IPL 2020 By Numbers

IPL 2020 Datasets For Game and Venue Analysis

@kaggle.rajatrc1705_ipl_2020_by_numbers

Table List

2 tables(40.39 KB)

Game

@kaggle.rajatrc1705_ipl_2020_by_numbers.game

14.99 KB
56 rows
20 columns

game Game	stadium Stadium	team_1 Team 1	team_2 Team 2	toss_winner Toss Winner	toss_decision Toss Decision	match_winner Match Winner	winner_num Winner Num	runs_pp1 Runs Pp1	runs_mo1 Runs Mo1	runs_do1 Runs Do1	wkt_pp1 Wkt Pp1	wkt_mo1 Wkt Mo1	wkt_do1 Wkt Do1	runs_pp2 Runs Pp2	runs_mo2 Runs Mo2	runs_do2 Runs Do2	wkt_pp2 Wkt Pp2	wkt_mo2 Wkt Mo2	wkt_do2 Wkt Do2
	AbuDhabi	MI	CSK	CSK	Field	CSK	2	51	85	26	2	3	4	37	84	45	2	1	2
1	Dubai	DC	KXIP	KXIP	Field	DC	1	23	70	64	3	2	3	35	63	59	3	2	3
2	Dubai	SRH	RCB	SRH	Field	RCB	2	48	79	26		2	3	53	71	39	1	4	6
3	Sharjah	RR	CSK	RR	Field	RR	1	54	112	50	1	3	2	53	85	62		5	2
4	AbuDhabi	KKR	MI	KKR	Field	MI	2	33	69	44	2	4	3	59	89	47	1	2	2
5	Dubai	KXIP	RCB	RCB	Field	KXIP	1	50	82	74		3		40	62	7	3	5	2
6	Dubai	CSK	DC	CSK	Field	DC	2	34	67	30	2	2	3	36	98	41		2	1
7	AbuDhabi	KKR	SRH	SRH	Bat	KKR	1	52	68	25	2	1		40	70	32	1	1	2
8	Sharjah	RR	KXIP	RR	Field	RR	1	69	92	65	1	1	4	60	118	45			2
9	Dubai	RCB	MI	MI	Field	RCB	1	59	77	65		2	1	35	87	79	2	2	1


CREATE TABLE game (
  "game" BIGINT,
  "stadium" VARCHAR,
  "team_1" VARCHAR,
  "team_2" VARCHAR,
  "toss_winner" VARCHAR,
  "toss_decision" VARCHAR,
  "match_winner" VARCHAR,
  "winner_num" BIGINT,
  "runs_pp1" BIGINT,
  "runs_mo1" BIGINT,
  "runs_do1" BIGINT,
  "wkt_pp1" BIGINT,
  "wkt_mo1" BIGINT,
  "wkt_do1" BIGINT,
  "runs_pp2" BIGINT,
  "runs_mo2" BIGINT,
  "runs_do2" BIGINT,
  "wkt_pp2" BIGINT,
  "wkt_mo2" BIGINT,
  "wkt_do2" BIGINT
);