ipl

The goal of ipl is to provide data and functions related to the Indian Premier League (IPL) matches and standard cricket statistics. This package allows users to avail of IPL data and conduct analysis of cricketers and IPL teams using functions of this package.

This is package is important because there isn’t a consolidated database where one can find all the data to analyse past IPL matches and players. These functions will also aid in conducting data analysis for those who are interested in analysing IPL trends.

Description

The ipl R package consists of datasets on all IPL matches played in the years 2008-2020, and provides functions to calculate typical crickets statistics.

Our package includes datasets on IPL matches played and cricketers in the years 2008-2020, acquired primarily from Kaggle, which have been cleaned so users can use it directly for data analysis. Moreover, it comprises functions for analysis of individual cricketers and games, as well as summary statistics for the same.

Installation

You can install the development version of ipl like so:

remotes::install_github("Swaha294/ipl")
#> Downloading GitHub repo Swaha294/ipl@HEAD
#> tibble  (3.1.6 -> 3.1.7) [CRAN]
#> ggplot2 (3.3.5 -> 3.3.6) [CRAN]
#> Installing 2 packages: tibble, ggplot2
#> 
#>   There are binary versions available but the source versions are later:
#>         binary source needs_compilation
#> tibble   3.1.6  3.1.7              TRUE
#> ggplot2  3.3.5  3.3.6             FALSE
#> installing the source packages 'tibble', 'ggplot2'
#> * checking for file ‘/private/var/folders/0p/hkwpsbqj047d4nq34kz3_wdr0000gn/T/RtmprsNSua/remotes41121ff051a6/Swaha294-ipl-993c34c/DESCRIPTION’ ... OK
#> * preparing ‘ipl’:
#> * checking DESCRIPTION meta-information ... OK
#> * checking for LF line-endings in source and make files and shell scripts
#> * checking for empty or unneeded directories
#> * building ‘ipl_0.0.0.9000.tar.gz’

Datasets Included

• deliveries: Ball-by-ball data of IPL matches played in 2008-2020
• teams: Winning team, overs bowled, runs made and wickets fallen for each match played by each IPL team in 2008-2020
• ipl: More information on matches from 2008 to 2020
• batsman_100: Information of top 100 batsmen of IPL
• bowlers_100: Information of top 100 bowlers of IPL

Functions Included

The following functions allow for individual analyses of cricketers and IPL matches, as well as for combined statistical analysis of the same.

• bat_avg \~ 134,112 B
• bat_max \~ 113,136 B
• batsman_summary \~ 130,616 B
• bowler_score \~ 81,216 B
• bowler_summary \~ 90,000 B
• bowling_analysis \~ 93,216 B
• cents_halfcents \~ 120,688 B
• fours \~ 87,072 B
• overs_balls \~ 90,600 B
• overs \~ 77,240 B
• partnership_runs \~ 93,000 B
• runs \~ 76,984 B
• sixes \~ 87,072
• strike_rate \~ 118,520 B
• toss_choice \~ 87,016 B
• wickets_taken \~ 77,888 B
• winloss \~ 120,768 B

Basic Usage

These are a few examples of how to use the package to compute different statistics for cricketers and IPL matches

Load ipl R package

library(ipl)

1. Visualize the number of runs made by Mumbai Indians in their match against Delhi Capitals on 2019-03-24, by partnerships

partnership_runs(1175358, "Mumbai Indians")

2. Get the summary table of all batting statistics for MS Dhoni for all IPL matches he played between 2008 and 2020

batsman_summary("MS Dhoni")
#>    year player_runs player_wickets batting_avg max_runs strike_rate centuries
#> 1  2020         200              8       25.00       47      116.28         0
#> 2  2019         416              5       83.20       84      134.63         0
#> 3  2018         455              7       65.00       79      150.66         0
#> 4  2017         290             13       22.31       61      116.00         0
#> 5  2016         284              8       35.50       64      135.24         0
#> 6  2015         372             14       26.57       53      121.97         0
#> 7  2014         371              5       74.20       57      148.40         0
#> 8  2013         461             11       41.91       67      162.90         0
#> 9  2012         358             11       32.55       51      128.78         0
#> 10 2011         392             10       39.20       70      158.70         0
#> 11 2010         287              9       31.89       66      136.67         0
#> 12 2009         332              8       41.50       58      127.20         0
#> 13 2008         414             10       41.40       65      133.55         0
#>    half_centuries num_4s num_6s
#> 1               0     16      7
#> 2               3     22     23
#> 3               3     24     30
#> 4               1     15     16
#> 5               1     18     14
#> 6               1     27     17
#> 7               1     22     20
#> 8               4     32     25
#> 9               1     26      9
#> 10              2     25     23
#> 11              2     26      8
#> 12              2     22      9
#> 13              2     38     15

3. Get the summary table of wins and losses for Sunrisers Hyderabad in 2017

winloss("Sunrisers Hyderabad", 2017)
#>   toss_decision wins losses      wpct
#> 1           bat    2      0 1.0000000
#> 2         field    6      6 0.5000000
#> 3         total    8      6 0.5714286

4. Get the bowling analysis for Rahul Sharma

bowling_analysis("Rahul Sharma")
#>         bowler overs runs wickets_taken
#> 1 Rahul Sharma 154.4 1086            40

More examples can be found in the vignette.

Contributors

• Swaha Bhattacharya
• Anushree Goswami
• Haley Schmidt