cricket_data

This repository will act as a backend for the cricket data processed from Cricsheet

General format of each game type

Each game type has a folder with 11 files in it. These files contain ball by ball data, meta information about the game and meta information about the file itself. The 11 files are:

1. Bowl out Dataframe - information about who participated in the Bowl out if it occurred for a match - bowl_out_cf.csv
2. Dates dataframe - date or dates of when each match was played - dates_df.csv
3. Info Dataframe - information about where and when each match occurs. It also contains the player of the match - info_df.csv
4. Innings Dataframe - ball by ball information on each match - innings_df.csv
5. Meta Dataframe - meta information about the file containing match details - meta_df.csv
6. Outcome Dataframe - information about which team won the match and by what margin - outcome_df.csv
7. Player of match Dataframe - information about the player or players of the match. There have been matches where there were more than 1 player of the match - pom_df.csv
8. Supersub Dataframe - information about who participates in the supersub format. - supersub_df.csv
9. Team Dataframe - information about which teams are participating in the match - team_df.csv
10. Toss Dataframe - information about which team won the toss and whether they chose to bat or field - toss_df.csv
11. Umpires Dataframe - information about who were on field umpires in each match - umpires_df.csv

Game types available

Game Type	Abbreviation	Link
Afghanistan Premier League	apl	APL Data
Big Bash League	bbl	BBL Data
Bangladesh Premier League	bpl	BPL Data
Caribbean Premier League	cpl	CPL Data
Indian Premier League	IPL	IPL Data
Lanka Premier League	lpl	LPL Data
Mzansi Super League	msl	MSL Data
Natwest T20 Blast	ntb	NTB Data
Pakistan Super League	PSL	PSL Data
T20 Internationals	t20s	T20I Data
Women's Big Bash	wbb	WBB Data
Women's Cricket Super League	wsl	WSL Data
Women's T20 Challenge	wtc	WTC Data

How to use the API to fetch data

1. The base url for a dataframe of any game type is "https://sawlachintan.github.io/cricket_data/"
2. If the game type required is "IPL" and the dataframe required is toss, then append "ipl_data/toss_df.csv" to the base url.

Note

For any issues with the files, raise an issue in the repo.

Strucutre of the dataframes

Meta

Name	Type	Desc
key	string	A common ID to relate info across dataframes
data_version	float	version of the file from where data is fetched
created	date	date on which the file was created
revision	int	number of times the file was revised.

---

Info

Name	Type	Desc
key	string	A common ID to relate info across dataframes
city	string	name of the city where the match is played
competition	string	name of the competition
date	date	date of the match
gender	string	gender of the players in the match
match_type	string	format of the game
player_of_match	string	name of the first player of the match
venue	string	name of the stadium where the match is held
neutral_venue	boolean	if the match is played at a neutral venue or not

---

Dates

Name	Type	Desc
key	string	A common ID to relate info across dataframes
date	date	dates of when the matches were held

---

Player of Match

Name	Type	Desc
key	string	A common ID to relate info across dataframes
player_of_match	string	name of the players of match

---

Umpires

Name	Type	Desc
key	string	A common ID to relate info across dataframes
umpire	string	Names of the umpires for the match

---

Outcome

Name	Type	Desc
key	string	A common ID to relate info across dataframes
by_innings	int	number of innings the match was won by
by_type	string	how the winning team won - runs or wickets
by_margin	string	number by which the team won
bowl_out	string	name of the team who won the bowl_out
eliminator	boolean	if the match was an eliminator match or not
method	string	different method of winning D/L or 1st innings score
result	string	draw, no result, or tie when no team won the match
winner	string	name of the team who won the match

---

Teams

Name	Type	Desc
key	string	A common ID to relate info across dataframes
team	string	Names of the teams participating in the match

---

Toss

Name	Type	Desc
key	string	A common ID to relate info across dataframes
decision	string	Choice of team winning the toss
winner	string	Name of the team winning the toss for the match

---

Innings

Name	Type	Desc
key	string	A common ID to relate info across dataframes
inning_no	int	Innings number of the particular match
delivery_no	float	ball and over number of the innings
batting_team	string	name of the team batting in that innings
batter	string	name of the batsman facing the ball
bowler	string	name of the bowler bowling the ball
non_striker	string	name of the person on the other end of the pitch
runs_batter	int	number of runs scored by the batsman in that ball
runs_extras	int	extra runs gotten off the delivery
runs_non_boundary	int	runs that were more than 4 but not from a boundary
runs_total	int	total runs scored from the delivery
wicket_fielder	string	name of the fielder who is part of getting the wicket
wicket_kind	string	manner in which batsman/non_striker lost the wicket
wicket_player_out	string	name of the player who got out in that delivery
extras_type	string	name of the way in which the extra runs were rewarded
extras_run	int	runs rewarded from the type of extras
over	int	over number of the innings
n_ball	int	ball of the over