Big5 Soccer Leagues Players Statistics Last5 Years

Serie A, Bundesliga, League 1, Premier League, La Liga last 5 years statistics

@kaggle.matteonotaro_big5_soccer_leagues_players_statistics_last5_years

Table List

1 table(599.08 KB)

Whole

@kaggle.matteonotaro_big5_soccer_leagues_players_statistics_last5_years.whole

599.08 KB
17120 rows
37 columns

player Player	nation Nation	pos Pos	age Age	playing_time_mp Playing Time MP	playing_time_1_starts Playing Time.1 Starts	playing_time_2_min Playing Time.2 Min	playing_time_3_90s Playing Time.3–90s	performance_gls Performance Gls	performance_1_ast Performance.1 Ast	performance_2_g_a Performance.2 G+A	performance_3_g_pk Performance.3 G-PK	performance_4_pk Performance.4 PK	performance_5_pkatt Performance.5 PKatt	performance_6_crdy Performance.6 CrdY	performance_7_crdr Performance.7 CrdR	expected_xg Expected XG	expected_1_npxg Expected.1 NpxG	expected_2_xag Expected.2 XAG	expected_3_npxg_xag Expected.3 NpxG+xAG	progression_prgc Progression PrgC	progression_1_prgp Progression.1 PrgP	progression_2_prgr Progression.2 PrgR	per_90_minutes_gls Per 90 Minutes Gls	per_90_minutes_1_ast Per 90 Minutes.1 Ast	per_90_minutes_2_g_a Per 90 Minutes.2 G+A	per_90_minutes_3_g_pk Per 90 Minutes.3 G-PK	per_90_minutes_4_g_a_pk Per 90 Minutes.4 G+A-PK	per_90_minutes_5_xg Per 90 Minutes.5 XG	per_90_minutes_6_xag Per 90 Minutes.6 XAG	per_90_minutes_7_xg_xag Per 90 Minutes.7 XG+xAG	per_90_minutes_8_npxg Per 90 Minutes.8 NpxG	per_90_minutes_9_npxg_xag Per 90 Minutes.9 NpxG+xAG
Remo Freuler	ch SUI	MF	26	39	39	3349	37.2	2	6	8	2			7		3.2	3.2	3.9	7.2	100	276	77	0.05	0.16	0.21	0.05	0.21	0.1	0.12	0.21	0.1	0.21
Papu Gómez	ar ARG	MF,FW	30	40	39	3344	37.2	9	11	20	9			5		8.4	8.4	12.8	21.3	239	238	264	0.24	0.3	0.54	0.24	0.54	0.26	0.4	0.66	0.26	0.66
Hans Hateboer	nl NED	DF	24	39	37	3333	37	5	5	10	5			7		5.2	5.2	5	10.1	100	136	243	0.14	0.14	0.27	0.14	0.27	0.16	0.15	0.31	0.16	0.31
Duván Zapata	co COL	FW	27	42	37	3333	37	26	8	34	25	1	2	6		18.9	17.3	9.5	26.8	108	68	374	0.7	0.22	0.92	0.68	0.89	0.59	0.3	0.88	0.54	0.83
Marten de Roon	nl NED	MF	27	39	38	3328	37	3	3	6	2	1	1	8		1.8	1	2	3	33	254	40	0.08	0.08	0.16	0.05	0.14	0.05	0.06	0.11	0.03	0.09
José Luis Palomino	ar ARG	DF	28	35	30	2709	30.1	1	1	2	1			6	1	1.9	1.9	0.5	2.4	5	63	4	0.03	0.03	0.07	0.03	0.07	0.08	0.02	0.1	0.08	0.1
Josip Iličić	si SVN	FW,MF	30	36	28	2525	28.1	13	10	23	12	1	2	5	1	10.6	9.9	7.5	17.4	155	181	286	0.46	0.36	0.82	0.43	0.78	0.45	0.32	0.76	0.41	0.73
Timothy Castagne	be BEL	DF	22	33	26	2450	27.2	5	4	9	5			3		2.8	2.8	2.6	5.4	61	82	159	0.18	0.15	0.33	0.18	0.33	0.13	0.12	0.24	0.13	0.24
Gianluca Mancini	it ITA	DF	22	32	26	2342	26	5	2	7	5			6		5.3	5.3	1.4	6.7	26	90	20	0.19	0.08	0.27	0.19	0.27	0.21	0.06	0.27	0.21	0.27
Berat Djimsiti	al ALB	DF	25	28	24	2167	24.1	1	2	3	1			5		1	1	2	3	5	37	2	0.04	0.08	0.12	0.04	0.12	0.05	0.1	0.15	0.05	0.15


CREATE TABLE whole (
  "player" VARCHAR,
  "nation" VARCHAR,
  "pos" VARCHAR,
  "age" DOUBLE,
  "playing_time_mp" DOUBLE,
  "playing_time_1_starts" DOUBLE,
  "playing_time_2_min" DOUBLE,
  "playing_time_3_90s" DOUBLE,
  "performance_gls" DOUBLE,
  "performance_1_ast" DOUBLE,
  "performance_2_g_a" DOUBLE,
  "performance_3_g_pk" DOUBLE,
  "performance_4_pk" DOUBLE,
  "performance_5_pkatt" DOUBLE,
  "performance_6_crdy" DOUBLE,
  "performance_7_crdr" DOUBLE,
  "expected_xg" DOUBLE,
  "expected_1_npxg" DOUBLE,
  "expected_2_xag" DOUBLE,
  "expected_3_npxg_xag" DOUBLE,
  "progression_prgc" DOUBLE,
  "progression_1_prgp" DOUBLE,
  "progression_2_prgr" DOUBLE,
  "per_90_minutes_gls" DOUBLE,
  "per_90_minutes_1_ast" DOUBLE,
  "per_90_minutes_2_g_a" DOUBLE,
  "per_90_minutes_3_g_pk" DOUBLE,
  "per_90_minutes_4_g_a_pk" DOUBLE,
  "per_90_minutes_5_xg" DOUBLE,
  "per_90_minutes_6_xag" DOUBLE,
  "per_90_minutes_7_xg_xag" DOUBLE,
  "per_90_minutes_8_npxg" DOUBLE,
  "per_90_minutes_9_npxg_xag" DOUBLE,
  "mp" DOUBLE,
  "playing_time_starts" DOUBLE,
  "playing_time_1_min" DOUBLE,
  "playing_time_2_90s" DOUBLE
);