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Team Statistics

Aggregated team performance data including expected goals, shots, possession, corners, and discipline stats.

All Leagues1. HNL1. Lig2. BundesligaA-League MenA-League WomenAdmiral BundesligaAFC Asian CupAFC Champions League EliteAFC Champions League TwoAfrica Cup of NationsAfrica Cup of Nations QualificationsAllsvenskanAsian Cup QualificationAtlantic CupBotola ProBrasileiro WomenBundesligaCAF Champions LeagueCAF World Cup QualifiersCanadian Soccer LeagueCarabao CupChallenger Pro LeagueChampions LeagueChampionshipChance LigaCommunity ShieldConcacaf LeagueCONMEBOL Pre-Olympic TournamentCopa AmericaCopa de la SuperligaCopa Del ReyCopa do BrasilCopa LibertadoresCopa MXCopa SudamericanaCoppa ItaliaCoupe de FranceCoupe de la LigueDFB PokalEerste DivisieEkstraklasaEliteserienEnterprise National LeagueEredivisieEuropa Conference LeagueEuropa LeagueEuropean ChampionshipFA CupFIFA Intercontinental CupFirst DivisionFirst LeagueFNLFriendly InternationalIndian Super LeagueJ1 LeagueK League 1Kings CupKNVB BekerLa LigaLa Liga 2League OneLeague TwoLiga MXLiga PortugalLiga Profesional de FútbolLigat ha'AlLigue 1Ligue 1Ligue 1 Play-offsLigue 2Major League SoccerNASLNwsl Challenge Cup WomenOFC Champions LeagueOlympic GamesOlympic Games WomenOlympic Qualifying ConcacafOlympic Qualifying: OceaniaParva Liga - Play-offsPersian Gulf Pro LeaguePremier LeaguePremier LeaguePremier LeaguePremier LeaguePremier LeaguePremier League - PlayoffsPremiershipPremiership Play-OffsPrimera DivisionPro LeaguePro LeagueQatar Prince CupRussian CupSerie ASerie ASerie BSerie BStars LeagueSuper CupSuper CupSuper CupSuper LeagueSuper LeagueSuper LeagueSuper League Play-offsSuper LigSupercopa do BrasilSuperligaSuperligaTaça De PortugalUAE Pro LeagueUEFA Europa League Play-offsUEFA Nations LeagueUEFA Super CupUEFA Women's Champions LeagueUEFA Youth LeagueV-LeagueVeikkausliigaWC Qualification AsiaWC Qualification ConcacafWC Qualification EuropeWC Qualification OceaniaWC Qualification South AmericaWomen's Olympic QualifyingWomen's Olympic Qualifying CAFWomen's Super LeagueWorld CupYouth League

Serie B — 44 teams

TeamLeagueMPGoalsAvg xGShots/GPoss%Corners/GCards/G
EmpoliSerie B73112014.651%5.72
PalermoSerie B111168013.750%5.12.3

Understanding Expected Goals (xG)

Expected Goals (xG) is the single most important advanced metric in modern football analytics. It measures the quality of scoring chances by assigning each shot a probability of being scored, based on factors like distance, angle, assist type, and whether it was a header. A penalty is worth about 0.76 xG, while a long-range shot might be just 0.03.

The Avg xG column shows how many goals a team is expected to score per match based on their shot quality. Teams with high xG but lower actual goals are likely due a positive regression — they are creating chances but not converting them yet. The reverse (low xG, high goals) suggests a team overperforming that may regress. Read our detailed xG explainer for a deeper dive.

Shots, Possession, and What They Tell You

Shots per game indicates offensive intent — teams averaging 15+ shots are creating volume. But shots alone do not tell you about quality, which is why xG is the more reliable predictor. A team with 10 shots and 1.8 xG is more dangerous than one with 16 shots and 1.2 xG.

Possession (highlighted green above 55%) reflects control but not necessarily dominance. Some of Europe's best counter-attacking teams thrive on low possession. For betting, possession is most useful in predicting corner counts (high-possession teams win more) and tempo (high-possession games tend to be lower scoring).

Discipline: Cards Per Game

The Cards/G column tracks total cards per match per team. This is useful for the cards/bookings market, which some bookmakers offer as over/under on total cards or total booking points. Teams with aggressive pressing styles or those frequently defending deep tend to commit more fouls and receive more cards. Cross-reference with form — teams on losing streaks often accumulate more cards from frustrated tackles. Check our corner data alongside cards, as set-piece-heavy teams with high card counts create chaotic matches ideal for Over bets.

CesenaSerie B8090011.848%4.82.4
FrosinoneSerie B155207014.350%5.52.5
Virtus EntellaSerie B8371010.948%4.52.1
AvellinoSerie B423909.848%4.82.1
Juve StabiaSerie B7279011.253%4.72.7
VeneziaSerie B118197014.554%5.22.1
SampdoriaSerie B109124—12.549%4.52.8
BeneventoSerie B4164—14.554%5.32.1
CagliariSerie B65—11.757%6.30.8
VicenzaSerie B7884—12.747%5.13
PerugiaSerie B3942—12.851%4.83.3
ModenaSerie B122129—12.949%52.3
AscoliSerie B115127—1348%4.52.9
PisaSerie B158222—13.350%4.72.6
PescaraSerie B8177—12.748%4.42.2
MonzaSerie B112171—13.855%5.72.3
SassuoloSerie B3878—13.652%4.31.9
ReggianaSerie B144142—10.947%3.82.7
TernanaSerie B78102—13.547%4.82.7
CatanzaroSerie B112167—11.756%4.22.3
SalernitanaSerie B7781—12.147%3.92.4
CarrareseSerie B6875—12.250%52.5
LecceSerie B80132—15.153%5.62.3
AlessandriaSerie B3837—11.849%5.32.9
RegginaSerie B7673—10.849%4.23.1
CittadellaSerie B156160—12.849%53
PordenoneSerie B7669—11.946%4.82.7
CremoneseSerie B162230—15.254%5.32.6
BresciaSerie B157206—13.250%4.92.3
LeccoSerie B3835—13.547%4.92.8
FeralpiSalòSerie B3844—12.345%4.62.2
MantovaSerie B6879—13.860%4.52.5
CosenzaSerie B154147—11.848%4.63
CrotoneSerie B3841—12.652%5.32.7
Calcio PadovaSerie B3335—10.848%3.92.5
ChievoVeronaSerie B3952—13.152%6.11.9
SüdtirolSerie B106127—11.244%4.22.5
ComoSerie B80109—12.747%4.32.2
SpeziaSerie B118134—13.650%5.22.7
SPALSerie B7688—13.451%5.22.6
ParmaSerie B76114—13.250%5.52.5
Bari 1908Serie B119121—12.350%4.82.4