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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
200924Malmöse SWE1. Allsvenskan7th29292,61029.0156100400.030.170.210.030.21
201025Malmöse SWE1. Allsvenskan1st22221,90921.2044000310.000.190.190.000.19
201126Malmöse SWE1. Allsvenskan4th30292,57528.6000000000.000.000.000.000.00
201227Malmöse SWE1. Allsvenskan3rd28282,52028.0213111600.070.040.110.040.07
201328Malmöse SWE1. Allsvenskan1st27272,35726.2055000400.000.190.190.000.19
201429Malmöse SWE1. Allsvenskan1st23221,94821.6011000400.000.050.050.000.05Matches
2017-201832Oxford Unitedeng ENG3. League One16th36292,71730.2358300510.100.170.260.100.26Matches
2018-201933Twentenl NED2. Eerste Divisie1st34343,01433.5123100700.030.060.090.030.09Matches
8 Seasons3 Clubs3 Leagues22922019,650218.3723306113320.030.110.140.030.13
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
Malmö (6 Seasons)1 League15915713,919154.7316192112110.020.100.120.010.12
Oxford United (1 Season)1 League36292,71730.2358300510.100.170.260.100.26
Twente (1 Season)1 League34343,01433.5123100700.030.060.090.030.09
Allsvenskan (6 Seasons)15915713,919154.7316192112110.020.100.120.010.12
League One (1 Season)36292,71730.2358300510.100.170.260.100.26
Eerste Divisie (1 Season)34343,01433.5123100700.030.060.090.030.09

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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
200924Malmöse SWE1. Allsvenskan7th29.01130.450.0800
201025Malmöse SWE1. Allsvenskan1st21.2030.140.0000
201126Malmöse SWE1. Allsvenskan4th28.6040.140.0000
201227Malmöse SWE1. Allsvenskan3rd28.0240.140.2511
201328Malmöse SWE1. Allsvenskan1st26.2030.110.0000
201429Malmöse SWE1. Allsvenskan1st21.6040.180.0000Matches
2017-201832Oxford Unitedeng ENG3. League One16th30.23040.000.130.7500Matches
2018-201933Twentenl NED2. Eerste Divisie1st33.5100Matches
8 Seasons3 Clubs3 Leagues218.370350.000.190.1411
Country Comp LgRank 90s Gls Sh SoT SoT% Sh/90 SoT/90 G/Sh G/SoT Dist PK PKatt Matches
Malmö (6 Seasons)1 League154.73310.200.0611
Oxford United (1 Season)1 League30.23040.000.130.7500
Twente (1 Season)1 League33.5100
Allsvenskan (6 Seasons)154.73310.200.0611
League One (1 Season)30.23040.000.130.7500
Eerste Divisie (1 Season)33.5100

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
200924Malmöse SWE1. Allsvenskan7th292,6109096.729.0290
201025Malmöse SWE1. Allsvenskan1st221,9098770.721.2220
201126Malmöse SWE1. Allsvenskan4th302,5758695.428.6291
201227Malmöse SWE1. Allsvenskan3rd282,5209093.328.0280
201328Malmöse SWE1. Allsvenskan1st272,3578787.326.2270
201429Malmöse SWE1. Allsvenskan1st231,9488572.121.62221122.304722+25+1.16+0.80Matches
2017-201832Oxford Unitedeng ENG3. League One16th362,7177565.630.22927741.25444400.00+0.32Matches
2018-201933Twentenl NED2. Eerste Divisie1st343,0148988.133.5348930022.096032+28+0.84-0.27Matches
8 Seasons3 Clubs3 Leagues22919,6508682.7218.32208978981.8215198+53+0.62+0.52
Country Comp LgRank MP Min Mn/MP Min% 90s Starts Mn/Start Compl Subs Mn/Sub unSub PPM onG onGA +/- +/-90 On-Off Matches
Malmö (6 Seasons)1 League15913,9198885.9154.715721222.304722+25+1.16+0.80
Oxford United (1 Season)1 League362,7177565.630.22927741.25444400.00+0.32
Twente (1 Season)1 League343,0148988.133.5348930022.096032+28+0.84-0.27
Allsvenskan (6 Seasons)15913,9198885.9154.715721222.304722+25+1.16+0.80
League One (1 Season)362,7177565.630.22927741.25444400.00+0.32
Eerste Divisie (1 Season)343,0148988.133.5348930022.096032+28+0.84-0.27

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
200924Malmöse SWE1. Allsvenskan7th29.04034
201025Malmöse SWE1. Allsvenskan1st21.23122
201126Malmöse SWE1. Allsvenskan4th28.60028
201227Malmöse SWE1. Allsvenskan3rd28.06027
201328Malmöse SWE1. Allsvenskan1st26.24032
201429Malmöse SWE1. Allsvenskan1st21.64016Matches
2017-201832Oxford Unitedeng ENG3. League One16th30.25103400000000Matches
2018-201933Twentenl NED2. Eerste Divisie1st33.57001Matches
8 Seasons3 Clubs3 Leagues218.3332019300000001
Country Comp LgRank 90s CrdY CrdR 2CrdY Fls Fld Off Crs Int TklW PKwon PKcon OG Matches
Malmö (6 Seasons)1 League154.7211159
Oxford United (1 Season)1 League30.25103400000000
Twente (1 Season)1 League33.57001
Allsvenskan (6 Seasons)154.7211159
League One (1 Season)30.25103400000000
Eerste Divisie (1 Season)33.57001

Player Club Summary

Leaderboard Appearances, Awards, and Honors

Additional Resources

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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