micahmelling

def run_match_up_simulation(fastball_surrender_prob, curve_surrender_prob, change_surrender_prob, fastball_hit_prob,
                            curve_hit_prob, change_hit_prob, zero_zero_pitch_probs, zero_zero_hit_surrender_prob,
                            zero_zero_hit_prob, one_zero_pitch_probs, one_zero_hit_surrender_prob, one_zero_hit_prob,
                            zero_one_pitch_probs, zero_one_hit_surrender_prob, zero_one_hit_prob, one_one_pitch_probs,
                            one_one_hit_surrender_prob, one_one_hit_prob, two_zero_pitch_probs,
                            two_zero_hit_surrender_prob, two_zero_hit_prob, zero_two_pitch_probs,
                            zero_two_hit_surrender_prob, zero_two_hit_prob, one_two_pitch_probs,
                            one_two_hit_surrender_prob, one_two_hit_prob, two_one_pitch_probs,
                            two_one_hit_surrender_prob, two_one_hit_prob, three_zero_pitch_probs,
                            three_zero_hit_surrender_prob, three_zero_hi

micahmelling

def run_pitch_simulation(count, count_swing_prob, pitch_probs, count_surrender_prob, fastball_surrender_prob,
                             count_hit_prob, fastball_hit_prob, curve_surrender_prob, curve_hit_prob,
                             change_surrender_prob, change_hit_prob, df):

micahmelling

        if pitch == 'fastball':
            hit_prob = (count_surrender_prob + fastball_surrender_prob + count_hit_prob + fastball_hit_prob) / 4
            if swing == 'yes':
                outcome = np.random.choice(a=['hit', 'no_hit'], p=[hit_prob, 1 - hit_prob])
            elif swing == 'no':
                outcome = 'no_hit'
            df = df.append(pd.DataFrame({'count': count, 'pitch': 'fastball', 'swing': swing, 'result': [outcome]}))

        elif pitch == 'curve':
            hit_prob = (count_surrender_prob + curve_surrender_prob + count_hit_prob + curve_hit_prob) / 4

micahmelling

pitch = np.random.choice(a=['fastball', 'curve', 'change'], p=pitch_probs)
swing = np.random.choice(a=['yes', 'no'], p=[count_swing_prob, 1 - count_swing_prob])

micahmelling

at_bat_results = pd.DataFrame()

at_bat_results = run_pitch_simulation(count='0-0',
                                      count_swing_prob=zero_zero_swing_prob,
                                      pitch_probs=zero_zero_pitch_probs,
                                      count_surrender_prob=zero_zero_hit_surrender_prob,
                                      fastball_surrender_prob=fastball_surrender_prob,
                                      count_hit_prob=zero_zero_hit_prob,
                                      fastball_hit_prob=fastball_hit_prob,
                                      curve_surrender_prob=curve_surrender_prob,

micahmelling

last_row_df = at_bat_results.tail(1)

if last_row_df['swing'].any() == 'yes':
   end_of_at_bat = np.random.choice(a=['yes', 'no'], p=[swing_produces_out, 1 - swing_produces_out])
else:
   end_of_at_bat = 'no'

if at_bat_results['result'].any() == 'no_hit' and end_of_at_bat == 'no':
   new_count = np.random.choice(a=['0-1', '1-0'], p=[0.50, 0.50])

micahmelling

simulation_runs = 100
counter = 0
while counter < simulation_runs:
    temp_df = run_match_up_simulation(fastball_surrender_prob, curve_surrender_prob, change_surrender_prob,
                                      fastball_hit_prob, curve_hit_prob, change_hit_prob, zero_zero_pitch_probs,
                                      zero_zero_hit_surrender_prob, zero_zero_hit_prob, one_zero_pitch_probs,
                                      one_zero_hit_surrender_prob, one_zero_hit_prob, zero_one_pitch_probs,
                                      zero_one_hit_surrender_prob, zero_one_hit_prob, one_one_pitch_probs,
                                      one_one_hit_surrender_prob, one_one_hit_prob, two_zero_pitch_probs,
                                      two_zero_hit_surrender_prob, two_zero_hit_prob, zero_two_pitch_probs,

micahmelling

import pandas as pd
import subprocess

from sklearn.tree import DecisionTreeClassifier, export_graphviz


def main():
    df = pd.DataFrame({
        'location': ['MO', 'MO', 'MO', 'MO', 'KS', 'KS', 'KS', 'IL', 'IL', 'IL'],
        'age': [29, 30, 21, 40, 45, 60, 35, 24, 47, 50],

micahmelling

import sqlite3
import pandas as pd
import numpy as np

from time import sleep
from datetime import datetime


def connect_to_sqlite(db_name):
    """

micahmelling

import sqlite3
import pandas as pd
import os
import sys


# update db connection as needed
def connect_to_sqlite(db_name):
    return sqlite3.connect(db_name)