Betting Analytics
Use this data to identify leagues where outcomes are most predictable based on years of historical results. Higher favourite win rates mean more reliable pre-match favourites.
Result distribution
Goals per game
Over 2.5 goals
Predictability (favourite wins)
Detailed table
| League | Home | Draw | Away | Avg goals | Over 2.5 | Favourite wins | Predictability |
|---|---|---|---|---|---|---|---|
| 47.3% | 23.6% | 29.1% | 3.07 | 58.5% | 56.2% | 56% | |
| 46.3% | 25.5% | 28.2% | 2.53 | 46.4% | 55.0% | 55% | |
| 48.9% | 24.3% | 26.8% | 2.46 | 44.9% | 54.8% | 55% | |
4.Serie A | 45.4% | 27.4% | 27.1% | 2.65 | 49.5% | 54.4% | 54% |
| 45.6% | 25.5% | 28.8% | 2.70 | 50.6% | 54.1% | 54% | |
| 43.6% | 24.2% | 32.1% | 2.68 | 50.6% | 53.8% | 54% | |
7.La Liga | 47.3% | 25.8% | 26.9% | 2.66 | 49.4% | 53.5% | 54% |
| 46.9% | 24.9% | 28.2% | 2.80 | 53.1% | 52.7% | 53% | |
| 46.5% | 24.5% | 28.9% | 2.87 | 54.2% | 52.6% | 53% | |
10.Bundesliga | 46.1% | 25.4% | 28.5% | 2.94 | 56.2% | 51.7% | 52% |
11.Ligue 1 | 46.3% | 27.9% | 25.8% | 2.47 | 44.7% | 51.0% | 51% |
12.Scottish League One | 42.8% | 23.7% | 33.5% | 2.92 | 56.0% | 50.2% | 50% |
13.Scottish League Two | 42.9% | 22.3% | 34.8% | 2.87 | 53.7% | 50.2% | 50% |
14.National League | 43.2% | 25.5% | 31.3% | 2.71 | 50.6% | 48.6% | 49% |
| 41.2% | 26.8% | 32.0% | 2.67 | 49.4% | 48.1% | 48% | |
16.League One | 43.6% | 26.3% | 30.1% | 2.61 | 49.0% | 47.7% | 48% |
| 45.5% | 27.6% | 26.8% | 2.76 | 52.1% | 47.2% | 47% | |
18.Championship | 43.4% | 27.4% | 29.2% | 2.55 | 47.4% | 46.4% | 46% |
19.Ligue 2 | 44.5% | 31.0% | 24.5% | 2.32 | 41.1% | 46.3% | 46% |
20.Serie B | 44.0% | 32.3% | 23.7% | 2.42 | 43.7% | 46.2% | 46% |
| 44.8% | 30.0% | 25.3% | 2.36 | 41.9% | 45.9% | 46% | |
22.League Two | 42.0% | 27.3% | 30.7% | 2.55 | 46.9% | 45.4% | 45% |
This page shows historical statistics — not betting recommendations. The data describes long-term patterns, not the outcome of individual matches. Any betting decision you make is entirely your own responsibility.
What each metric means
Result distribution (H / D / A)
Percentage of matches ending in a home win, draw, or away win — calculated across all available seasons. If home teams win 46% of games and you see odds of 1.90 for the home win, the implied probability is 53% (1/1.90). The historical base rate is 46%. The bookmaker is asking for more than history suggests — that alone is not a reason to bet or avoid, but it is important context.
Average goals per game
Average total goals per match in this league. Leagues above 2.70 historically produce more goals, raising the base probability that a given match finishes over 2.5. This does not mean every match will be high-scoring — only that the league as a whole leans offensive. The base rate for any specific match depends on team form, absences, and tactics.
Over 2.5 goals (%)
The direct historical base rate for "over 2.5 goals" bets: what percentage of matches in this league finished with 3 or more goals. If a league sits at 55% and the bookmaker offers 1.70 (implied probability 59%), the bookmaker estimates slightly above the long-term history. Again — not a recommendation, just a comparison of your estimate against the historical base rate and the offered price.
Predictability (favourite wins)
Percentage of matches where the team with the lower odds (the favourite) won. A higher value means odds have historically been a good indicator of the outcome — results in this league are easier to call. Important caveat: even in a "predictable" league, the favourite loses 40% of the time. And odds are set precisely to reflect these probabilities over the long run — blindly backing favourites is not a profitable strategy.
How to interpret this data without being misled
When a league has 46% home wins, that applies to the average of all matches over 20 years. A specific match between the league leader and the bottom team has a very different probability. The base rate gives you context, not the answer.
Bookmakers have the same data and far more sophisticated models. Odds are set to reflect these base rates plus margin. Simply following statistics offers no edge — value can only arise where your assessment of a specific match, for a good reason, differs from the implied probability in the odds.
Practical example: if you are analysing a Bundesliga match (avg 2.90 goals, 60% over 2.5) versus a French Ligue 2 match (avg 2.35, 45% over 2.5), the data helps you understand the context before you look at the odds. That is a legitimate use of statistics — not as the basis for a bet, but as a framework for forming your own view.
Even the best statistics cannot remove the uncertainty of individual matches. Betting carries financial risk. If you have concerns about your relationship with gambling, visit sites like BeGambleAware.org or GamCare.org.uk.
Data source: football-data.co.uk — historical results and closing odds. This data is not live odds and should not be used as the sole basis for any betting decision.