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Home advantage, league by league

Across 12,410 matches in 26 competitions, the home side outscores the away side by 0.32 goals per game and wins 14.3 percentage points more often. The average is not the story — the spread between leagues is.

Recomputed Sep 20, 2026 from the full results dataset · how we work

Goal edge and win-share gap per league

LeagueMatches Home goals/gAway goals/gGoal edge Home win %Away win %Win gap
UEFA Champions League 207 2.06 1.47 +0.58 51.2% 31.9% +19.3
Campeonato Brasileiro Série A 653 1.52 1.06 +0.47 48.9% 24.2% +24.7
Primera Division 448 1.59 1.15 +0.44 48.4% 27.0% +21.4
Mexico Ligamx 673 1.63 1.20 +0.43 47.3% 28.7% +18.6
Norway Eliteserien 461 1.76 1.33 +0.43 48.6% 31.2% +17.4
Bundesliga 341 1.84 1.45 +0.38 44.6% 31.4% +13.2
Poland Ekstraklasa 600 1.58 1.21 +0.37 45.2% 28.7% +16.5
Usa Mls 1003 1.72 1.36 +0.36 45.4% 29.7% +15.7
Spl 253 1.57 1.22 +0.35 44.3% 30.0% +14.2
Ligue 1 349 1.58 1.25 +0.34 45.6% 29.5% +16.0
England League1 599 1.50 1.16 +0.34 45.6% 28.9% +16.7
Greece Super League 249 1.44 1.13 +0.31 41.8% 30.5% +11.2
Germany Bundesliga2 333 1.64 1.34 +0.30 45.3% 30.9% +14.4
Premier League 430 1.53 1.23 +0.29 41.9% 30.2% +11.6
Eredivisie 369 1.79 1.50 +0.29 42.0% 31.7% +10.3
Argentina Primera Division 1066 1.14 0.86 +0.28 41.8% 26.5% +15.4
Spain Segunda Division 495 1.45 1.17 +0.28 44.8% 30.3% +14.5
Austria Bundesliga 385 1.49 1.23 +0.26 42.3% 31.9% +10.4
Denmark Superliga 378 1.66 1.40 +0.25 44.2% 29.6% +14.6
Primeira Liga 365 1.47 1.23 +0.24 40.8% 31.8% +9.0
Japan J League 526 1.36 1.13 +0.23 44.1% 30.6% +13.5
Sweden Allsvenskan 466 1.52 1.30 +0.23 41.0% 34.5% +6.4
Turkey Super League 333 1.45 1.22 +0.23 42.3% 29.1% +13.2
Championship 652 1.43 1.21 +0.22 41.6% 31.3% +10.3
Belgium First Div 347 1.47 1.26 +0.21 41.5% 33.4% +8.1
Serie A 429 1.30 1.18 +0.11 39.4% 35.4% +4.0

Goal edge = home goals per game minus away goals per game. Win gap = home-win share minus away-win share, in percentage points. Leagues qualify at 100+ recorded matches.

How to read this as a bettor

The market prices home advantage into every 1X2 line, but it largely prices the global effect. When a league sits at the top of this table, generic pricing slightly underrates its home sides; at the bottom, it overrates them. The edges are small — a tenth of a goal moves an even-match win probability by two or three points — but they are systematic, which is more than can be said for most angles sold to bettors.

Two honest caveats. First, sample: a season of one league is a few hundred matches, and the extremes of any such table partly reflect noise that will regress. Second, home advantage is not constant — it has drifted downward across football for decades and moves with attendance, altitude and travel distances. That is exactly why this page recomputes from the live dataset on every build instead of quoting a study from five years ago.

Our own model carries separate home and away rates per team rather than one global constant, so league-level differences flow into every probability it publishes. The point of the table is transparency: you can see the raw effect the model sees.

⚠️ Our AI model is still learning from match data. All predictions are experimental statistical estimates for information purposes only — not financial advice and not an invitation to bet. Outcomes are never guaranteed. 18+ · Gamble responsibly.