLEJQ5HUF0YQiFFYO0sTZiU8g9gUp49IWZB4byxqFYZQCw48yz3yv55VXq1UY\nxlpuBLaBaAjZ7Bqe48+8UJpWaFqUy4jdSfp74PS4s9CyV+JuI4gM9PdbyOU2guWZ2g1rDMMtmRpF\nRi/Myxb077Ozs7F491V4On6kybhEHYqzVycEf5jmerDc/S0+HvF7+guQRXhnZ2cbnwlybp155vPh\nFYogGsYAvRkfo2c3vvkO2gGdbofcqcN6B3idSoZRhmmuha06V+DXHM3/3ABNK4VG3RVWJtLE2YlP\nIPYFKePSFsK8yVHz03vBaxwln97rHTeMMpaWllCpVFCpVCLNlxUzC+NSh99rNQQWpnZ+rwyi43Hm\nmS8AK2o7iRuLtfCq/ESJeHQeIej856TC0/EiTcYl6lCcvXohkwJ1cpHf0/+nvs24iBAILrLTLusQ\nfVZE9JU1n7Q/+/tk4L95b4EHKIMX08ccG/YxsBQjW0Z6enrG0Z8AjVEsbnOo1Am74u16HB51V1iZ\nSBNnJz6B2BekjEvb6NTjW6lUkM+7vTdxe0CiqFYUi1saRcEyuHWiuapEi+v1F615vVZbQHQR9zKN\nQWj9Z7PCcyQM3DUg0nHppa9qyzDMzc3zIruRRoGbbK3en2nPefefeAK4/37gu98Fbr0V+MAHgM9/\nPtk5JYA0GZeoQ3F28kjqYB/WcV7mvCGy8IxnPItz6HoQGbjkkkt9kelMxuIbeVv1bffut4Aoyz97\nIl5LRiNF6DebNmGTXoS72NiuF/DKSHsdKoZRbnQbFpw6OTnVctRdYeUhTZyd+ARiX5AyLh2hXcMg\nNqayZl5xGZmwdCSbpN0FZ0GHAn/fAXkOq/P+3vcyNzfPvVvrpF4rZrAs9PUZKBRGYZplnprkvM6A\naGwTRZYu6J3k81sDDUzQz3RZNgGPPw788pfAt74FfPazwPveB0xNAa95DfDiFwNPfzpwwgmAYQDu\nXQFwzjndm1ePIk3GJepQnJ0skkzzlKf32AILlnUi7DqtIRjGOlSrVeze/RZks8UG7zEZ6OCmXplM\nruGIGaAyPkYnNnjm3dkjkM8WePRgA9zFy3I75nUq6foJjQhCs4h5s6i7eC8q8roykCbOTnwCsS9I\nGZdlh5v4/J1643+Gn6SDJEVFXr64h7xVvCgOPhGaVvAdIqanZ2AYJRSL/hzXhYUFEB0HJkU3BFaX\nYHHPP/NqaVqpkY7kDjXLuyFHNQKJpmgdPgzcdx/w9a8Dt9wCzMwAb3kLcMUVwPbtwFOeAhx3HJDN\nAt6NftAolYCTTgJOOw04/3zgXe/q/jp6DGkyLlGH4uzk0AtpnrJeMqXSOOdWkWJjRwiYp9/rgMnB\nVnmrgmhEyrO/R7fjR3QsQIRfE+Fs2gdWm1CEM5VHyJuynjbyaLNMUlrITQt0Ih3aq3V4Cm6kibMT\nn0DsC1LGZdnhD/u6Q6zdeYY7HSlIUlQ03GKb+nJDFUL0GGBkHhxZ8Oew7gnIcRXqEteD6EjYxWVl\nEK1p1Ca4ja+/G3I+P9ZYU61Ww/79+7GwsCA10FGk+1r2ND36KPDTnwL/9V/AJz8J3HgjcM01wKWX\nAi98IXDqqcAxxwCZDFwPDhuDg8DmzcAZZwCvfCXwxjcC73gHsLAAfPnLwA9+APz2t53890gN0mRc\nog7F2ckhbvngdmUyZb1kKpUKNE0U6m4D0QD6+4/k0QBviuYw/zzgjxAcANEwJmg/HiHWaOx2MnAi\n6SDawTl6BE5p6EJhFBdccCF0vdSwGSKNSazxpptu8vE30bDP7rXyTnrhgKbQGtLE2YlPIPYFKeOy\n7FgOEovyDPfm3L6GeZQMeIu5hOefSISl/e3rvQVvREMoFEYbBO9OUzqZP8efPvSc55wOwPb+GMYp\nkKlYiDWxxmcinWgY2Wyx0QAnahG309M0YAxg/1//DX716U8DH/sY8E//BOzaBVx0EfC85wFjY8Ca\nNUBfn9O6hY8jjmCfe97z2H2uvhq44Qbgox8FvvpV4Mc/Bg4diu3/wGpAmoxL1KE4OznEyd2deLZl\nnvSlpSUpl2Yygz6+1rQSNK0Iu19BFszrvw0DVMJHyXZg7KeXQadBx8FhEU5+Z9Fdi2/2B/khgUUh\nstk8NK3AU5mEdPQi7AhGriNHmOrvsvKQJs5ul8AzRPTypCcfMLfQH55Cd7AcRapRnmFHArbBsoZw\n8cWv4uTu9gCJyEGtVpN6nIrFbVI1CdZUzJKkHYnmNzeCaNTzmTEQGVhaWkK1WsXS0pKjfsFOsdK0\nEubm5lGr1fhhwSlryoyeYZSQz5/UKCBeeP8HcIoxgOflNuLlWh5ff+UFwFVX4dA55+ALmSzupGHc\nT3kgaFPvHZkMcPTRLBLwwheyyMA117BIwSc/ySIHP/0p8Mgjsf98FdJlXKIOxdnJQvBqWHpMM8Rx\nsHA6O1h9VglMqtnPpUSvBvPsbwGRhb179/miDEQWfo8s/IiGACI8SISX0tEuO8A2/c6mlOslhxBR\nXLyRHzLy/NmL/FphXyxkMmZHjjAVIVh5WAmcHXXP3uwmJSK6moj+iYjOJKI+InotEd1LRJ9KepEB\nc470Q1SIH8tRCBVVjlNs9mUefiE1Kk/7YdeZ5iAWFhZgmoOezw9C04oeD/0iiGa5carD3/xmCETr\noWmFgC7QdeRydorV7OwsCnQcRugU/BEt4mU0h7+mv8deyuFDpOGLVMBdlMGvo27yifAoZfE/dCyq\ntBm3ZDQ8fMEFLOd/ZobVAHzjG6wm4PDhrv3sFJpjJRiXuIfi7OThTamM6tDxS33atNOOZ7terzua\nMy6CyCvbOQShLsQiu0xlyO9ZfwITdBweoX6ACN8gHcP0TjCnzaLjft4IgeFTyrM7GduNJVkkou6b\nn7eGoB30nAKcQih6ibM73bM3u/mniGiWiC4nog8T0W1E9O9EtC3phYfMOfpPUqFjxHkIaDf/NOgz\nrNDY6+HfAKKMT+ZzenrG1ZyMSIdlrUd/v8W/FtKh8y5Dx1J7LBAd5ThUiAOGLTfKvv4SyvQrnEwf\nx+mk4+W0C2+gPfgHegU+3K/jkT/4A2DDBjxuWUDEjf7jmsZUep7+dODss5l6z9QUfvOOd+DP9AK2\n0hTW0Bb00eMdGWqF5UEvGZflGoqzk0W7XmlnipBpln2a+2H3EBv/SqXSUN0RdV35/Emwc/P3BXDp\nous5zt4qJfo1PkzPbXDkDWRBJxMsClzgh4JhGEYZp512OpwNJc877xUS1aMcmJNHRBWG+X0OgDmB\nqhAFzXFxq1IZWjnoJc7udM/e7OZ3Ov7eT0R1IjKTXnSTOUf7Ka5ixEU2caohtHOvZp+RS9r58/IB\nOFKHrgdL/xGNxM7nn9nIv7aLisX9++iLOILK2EKvw5lUwIV0HK6mDPZTBh+hHJYogx9RPx4ms2Gk\nmo1Hsln8kAhfoQwWKI93Uj+uoifhAprFGXQrNtOdGKR1qHzuc6Hvp9tSsArxopeMy3INxdnJImre\nerP6JU0rROr4Pjc3z/P9c3zjb8EwhHTzHr65dkZmz+YcLNJ5jnfNVaR/zs3N4w+MEn7IG409SBZe\nSrvhTwEy0d+fa6jGnX/+K6BpBeTzo7CsIUxM7Gh46E1zEH197vozNt/jwWoI3D1lwqSrFdKJXuLs\nTvfszW7+zbCve3Eo4xKOuDbxceY6tnMv92fqIDoA0yw3jFWlUsHCwgJ27tzFG3eNgeXlu/sAGEYZ\nO3fuckQCTuXkfiUyZOEoWodtVMQL6CpcQrvxZsriu3/4R8BZZ+GhzZvx0z4Nj1B0ac0HqYi76QT8\neyaLe5/5TPz47LPx0O7dwIc+BHzxi7h/aQnf+NKXUP/lL10qQ7VazeeBixKertfrmJycUiHoFYJe\nMi7LNRRnJ4so/Ou1G7KmW8XiNui68JzbakFO3X1bUcibiulUfKuDeeNzMM3NfNP912BditdAKi39\ny18C73oXntB1gAjf7Mtgi7UOul6AaXprutaBOX7sWgNvxGFhYaGhDGf3ehmDZQ1h79592L9/vycd\nlRUim+ZmxbGrDL3E2Z3u2Zvd/HEi+g0fDxHRYcfff5P04gPmHOmHuBoR5yY+TjWEdu5l9x2YAvPc\nnwqiHM4551zufbIbfmlaCWef/RIQPRlEp6KfHsOT6Wf4PbodL6Kj8Soq4TrK4j30Evwr/SlupxH8\njAiP8fzTKONX1Ifv0Yn4Ap2OD9KfYA+ZeB1djz+neTw/txGvff6fIE8mRGi6vz/nO5TJDmveQjun\nYWq1s7IKQfc+esm4LNdQnJ08wvLWg+wG29i7N+aMk21qNM31MIyy6yDBUoK83YnHwVJvxvifzJNv\nGCfyDbsQh9gAVtQ7wK+18L5/fAcObd/euNnXxk9FUSsgl9vMIxa6Y54i5cjuecA42VlYPIx8/iTX\nexD8KU9rkqvbKa5dHeglzu50z574ArrwQiL8CFcn4tzEJx0hsAuBbWk4nW7HWjLwNMrhLMrj1bQL\nk/QmvJfOwmf6+vFN6sPPqQ+PU3RpzTodgW/TFnyOing/PRtvz5r4yrkvw3l6AWdYGzCcySOfMWGa\n6xoeIjv0DYgOyLaqUAXeQjR3DuwihIRdf38epjnYMKbT0zONvNtOlSzU4aA30UvGZbmG4uzeQBAv\nVKtVWJZ7o29Zo77Io93bJbhjMJNcLsGOENTBlNkKIPoEWBRXHAImAu/DvtZxzQtfhF+vWQMQ4UHK\n4BzKwl9zUAJzGp0suc8AvJLUbG52hMPZ2NIdlRbSpcH9bxTSjzRxduITiH1ByrgEIm5JszjVEELv\n9fDDwI9+BHzlK8CHP4yHpqbw9qyJWXoRKvRcfIc24GALm/zHifALYgeET9M2vJfOx/Vk4NW0C39G\nn8BT6V04ngxo9HWHkcjBNMsSo8eM0/btf4alpSXMzs5i79593IPGcl4NYzNYtGKeb/b9h7LZ2Vmu\nbT0EO23JgNez1aoKSNB7DopCKCSLNBmXqENxdm+DySD7N+S1Ws3HHU7ZZ8Mo8YNEHaLwtlQax+Tk\nFK/XEj1bhJCDxg8GW/j3Z/jzqvDLj27CqymL/8d5/5t0EjbQf0KeijQK5oi5VnKfDSAykMmYPK1U\n8LTNzWJj73eozcNWO5KkMSk+XRVIE2cnPoHYF6SMSyjiljTraDP50EPA978P3HYbcPPNeOj663Hf\nK16BQy95CXD66XhsZASPFQqAZFMvG49RBj8jQpX68SnSME0vwW7ajVfRm/Ei0vG1G27A9xcXccM/\n/iNuuukmT8hbNKMRxuh8TvIsLP28570AlUoFO3fugr875RiINJc3f8eOK6Hr7noFZqxqPqNlWUMB\nTXhy3JjWfQannYOcvBCwGFthuELnSJNxiToUZ/c2qtUqNE2oqLGUx2x2jc8DLmxLsbgFhlHC3r37\nePrmIHdyDELTCqjX65KaqEUJ/wlPvfvfivQfmHekc95IT4JBhyBztjA+L/L7fELyjKHG/d02wV2X\nBsj4cxGalufrEM0pmb1op5eDwspEmjg78QnEviBlXJqiqx7hJ54Afv1roFYDvvhFViy7dy/wV38F\nvOxlwB/9EbBxI9DCRv8RIvz2iCOApz0NOOssPHzRRXhL1sLFtBsvoE9jKy3gSLKQaehDz4N5msTX\nBWSzed96vYej7dv/DLpeRDZ7LOxmMyUQPQdEBixrBMwjlPcYFb+SD/vagtPbxHJTR6BpBej6gOtQ\n5g/L10F0LFg4vQpvSDpKqpf35+z3cNV981a5r8kiTcYl6lCc3duwIwSLsDvyWi41HZmzwTTLPIff\n3VyxVquhUqnANDfBluysgGgthHyn4EuiNTDNckP555m5EXyfdx3+DRVwLr0HtrPEq07EIhn9/Tnu\n/TdgRyU2wN2gbCNmZ2d9Cki6PuBykgibIaK/lrWlweedNHZTWLlIE2cnPoHYF6SMS3fwxBPA//0f\ncOedQKUCzM4Cf/d3wI4dwEtfCjzzmcCJJwItaOjDNIH169lnX/pS4LWvBd76Vjy4fz9epBcwSh/F\nk+gg+ugOqeoFU3nYyIl9Csz7Lja4dRBdAlZQtt5H7ALeol3TLMM013LjJAqWj4EdPRgEUT/ceaoT\n3Hg5lyea2bjzUUX+v3ez7jaoonvxBv6cNWi1aM2bGiTqD9xG+wC80Q7VoyBZpMm4RB2Ks3sbQTUE\nTp6Q1afl8yOSJl8b0d+fQyYjOvxuBcvjz3MOHeT8J+oE1kPXS5i8/m9x37XXsr4rRLiD+rCB/hXO\ndEr2eXfBcX//UCNia3PoLfDXDdgpUM3SamUNL02z3HFtl8LKRJo4O/EJxL4gZVxaw+OPA7/4BXDH\nHcBnPgP88z8Dk5PAX/4l8OIXM6/82rUAl3OLNPJ5YMMG4NnPBs49F3jd64C3vx344AeBL3wB+N73\ngF/9ih0yJIha/MyIWRTrshBvNpuHZQ2hUBhtaRPtLxgbgF00JmtU80zY2tgmstmi5xohn8eiAlHS\ncebm5pHN5n3GStNKjbqEsFQvZ4dmWZ1DsbjFFZ1otZmQQveRJuMSdSjO7m1E2SQHRQj8PDTEN+1e\nvrQdJ6JgmEmNTqFIA7iZ7IjywxdeiEJWbPxHQDSAbDaPSy99FVhR8ilgkd1r4OxMb5onO2zKDjhT\noCYmdgCIZnviFOdQWPlIE2cnPoHYF6SMC8NjjwH/+7/A178O3HILMDMDXHcdcPnlwPbtwO//PnDs\nsUB/dGlNDAwAmzYBz3kOfvzMZ+EfsiZ2mcfiAi2Pz19zLXDPPcBvftPx1FspfpaFeKenZzA7O+vr\nUpzPj6FSqUif6Sf5XWAeJ1le6jBEiPu0056DpaUlnHPOubC9VLaXyxkVEGsLSteylZNE1IOFs4Vi\nRdhnnREBu5jPOWfRUdPtzYq7pkShM6TJuEQdirO7izhSRKPwhPea6ekZTE5OeSK558Ju9OjkJyE7\nOg9nw7JtpOH7tBYgwm8oh1dqLPXT7hC/HkQGTjvtdO4cOhHOzsEsUlBpFDm7C39LmJqawsLCQkid\nQLTDj7ffgsLqQZo4O/EJxL6gtBuXRx8FfvpT4D//E/jEJ4B3vxu45hrg0kuBP/kTYHwcOOooIJMB\ngjb23jE0BGzeDJxxBnDBBcBVVwHvfCfw4Q8zZZ8f/hD43e8aU4hbrUiGqBvVMHL2e6eYUlCQd92d\nsjPADdMi/BGCAYg82r179/FCNIt/fwIszchfXCZSkvL5k3zzqNfrAVEG5t2ShaODIwKLkMv0MdUO\nrzdLqQz1DtJkXKKO1HN2goizm3wUnvDq9TMHxQAyGR1M5Sco6uoVXHgCl9ObcIjbqG/RGDbSPSiV\nxh2pj6KQdyvnt9dL7psD0QD6+3OYnp7h/DvC6xKulL6bubl5HjkN7rjstU+ixkGJM6w+pImzE59A\n7AtKg3H56leBG24Arr4auOgi4HnPA8bGAK63HGn09QFHHgls3Qo8//nAX/wFsGsXu+/HPsae8eMf\nA4cOtTy95QqZyvLsvQYpbC6CtBmxD4DVBCw2Di/e+7G6hBLslB2Ry88UNvr7N3LDw2oKLrnkUn7/\nAyByNtthMnvZ7IZGRKJerwcqbgDg6kXeOgQmidffb4U2MfNHBOp8DYNgnrdBbhiZ1ncr3ix1WFhe\npMm4RB2p4OweQHhdEuCNWMb9u90sZZHxpuC4eb5538h5SQfRcSAaRpEexM10boMIp+l0mPSwa/6s\nAZr3GWXu9BCc765HEGmX+fzW0HRJu5uyu+NydIeMSr1cTUgTZyc+gdgXlAbjcsUVDTL0jUwGOOYY\n4NRTgRe+kEUGrr0WuPFG4FOfAqpV4H/+h0USuoTliBB4EaSfz9QqyoFzqVQq0PVj4dT3N811jaY6\nzvvZhcojsFN26sjnR7CwsIBqtdroNSCUMljRXJ0bI7/ChWGUMDc3zzf8fiUiYZx1vSD9d6IjuWGy\n19Y8IiCKhYX+9wy/FzvQnHnmCyJ5s+L0LipEQ5qMS9SRCs5OGLLfVZmzRHTh1fUBaFohtt9tt4Oi\nDMta73nuGFgapuXhLQOs/4AFoiOxlQzcw1OEHiIL55EGVhcwDE0rNcQRmOPGW7As0iJv5IcLp2LR\neo/iUbCgQpiTKapTSjUmWz1IE2cnPoHYF5QG47KwwA4Fb3kLy/3/t38DvvEN4Oc/Bw4fTnp2AOLv\nZwAEe6NlBxBdH4BpljEwcGrDuHnnUq/XsbCwAFn6jOwQ4f2eSNnR9QGpZCm7XmziZ7jhEnUEojBu\ngnujCj4DRDSMSqWCarXKPV4FuL36eX4fYdjY4WT//v0+A2QY62AY5UaxsG385FJ8zqLlIO+X8not\nP9JkXKKOVHB2gmgtbdJZvOtWQGvld9vJ1bLnezmGOUycaT5jnC/7waK338KraKcjRcjECA2Aqb1V\nQHQAmlZscD4TX5ClRa7n9/X2gDEc/CtkTuWSy0Hv05kG5bUzsvUr+dHVgTRxduITiH1ByrgsG+IM\nOYd5o4M8XV7PuTPPXtwvnz/JtxE3jFP49+3v5fNjju8Jz/p6EBVdqT1i3e56A2fPA4sbnxmIQ4Vl\nnYhcbjM3fG5NbrcB2gOmvsH6IGSzed7R0y1FapqDju8LA2Rix44rXcXCLCR+LPypSBv5+tjXsnQv\npaSRDNJkXKIOxdmdIUrapKwLL+vgOwvRQTjq77aXqycnp3zPt6xR7sUXnDgBd0rlFETUskAWDtBT\nGx+epj+FSV+GXWsgHCJuzs9m842uyJY1hL179/GDwjUSTr6U86ez7kCHppWkTi1ZgXSYg8QWhBBS\n1HuUA2WVIE2cnZQBGCGiO4jom/zPB4loBxENEtGtRHQPEVWIaMDxmauJ6AdEdBcRnRly7+g/SYWe\ngMzDYhjlRuMbuQdGdPF1G0D/9X4PuTsaYHekZN/zFqrtayI7J9KF7HxTtxEbg64XPEVwTBLVW3DM\nNvDrQGQgkzExPT0jiUSgcZhgnrAxfogogWiDNELi1cxWEYLeRZqMS9ShOLszNPtdladWCu1+Fo30\nOj1aeZZhlHwcIyIULFVSpAQJkYYFvmFfxBh9C/fQEQARHqIMzueNwwoFwb97QjlfRFiFY4U5SgY5\nx+Y4N9b4Z8Sm3S2NGtQ/wOnwauYgsaO8tsKRcqCsDsg4u5t73G6OXjAGGSK6j4iOJ6I9RPRG/v2r\niOht/O+n8JeaJaJ1RPRDIuoLuF+bP1aFJFCv16USoUQbG/n3gNcDUwJLxwmuG2DefmE8mJRdPj/m\nqhfwypVecsmlPoNBNOhqXy/mbBtF4ek6FXbdwRiExKfY+AuPU1A3y1qtxtOKboQ3jL+wsADT3Ogy\nhvn8GHI5IX8aLoEXpIjRLN1LSZIuP9SBQKEdtCILKuvRIkuLlMG/MWbcqusngHXuHfU9f/fut6C/\n3+Cbc6PBuZdSDg8TazT2bdqIEbobzNlRxM6duxxpQccimy34oqJeB4U9txpY5GMJbkeKv25ASFFH\nUU9qduhSDpTViWacHfcet5ujF4zBmUT0Ff73u4noKP73o4nobv73nUR0leMznyWipwXcr/WfqEJH\naDd1SBgo5lnxbsRZ/r4gVdsDUwHzyDtzUW1vO/OoD3LiL0OoTHg9QUGeLr9+/zAmJ6ekc5d57pl3\nykQ+PwpdL2Hnzl1NexDIi5mZh0kUP7P12KoZdpTjALx9EkS43luA3UyxKc6frUJ7UAcChXYRVRZU\n5oCJ6s0Oj74uwjBKjcguAEe/gI0Quf15+ho+SC9vPPw9NMhVhNi37J4BguOZfbj44st8hx5vLYNX\nyS2TMbmN2cYPI25pZ00rNeoSmjk9bHu1DYZR9jl1lANldSLCgSDWPW43Ry8Yg38molfzvz/g+bdf\n8T9vIKLzHd9/LxGdHXC/ln6YCp2hXSUa/4ZchLDdTbkKhdGGqo8t8emW98znNzWu8UrJBfUekNcl\nHA9vl+AgLw9L8SnA32BnGJdeehle/OKX+Dbl0d6DOAx9ArpekBQ62+sJPpQ0TwlS6E2oA4FCM3R6\nSO/Umz0xIbr8Hg+W4minyVjWaONgUavV4FU/20LH4y46CSDCQ5THy+kozrn2oULTCsjlhB1wp5E6\nVd68tmd6esbH/7o+gFqthsnJKZ5meTSE8IOmlZpGHbyYnp6BYZRQLG6R8rpyoKw+RDgQxLrH7eZI\n2hBoRHSQiI5wvhzHv9/f6ssiIuzevbsxFhcXW/jRKrSCTgyLbEOez49C0/KOzSw7JBQKzCNz8cWX\nSTbA7JpicZx72Y/2bdAXFhYizF0cSEQ4/ahAwrfzcRd9RiuTyTkONhZYZ87FwFxV+cGE9TkwjM3w\nFgJ6uy3X6/VGFKFUGpdK/qlc1t7F4uKii6/UgUAhDHFJATu92aZZxuTkVIs1BIsgeh3nuK2wFYQs\n3HLLLQCA2dlZsKgnQPQELqF/wMOclL5DoziJPgkiC5r2ZDARhePBFOAEB5/g4jGhpCbW7t3Ms426\nP/JhNzJzRzJ27LgSQdKj4WtXaUGrGa1wdjf2uN0cSRuC7UT0OcfXd3nCKXfxv3vDKZ9TKUPJoxMl\nmmbSbrI8V9FcRmyAg65xy93lXBto5/PFfXK5UyT3yWFqym0kbcWOrY6Nut1gR9dL0vsw+dAc8vmt\nPiPufw+Lkns0lwdUTXLSAXUgUAhC3BtSJwdGPWDYnC/EFLzceySILExM7GhECAr0VVeK0E2kw6Kt\nYCk9FnRdRATCuFzGi+4iY1af5S9urlQqPjtVKIxyvvYLTgS9T6W8piBDkwNB7Hvcbo6kDcHNRHSh\n4+s94qWQvOBCJ6L1pIqKewKdGqggL5XIcy0UtrnIl2gMhlFyXeMvRh4GyxMNVs9wbuxNs4wLL7wI\nsh4BudywK1c1WNObeZympqZge8TE2AZv3qr3HdkKQ8Nw62Xbc8nnRyJ7BFUu68qFOhAoBCHuDWkY\nfzfvCXOAc6yTp4TKDtvM12o1vPVl5+Nu6gOI8FsivIIGYPcBqIDTgvw3AAAgAElEQVSlHB3gn3M3\nGjPNzdC0QqOmQFbfZau7MaU44VDy1hnI6sWY7RAOnXEQ5aT1YlHel8LqRZMDQex73G6OJI1AjodS\nio7vDRHRF4hJMt1KRGXHv13NX5KSHe0hdLr5DPJS1et1iVwmiwrI5UXZNbo+AMMoIZ8fkdYO1Ot1\nvvle5EZoEZpW9HSx/DaYkpHtlV9YWPAoF8G3UV9aWoLfi1XghjLYiNfrdUeBcA1ez5vwcrXbOKhV\nqDzY5KAOBApBiHtDGnTAaBY1CK5dEnLLdRAdh3876ywc1nWACHfScdhEt3AnyjWc40SEdyaQ94Ra\nmrzJ2gBE9FUoxckEFMScnXbK3VfAPlA0e5fK2aLgRRBnd2uP282RuDGIfUHKuCw7mm0gw/49rAeB\nrNmLNxdfRtBhz6tUKmA5+kOwpUKPws6dV8OyhmBZQr96HqJo2TDW8sOJX+nH2QiMKWPocHcb1uHt\nmhkslwd4G50JI7dckOUoh3kL1cEhXqgDgUIY4tyQBh0wZF3cZb/7O3deDcMoI5cTKnF7QDSPPJXx\nL1SAOGXcRAVY9GXOp5cFOE3KYEXKFgzjlMCDCHPmbOC8PQOZ5HJUO9RJHYXiPQWBNHF24hOIfUHK\nuPQUmhXByYtq7R4EQtWhUBiFphWh6wPS1vFRCfqmm26CV0mIyMLCwkKjYJht7Ce4kRpzGDtxvVu5\nyDas14OlDIlOx3UQbUAmY0DXBwKNuLtQr3WvlRftGqygiItMli+u4kYFN9JkXKIOxdmtIc4NqfD2\ni4iqrOuwLC3JKRnN+gXoILKwmUzUaD1AhN+SiVeSCbvwWEQV3KlBLPXnEs59m0FkYO/efdL57t79\nFgd/+9OMvA0qo8iwtlpHoaDgRJo4O/EJxL4gZVx6BlFyVOWhYHcPArFR7yRcLoifeZjc0qZEw43C\nY9awrMSNlB0NcHYfFko/Yg120ZpXZo8dNpaWlpoaJzvC4K5BaDVHuJONuvxwJvJ07XeuCpe7hzQZ\nl6hDcXYyEJxomoMNwQN3Ko38d1teT1XGX9AV+B2vF7iTNmOTtDHYOp9X3+5i7I4SB9cviP4EfjEI\nMdeoPKjqAhQ6RZo4O/EJxL4gZVx6BlFzVCcmdvCUHPdG3dsavtWCOrEJn56eCcl5XWx06QzuCVCH\ns/uw03D6JfCERvcGCLWNqKjValKVjFYOPZ0emvzrdyt5lErjmJ2dVWobXUKajEvUoTh7+RFUB+Dk\ntqCIppeLc/RbzNJQgwzeR9uRo9/C3xm4zp/nbirJxjoXnxSL23x84n4ui8Lq+vEwjHLTIuIgHlTK\nQQqdIk2cnfgEYl+QMi49g1ZyVJeWlriHfFFK4q1udv1dkP0dfZ2pSUCQh3wcRDeCyEA+vynQiyZS\na1gvgBIuv/zVro6dUdFujrCtuhRewNzq82WNe1SEoHtIk3GJOhRnLy/cSkHyzXDUuq/NdCe+RycC\nRPgdWbiQzgHrJbAZrDOx1wmjg9UMrANL/cmD1QL4DybBEQJ54bG4PmiTX6lUfGuyRSbcXK64TCEq\n0sTZiU8g9gUp49JT8G4ww3JUm22Go26W3YZD5JnWIet86dy0B3vITZjm5ka7+mq1yjfedofOIIPT\nKkR6VCuqQvbhZxzeeod2NurOzUDQO1dqG91BmoxL1KE4e3nh7iUQfLAPOxRMvOa1uIi0RorQd6kP\nv2+d0JD+FOmg8qaJNX4ouBFCyY19PcSdNOXIakEy3mmlFqper3Onhy0EIZOqVlAIQpo4O/EJxL4g\nZVx6Dk5ib+bp70SxSMAfWhbPm+fEPxxoTOweBWPIZovco+We6969++Dt0Nlqao5s099O/r/8EGOh\nUBiNbaOuVIaWD2kyLlGH4uzlhZsz5JwYxkX1H/8YH+xncqIgwvvpeciRiVxuM0xzEDt3Xt3gNifX\nuSOL82BFxs5aLdbPpVarhT8/Au9EiXSK+9iHI+bgabUwWWF1I02cnfgEYl+QMi49j257l/2b5D18\nAz8MTSuGysuJ3NpcbpgfBtwqFoXCVp7a5N6AT0/PRJqbWzovB00rBOS92sbRuS6vcZKFx4vFbZid\nnVUb+BWINBmXqENx9vIjTHIzLDXnOzffjIfWrgV4itBF9D4INTXWaExEVS3ehditCud97jnnnNtI\ntfTXACxC9IrpJNIp61TsTI0KclApJTWFKEgTZyc+gdgXpIzLikCrm9NWvdSCzG0P1AyayXj6U402\n+0Lquj7gy9MvFrf50oVk85J78wcbvRXcvQiGQDTSCJ8HGaeotRXKuK0MpMm4RB2Ks7uDVqOtYRto\n01yPy7JWI0WoRhmcQh9zRBhEb4B5sNSbA9wJs+jjJW+E1DuPSqUCXT8Wzl4xprmuaW1D2HsI48ig\nXjaqTkohCtLE2YlPIPYFKeOSOgRtZpttciuViq+7cFjRnDzVyK2Icf75r/AZimw2D8Moo1gcb6gm\nyeZVrVaRz3s1uMeRz484ZFUXfYeQoELsMIPmRJhxU1GD3kKajEvUoTg7frSacuO93plik6PP4P3U\n3yCtWXoRBrL5AOW2Mh91MNW4qo97w+YW3AXZwt69+9p2akThyCiFyUp9SMGLNHF24hOIfUHKuPQs\n2slFDwtfN/PgBH3WKxka7G2/hnu5TgHrNnyN6/Ol0jhvyuPvPRDkGQuKEIgQtawXQT4/xg82wcYp\n7B1GlX9VUYPkkSbjEnUozu4MMk9/K2kwYUW4T8lvwvf6MkBDRej9Df7Yv3+/xMExDKJzA3kwjLfD\n1I80bWNHksyy99TsWhUhUIiCNHF24hOIfUHKuPQk2vXyB21mo2rhez1DzRrvOK83jBJM82Q41YQK\nhVHMzs6iVqs5uhp7jaLcMybuz2oIhuGsIRAI6kUQFiFohiDj1sk9FbqDNBmXqENxdvuQ8WcQZy4s\nLEi5JSjH/s7Xvx6HTRMgwl19GWymjzbd3LP0IdZbIJMxfR3aJyen4O5NYPNjmPoRkYFCYVtTvu/G\nu1VKagphSBNnJz6B2BekjEtH6EYKSVCRWCde/la08J1rihIKFtf5n8GKk0Vq0OTkFK8nkHXeXAyc\nV61Ww/79+7GwsOBbq2ik5j3EsI6i5baNUyvyrwrJIU3GJepQnN0eonPjIvr7c9D1Ilj00a2o405X\nrCJHn8G/OFSEDp1zDt725mulm2O2wc+B1Q2wGoJcbgv279/vS0ms1+vcCTEo5e0g9SOiIRjG8R1H\nCNp9xyqlUiEMaeLsxCcQ+4KUcWkb3So8rVarMIz18BaJtevl70QLv9VQsHhGoTAKb2qQ7WV31xlc\nfPFlvg29V9ffG7IXG/5icQsMo4S9e/e5Dgfi+jCFpChrjyr/qpAM0mRcog7F2e1B1rm3UBh15emb\n5nrYDcIWQVTkG+1T4dTcn5i4EkQWTqa1+C4vHH5M17F4wYUw9CKKxS0+NSIAjk3+AT4Hpo62tLQU\nUqMlRBPGQZTD5ORU4xq3GMQAiKYaDqRmHZQVFJJAmjg78QnEviBlXNpCNzeItm6/24u+tLTUlpc/\nyvfD0OpBol4XXYDHfYcXkYdfKIzCMEoN+VGvt19WrEf0bWhaEaYpVDpKYA16tsJZRNetTbsKifce\n0mRcog7F2e3B5mzhkGC8ITjITj8UOfl1vsl21wqIiMIr6W/xW8oBxFSExjImovRbcR8+LGjaWhBZ\nsKwtITVadQSpvjkdJF5uUh57hV5Dmjg78QnEviBlXNpCu6oKUaTtWJ79Zte9TXNzpO7E3UKtVmvU\nAkRBmDELO6z4c2xzsFWPaiAy4EwvYt67Oj8sFKSHkKhNc6IYT2d6lDK0ySNNxiXqWG2c3Wpxa9i1\n09Mz0silOz1S5OT7i3VLpXF88D3vwWx2qPHNf6FXIE8ng0jzcBNzfMg6stuHj0W4Uyjd/VRa4Xu1\n+VdYCUgTZyc+gdgXtMqMS1xoJ0IQJcWoWq1K8+wNw/YMtUv87WpSt6uuMzc3D00r8k39Buj6QOhn\nZYcsFgq/kYfCS2AFyEK/G2BhdFaQnM+PBubNNnv3raR/Rb1WGejuI03GJepYTZwd9+9ltVqFaY66\nOMayRiVNt+Z5dMB9eNiiFXBo40aACA+TgYvpvSB6G7/OyU2s+VgmY0nnZHNd1XHo8PdTAVp3xjih\nOEih15Amzk58ArEvaBUZl7jRqvcmygHCH9ZmefZRO/s2m2srm/ogjeuoaTitHpr81y/yiIDumwN7\nN4uuCEFQ3myzebQyz6jXqsZmy4M0GZeoY7Vwdjd+L2u1mm+TT2RJPfKGUUImY3GOGcfLKYeH+Cni\nwWOejPFsAUTrJPcb4GOY/9sen/ffHyEQf4ZLPrdSE6U4SKEXkSbOTnwCsS9olRiXbiGqB6aVFCNn\nYa4zz76TOUZRJ5Jrc8vD5lHUdaKu2flsd36t7vC8uaX3iDaivz+P/v48isVtLoPn9ag1m0crP5sw\nGcBW3rdCPEiTcYk6Vgtnt/J7GfXaarUKyxKCDUzpR3T1FRB8JORFLboXN9H2xo3nMho+/L5Z1Ot1\n7N+/H7ncmIeb1oHo+oajgj1rBsL7r2klaFoBhiEOE8dxx8dG130Y/7sjnkQ5GEYpUh2X4iCFXkSa\nODvxCcS+oFViXJJEvV53SNVF95Z3GuoVG+OFhQWpsRS5rbLGY2Ea11ELmaMYJZkXq1ar8VQjUdBX\nh1d6zzDKqNVqvmdGbSRkWUONOoCokqzNZAAFVNfO5UOajEvUsVo4uxsRAvu6RXglnb18W6/XsdUY\nwHdoA8BThC6hHIi+BNMso1KpBEotO2VFWaNG78ZeRDYXwVIh3whvpMEwSr5eAuzQUISmFbCwsIBK\npSJ9H4qDFHoVaeLsxCcQ+4JSYFx6OU/SuUHVtIKv8Uy3IGTxmI62iWy26DI2orMmq1fwF9m5DZ2t\ncR00b9lGnNUQFMDSfYZ9NQRBRnznzl3ca+YsEJ6HqEUgsjAxscM3h7BNgTe9a2LiStd8JyZ2NE3/\niiID2GweCvEiTcYl6kgDZ0dFK2mZUa/1c8EOeWrNhz6E/6dpABHuJg1byADRjgYX5fNbYVlDOPPM\nF3AOXe/jUsabOrzef2ftk31gcKeJPuMZz5bcTxxmciA6BrJmjYDiIIXeRZo4O/EJxL6gFW5cejlP\nUkbKwrPUTWL258kugkiDYdiydLacZxXezsHCk+Q0nEJTO8iTJlun7YmrgOhGn2SezItVKIxC10vc\na+b2xLOIQQVEi9D1Ad87bOYVcyoEhUUMotU4BMsAAkqidLmQJuMSdax0zm4VcaoMea+TccGgOYiH\nX/GKBol8iP4YBVrkXFaG39tvgegTINoPInfBMtEwduy4UpL6MwCmmsa4mR0mALsJmlAtysN2hDjF\nFIY5F7JDh4yHFAcp9CLSxNmJTyD2Ba1g49LrXpCkwrazs7NgkQHA9mZvhKYVMTk51ciNtQ1QeMFt\nWJMwsU4Waajy+9VhmmuhacfD21zNuXZWWFeCU6rPMEpcOlREBHLc+OUcxpAZxEql4lp31P8PlUoF\n+bz8ENQMskNSN9O+FMKRJuMSdaxkzm4Xcf8ueesEBA+cRHfhzowJEOFxw8CEtRZETzi44njI6pmI\ndnEnhlv8wDQHUalUcPHFl8Guh7L4ocIAkQXT3Ax38fG3Pfeq8YPBItwHCiHHPI58fkTKX4qDFHoN\naeLsxCcQ+4JWsHHp9TzJpA4sdoRgUbrZD8p79RbnRl2Lre29FayzZwkitcdt5PxqHpa1hRvFdS5V\nDdsL/3YQ9cMfOs9h585dvnk284p1qpwk3kW7UqwK8SJNxiXqWMmc3Q7ijgJ77yeipefRATxEFkCE\nx4aHcf+XvuTjPF0v8caI3giBCW96pSgeZg4OC0TXQNQtMF4ekNznFP5vl4A5QoRtEw6SUyS8Ko8Q\nKCj0ItLE2YlPIPYFrWDj0usRAiC5sO3ExA7IlCtk6UBiIx7mSQo6fLmLpf3Fv8y4MU+WXO9bGNoB\nLC0t+d6ZYZRhGGvBOhIz+T/2J1PbkKVfyYqb/ekBzesigrAS/t+tFqTJuEQdK5mzW0Xcv2uy+5W0\nEt6b0RrE9uNnPAMH//u/XYILTv4W/FQsbuObcwPutMs6NG09dN3dZd3JhaxO4CQXn5rmZmhanqdN\nFuBvwlgASxO6hj+XRU5lNQQKCr2KNHF24hOIfUEr3LishDzJpMK2S0tL0HW3F8ppTFtpeBNkmN0h\nd2eTHTgMX9X1bHkDso0uOT3/Jn4PWJh9A5g37lVwFvY1KyAcGDgVhlEGkxy0DXc+P+JLPWqGXo9M\nrSakybhEHSuds1tB3L9r3vuN0N34dp8OEOEQ9eE1Wg4Tr3mtK4Igc5bU63XMzs4ilxsGkb+RpK4P\n8DRKORfKIgQiejs5OcVrDkR60VqwqKuBfH6sMadKpdL1ejQFhbiRJs5OfAKxLygFxkXlSQYj6MDU\nbqMyy3L3R/AX2vrD6YXCqOsZssOFUM/wev/q9Tp27tzFPWbHg6Uk7fM9J1xi0BuWX+zI26giBL2D\nNBmXqCMNnB0V7fRQCbqPN0rIUoRYvcA9tBZj9K2WOMItQ+xWCNq7d5+Ue0xzE4gsGMbx6O+3oGnF\npk0UmSPkE8siSKGg0G2kibMTn0DsC1pFxiUtaPUA1E5/gCBMT8/AMMooFv0h9FJpHJpW4BKnLJyd\nzealhbdzc/MOL5itnuH0/s3NzfMIxwYQ5ZDJWMhm88jnR9CsORgg9y5aFjvMdBpRWgmRqdWANBmX\nqGO1cXbY71oUx4bzGtMs4/yzX4Kb+vUGKSz0D6BAv3HwxAbYkqDhEQm3tPI6ZLP5RiPJoLTMvXv3\nuTjUyY9MoGHcxVmMI42OG1QqKPQC0sTZiU8g9gWtMuOy0hFHgV27Yfiwg4TTA8e8ZgcgOnUGHTZk\nKkPO+/k9Zax4bmFhIdKBpllDsk49bSoylTzSZFyijtXI2bLftajRA2fd0EYq4VvEDgOPZbO479pr\nYUmLhP2cFDa3oPSdVp0x9XpdIlFaRj6/SaUkKqQCaeLsxCcQ+4JWoXFZqWjXsx9XhCDKQcJ/TXie\nfpD3r1qt+qRBnfJ64nMipzboYGRHNNwKSp1s5tVBoHeQJuMSdaxUzo779yaKfLCz4/rLKI/fUA4g\nwvdpLZ5mlFCr1XDFFa/mHn7RXXgHWH1SOLe0gygcylTbTB6pYA3LVEqiQlqQJs5OfAKxL2iFGpfV\nCJkxKRa3YXZ2NtBYBEUU2kl5accjx/JrN4Q+Q+ZhC4sQiJ4IpllGPn8STLMcmipQLG5p1DzI3klY\nL4Go71MhGaTJuEQdK5GzuyEdGkU+uF6vo6SVcCOd3iDNm+lcFOlB6PrJjr4nJogmGlFNEYmsVCqx\nRRTFfJpxKEtDEtLNSkVIIV1IE2cnPoHYF7QCjctqhNg0ywrVisUtUiMbJTzdai2C0N/3HiS8Dcya\nGWvv9UGHFlZD4JbXa/1gYl8j60xKlAs8VLTyPhWWH2kyLlHHSuPsTn5vglKF2Ia5uXzw/V/7Gr5F\nGYAIh4hwBb0JrNGYPzXIKYAwMbEDplmGYTwZRCYsy8+xrRQzezf8Qc4YxTEKaUeaODvxCcS+oBVm\nXFYjnBtmb9Eu62A5LzUcQRGFdnJRncXE3g69sg19pVJBLrcZdvdifw+EYpH1GRCNgYIODgsLC9i/\nf39DHrW91CV2zezsrETydBxEB5oaXiU32ntIk3GJOlYaZ7f6eyM20aIHgNdRsHPnLribdtVBdCym\npjyRvvl5HM6xFKEf0Dpso9c0IpZMxvMY15wKha249tprsbS0BE0rwpY5HvRxbKvFzF7nSVDNgeIY\nhbQjTZyd+ARiX9AKMy6rDX6P0SIPb9tFu6LhjddwBMlutqpWYXcilhcTyzxae/fug929mPURCPPQ\n2w17/EpDXqMaf4RgCES1pj0JlPeu95Am4xJ1rDTObuX3xpnmJ+OcWq3GJYhzPg7J5ViUYH72X4Ar\nroAglI/26yjSf/BN/QCIjgNr8uXtfs6irbpektzf5lhZpDYq/wQdctp5VwoKKxFp4uzEJxD7glaY\ncVlt8HuMqiAacXmQwjzc9mZ+zLUxbyVNiCkBuYv3RKRB5tFifQq8ShlWQ3bPL6s3zA84bgMYZhyj\n1EA068HAnjsIVkTYvNYh7J4KySBNxiXqWImcHeX3xv37XvVxjojwscOCv3M5UR0b6F/xrb5+9gFd\nB979bswduFmawtjfn+OpR95o6wG4IxBujnU3Y7Tn1ixCKeNFGRcrjlFIM9LE2YlPIPYFrUDjspog\njxB4PVvBOfBsA74FstSdKLA/796YG0Y5cNNuF+rZxlAcIOSyegMgsnyqHs3C5+3m8Irvs46gfm9g\nFJlBpTLUG0iTcYk6VipnN/u9cf++132c447weTuXz+AcWsCDVASI/n979x4mV13fcfz9heySTUKW\nBJegXHaDFAJ9iiSYgBWaDUYqFgNankC0cotXtBK0CKG1oLYIlUrVgsojF1EMgRBJvEFKyRZphSxJ\nCEgSBMOuihKGS9DoEnP59o9zNplsZnbPzuVc5nxezzNPzsycmfn+Mnu+5/zmd/O+gw92X7ly53uX\nmpFo332PDVsbBra2rt0jJxTn2EpbKEvlxXK5WDlGGlUj5ewkTwKtwF3AOuBJ4HhgHLAMeAq4D2gt\n2n8+8HS4/ymDvG/kL1KSMfAXo49//BO73R9slpzhNkGXn6J095U4i7sdlVqAZ7DPLNVqUWoVzjia\nz6NMXSjp1Ugnl6i3Rs3Zex7v13jQjefY3fLcwBXTR+89yq9n9s4DeNHezV545pkh3ntNOCbqL0q2\nBDQ1jfGRI8f56NHH+MiR4/bIsZW0UA6VF0XyoFzOrtc1bj1vSZ4EbgXOD7dHhP951wCfDh+7FLg6\n3D4aWB3u1wE8A1iZ963wa5U4lbpQj/oLUtQm6KGmKO0/AZcagzAwnqE+MxikPHbnrB5DxVSv5nP1\n2c02VQgaS6mL6M9//l995Mj99hhHtGLFCn/x4Yf9pY4Od/DXMJ/XNMq/e/uCyO892IxjQ+XYSloo\n1R1I8m6QCkFdrnHrebMwmFiZ2Vhgtbu/ccDj64Hp7r7RzA4Eutx9kpldRvCffk2434+BK939kRLv\n7UmUSeJVKBTo6emho6ODtra2ks+3t0+ir285cAzwOC0tM+jtXU9bW9uQrx/uZxYKBVavXg3A5MmT\nB33PSj57OBYsWMjcuRfS1NTO1q293HTTDcyZc1bNP0dqz8xwd0s6jjg1es4uPt6BsnlpnyVLGD1v\nHnv/4Q9sb29n/ec+xwGnnjqsXDLw2L/88k/x4Q9/sC55plwMInlSKmfX8xq3nkbE+WFFJgIvmtkt\nwJuAR4F5wAR33wjg7s+b2QHh/gcBPy16/XPhY5JTbW1tg558enp6aG7uoK/vmPCRY2hqaqenp2fn\na2t18uo/CTc3d/CnP/UMeQFey88uZc6cs5g582SdpEViMthFcfHx3t3dvUdeGjPiEHre9S6mPhKc\n+xfv1cSOz1zBmeecM+TnDswlSRz79c5nIhmUyWvcpCoEI4ApwMfc/VEzuw64DBj4M1FFPxtdeeWV\nO7c7Ozvp7OysLErJrI6O4OIcHqf/l7itW3t3/ko3XOUu+guFAnPnXkhf3/LwJP84c+fOYObMkxM9\nSZY6SeuXvPTp6uqiq6sr6TCkCsP5QWBgXjqMH7Jo88+Y/Mh2ttDEp/gS1+84iZa/P5nps06r6BjW\nBbpI/UTM2XW9xq2buPsohU3DE4ANRfdPBH5AMJhiQvjYgcC6cPsy4NKi/e8Fji/z3uU7e0kqxDXj\nRK36tw7WLz8rC+9EWXhIkofGEGRKJWN2+hdFfP/IDt+EuYNv2KvZp/DooDlEx7BI+pTK2fW8xq3n\nba/6VTXK86DJ5FdmdkT40NsIRmEvBc4LHzsXWBJuLwXONrNmM5sIHA6siC9iqZUFCxbS3j6Jt7/9\nI7S3T2LBgoV1+6w5c86it3c999//DXp711fcj76/+1HQ0gD93Y9Wr17NK6+8UvSLH1TbElEPxa0Y\nr766kr6+5cydeyGFQiHp0EQyrVxu6OnpKbn/ggULuXTepXx5x97c9loPrThbTjuNtzSPYhVN4V67\n55BCocCyZct0DItkRGavceOugRTVgN4EdAOPAYsJRmCPB+4nmJJpGbBf0f7zCUZea9rRjMrqDDil\n4m5ubt05U0hT0xhvbm5N7UwbWWnFkNK/NjX6Lcs5ezg57YUXXvCj92n1bo72YBahJr+4aZS/sHHj\nkIsOjh59pAdrFOgYFkmTcjm7Xte49bwlNYYAd18DTC3x1Mwy+38B+EJdg5K6Gmqgb5pdfvmnuOqq\nGTtn79i2bTuvvfa/vPZaMG5g5Mjp3HXX1UPOMJSEWo+nEJFAW1sbN910A3PnzthtVq9SOeDVm2/m\n/7b8nlbWsoGJzOZOnm75EHN6e5k582TuuWcBsGuWsuKWPXg9cCQ6hkWyIYvXuIlVCCR/snhhWjxg\n0H0Hl1xyJtOmvZnZs+fz6qu7KjbNzRMZN25c6ioDMLyLFhEZniFn9tmyBS65hMO/+lUA7uZtzGUR\nr/JLWrb2smrVY0yf/o49BiXv+QPK14C3MHr04ezY8WsdwyJSU4msQ1BPjT6nddZlaY78cmsZrFz5\nEMcdd2LZNQ7SSrMMpZ/WIWgwGzbA7NmwciU0NbFyzns56c6lNDV3sHVrL9dddzUXX3xZyVwCe65Z\nMHLkdJYsWZjKlkiRPGqknK0WAolVlubIL9fFafPmzZn8xV3TEYrEaPFiOP98+N3voKMDFi7kuGnT\n6L12V8V8sG6UU6dOLZFnvs4pp5ySZKlEpEGpQiB1EXWhnrQqFAoDZhDavYvT1KlTM1OxEZEYbdkC\nn/40fOUrwf13vxtuvhn222+PXct1oxwzZgzd3d3MnHkyvb3rlWdEpO4SmXZUGlucU4tWo1Ao0N3d\nvcfUff3xz549n23b/kRz818xduwUWlpm7NYS0NbWxtSpUzufCmUAABMWSURBVKs6SZeLQUQyaMMG\nOPHEoDLQ1ATXXQd3372zMjAwN95//wPcdNMNtLTM2Jlj5s79O4477sTd9pk6NRibmESuUI4SyYkk\npjaq540MT2HXCGoxtWgcC5eVW+SnVPwjR+7n9913X83j0UJDMhCadjS77r7bvbXVHdw7OtwfeWS3\npwfLjf05b+3ateE+yx1WOCz3lpbx/vWv35hIrlCOEhlcI+XsxAOoeYEa5eSSUdXOeR/HCSgNKw9n\ndU0Gqa9GOrlEvWU+Z2/Z4n7RRbsSxhlnuL/88h67RcktK1as8JaWwxzGO0xxGO/77HOI77PPfrHn\nCuUokaE1Us5WlyGpqd37xMJwphaNa0XdwVYXrSb+WsUgIhnx7LNBF6Evf3lXF6HFi2HcuD12jZJb\nxowZQ1/fb4HlwEpgOVu2vEBTUwdx5wrlKJF8UYVAaqp/zvviPrFRZ+CJ6wQ02Im5mvhrFYOIZMD3\nvgeTJ0N3N7S3w0MPwbx5YKVnIIySWzZv3kxLy+EU58CRIyeydWsPcecK5SiRnEm6iaLWN7Le/Nwg\nKhkHEGcTdX/XpLFjJ5fsmhTnOIZyMUj+0EDNz1FvmcvZW7a4z5vnO/v9nH56yS5C5QyWW8rlwP4x\nBHHnCuUokcE1Us7WwmSSKnEuXJaGhbrSEIOkRyMtchNVpnJ2Tw+cdRasWAEjRsAXvwgXXVS2VaAS\n5XJgUrlCOUqkvEbK2aoQSOroBLSL/i/ypZFOLlGlMWeXPO6WLIHzzoNNm4IuQgsXwvHHx/f5IpI6\njZSzVSEQSan+Xwqbm4O+vPVsLZF0aKSTS1Rpy9kDj7tbvvEVzlq9MhgwDDBrFtxyC4wfn2ygIpK4\nRsrZqhCIpFChUKC9fRJ9fcvpX8G0pWUGvb3r9YthA2ukk0tUacrZA4+7Q7mXu+w0pvn2oIvQNdfA\nxRfXtIuQiGRXI+VszTIkkkKa8k8kfsXH3btYymPMYZpvZ8uECfCTn8AnP6nKgIg0JFUIRFJIU/6J\nxK+jowPf8izXcg5LOZ1xbOJHezXx+wcfhBNOSDo8EZG6UYVAJIXiWg9BRHZp++Mf+cXB+/Mpvs1W\nYP6IFl799m287ogjkg5NRKSuNIZAJMU020i+NFJ/1KhSlbOvvRYuuYTtBx3EU5/9LG2zZum4E5Gy\nGilnq0IgIpISjXRyiSpVOXvHDrjqKvjoR2H//ZOORkRSrpFytioEIiIp0Ugnl6iUs0UkqxopZ2sM\ngUidFQoFuru7KRQKSYciIkPQ8SoieaQKgUgdLViwkPb2Sbz97R+hvX0SCxYsTDokESlDx6uI5JW6\nDInUiRYXk+FqpObnqNKSs3W8ishwNVLOVguBSJ1ocTGR7NDxKiJ5pgqBSJ1ocTGR7NDxKiJ5pgqB\nSJ1ocTGR7NDxKiJ5pjEEInWmxcUkqkbqjxpV2nK2jlcRiaqRcrYqBCIiKdFIJ5eolLNFJKsaKWer\ny5CIiIiISI6pQiAiIiIikmOqEIjEIO7VT7XaqkjlanH86BgUkSxRhUCkzuJe/VSrrYpUrhbHj45B\nEckaDSoWqaO4Vz/VaqvZ1kgD1KJKU86uxfGjY1AkPxopZ6uFQKSO4l79VKutilSuFsePjkERyaLE\nKgRm1mNma8xstZmtCB8bZ2bLzOwpM7vPzFqL9p9vZk+b2TozOyWpuEWGI+7VT7XaqkjlanH86BgU\nkSxe4ybZQrAD6HT3ye4+LXzsMuB+dz8SeACYD2BmRwOzgaOAU4EbzKwhmmikscW9+qlWWxWpXC2O\nHx2DIkIGr3ETG0NgZs8Cb3b3l4oeWw9Md/eNZnYg0OXuk8zsMsDd/Zpwvx8DV7r7IyXeNzX9UUX6\nxb36qVZbzaZG6o8aVRpzdi2OHx2DIo2vXM6u1zVuPY2I88MGcOC/zGw78A13/yYwwd03Arj782Z2\nQLjvQcBPi177XPiYSCa0tbXFelEQ9+eJNJJaHD86BkVyLXPXuElWCN7q7r81szZgmZk9RfAfWKyi\nn42uvPLKndudnZ10dnZWGqOISN10dXXR1dWVdBgiIhLBMHJ23a5x6yUV046a2RXAZuADBH2u+ptT\nlrv7USWaU+4FrlCXIRFpJOoyJCKSHVFydi2vcespkUHFZjbKzMaE26OBU4AngKXAeeFu5wJLwu2l\nwNlm1mxmE4HDgRWxBi0iIiIiMoisXuMm1WVoAvA9M/MwhtvdfZmZPQrcaWYXAL0Eo65x97Vmdiew\nFtgKXKiflEREREQkZTJ5jZuKLkO1pOZnEckqdRkSEcmORsrZWqlYRERERCTHVCEQEREREckxVQhE\nRERERHJMFQIRERERkRxThUBEREREJMdUIRARERERyTFVCEREREREckwVAhERERGRHFOFQEREREQk\nx1QhEBERERHJMVUIRERERERyTBUCEREREZEcU4VARERERCTHVCEQEREREckxVQhERERERHJMFQIR\nERERkRxThUBEREREJMdUIRARERERyTFVCEREREREckwVAhERERGRHFOFQEREREQkx1QhEBERERHJ\nMVUIRERERERyTBUCEREREZEcU4VARERERCTHVCEQEREREckxVQhERERERHJMFQIRERERkRxThUBE\nREREJMdUIRARERERyTFVCEREREREckwVAhERERGRHFOFQEREREQkx1QhEBERERHJMVUIRERERERy\nLNEKgZntZWarzGxpeH+cmS0zs6fM7D4zay3ad76ZPW1m68zslOSijkdXV1fSIdSMypJOjVKWRimH\n5Ece/2ZV5saXt/IOJWvXuEm3EFwErC26fxlwv7sfCTwAzAcws6OB2cBRwKnADWZmMccaq0Y6sFSW\ndGqUsjRKOSQ/8vg3qzI3vryVN4JMXeMmViEws4OBdwLfLHr4dOBb4fa3gDPC7VnAHe6+zd17gKeB\naTGFKiIiIiISSRavcZNsIbgOuATwoscmuPtGAHd/HjggfPwg4FdF+z0XPiYiIiIikiaZu8Y1dx96\nr1p/qNnfAKe6+8fNrBP4pLvPMrNX3H1c0X4vufv+ZvZV4Kfu/t3w8W8CP3L3xSXeO/4CiYjUiLs3\ndHfIgZSzRSTLBubsel7j1tOIOD+syFuBWWb2TqAF2NfMvg08b2YT3H2jmR0IvBDu/xxwSNHrDw4f\n20PeTqYiIlmmnC0iDaZu17j1lEiXIXe/3N0PdffDgLOBB9z9/cD3gfPC3c4FloTbS4GzzazZzCYC\nhwMrYg5bRERERKSsrF7jJtVCUM7VwJ1mdgHQSzDqGndfa2Z3EozW3gpc6En0dRIRERERGb5UX+Mm\nMoZARERERETSIel1CCpiZu8ws/Vm9nMzu3SQ/aaa2VYze0+c8Q3HUGUxs+lmtilc3GKVmf1TEnFG\nEeV7MbNOM1ttZj8zs+VxxxhVhO/lH8JyrDKzJ8xsm5ntl0Ssg4lQjrFmttTMHgvLcV4CYUYSoSz7\nmdliM1tjZg+HczunjpndZGYbzezxQfb5SrhIzWNmdmyc8dVKhO/rveF3tcbMHjKzY4qeuzjMEY+b\n2e1m1hxv9JWJUOZZYXlXm9kKM3tr1NemVaVlNrODzewBM3syzD2fiD/6ylTzPYfP77ZgVRZU+bfd\namZ3WbDo1pNmdny80VemyjJnL4e5e6ZuBJWYZ4B2oAl4DJhUZr//Bn4AvCfpuCstCzAdWJp0rDUq\nSyvwJHBQeP91Scddzd9Y0f6nESw2knjsFXwn84Ev9H8fwEvAiKRjr7As/wZ8Jtw+Mo3fSRjbicCx\nwONlnj8V+GG4fTzwcNIx1+n7OgFoDbff0V9O4A3ABqA5vL8QOCfpMtWozKOKtv8CWBf1tWm8VVnm\nA4Fjw+0xwFONXuaixy4GvkMGzu21KDNwK3B+uD0CGJt0mepZ5qzmsCy2EEwDnnb3XnffCtxBsNjD\nQH8PLGLXKO40ilqWLMzCEaUs7wXudvfnANz9xZhjjCrq99JvDrAglsiGJ0o5HNg33N4XeMndt8UY\nY1RRynI0weqPuPtTQIeZtcUb5tDc/SHglUF2OR24Ldz3EaDVzCbEEVsNDfl9ufvD7v5qePdhdp93\ne29gtJmNAEYBv4kh5mpFKfMfi+6OAXZEfW1KVVxmd3/e3R8LtzcD68jG+kLVfM/lFqxKu4rLbGZj\ngZPc/ZZwv23u/rt4wq5KVd8zGcxhWawQDFzA4dcMSCJm9gbgDHf/Gum+mB6yLKG3hF0HfpjWbhBE\nK8sRwHgzW25m3Wb2/tiiG56o3wtm1kLw6+bdMcQ1XFHK8Z/A0Wb2G2ANwVLraRSlLGuA9wCY2TTg\nUILp27ImFYvUVCnyMRT6APBjAHf/DfDvwC8Jyr7J3e+vU5y1FKnMZnaGma0jmHHkguG8NoWqKXPx\n8x0ErWaP1CXK2qq2zKUWrEq7aso8EXjRzG4Ju0ndGJ43067iMmc1h2WxQhDFfwDF/b3SXCkYykrg\nUHc/luDi7Z6E46nGCGAKQZeIdwCfMbPDkw2pau8CHnL3TUkHUqG/Bla7+xuAycD1ZjYm4ZgqdTUw\nzsxWAR8DVgPbkw1JhmJmM4DzCXO2BWNxTidoqn8DMMbM3ptchLXl7ve4+1HAGcC/JB1PHAYrc5hv\nFgEXhS0FDaFUmS1YsGpj2DJiZPvaZA9lvuf+8/717j4F+CNwWUIh1lyZ7zmTOSyLFYLnCH7561dq\nAYc3A3eY2bPAmQQXObNiim84hiyLu2/ub5Zy9x8DTWY2Pr4QI4vyvfwauM/dX3P3l4AHgTfFFN9w\nRClLv7NJZ3chiFaO84HFAO7+C+BZYFIs0Q1PlGPl9+5+gbtPcfdzCZaF3xBjjLWSikVqqhTpGAoH\nEt8IzHL3/m5UM4EN7v6yu28n+Pv8yzrHWwvDyRv9XccOC/P5sF6bItWUmbA7xSLg2+6+pNzrUqaa\nMvcvWLWB4Lwxw8xuq2ewNVJNmX8N/MrdHw2fXkRQQUi7asqczRyW9CCG4d4I+mX1D/RoJhjoc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"text/plain": [
"<matplotlib.figure.Figure at 0xb60beb0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# create subplot, define subplots outside of plotting function to be able to adjust them.\n",
"fig, axes = plt.subplots(2, 2, figsize = (12, 12))\n",
"\n",
"# some handy variables\n",
"year1 = 2000\n",
"teams_year = teams[teams.yearID >= year1]\n",
"\n",
"def correl(data, X, Y):\n",
" # eprforms OLS\n",
" results = sm.ols(Y + ' ~ ' + X, data = data).fit()\n",
" return results # summary of complete regression\n",
"\n",
"def correl_plot(data, X, Y, ax):\n",
" # plot data and linear regression fit\n",
" data.plot(x = X, y = Y, kind = 'scatter', ax = ax)\n",
" results = correl(data, X, Y)\n",
" Xfit = np.linspace(data[X].min(), data[X].max(), 100)\n",
" Yfit = Xfit * results.params[X] + results.params.Intercept\n",
" ax.plot(Xfit, Yfit, color = 'red', linewidth = 2)\n",
" return results\n",
" \n",
"# plot slug percentage\n",
"SLG_results = correl_plot(teams_year, 'SLG', 'R', axes[0, 0])\n",
"# plot batting average\n",
"AVG_results = correl_plot(teams_year, 'AVG', 'R', axes[0, 1])\n",
"# pl0t successful base steals\n",
"SBP_results = correl_plot(teams_year, 'SBP', 'R', axes[1, 0])\n",
"# plot on base percentage\n",
"OBP_results = correl_plot(teams_year, 'OBP', 'R', axes[1, 1])\n",
"\n",
"axes[0, 1].yaxis.tick_right()\n",
"axes[0, 1].yaxis.set_label_position(\"right\")\n",
"axes[1, 1].yaxis.tick_right()\n",
"axes[1, 1].yaxis.set_label_position(\"right\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### discussing results\n",
"From the above graph, clearly a higher OBP, AVG, and SLG are correlated with higher amount of runs earned by the team throughout a season. To make a better comparison between the methods a linear regression can be used. Statsmodels is a module that allows you to implement many different statistical models, here ordinary least squares (OLS) is used. In the figures you can see the linear fit of these models and below you can see the full results of the regression. Both the standard error and the CI give a measure for how much we expect the parameters of the fit to vary. In order to determine which statistic correlates best with runs, we compare $R^2$ values.\n",
"\n",
"$R^2$ gives the correlation percentage between the statistics and runs. Looking thought the summaries we find that: $R^2_SLG = 0.840$, $R^2_OBP = 0.805$, and $R^2_AVG = 0.663$. From these results we can conclude that SLG and OBP both have a high correlation with runs earned (i.e. >80% of variation in runs is explained by a variation in the statistic). While AVG has a significantly lower correlation percentage. The former two statistics are thus a better measure of a teams offensive capability of earning runs.\n",
"\n",
"Successful stolen base percentage is not correlated though. Even though it seems stealing bases is mostly successful, their contribution to runs earned is not clear, or too small to notice. A successful steal usually (?) results in a single base gain, the other statistics include more base gain methods (like OBP takes hits, which includes total of 1B, 2B, 3B, HR, and also includes BB), which can be an explanation to why the effect is very small. A second contribution could be that stolen bases are relatively rare compared to other ways of getting on base."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: R R-squared: 0.840\n",
"Model: OLS Adj. R-squared: 0.840\n",
"Method: Least Squares F-statistic: 2512.\n",
"Date: Mon, 21 Mar 2016 Prob (F-statistic): 1.95e-192\n",
"Time: 19:02:50 Log-Likelihood: -2372.0\n",
"No. Observations: 480 AIC: 4748.\n",
"Df Residuals: 478 BIC: 4756.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept -459.3213 23.969 -19.163 0.000 -506.419 -412.224\n",
"SLG 2893.3187 57.726 50.122 0.000 2779.891 3006.746\n",
"==============================================================================\n",
"Omnibus: 9.224 Durbin-Watson: 1.801\n",
"Prob(Omnibus): 0.010 Jarque-Bera (JB): 11.022\n",
"Skew: 0.221 Prob(JB): 0.00404\n",
"Kurtosis: 3.597 Cond. No. 43.7\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: R R-squared: 0.664\n",
"Model: OLS Adj. R-squared: 0.663\n",
"Method: Least Squares F-statistic: 943.9\n",
"Date: Mon, 21 Mar 2016 Prob (F-statistic): 3.15e-115\n",
"Time: 19:02:50 Log-Likelihood: -2550.4\n",
"No. Observations: 480 AIC: 5105.\n",
"Df Residuals: 478 BIC: 5113.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept -766.2226 49.062 -15.617 0.000 -862.627 -669.818\n",
"AVG 5765.6377 187.665 30.723 0.000 5396.887 6134.389\n",
"==============================================================================\n",
"Omnibus: 1.211 Durbin-Watson: 1.846\n",
"Prob(Omnibus): 0.546 Jarque-Bera (JB): 1.228\n",
"Skew: 0.121 Prob(JB): 0.541\n",
"Kurtosis: 2.950 Cond. No. 89.2\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: R R-squared: 0.805\n",
"Model: OLS Adj. R-squared: 0.805\n",
"Method: Least Squares F-statistic: 1975.\n",
"Date: Mon, 21 Mar 2016 Prob (F-statistic): 7.28e-172\n",
"Time: 19:02:50 Log-Likelihood: -2419.6\n",
"No. Observations: 480 AIC: 4843.\n",
"Df Residuals: 478 BIC: 4852.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept -987.2760 38.896 -25.383 0.000 -1063.704 -910.848\n",
"OBP 5257.5131 118.309 44.439 0.000 5025.043 5489.983\n",
"==============================================================================\n",
"Omnibus: 2.666 Durbin-Watson: 1.847\n",
"Prob(Omnibus): 0.264 Jarque-Bera (JB): 2.461\n",
"Skew: 0.166 Prob(JB): 0.292\n",
"Kurtosis: 3.111 Cond. No. 76.6\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
]
}
],
"source": [
"# OLS data for fit:\n",
"print SLG_results.summary()\n",
"print AVG_results.summary()\n",
"print OBP_results.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Obviously runs is not the only important thing to win a match, a team also needs to prevent runs when on defense. You can easily see this by plotting runs vs. win rate, which has very little correlation. In order to find out more about a teams total perfermance you need to look into pitching and fielding statistics too."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0xb026530>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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CYsuRSrncaunpWeO5vqfnUvvsDHcb1RMO/QL3xhvfFwgMCLsuareelO8gTpSU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\nE5GXRORlAF8G8A7ocbTl+ETkGIAf+N6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"text/plain": [
"<matplotlib.figure.Figure at 0xb01f6b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"teams[teams.yearID > year1].plot(x = 'R', y = 'Wrate', kind = 'scatter')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To improve on the results above you might want to look at average runs per game (if one finds out that some teams have a lot less games played per season, not something that I would expect, although the number of games could vary over the years by significant amount). Or maybe separate per league to get an idea of how leagues compare to eachother (though it seems teams do play interleague matches, something I've never heard of before either). \n",
"\n",
"As mentioned before, to dive deeper into offensive statistics you could look into how the statistics are distributed by player instead of per team. Below are some examples of histograms to start out with this. In the case of single players, it is probably a good idea to merge the appearances table too, this allows you to select only players with with a certain number of games (At Bats could also work for that, see below). Without filtering out players with very few games, the data looks very rough, because it is possible to get very high values of statistics that way (see first graph below, blue histogram). Also, many players will have zero values due to no games played as batter.\n",
"\n",
"One of the more interesting things I would look into is to calculate [on-base against](https://en.wikipedia.org/wiki/On-base_percentage), on-base percentage of all batters against a specific pitcher. "
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xb8191f0>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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JG3SoXa2D4HTrVtDk10uWZA86lEkUi5BiEaIJgw41pU/iA+BUM2sfdECfAawG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\nEpeShIiIxKUkISIicSlJiIhIXP8f1VTLBEfO2G4AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xbad0110>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x8748750>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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9TvsgZ/18j/ZPlt5R3O5cSf8K+BcjCWq2grxFYFaQdLqk13UMTQEzc1d3Lf5J\n4PKiwTzn+BrjmdXGWwRm804APi5pPe3fpH6S9jTRl4CvSnq5WO6+iHinpHcCf1L8BOYPgWeB/5gg\nt9lQfBhqM7OG89SQmVnDuRCYmTWcC4GZWcO5EJiZNZwLgZlZw7kQmJk1nAuBmVnDuRCYmTXc/wd9\nz4Ehwx21GAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x915e370>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# just some quick examples of player statistics. \n",
"AVG(batting).hist(bins = 60, label = 'all players') # every player in database\n",
"AVG(batting[batting.AB > 100]).hist(bins = 60, label = 'AB per season > 100') # one per player per year, players with > 100 AB a season\n",
"a = batting.groupby('playerID').sum()\n",
"AVG(a[a.AB > 1000]).hist(bins = 60, label = 'AB per career > 100') # over complete player career, players > 1000 AB in career\n",
"plt.xlabel('AVG')\n",
"plt.legend()\n",
"\n",
"plt.figure()\n",
"OBP(batting[batting.AB > 100]).hist(bins = 60) # one per player per year, \n",
"a = batting.groupby('playerID').sum()\n",
"OBP(a[a.AB > 1000]).hist(bins = 60) # over complete player career, players > 1000 AB in career\n",
"plt.xlabel('OBP')\n",
"\n",
"plt.figure()\n",
"SLG(batting[batting.AB > 100]).hist(bins = 60) # one per player per year, \n",
"a = batting.groupby('playerID').sum()\n",
"SLG(a[a.AB > 1000]).hist(bins = 60) # over complete player career, players > 1000 AB in career\n",
"plt.xlabel('SLG')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You have reached the end! I've done various exploratory data analysis of the [Lahman database](http://www.seanlahman.com/baseball-archive/statistics/), discussed how I cleaned the data, and provided initial statistical analysis. Also I showed how to improve, or extend on the methods I used. Feel free to comment, or question regarding the data analysis, the code, or about anything baseball."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### extra stuff"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Two of the sources I used the most are [wikipedia](https://en.wikipedia.org/wiki/Main_Page) and [baseball reference](http://www.baseball-reference.com/). Especially for analyzing sports data there is splenty of information online to help you make sense of your results. While looking up some outliers or weird cases you get to read some interesting trivia."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>nameLast</th>\n",
" <th>nameGiven</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>93657</th>\n",
" <td>Rodriguez</td>\n",
" <td>Alexander Enmanuel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93658</th>\n",
" <td>Beltran</td>\n",
" <td>Carlos Ivan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93659</th>\n",
" <td>Sabathia</td>\n",
" <td>Carsten Charles</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93660</th>\n",
" <td>Capuano</td>\n",
" <td>Christopher Frank</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93661</th>\n",
" <td>Teixeira</td>\n",
" <td>Mark Charles</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93662</th>\n",
" <td>Davies</td>\n",
" <td>Hiram Kyle</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93663</th>\n",
" <td>McCann</td>\n",
" <td>Brian Michael</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93664</th>\n",
" <td>Drew</td>\n",
" <td>Stephen Oris</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93665</th>\n",
" <td>Miller</td>\n",
" <td>Andrew Mark</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93666</th>\n",
" <td>Young</td>\n",
" <td>Christopher Brandon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93667</th>\n",
" <td>Ellsbury</td>\n",
" <td>Jacoby McCabe</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93668</th>\n",
" <td>Headley</td>\n",
" <td>Chase Jordan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93669</th>\n",
" <td>Jones</td>\n",
" <td>Garrett Thomas</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93670</th>\n",
" <td>Ryan</td>\n",
" <td>Brendan Wood</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93671</th>\n",
" <td>Gardner</td>\n",
" <td>Brett M.</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93672</th>\n",
" <td>Petit</td>\n",
" <td>Gregorio Jesus</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93673</th>\n",
" <td>Bailey</td>\n",
" <td>Andrew Scott</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93674</th>\n",
" <td>Rogers</td>\n",
" <td>Esmil Antonio</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93675</th>\n",
" <td>Nova</td>\n",
" <td>Ivan Manuel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93676</th>\n",
" <td>Santos</td>\n",
" <td>Sergio Jose</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93677</th>\n",
" <td>Ackley</td>\n",
" <td>Dustin Michael</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93678</th>\n",
" <td>Betances</td>\n",
" <td>Dellin</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93679</th>\n",
" <td>Carpenter</td>\n",
" <td>Darrell David</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93680</th>\n",
" <td>Eovaldi</td>\n",
" <td>Nathan Edward</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93681</th>\n",
" <td>Pineda</td>\n",
" <td>Michael Francisco</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93682</th>\n",
" <td>Romine</td>\n",
" <td>Austin Allen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93683</th>\n",
" <td>Gregorius</td>\n",
" <td>Mariekson Julius</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93684</th>\n",
" <td>Warren</td>\n",
" <td>Adam Parrish</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93685</th>\n",
" <td>Wilson</td>\n",
" <td>Justin James</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93686</th>\n",
" <td>Murphy</td>\n",
" <td>John Ryan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93687</th>\n",
" <td>Figueroa</td>\n",
" <td>Stephen Cole</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93688</th>\n",
" <td>Martin</td>\n",
" <td>Christopher Riley</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93689</th>\n",
" <td>Mitchell</td>\n",
" <td>Bryan Bedford</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93690</th>\n",
" <td>Pirela</td>\n",
" <td>Jose Manuel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93691</th>\n",
" <td>Ramirez</td>\n",
" <td>Jose Altagracia</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93692</th>\n",
" <td>Shreve</td>\n",
" <td>Chasen Dean</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93693</th>\n",
" <td>Tanaka</td>\n",
" <td>Masahiro</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93694</th>\n",
" <td>Whitley</td>\n",
" <td>Chase Coleman</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93695</th>\n",
" <td>Bird</td>\n",
" <td>Gregory Paul</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93696</th>\n",
" <td>Burawa</td>\n",
" <td>Daniel James</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93697</th>\n",
" <td>Cotham</td>\n",
" <td>Caleb Kent</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93698</th>\n",
" <td>De Paula</td>\n",
" <td>Jose Alberto</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93699</th>\n",
" <td>Flores</td>\n",
" <td>Ramon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93700</th>\n",
" <td>Goody</td>\n",
" <td>Nicholas Gunnar</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93701</th>\n",
" <td>Heathcott</td>\n",
" <td>Zachary Slade</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93702</th>\n",
" <td>Lindgren</td>\n",
" <td>Jacob Stephen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93703</th>\n",
" <td>Moreno</td>\n",
" <td>Diego Rafael</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93704</th>\n",
" <td>Noel</td>\n",
" <td>Jablonski Rico</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93705</th>\n",
" <td>Pazos</td>\n",
" <td>James Manuel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93706</th>\n",
" <td>Pinder</td>\n",
" <td>Branden Henry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93707</th>\n",
" <td>Refsnyder</td>\n",
" <td>Robert Daniel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93708</th>\n",
" <td>Rumbelow</td>\n",
" <td>Nicholas Bruno</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93709</th>\n",
" <td>Sanchez</td>\n",
" <td>Gary</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93710</th>\n",
" <td>Severino</td>\n",
" <td>Luis</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93711</th>\n",
" <td>Tracy</td>\n",
" <td>Matthew J.</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93712</th>\n",
" <td>Williams</td>\n",
" <td>Mason</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" nameLast nameGiven\n",
"93657 Rodriguez Alexander Enmanuel\n",
"93658 Beltran Carlos Ivan\n",
"93659 Sabathia Carsten Charles\n",
"93660 Capuano Christopher Frank\n",
"93661 Teixeira Mark Charles\n",
"93662 Davies Hiram Kyle\n",
"93663 McCann Brian Michael\n",
"93664 Drew Stephen Oris\n",
"93665 Miller Andrew Mark\n",
"93666 Young Christopher Brandon\n",
"93667 Ellsbury Jacoby McCabe\n",
"93668 Headley Chase Jordan\n",
"93669 Jones Garrett Thomas\n",
"93670 Ryan Brendan Wood\n",
"93671 Gardner Brett M.\n",
"93672 Petit Gregorio Jesus\n",
"93673 Bailey Andrew Scott\n",
"93674 Rogers Esmil Antonio\n",
"93675 Nova Ivan Manuel\n",
"93676 Santos Sergio Jose\n",
"93677 Ackley Dustin Michael\n",
"93678 Betances Dellin\n",
"93679 Carpenter Darrell David\n",
"93680 Eovaldi Nathan Edward\n",
"93681 Pineda Michael Francisco\n",
"93682 Romine Austin Allen\n",
"93683 Gregorius Mariekson Julius\n",
"93684 Warren Adam Parrish\n",
"93685 Wilson Justin James\n",
"93686 Murphy John Ryan\n",
"93687 Figueroa Stephen Cole\n",
"93688 Martin Christopher Riley\n",
"93689 Mitchell Bryan Bedford\n",
"93690 Pirela Jose Manuel\n",
"93691 Ramirez Jose Altagracia\n",
"93692 Shreve Chasen Dean\n",
"93693 Tanaka Masahiro\n",
"93694 Whitley Chase Coleman\n",
"93695 Bird Gregory Paul\n",
"93696 Burawa Daniel James\n",
"93697 Cotham Caleb Kent\n",
"93698 De Paula Jose Alberto\n",
"93699 Flores Ramon\n",
"93700 Goody Nicholas Gunnar\n",
"93701 Heathcott Zachary Slade\n",
"93702 Lindgren Jacob Stephen\n",
"93703 Moreno Diego Rafael\n",
"93704 Noel Jablonski Rico\n",
"93705 Pazos James Manuel\n",
"93706 Pinder Branden Henry\n",
"93707 Refsnyder Robert Daniel\n",
"93708 Rumbelow Nicholas Bruno\n",
"93709 Sanchez Gary\n",
"93710 Severino Luis\n",
"93711 Tracy Matthew J.\n",
"93712 Williams Mason"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# with batting, master, and teams tables combined it is eassy to get a list of team composition (2 ways): \n",
"# used a lot of similar functions to check what i was doing (wrong mostly).\n",
"battingcomplete[(battingcomplete.yearID == 2015) & (battingcomplete.teamID == 'NYA')][['nameLast', 'nameGiven']]\n",
"battingcomplete.groupby(['yearID','teamID']).get_group((2015, 'NYA'))[['nameLast', 'nameGiven']]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Index([u'playerID', u'yearID', u'stint', u'teamID', u'lgID', u'G_x', u'AB_x',\n",
" u'R_x', u'H_x', u'2B_x', u'3B_x', u'HR_x', u'RBI', u'SB_x', u'CS_x',\n",
" u'BB_x', u'SO_x', u'IBB', u'HBP_x', u'SH', u'SF_x', u'GIDP',\n",
" u'birthYear', u'birthMonth', u'birthDay', u'birthCountry',\n",
" u'birthState', u'birthCity', u'deathYear', u'deathMonth', u'deathDay',\n",
" u'deathCountry', u'deathState', u'deathCity', u'nameFirst', u'nameLast',\n",
" u'nameGiven', u'weight', u'height', u'bats', u'throws', u'debut',\n",
" u'finalGame', u'retroID', u'bbrefID', u'franchID', u'divID', u'Rank',\n",
" u'G_y', u'Ghome', u'W', u'L', u'DivWin', u'WCWin', u'LgWin', u'WSWin',\n",
" u'R_y', u'AB_y', u'H_y', u'2B_y', u'3B_y', u'HR_y', u'BB_y', u'SO_y',\n",
" u'SB_y', u'CS_y', u'HBP_y', u'SF_y', u'RA', u'ER', u'ERA', u'CG',\n",
" u'SHO', u'SV', u'IPouts', u'HA', u'HRA', u'BBA', u'SOA', u'E', u'DP',\n",
" u'FP', u'name', u'park', u'attendance', u'BPF', u'PPF', u'teamIDBR',\n",
" u'teamIDlahman45', u'teamIDretro'],\n",
" dtype='object')"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"battingcomplete.columns"
]
},
{
"cell_type": "code",
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"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
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"display_name": "Python 2",
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