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BallByBallEventPredictor.qmd
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---
jupyter: python3
---
---
title: "Project Step II"
subtitle: "Group 11 - Ball by Ball Event Predictor"
date: 10/17/2023
date-modified: last-modified
date-format: long
format:
html:
theme: [cosmo, theme.scss]
toc: true
embed-resources: true
number-sections: true
author:
- name: Tegveer Ghura
affiliations:
- id: gu
name: Georgetown University
city: Washington
state: DC
---
# Data Preparation
## Import the necessary libraries
```{python}
import random
random.seed(1310)
from seaborn.palettes import color_palette
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.preprocessing import LabelEncoder
import re
import plotly.express as px
import plotly.io as pio
# pio.renderers.default = "notebook"
pio.renderers.default = "plotly_mimetype+notebook_connected"
from sklearn.metrics import (
classification_report,
confusion_matrix,
ConfusionMatrixDisplay,
)
from sklearn.exceptions import ConvergenceWarning
from sklearn.exceptions import DataConversionWarning
ConvergenceWarning("ignore")
DataConversionWarning("ignore")
from sklearn.model_selection import (
cross_val_score,
RepeatedKFold,
GridSearchCV,
RandomizedSearchCV,
)
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import (
GradientBoostingClassifier,
BaggingClassifier,
RandomForestClassifier,
StackingClassifier,
AdaBoostClassifier,
)
from xgboost import XGBClassifier
#from catboost import CatBoostClassifier
import pickle
import joblib
import json
import sys
import os
import shutil
import warnings
```
# Load the dataset and display the dataframe
```{python}
df = pd.read_csv("data/raw/deliveries.csv", encoding="ISO-8859-1", na_filter=False)
```
```{python}
df.head()
```
```{python}
df.tail()
```
```{python}
df.shape
```
```{python}
df.columns
```
## Check for Missing Values/NAs
```{python}
df.isna().sum()
```
## Remove Unnecessary Columns
```{python}
#| scrolled: true
columns_to_remove = ["player_dismissed", "fielder", "penalty_runs"]
df.drop(labels=columns_to_remove, axis=1, inplace=True)
```
```{python}
df.head()
```
## Feature Engineering `bowler_type`
In the code cell below, we have created a custom list of all spin bowlers for each team. We have then modified the `bowler` column in the dataframe which will be used to identify the type of bowler, either "spinner" or "pacer". Therefore, instead of dropping the `bowler` column, we have created a new column `bowler_type` which will be used for our analysis and enhance the predictive power of our models.
```{python}
# Replacing all spinner names with 'spinner' and all pacer names with 'pacer' under `bowler` column
rcb_spin = [
"SB Joshi",
"KP Appanna",
"A Kumble",
"J Arunkumar",
"Abdur Razzak",
"CL White",
"TM Dilshan",
"KP Pietersen",
"RE van der Merwe",
"S Sriram",
"DL Vettori",
"KB Arun Karthik",
"CH Gayle",
"S Sriram",
"AA Kazi",
"R Ninan",
"J Syed Mohammad",
"M Muralitharan",
"M Kartik",
"P R Barman",
"Sachin Baby",
"YS Chahal",
"Yuvraj Singh",
"SB Jakati",
"Iqbal Abdulla",
"T Shamsi",
"Parvez Rasool",
"S Baby",
"TM Head",
"KM Jadhav",
"P Negi",
"S Badree",
"Washington Sundar",
"M Ali",
"M Ashwin",
]
mi_spin = [
"A Dananjaya",
"AG Murtaza",
"A Roy",
"GJ Maxwell",
"Harbhajan Singh",
"J Suchith",
"J Yadav",
"JP Duminy",
"KH Pandya",
"KV Sharma",
"M Markande",
"N Rana",
"PP Ojha",
"RD Chahar",
"RG Sharma",
"RJ Peterson",
"RW Price",
"S Gopal",
"SD Chitnis",
"ST Jayasuriya",
"TL Suman",
"VS Yeligati",
]
kkr_spin = [
"BAW Mendis",
"BJ Hodge",
"DJ Hussey",
"GB Hogg",
"J Botha",
"KC Cariappa",
"M Kartik",
"CH Gayle",
"Iqbal Abdulla",
"Kuldeep Yadav",
"MB Parmar",
"MK Tiwary",
"Mohammad Hafeez",
"N Rana",
"PP Chawla",
"RS Gavaskar",
"S Ladda",
"Shakib Al Hasan",
"SMSM Senanayake",
"SP Narine",
"YK Pathan",
]
csk_spin = [
"DJ Hussey",
"F du Plessis",
"Harbhajan Singh",
"Imran Tahir",
"RA Jadeja",
"KV Sharma",
"M Santner",
"M Muralitharan",
"P Negi",
"R Ashwin",
"S Badree",
"S Randiv",
"S Vidyut",
"SB Jakati",
"SK Raina",
"SMSM Senanayake",
]
dc_spin = [
"A Mishra",
"AA Jhunjhunwala",
"Ankit Sharma",
"CL White",
"PP Ojha",
"DB Ravi Teja",
"JP Duminy",
"LPC Silva",
"R Sharma",
"RG Sharma",
"S Dhawan",
"Shahid Afridi",
"TL Suman",
"Y Venugopal Rao",
]
dd_spin = [
"A Mishra",
"AJ Finch",
"AR Patel",
"BMAJ Mendis",
"DL Vettori",
"GJ Maxwell",
"H Vihari",
"Imran Tahir",
"J Suchith",
"J Botha",
"J Yadav",
"JP Duminy",
"KP Pietersen",
"MK Tiwary",
"P Negi",
"R Sharma",
"R Tewatia",
"RE van der Merwe",
"S Ladda",
"S Lamichhane",
"S Nadeem",
"S Sriram",
"Shoaib Malik",
"TM Dilshan",
"Sunny Gupta",
"V Sehwag",
"Y Venugopal Rao",
"Yuvraj Singh",
"Y Nagar",
]
srh_spin = [
"A Mishra",
"Ankit Sharma",
"Bipul Sharma",
"CL White",
"DJ Hooda",
"KS Williamson",
"KV Sharma",
"Mohammad Nabi",
"Parvez Rasool",
"Rashid Khan",
"S Nadeem",
"Shakib Al Hasan",
"Y Venugopal Rao",
"YK Pathan",
"Yuvraj Singh",
]
rr_spin = [
"A Chandila",
"AA Chavan",
"AA Jhunjhunwala",
"AC Voges",
"AJ Finch",
"AL Menaria",
"Ankit Sharma",
"AS Raut",
"BJ Hodge",
"D Short",
"DJ Hooda",
"D Salunkhe",
"GB Hogg",
"I Sodhi",
"J Botha",
"K Gowtham",
"L Livingstone",
"LRPL Taylor",
"M Lomror",
"PV Tambe",
"ND Doshi",
"R Parag",
"R Tewatia",
"S Badree",
"S Gopal",
"RA Jadeja",
"S Midhun",
"SK Warne",
"YK Pathan",
]
punj_spin = [
"AC Gilchrist",
"AR Patel",
"BA Bhatt",
"Bipul Sharma",
"DJ Hussey",
"GJ Maxwell",
"Gurkeerat Singh" "H Brar",
"Karanveer Singh",
"KC Cariappa",
"M Ashwin",
"M Kartik",
"M Ur Rahman",
"M Vijay",
"MK Tiwary",
"P Sahu",
"PP Chawla",
"R Ashwin",
"R Tewatia",
"RR Powar",
"Shivam Sharma",
"SN Khan",
"Swapnil Singh",
"V Chakravarthy",
"Yuvraj Singh",
]
```
```{python}
# Replacing all spin bowlers' names with 'spinner' under `bowler` column
df.loc[
(df.bowling_team == "Royal Challengers Bangalore") & (df.bowler.isin(rcb_spin)),
"bowler",
] = "spinner"
df.loc[
(df.bowling_team == "Delhi Capitals") & (df.bowler.isin(dd_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Delhi Daredevils") & (df.bowler.isin(dd_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Mumbai Indians") & (df.bowler.isin(mi_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Chennai Super Kings") & (df.bowler.isin(csk_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Kings XI Punjab") & (df.bowler.isin(punj_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Sunrisers Hyderabad") & (df.bowler.isin(srh_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Kolkata Knight Riders") & (df.bowler.isin(kkr_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Deccan Chargers") & (df.bowler.isin(dc_spin)), "bowler"
] = "spinner"
df.loc[
(df.bowling_team == "Rajasthan Royals") & (df.bowler.isin(rr_spin)), "bowler"
] = "spinner"
```
```{python}
# Replacing all fast/pace bowlers' names with 'pacer' under `bowler` column
l = ["spinner"]
df.loc[~df.bowler.isin(l), "bowler"] = "pacer"
```
```{python}
df.loc[df.bowler == "pacer"]
```
```{python}
df.loc[df.bowler == "spinner"]
```
```{python}
# sanity check - check for NaN values in `bowler` column
df.bowler.isna().sum()
```
## Feature Engineering `batsman` and `non_striker` Type
In cricket, the batting order is the sequence in which batters play through their team's innings, there always being two batters taking part at any one time. All eleven players in a team are required to bat if the innings is completed (i.e., if the innings does not close early due to a declaration or other factor).
The batting order is colloquially subdivided into:
1. Top order (batters one to three)
2. Middle order (batters four to eight)
3. Tail enders (batters nine to eleven)
In the code cell below, we have created a custom list of all top order batsman and tail enders for each team. We have then modified the `batsman` and `non_striker` columns in the dataframe which will be used to identify the type of batsman, "top_order", "middle_order" or "tail_ender". This column, we belive, should lend to the predictive power of our models. For example, a top order batsman is more likely to score a boundary than a tail ender, purely based on batting skill. Moreover, if given the scenario that a top order batsman bats till the last 5 overs of the game with a tail ender at the non-striker's end, the top order batsman is more likely to retain strike to maximize the number of runs scored in the last 5 overs.
We deliberately chose not to take the easier route of engineering these columns column based on the `wickets` column. Doing so would induce multicollinearity in the data and, more importantly, alter the `batsman` and `non_striker` columns in a way that would compromise the integrity of our data.
**Note:** It is not uncommon in cricket that an opening batsman may play in the middle order or vice-versa, given various factors such as recent form of the batsman or captain's/coach's discretion. Therefore, we have categorized individual batters with regards to their ideal batting position. For example, Robin Uthappa started off as a middle order batsman in 2008 with Mumbai Indians, but was promoted to the top order when he joined Royal Challengers Bangalore and Kolkata Knight Riders in 2010 and 2014 respectively.
```{python}
# Creating a list of all top order batsmen and tail enders for each team
rcb_top_order = [
"TM Dilshan",
"KP Pietersen",
"CH Gayle",
"PA Patel",
"V Kohli",
"AB de Villiers",
"R Dravid",
"JH Kallis",
"MK Pandey",
"W Jaffer",
"S Chanderpaul",
"LRPL Taylor",
"SR Watson",
"Mandeep Singh",
"A Mukund",
"BB McCullum",
"CA Pujara",
"MA Agarwal",
"KL Rahul",
"Q de Kock",
"J Arunkumar",
"S Sriram",
]
rcb_tail_enders = [
"SB Joshi",
"KP Appanna",
"A Kumble",
"Abdur Razzak",
"DL Vettori",
"KB Arun Karthik",
"S Sriram",
"AA Kazi",
"R Ninan",
"J Syed Mohammad",
"M Muralitharan",
"M Kartik",
"P R Barman",
"YS Chahal",
"SB Jakati",
"T Shamsi",
"Parvez Rasool",
"P Kumar",
"Z Khan",
"R Vinay Kumar",
"DW Steyn",
"ND Doshi",
"DP Nannes",
"JJ van der Wath",
"S Aravind",
"S Badree",
"CK Langeveldt",
"RR Bhatkal",
"P Parameswaran",
"JD Unadkat",
"RP Singh",
"R Rampaul",
"MA Starc",
"M Ashwin" "AB Dinda",
"VR Aaron",
"AN Ahmed",
"AF Milne",
"KW Richardson",
"CJ Jordan",
"TS Mills",
"A Choudhary",
"B Stanlake",
"Avesh Khan",
"UT Yadav",
"K Khejroliya",
"Mohammed Siraj",
"TG Southee",
"N Saini",
]
mi_top_order = [
"N Rana",
"RG Sharma",
"ST Jayasuriya",
"SR Tendulkar",
"YV Takawale",
"AM Rahane",
"DR Smith",
"L Ronchi",
"AC Blizzard",
"RV Uthappa",
"AT Rayudu",
"DJ Jacobs",
"S Dhawan",
"SS Tiwary",
"JP Duminy",
"AP Tare",
"AJ Finch",
"E Lewis",
"Ishan Kishan",
"Q de Kock",
"AM Rahane",
"LMP Simmons",
"CM Gautam",
"C Madan",
"PA Patel",
"BR Dunk",
"JC Buttler",
"SM Pollock",
"AS Yadav",
"HH Gibbs",
"UBT Chand",
"GJ Maxwell",
"MJ Guptill",
"RE Levi",
]
mi_tail_enders = [
"A Dananjaya",
"AG Murtaza",
"Harbhajan Singh",
"J Yadav",
"M Markande",
"PP Ojha",
"RD Chahar",
"RW Price",
"VS Yeligati",
"Z Khan",
"SL Malinga",
"JJ Bumrah",
"MG Johnson",
"P Suyal",
"A Nehra",
"DS Kulkarni",
"MA Khote",
"CRD Fernando",
"DJ Thornely",
"RR Raje",
"DR Smith",
"RP Singh",
"CJ McKay",
"NLTC Perera",
"R Shukla",
"A Nel",
"Z Khan",
"R McLaren",
"AN Ahmed",
"MM Patel",
"YS Chahal",
"P Kumar",
"K Santokie",
"M de Lange",
"R Vinay Kumar",
"MJ McClenaghan",
"TG Southee",
"Mustafizur Rahman",
"PJ Sangwan",
"R Salam",
"J Behrendorff",
"A Joseph",
"BB Sran",
]
kkr_top_order = [
"SC Ganguly",
"BB McCullum",
"RT Ponting",
"WP Saha",
"Salman Butt",
"AB Agarkar",
"Mohammad Hafeez",
"A Chopra",
"BJ Hodge",
"MK Tiwary",
"CA Pujara",
"CH Gayle",
"OA Shah",
"Mandeep Singh",
"AD Mathews",
"DJ Hussey",
"MS Bisla",
"JH Kallis",
"YK Pathan",
"G Gambhir",
"BJ Haddin",
"SP Goswami",
"EJG Morgan",
"RV Uthappa",
"MK Pandey",
"CA Lynn",
"C Munro",
"SP Narine",
"N Rana",
"S Gill",
"N Naik",
"J Denly",
]
kkr_tail_enders = [
"BAW Mendis",
"GB Hogg",
"KC Cariappa",
"M Kartik",
"Kuldeep Yadav",
"MB Parmar",
"R Vinay Kumar",
"PP Chawla",
"SMSM Senanayake",
"AB Dinda",
"I Sharma",
"AB Agarkar",
"Umar Gul",
"Shoaib Akhtar",
"CK Langeveldt",
"SE Bond",
"JD Unadkat",
"L Balaji",
"B Lee",
"M de Lange",
"PJ Sangwan",
"M Morkel",
"Mohammed Shami",
"R McLaren",
"Shami Ahmed",
"AS Rajpoot",
"TA Boult",
"MG Johnson",
"T Curran",
"S Mavi",
"P Krishna",
"J Searles",
"L Ferguson",
"H Gurney",
"P Raj",
"S Warrier",
"UT Yadav",
]
csk_top_order = [
"F du Plessis",
"SK Raina",
"M Vijay",
"ML Hayden",
"PA Patel",
"MEK Hussey",
"BB McCullum",
"S Vidyut",
"AT Rayudu",
"SP Fleming",
"DR Smith",
"S Anirudha",
"WP Saha",
"SR Watson",
"GJ Bailey",
]
csk_tail_enders = [
"Imran Tahir",
"M Muralitharan",
"R Ashwin",
"S Badree",
"S Randiv",
"S Vidyut",
"SB Jakati",
"P Amarnath",
"Joginder Sharma",
"M Ntini",
"L Balaji",
"S Tyagi",
"NLTC Perera",
"C Ganapathy",
"DE Bollinger",
"TG Southee",
"VY Mahesh",
"BW Hilfenhaus",
"DP Nannes",
"AS Rajpoot",
"B Laughlin",
"MM Sharma",
"IC Pandey",
"V Shankar",
"A Nehra",
"RG More",
"DL Chahar",
"M Wood",
"L Ngidi",
"KM Asif",
"S Kuggeleijn",
]
dc_top_order = [
"AC Gilchrist",
"VVS Laxman",
"HH Gibbs",
"LPC Silva",
"SB Styris",
"MD Mishra",
"TL Suman",
"Anirudh Singh",
"S Dhawan",
"IR Jaggi",
"KC Sangakkara",
"S Sohal",
"MJ Lumb",
"DJ Harris",
"PA Patel",
"PA Reddy",
]
dc_tail_enders = [
"A Mishra",
"Ankit Sharma",
"PP Ojha",
"WPUJC Vaas",
"RP Singh",
"D Kalyankrishna",
"DP Vijaykumar",
"PM Sarvesh Kumar",
"Jaskaran Singh",
"KAJ Roach",
"Harmeet Singh",
"RJ Harris",
"DW Steyn",
"I Sharma",
"Anand Rajan",
"DJ Harris",
"TP Sudhindra",
"V Pratap Singh",
"J Theron",
]
dd_top_order = [
"G Gambhir",
"V Sehwag",
"S Dhawan",
"AB de Villiers",
"TM Dilshan",
"DA Warner",
"KD Karthik",
"UBT Chand",
"AJ Finch",
"NV Ojha",
"CA Ingram",
"KP Pietersen",
"DPMD Jayawardene",
"MC Juneja",
"Q de Kock",
"M Vijay",
"MA Agarwal",
"SS Iyer",
"JP Duminy",
"MK Tiwary",
"SV Samson",
"KK Nair",
"AP Tare",
"C Munro",
"JJ Roy",
"P Shaw",
"S Dhawan",
]
dd_tail_enders = [
"A Mishra",
"Imran Tahir",
"J Yadav",
"R Sharma",
"S Lamichhane",
"S Nadeem",
"S Sriram",
"Sunny Gupta",
"GD McGrath",
"B Geeves",
"Mohammad Asif",
"VY Mahesh",
"PJ Sangwan",
"DP Nannes",
"UT Yadav",
"Y Nagar",
"A Nehra",
"AB Dinda",
"M Morkel",
"S Nadeem",
"VR Aaron",
"AM Salvi",
"DAJ Bracewell",
"Sunny Gupta",
"S Kaul",
"Mohammed Shami",
"WD Parnell",
"JD Unadkat",
"R Sharma",
"JA Morkel",
"DJ Muthuswami",
"Z Khan",
"GS Sandhu",
"J Yadav",
"K Rabada",
"TA Boult",
"Avesh Khan",
"L Plunkett",
"J Dala",
]
srh_top_order = [
"PA Reddy",
"PA Patel",
"CL White",
"KC Sangakkara",
"Q de Kock",
"GH Vihari",
"S Dhawan",
"A Ashish Reddy",
"AJ Finch",
"KL Rahul",
"NV Ojha",
"DA Warner",
"KS Williamson",
"RS Bopara",
"MC Henriques",
"DJ Hooda",
"WP Saha",
"R Bhui",
"MK Pandey",
"A Hales",
"SP Goswami",
"J Bairstow",
"V Shankar",
"MJ Guptill",
]
srh_tail_enders = [
"DW Steyn",
"I Sharma",
"A Ashish Reddy",
"Anand Rajan",
"B Kumar",
"TA Boult",
"Sandeep Sharma",
"P Kumar",
"A Nehra",
"Mustafizur Rahman",
"BB Sran",
"S Kaul",
"Mohammed Siraj",
"B Stanlake",
"Basil Thampi",
"K Ahmed",
"S Sharma",
"A Mishra",
"Ankit Sharma",
"Parvez Rasool",
"S Nadeem",
]
rr_top_order = [
"T Kohli",
"YK Pathan",
"SR Watson",
"M Kaif",
"Kamran Akmal",
"GC Smith",
"M Rawat",
"SA Asnodkar",
"NK Patel",
"Younis Khan",
"NV Ojha",
"MJ Lumb",
"DR Martyn",
"AA Jhunjhunwala",
"FY Fazal",
"AG Paunikar",
"R Dravid",
"AM Rahane",
"SP Goswami",
"OA Shah",
"BJ Hodge",
"MDKJ Perera",
"DH Yagnik",
"SV Samson",
"KK Nair",
"Ankit Sharma",
"KK Cooper",
"UBT Chand",
"SPD Smith",
"DJ Hooda",
"D Short",
"H Klaasen",
"RA Tripathi",
"JC Buttler",
]
rr_tail_enders = [
"A Chandila",
"AA Chavan",
"AS Raut",
"GB Hogg",
"I Sodhi",
"PV Tambe",
"ND Doshi",
"S Badree",
"S Gopal",
"S Midhun",
"SK Warne",
"MM Patel",
"SK Trivedi",
"Pankaj Singh",
"SW Tait",
"Kamran Khan",
"A Uniyal",
"M Morkel",
"S Narwal",
"SB Wagh",
"AP Dole",
"FY Fazal",
"A Singh",
"S Sreesanth",
"R Shukla",
"VS Malik",
"KW Richardson",
"DS Kulkarni",
"R Bhatia",
"TG Southee",
"J Theron",
"B Brainder Sran",
"JD Unadkat",
"B Laughlin",
"J Archer",
"Anureet Singh",
"VR Aaron",
"O Thomas",
]
punj_top_order = [
"K Goel",
"JR Hopes",
"KC Sangakkara",
"DPMD Jayawardene",
"Yuvraj Singh",
"SM Katich",
"SE Marsh",
"LA Pomersbach",
"RS Bopara",
"MS Bisla",
"PC Valthaty",
"AC Gilchrist",
"Mandeep Singh",
"N Saini",
"M Vohra",
"Gurkeerat Singh",
"CA Pujara",
"V Sehwag",
"WP Saha",
"KK Nair" "M Vijay",
"HM Amla",
"EJG Morgan",
"MJ Guptill",
"KL Rahul",
"MA Agarwal",
"CH Gayle",
"AJ Finch",
]
punj_tail_enders = [
"BA Bhatt",