How well the model reads each competition
The same log that scores the model on the accuracy page, grouped by competition. Every prediction here was written down before kick-off and scored once the match finished; nothing is added afterwards. A competition appears once it has 25 settled predictions behind it, which 75 competitions now do.
The order is the plain hit rate — how often the model called the right result, home win, draw or away win, in that competition's matches. Nothing is smoothed or weighted on the way: whoever we have got right most often is top, whoever we have got wrong most often is last.
Which is exactly why the sample column matters. At 25 predictions the margin of error on a hit rate is around 18 percentage points, so the very top and the very bottom of this table are partly luck and will move. Read the number of predictions next to every figure. The middle of the table, where most sit near 50.0%, is the honest picture of this model.
Read best
- Premier League — 65.0% of 40 calls right.
- Bundesliga — 63.9% of 72 calls right.
- 1. Division — 62.9% of 35 calls right.
- Ligue 3 — 62.9% of 35 calls right.
- Süper Lig — 61.6% of 99 calls right.
- UEFA Champions League — 60.4% of 134 calls right.
- Serie A — 60.0% of 110 calls right.
- Super Liga — 59.8% of 82 calls right.
Read worst
- Botola Pro — 32.7% of 55 calls right.
- Ligue 2 — 34.3% of 108 calls right.
- K League 1 — 35.4% of 79 calls right.
- Pro League — 35.7% of 28 calls right.
- Premyer Liqa — 36.7% of 30 calls right.
- Finnish Premier League — 36.9% of 65 calls right.
- Serie B — 38.2% of 110 calls right.
- Liga MX — 39.3% of 135 calls right.
Every competition we have scored
All 75 of them, best-called first. The last column is the part that is about the model rather than about the football: how much ground it gained on a forecast that knew nothing and split every match three ways. A row can sit high on the hit rate and low on that one — a side or a league whose matches are easy to call flatters us — and where the two disagree, the last column is the one describing us.
| # | Competition | Predictions | Correct result | Exact score | Beat the baseline by |
|---|---|---|---|---|---|
| 1 |  Premier LeagueBelarus | 40 | 65.0% | 12.5% | +23.6% |
| 2 |  BundesligaAustria | 72 | 63.9% | 4.2% | +19.2% |
| 3 |  1. DivisionCyprus | 35 | 62.9% | 11.4% | +19.8% |
| 4 |  Ligue 3 | 35 | 62.9% | 17.1% | +15.9% |
| 5 |  Süper Lig | 99 | 61.6% | 13.1% | +15.9% |
| 6 |  UEFA Champions League | 134 | 60.4% | 6.7% | +14.6% |
| 7 |  Serie AItaly | 110 | 60.0% | 11.8% | +16.6% |
| 8 |  Super LigaSerbia | 82 | 59.8% | 6.1% | +18.8% |
| 9 |  Pro LeagueSaudi Arabia | 69 | 59.4% | 8.7% | +18.3% |
| 10 |  HNL | 64 | 59.4% | 18.8% | +15.0% |
| 11 |  Jupiler Pro League | 99 | 58.6% | 9.1% | +17.2% |
| 12 |  Super League 1 | 68 | 57.4% | 4.4% | +15.1% |
| 13 |  UEFA Nations League | 132 | 56.8% | 15.9% | +13.8% |
| 14 |  Primera DivisiónPeru | 48 | 56.3% | 10.4% | +10.6% |
| 15 |  Primeira Liga | 98 | 56.1% | 14.3% | +14.2% |
| 16 |  Superliga | 84 | 56.0% | 10.7% | +8.1% |
| 17 |  BundesligaGermany | 81 | 55.6% | 12.3% | +11.2% |
| 18 |  League One | 76 | 55.3% | 9.2% | +11.9% |
| 19 |  Premier Soccer League | 66 | 54.5% | 16.7% | +9.9% |
| 20 |  Eliteserien | 103 | 54.4% | 8.7% | +12.4% |
| 21 |  Premier LeagueEgypt | 54 | 53.7% | 14.8% | +6.8% |
| 22 |  Ligat Ha'al | 58 | 53.4% | 10.3% | +12.0% |
| 23 |  Primera A | 94 | 53.2% | 12.8% | +12.2% |
| 24 |  UEFA Europa League | 140 | 52.9% | 8.6% | +14.8% |
| 25 |  Serie BBrazil | 74 | 52.7% | 27.0% | +9.9% |
| 26 |  First League | 93 | 52.7% | 10.8% | +9.8% |
| 27 |  Stars League | 42 | 52.4% | 9.5% | +10.0% |
| 28 | Serie ABrazil | 155 | 52.3% | 10.3% | +10.0% |
| 29 |  UEFA Europa Conference League | 260 | 51.5% | 6.2% | +8.7% |
| 30 |  Czech Liga | 111 | 51.4% | 10.8% | +4.0% |
| 31 |  Premier LeagueUkraine | 37 | 51.4% | 2.7% | +18.7% |
| 32 | Ligue 1France | 90 | 51.1% | 10.0% | +12.2% |
| 33 |  AFC Champions League Elite | 47 | 51.1% | 6.4% | +14.9% |
| 34 |  Eredivisie | 108 | 50.0% | 6.5% | +5.5% |
| 35 |  Erovnuli Liga | 48 | 50.0% | 6.3% | +9.4% |
| 36 |  Division Profesional - Clausura | 42 | 50.0% | 9.5% | +3.7% |
| 37 |  Super LigaSlovakia | 32 | 50.0% | 12.5% | +5.8% |
| 38 | 1. DivisionDenmark | 30 | 50.0% | 6.7% | +5.5% |
| 39 |  La Liga | 119 | 49.6% | 11.8% | +10.1% |
| 40 |  Liga I | 116 | 49.1% | 12.9% | +7.1% |
| 41 |  Ligue 1Algeria | 45 | 48.9% | 22.2% | +9.5% |
| 42 |  Super LeagueSwitzerland | 78 | 48.7% | 7.7% | +5.0% |
| 43 |  Primera DivisiónChile | 33 | 48.5% | 18.2% | +10.7% |
| 44 |  Ligue 1Tunisia | 25 | 48.0% | 8.0% | +8.4% |
| 45 | ChampionshipEngland | 180 | 47.8% | 7.8% | +3.9% |
| 46 | Segunda División | 147 | 47.6% | 9.5% | +6.0% |
| 47 | 2. Bundesliga | 99 | 47.5% | 9.1% | +3.1% |
| 48 | 1. Lig | 59 | 47.5% | 8.5% | +4.2% |
| 49 |  Super LeagueChina | 68 | 47.1% | 5.9% | +7.2% |
| 50 | Eerste Divisie | 64 | 46.9% | 7.8% | +5.6% |
| 51 |  Allsvenskan | 124 | 46.8% | 10.5% | +2.4% |
| 52 | 3. Liga | 60 | 46.7% | 10.0% | +6.0% |
| 53 | League Two | 90 | 45.6% | 12.2% | +1.8% |
| 54 |  Ekstraklasa | 121 | 45.5% | 9.9% | +8.5% |
| 55 |  Premiership | 75 | 45.3% | 13.3% | +6.2% |
| 56 |  Premier LeagueRussia | 89 | 44.9% | 10.1% | +4.4% |
| 57 |  Major League Soccer | 287 | 44.6% | 11.1% | +3.4% |
| 58 |  Persian Gulf Pro League | 45 | 44.4% | 13.3% | +8.7% |
| 59 | ChampionshipScotland | 34 | 44.1% | 14.7% | +4.0% |
| 60 |  Premier Division | 37 | 43.2% | 10.8% | +4.4% |
| 61 | Premier LeagueEngland | 100 | 42.0% | 13.0% | +4.8% |
| 62 |  Liga Profesional Argentina | 240 | 41.7% | 13.8% | +2.7% |
| 63 | I Liga | 46 | 41.3% | 15.2% | +3.8% |
| 64 | Segunda Liga | 40 | 40.0% | 15.0% | +2.6% |
| 65 |  Liga Pro | 40 | 40.0% | 7.5% | +0.2% |
| 66 |  1. SNL | 25 | 40.0% | 12.0% | +0.7% |
| 67 |  NB I | 76 | 39.5% | 10.5% | +2.0% |
| 68 |  Liga MX | 135 | 39.3% | 5.2% | +0.5% |
| 69 | Serie BItaly | 110 | 38.2% | 7.3% | −1.9% |
| 70 |  Finnish Premier League | 65 | 36.9% | 13.8% | −5.0% |
| 71 |  Premyer Liqa | 30 | 36.7% | 13.3% | −0.7% |
| 72 |  Pro LeagueUnited Arab Emirates | 28 | 35.7% | 10.7% | −2.6% |
| 73 |  K League 1 | 79 | 35.4% | 6.3% | −2.9% |
| 74 | Ligue 2 | 108 | 34.3% | 5.6% | −6.8% |
| 75 |  Botola Pro | 55 | 32.7% | 12.7% | +0.7% |
The same question, club by club
A league is the sturdier sample, but the match in front of you is played by two clubs, not by a league — which is why that table uses a bar of 5. How well the model reads each club is the same record at the other level.
A statistical estimate, not betting advice. Nothing here predicts a future match; it records how the model has done so far.