Standard Stats: Domestic Leagues

Standard Stats: Domestic Leagues Table
Playing Time Performance Per 90 Minutes
Season Age Squad Country Comp LgRank MP Starts Min 90s Gls Ast G+A G-PK PK PKatt CrdY CrdR Gls Ast G+A G-PK G+A-PK Matches
2008-200924Trevisoit ITA2. Serie B22nd1198109.0000000300.000.000.000.000.00
201429Deportivo Cuencaec ECU1. Serie A8th36363,20735.6202200810.060.000.060.060.06Matches
201530Barcelonaec ECU1. Serie A5th15141,11012.3000000500.000.000.000.000.00Matches
201530Temperleyar ARG1. Primera Div25th1066016.7000000400.000.000.000.000.00Matches
202035SD Aucasec ECU1. Serie A8th141299011.0000000500.000.000.000.000.00Matches
202136Manta Fútbol Clubec ECU1. Serie A15th111191110.1000000400.000.000.000.000.00Matches
5 Seasons6 Clubs3 Leagues97887,62984.82022002910.020.000.020.020.02
Country Comp LgRank MP Starts Min 90s Gls Ast G+A G-PK PK PKatt CrdY CrdR Gls Ast G+A G-PK G+A-PK Matches
Deportivo Cuenca (1 Season)1 League36363,20735.6202200810.060.000.060.060.06
Barcelona (1 Season)1 League15141,11012.3000000500.000.000.000.000.00
SD Aucas (1 Season)1 League141299011.0000000500.000.000.000.000.00
Manta Fútbol Club (1 Season)1 League111191110.1000000400.000.000.000.000.00
Treviso (1 Season)1 League1198109.0000000300.000.000.000.000.00
Temperley (1 Season)1 League1066016.7000000400.000.000.000.000.00
Serie A (4 Seasons)76736,21869.12022002210.030.000.030.030.03
Serie B (1 Season)1198109.0000000300.000.000.000.000.00
Primera Div (1 Season)1066016.7000000400.000.000.000.000.00

Shooting: Domestic Leagues

Shooting: Domestic Leagues Table
Standard
Season Age Squad Country Comp LgRank 90s Gls Sh SoT SoT% Sh/90 SoT/90 G/Sh G/SoT Dist PK PKatt Matches
2008-200924Trevisoit ITA2. Serie B22nd9.0040.440.0000
201429Deportivo Cuencaec ECU1. Serie A8th35.6200Matches
201530Barcelonaec ECU1. Serie A5th12.3000Matches
201530Temperleyar ARG1. Primera Div25th6.7000Matches
202035SD Aucasec ECU1. Serie A8th11.0000Matches
202136Manta Fútbol Clubec ECU1. Serie A15th10.1000Matches
5 Seasons6 Clubs3 Leagues84.8240.440.0000
Country Comp LgRank 90s Gls Sh SoT SoT% Sh/90 SoT/90 G/Sh G/SoT Dist PK PKatt Matches
Deportivo Cuenca (1 Season)1 League35.6200
Barcelona (1 Season)1 League12.3000
SD Aucas (1 Season)1 League11.0000
Manta Fútbol Club (1 Season)1 League10.1000
Treviso (1 Season)1 League9.0040.440.0000
Temperley (1 Season)1 League6.7000
Serie A (4 Seasons)69.1200
Serie B (1 Season)9.0040.440.0000
Primera Div (1 Season)6.7000

Playing Time: Domestic Leagues

Playing Time: Domestic Leagues Table
Playing Time Starts Subs Team Success
Season Age Squad Country Comp LgRank MP Min Mn/MP Min% 90s Starts Mn/Start Compl Subs Mn/Sub unSub PPM onG onGA +/- +/-90 On-Off Matches
2008-200924Trevisoit ITA2. Serie B22nd118107421.49.092
201429Deportivo Cuencaec ECU1. Serie A8th363,2078984.835.6368935001.223745-8-0.22+1.03Matches
201530Barcelonaec ECU1. Serie A5th151,1107428.012.31476814531.532012+8+0.65+0.55Matches
201530Temperleyar ARG1. Primera Div25th106016022.36.7679443331.0025-3-0.45-0.15Matches
202035SD Aucasec ECU1. Serie A8th149907136.711.01281628111.87181800.00-0.21Matches
202136Manta Fútbol Clubec ECU1. Serie A15th119118333.710.111838010.82610-4-0.40+0.26Matches
5 Seasons6 Clubs3 Leagues977,6297938.984.8888461927181.308390-7-0.09+0.12
Country Comp LgRank MP Min Mn/MP Min% 90s Starts Mn/Start Compl Subs Mn/Sub unSub PPM onG onGA +/- +/-90 On-Off Matches
Deportivo Cuenca (1 Season)1 League363,2078984.835.6368935001.223745-8-0.22+1.03
Barcelona (1 Season)1 League151,1107428.012.31476814531.532012+8+0.65+0.55
SD Aucas (1 Season)1 League149907136.711.01281628111.87181800.00-0.21
Manta Fútbol Club (1 Season)1 League119118333.710.111838010.82610-4-0.40+0.26
Treviso (1 Season)1 League118107421.49.092
Temperley (1 Season)1 League106016022.36.7679443331.0025-3-0.45-0.15
Serie A (4 Seasons)766,2188247.369.1738457320151.348185-4-0.06+0.12
Serie B (1 Season)118107421.49.092
Primera Div (1 Season)106016022.36.7679443331.0025-3-0.45-0.15
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Miscellaneous Stats: Domestic Leagues

Miscellaneous Stats: Domestic Leagues Table
Performance
Season Age Squad Country Comp LgRank 90s CrdY CrdR 2CrdY Fls Fld Off Crs Int TklW PKwon PKcon OG Matches
2008-200924Trevisoit ITA2. Serie B22nd9.030
201429Deportivo Cuencaec ECU1. Serie A8th35.68100Matches
201530Barcelonaec ECU1. Serie A5th12.35000Matches
201530Temperleyar ARG1. Primera Div25th6.74000Matches
202035SD Aucasec ECU1. Serie A8th11.05000Matches
202136Manta Fútbol Clubec ECU1. Serie A15th10.14000Matches
5 Seasons6 Clubs3 Leagues84.829100
Country Comp LgRank 90s CrdY CrdR 2CrdY Fls Fld Off Crs Int TklW PKwon PKcon OG Matches
Deportivo Cuenca (1 Season)1 League35.68100
Barcelona (1 Season)1 League12.35000
SD Aucas (1 Season)1 League11.05000
Manta Fútbol Club (1 Season)1 League10.14000
Treviso (1 Season)1 League9.030
Temperley (1 Season)1 League6.74000
Serie A (4 Seasons)69.122100
Serie B (1 Season)9.030
Primera Div (1 Season)6.74000

Player Club Summary

About FBref.com

FBref.com launched (June 13, 2018) with domestic league coverage for England, France, Germany, Italy, Spain, and United States. Since then we have been steadily expanding our coverage to include domestic leagues from over 40 countries as well as domestic cup, super cup and youth leagues from top European countries. We have also added coverage for major international cups such as the UEFA Champions League and Copa Libertadores.

FBref is the most complete sources for women's football data on the internet. This includes the entire history of the FIFA Women's World Cup as well as recent domestic league seasons from nine countries, including advanced stats like xG for most of those nine.

In collaboration with Opta, we are including advanced analytical data such as xG, xA, progressive passing, duels and more for over twenty competitions. For more information on the expected goals model and which competitions have advanced data, see our xG explainer.

Note that player records are likely not complete for their careers. Players may come from or move to leagues we don't currently cover. This issue will go down over time, as we add new leagues and seasons. We will never in the future have less data than we do today.

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