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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"# Data-driven Approach to Indian Quizzing"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Author: Pavan B G"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## What is Indian Quizzing?"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Quizzing in India has its own set of interesting rules, but there seems to be lot of homogenity in a diverse country regarding how it is conducted. This notebook is going to look at how each of those quirks affects the underlying dynamics and suggests a few changes."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"A brief summary of how Indian quizzing works is as follows:"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"* Multiple teams compete against each other and every round consists of taking turns to answer a question posed by the Quizmaster, also referred to as QM.\n",
"\n",
"\n",
"* Before the question goes to the teams, some allow for a \"pounce\", where teams discretely let the QM know their answer. If it is wrong however, they would lose a few points. The bounty is higher on getting it right usually, as there is a risk involved.\n",
"\n",
"\n",
"* Once the pounces have been noted, the \"infinite bounce\" begins, where the team designated as the direct gets to answer first and then, teams successively get a chance to answer. Getting it right would give them a few points and there are usually no penalties on a wrong answer here.\n",
"\n",
"\n",
"* If a team gets it right on the \"bounce\", the next question is fielded to the ones right next to it.\n",
"\n",
"\n",
"* If no team gets it on the \"bounce\", there are two famous variants - \"Chennai\" bounce and \"Bengaluru\" bounce. The next question goes either to the same team that got it previously (Chennai) or the team next to it (Bengaluru - the more progressive ones if it helps you to remember)"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## QM's Dilemma"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"There are a lot of choices to make and there are no simple answers to questions like:\n",
"\n",
"* How many is too many teams?\n",
"\n",
"\n",
"* What happens when we place two very good teams together?\n",
"\n",
"\n",
"* Which variant of bounce do we go for?\n",
"\n",
"\n",
"* How much should we penalize a wrong answer on the pounce?"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## QuizSim"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"For this purpose, I have written a \"simulator\" that runs a quiz with specified parameters and offers a testbed to figure out the effects of various interventions, as doing it in real life would be too cruel for some. I've written a few test-cases as well and things look fine, but would be more than happy to make corrections if required."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"The simulator code can be found here - [https://github.com/gpavanb1/QuizSim](https://github.com/gpavanb1/QuizSim)"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"### Assumptions"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"It is important to list out the assumptions we are making in the simulations. \n",
"\n",
"* Every team has a \"strength\" - how likely they are to know the right answer to a question?\n",
"\n",
"\n",
"* Every team has a \"dare factor\" - how likely they are to pounce on a question?\n",
"\n",
"\n",
"Note that the ground reality is much more complicated and all deductions in this post are under the simplified picture that has been made."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## Let's get started"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from quizsim import runQuiz\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Let's define an ensemble average function - to ensure the results aren't a chance encounter, we take the average of multiple quizzes. We are using `numpy.allclose` to define the convergence. Relative tolerance has been specified as 1e-3."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"rtol = 1e-3\n",
"\n",
"def ensemble_average(**kwargs):\n",
" res = runQuiz(**kwargs)\n",
" lastAvg = np.array(res)\n",
" \n",
" # Initialize variables\n",
" count = 1\n",
" \n",
" # Run averaging till convergence\n",
" while True:\n",
" res += runQuiz(**kwargs)\n",
" count += 1\n",
" resAvg = (1.0/count) * res\n",
" \n",
" if np.allclose(lastAvg, resAvg, rtol) and count > 2:\n",
" break\n",
" \n",
" if count > 5000:\n",
" print('Too many iterations. Returning last value')\n",
" break\n",
" \n",
" lastAvg = resAvg\n",
"\n",
" return count, resAvg"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Let's try this out on an example. The first value returned is the number of quizzes that were held to arrive at the average value."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"text/plain": [
"[91, array([160.98901099, 47.36263736])]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(ensemble_average(CAN_POUNCE=False, POUNCE_DARE=[0.0, 0.3], TEAM_STRENGTH=[0.6, 0.2]))"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## Results"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"### How many teams is too many?"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Let's start with teams being equally good with varying strengths. Then, for 30 questions, let's observe the dynamics with increase in number of teams. Teams cannot pounce to start with."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"For teams that are likely to get every 2nd question - 50% skill teams (or referred to as strength)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"text/plain": [
"[113.84615384615385, 111.38461538461539]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0.5, 0.5], POUNCE_DARE=[0., 0.])[1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Note that both teams are likely to score the same when there is no pounce and there are just two teams. Let's ramp up the number of teams."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"text/plain": [
"[88.875, 87.625, 84.5]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0.5, 0.5, 0.5], POUNCE_DARE=[0., 0., 0.])[1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"The margins are quite tight here as well. But it looks like the overall scoring is high. Note that the maximum is 300 and it looks like 3 teams are already good enough to get all questions right. Let's look at this as a function of number of teams."
]
},
{
"cell_type": "code",
"execution_count": 358,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"xAxis = range(2, 10)\n",
"yAxis = [sum(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0.5]*s, POUNCE_DARE=[0.]*s)[1]) for s in xAxis]"
]
},
{
"cell_type": "code",
"execution_count": 362,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"whitegrid\", font_scale=1.5)\n",
"fig = plt.scatter(xAxis, yAxis, );\n",
"plt.xlabel('# of teams')\n",
"plt.ylabel('Total score')\n",
"plt.title(\"Teams vs Total Score\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"If teams have 50% strength, then it is very unlikely that any question in the quiz remains uncracked. \n",
"\n",
"For the truly interested (Math Ahead!), this can actually be nicely quantified as well. If team strength is $s$, then $(1-s)^{t}$, where $t$ is the number of teams gives the chance a question goes to the audience. If the quiz has $n$ questions, then just check if $n * (1-s)^{t} \\lt 1$ for it to be perfectly crackable.\n",
"\n",
"Let's look at a figure to see how that is for 30 questions."
]
},
{
"cell_type": "code",
"execution_count": 363,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"n = 30\n",
"t = np.arange(2, 10)\n",
"s = (100.0) * np.array([1 - (1/n)**(1/x) for x in t])"
]
},
{
"cell_type": "code",
"execution_count": 364,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"whitegrid\", font_scale=1.5)\n",
"fig = plt.scatter(t, s);\n",
"plt.xlabel('# of teams needed to answer all')\n",
"plt.ylabel('Teams skill (%)')\n",
"plt.title(\"Teams vs Skill to 'crack' the quiz\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"**Conclusion #1**: Most quizzes have 6 to 8 teams on-stage and thus, a good (and already borderline difficult) quiz should just about have one question going to the audience."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"### Chennai vs Bengaluru Bounce"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"This is likely to be a very controversial section and would like to once again remind the readers that this is based on a simplified model. Let's look at whether this choice of bounce type is likely to make a difference in the outcome of the quiz. I also remember someone analyzing this in the past and would be great if I can be connected to them.\n",
"\n",
"Let's not allow pounce to understand the importance of the type of bounce."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"For 6 teams with equal skill of 50%, we have:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"text/plain": [
"[53.41463414634146,\n",
" 50.19512195121951,\n",
" 48.78048780487805,\n",
" 48.146341463414636,\n",
" 48.58536585365854,\n",
" 46.19512195121951]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0.5]*6, POUNCE_DARE=[0.]*6, BOUNCE_TYPE='Chennai')[1])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"text/plain": [
"[50.5668016194332,\n",
" 50.0,\n",
" 50.445344129554655,\n",
" 48.34008097165992,\n",
" 48.663967611336034,\n",
" 46.39676113360324]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0.5]*6, POUNCE_DARE=[0.]*6, BOUNCE_TYPE='Bengaluru')[1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"The effect of bounce type cannot be seen when the teams are equal. It is only when we have particular configurations, that this is seen. \n",
"\n",
"The classic case is when there are two strong teams side-by-side. Let's assume the skill to be [0, 0, x, x, 0, 0], where `x` is the strength. \n",
"\n",
"Note that if `x` is 1, then one of them will always get a question right and we will not see any difference between the two bounce types. Things get interesting when we look at it as a function of strength.\n",
"\n",
"WARNING: This computation might take long depending on your hardware!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"%%time\n",
"xAxis = np.linspace(0., 1., 40)\n",
"# Look at the difference in scoring\n",
"diff_score = lambda x: abs(x[3] - x[2])\n",
"\n",
"chennai = lambda x: ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0, 0, x, x, 0, 0], POUNCE_DARE=[0.]*6, BOUNCE_TYPE='Chennai')[1]\n",
"bengaluru = lambda x: ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[0, 0, x, x, 0, 0], POUNCE_DARE=[0.]*6, BOUNCE_TYPE='Bengaluru')[1]\n",
"\n",
"# Create multiple iterations of the difference and average it\n",
"NUM_AVG = 100\n",
"cmat = []\n",
"bmat = []\n",
"for i in tqdm(range(NUM_AVG)):\n",
" cmat.append([diff_score(chennai(x)) for x in xAxis])\n",
" bmat.append([diff_score(bengaluru(x)) for x in xAxis])\n",
"\n",
"chennai_list = np.average(np.array(cmat), axis=0)\n",
"bengaluru_list = np.average(np.array(bmat), axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 380,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"whitegrid\", font_scale=1.5)\n",
"plt.figure(figsize=(10,5))\n",
"plt.plot(100.*xAxis, chennai_list, '--ro');\n",
"plt.plot(100.*xAxis, bengaluru_list, '--bo');\n",
"plt.xlabel('Team Skill (%)')\n",
"plt.ylabel('Score Difference')\n",
"plt.title(\"Score Variation vs Team Skill\");\n",
"plt.legend(['Chennai', 'Bengaluru'], loc='upper left');"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"The fluctuations have died down after substantial averaging and the difference is much larger than the noise. The above graph identifies a difference between the two bounce types and peaks when the teams are of lukewarm skill. This allows questions to bounce through and the effect of Chennai vs Bengaluru bounce is seen. In the extremes, either the teams both don't answer anything or answer everything they get, leading to no difference in the quiz format."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"As a fun exercise, let's repeat the above exercise when pounce is on (for fewer samples). Assuming teams are 50% likely to pounce on every question."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hideCode": false,
"hidePrompt": false,
"scrolled": true
},
"outputs": [],
"source": [
"%%time\n",
"xAxis = np.linspace(0., 1., 20)\n",
"# Look at the difference in scoring\n",
"diff_score = lambda x: abs(x[3] - x[2])\n",
"\n",
"chennai = lambda x: ensemble_average(CAN_POUNCE=True, TEAM_STRENGTH=[0, 0, x, x, 0, 0], POUNCE_DARE=[0.5]*6, BOUNCE_TYPE='Chennai')[1]\n",
"bengaluru = lambda x: ensemble_average(CAN_POUNCE=True, TEAM_STRENGTH=[0, 0, x, x, 0, 0], POUNCE_DARE=[0.5]*6, BOUNCE_TYPE='Bengaluru')[1]\n",
"\n",
"# Create multiple iterations of the difference and average it\n",
"NUM_AVG = 40\n",
"cmat = []\n",
"bmat = []\n",
"for i in tqdm(range(NUM_AVG)):\n",
" cmat.append([diff_score(chennai(x)) for x in xAxis])\n",
" bmat.append([diff_score(bengaluru(x)) for x in xAxis])\n",
"\n",
"chennai_list = np.average(np.array(cmat), axis=0)\n",
"bengaluru_list = np.average(np.array(bmat), axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 383,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"whitegrid\", font_scale=1.5)\n",
"plt.figure(figsize=(10,5))\n",
"plt.plot(100.*xAxis, chennai_list, '--ro');\n",
"plt.plot(100.*xAxis, bengaluru_list, '--bo');\n",
"plt.xlabel('Team Skill (%)')\n",
"plt.ylabel('Score Difference')\n",
"plt.title(\"Score Variation vs Team Skill (50% Pounce)\");\n",
"plt.legend(['Chennai', 'Bengaluru'], loc='upper right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"It is interesting to note that the trend is not straightforward once pounce is introduced. And Chennai Bounce is leading to higher score difference as well for low-skilled or difficult quizzes."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"**Conclusion #2:** Chennai Bounce and Bengaluru Bounce (that phrase means something completely different now) are observed to create unfairness. But which method is more unfair depends on several factors, such as how teams pounce and their skill levels. So please, let's not get into battles regarding which one is better. Please reserve metro pride for IPL."
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"### Pounce Penalty"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Another hot topic of discussion in several quiz clubs is how much should \"negs\" be on pounce. This relates to the skill levels of teams. One particular quirk that I've observed over the years is having +10/-10 sometimes. I always wondered what was the effect on teams, particularly whether +10/-10 evens out to not having pounce at all."
]
},
{
"cell_type": "code",
"execution_count": 415,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [],
"source": [
"pounce_test = lambda skill,right : max(ensemble_average(CAN_POUNCE=True, TEAM_STRENGTH=[skill]*6, POUNCE_DARE=[0.6]*6, POUNCE_RIGHT=right, POUNCE_WRONG=-10)[1])\n",
"no_pounce_test = lambda skill,right : max(ensemble_average(CAN_POUNCE=False, TEAM_STRENGTH=[skill]*6, POUNCE_DARE=[0.6]*6, POUNCE_RIGHT=right, POUNCE_WRONG=-10)[1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Let's look at two common scoring patterns +15/-10 and +10/-10. It is interesting to look at the winner score as a function of team skill. I've set pouncing tendency at 60% - teams are a bit excited today."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hideCode": false,
"hidePrompt": false,
"scrolled": true
},
"outputs": [],
"source": [
"xAxis = np.linspace(0, 1, 50)\n",
"moreList, sameList, noPounceList = [], [], []\n",
"for x in tqdm(xAxis):\n",
" moreList.append(pounce_test(x, 15))\n",
" sameList.append(pounce_test(x, 10))\n",
" noPounceList.append(no_pounce_test(x, 10))\n",
"moreList = np.array(moreList)\n",
"sameList = np.array(sameList)\n",
"noPounceList = np.array(noPounceList)\n",
"diffList = moreList - sameList"
]
},
{
"cell_type": "code",
"execution_count": 417,
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"whitegrid\", font_scale=1.5)\n",
"plt.figure(figsize=(10,5))\n",
"plt.plot(100.*xAxis, moreList, '--ro');\n",
"plt.plot(100.*xAxis, sameList, '--bo');\n",
"plt.plot(100.*xAxis, noPounceList, '--go');\n",
"plt.xlabel('Team Skill (%)')\n",
"plt.ylabel('Winner Score')\n",
"plt.title(\"Winner Score vs Team Skill\");\n",
"plt.legend(['+15/-10', '+10/-10', 'No Pounce'], loc='upper left');"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Pounce definitely makes the quiz interesting, and as expected, +15/-10 leads to higher scores on an average. More importantly, if it is an easy quiz, pounce having +10/-10 leads to higher scores than not having pounce, which tapers off to the maximum sum of 300 as discussed above spread over 6 teams. Note that +10/-10 crosses over the no-pounce line at exactly 50% skill, when the effect of guessing right and guessing wrong on a pounce cancel out. "
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"**Conclusion #3:** +10/-10 gives same winner score as no-pounce if teams can guess questions right 50% of the time and worse off if the quiz is tougher. Using +15/-10 consistently produces higher scores for the winner as expected. "
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"## Summary"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": false,
"hidePrompt": false
},
"source": [
"Indian quizzing has several quirks and simulations have allowed the study of various interventions on quizzing rules. Here's a TL;DR of the various things I've looked at:\n",
"\n",
"1) If there are more than even a couple of questions going to the audience, the problem is the QM, not you.\n",
"\n",
"\n",
"2) Chennai vs Bengaluru bounce is not worth fighting for.\n",
"\n",
"\n",
"3) Be generous and have +15/-10. Tough quiz is better off without pounce. The agony lasts shorter also."
]
}
],
"metadata": {
"hide_code_all_hidden": false,
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.2"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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