EPL insights
Tendency index, league-wide trends, and ranked dataset findings in one place.
Historical scoring and whistle tendencies across qualified officials. Descriptive associations with league baselines, not predictions. Sample: 48 officials (2016-08-13 – 2026-05-24).
Who moves the goals?
The 31 referees with 30+ games, ranked by historical associations in their games.
Biggest scoring bump
Michael Salisbury+0.5 GHe averages 0.5 more combined goals than the league baseline in his games.
Highest historical over-rate vs baseline
Sam Barrott66.1%Line benchmark is 2.5 combined goals; he clears it more often than peers in this sample.
Heaviest fouls ref
Michael Jones+2.5He runs 2.5 fouls called above average per game.
1 of 31 referees associate with higher scoring. 2 associate with lower totals. Numbers describe past games, not predictions for tonight.
| # | Official | Signals | ||||
|---|---|---|---|---|---|---|
| 1 | 61 | +0.5 | +1.3 | 65.6% | 1 notable | |
| 2 | 85 | +0.3 | -1.5 | 60.0% | 1 notable | |
| 3 | 62 | +0.3 | -1.3 | 66.1% | 1 notable | |
| 4 | 164 | +0.2 | -2.9 | 56.7% | 2 notable | |
| 5 | 295 | +0.2 | -0.3 | 58.6% | 1 notable | |
| 6 | 99 | +0.2 | +0.4 | 54.5% | ||
| 7 | 287 | +0.2 | +0.3 | 58.9% | 1 notable | |
| 8 | 133 | +0.1 | +1.6 | 57.9% | 1 notable | |
| 9 | 160 | +0.1 | -0.2 | 54.4% | ||
| 10 | 84 | +0.1 | +0.3 | 56.0% | 1 notable | |
| 11 | 44 | +0.1 | -1.4 | 61.4% | 1 notable | |
| 12 | 139 | +0.1 | +0.2 | 53.2% | ||
| 13 | 100 | +0.0 | -1.4 | 58.0% | 1 notable | |
| 14 | 30 | +0.0 | +2.5 | 56.7% | 2 notable | |
| 15 | 190 | +0.0 | +0.6 | 55.8% | ||
| 16 | 195 | +0.0 | -1.0 | 55.9% | ||
| 17 | 229 | -0.1 | +1.2 | 52.8% | ||
| 18 | 112 | -0.1 | +2.0 | 53.6% | ||
| 19 | 136 | -0.1 | -1.0 | 50.0% | ||
| 20 | 110 | -0.1 | +1.1 | 55.5% | ||
| 21 | 39 | -0.1 | +0.6 | 53.8% | ||
| 22 | 49 | -0.1 | +1.8 | 46.9% | ||
| 23 | 48 | -0.1 | +0.2 | 47.9% | ||
| 24 | 193 | -0.2 | -0.3 | 49.2% | ||
| 25 | 74 | -0.2 | +0.3 | 50.0% | ||
| 26 | 168 | -0.2 | -1.3 | 53.6% | ||
| 27 | 162 | -0.2 | -0.3 | 45.7% | ||
| 28 | 115 | -0.2 | +0.2 | 52.2% | ||
| 29 | 52 | -0.2 | +0.9 | 50.0% | ||
| 30 | 36 | -0.4 | -1.4 | 44.4% | ||
| 31 | 50 | -0.5 | +1.7 | 36.0% | 1 notable |
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