Home → Penalty Analysis
Penalty Analysis
Home/away penalty splits for every referee, adjusted for possession. Possession is used as a proxy for attacking intent — a team with more of the ball should, in theory, generate more penalty-worthy situations.
Avg Home Pen Bias
+10.6
across 21 referees (≥5 pens, ≥10g)
Total Penalties
266
across 1051 matches · 3 seasons
Home Penalty Share by Referee (possession-adjusted)
Possession-adjusted: how many percentage points more (or fewer) home penalties each referee awards vs what possession share predicts. Referees with ≥5 penalties and ≥10 games.
Full Penalty Data
| Referee | Games | Pens | P/game | Home | Away | Home% | Exp% | Bias ↓ |
|---|---|---|---|---|---|---|---|---|
| Simon Hooper | 63 | 8 | 0.127 | 8 | 0 | 100.0% | 50.9% | +49.1 |
| Lewis Smith | 10 | 5 | 0.500 | 5 | 0 | 100.0% | 58.4% | +41.6 |
| Jarred Gillett | 54 | 15 | 0.278 | 11 | 4 | 73.3% | 47.4% | +25.9 |
| Robert Jones | 59 | 16 | 0.271 | 12 | 4 | 75.0% | 51.2% | +23.8 |
| Andrew Madley | 58 | 10 | 0.172 | 7 | 3 | 70.0% | 49.6% | +20.4 |
| Darren Bond | 19 | 7 | 0.368 | 5 | 2 | 71.4% | 52.8% | +18.6 |
| Matthew Donohue small sample | 5 | 3 | 0.600 | 2 | 1 | 66.7% | 48.6% | +18.1 |
| Chris Kavanagh | 65 | 18 | 0.277 | 12 | 6 | 66.7% | 49.8% | +16.9 |
| David Coote | 22 | 6 | 0.273 | 4 | 2 | 66.7% | 51.6% | +15.1 |
| Tim Robinson | 46 | 10 | 0.217 | 6 | 4 | 60.0% | 49.0% | +11.0 |
| Michael Oliver | 70 | 10 | 0.143 | 6 | 4 | 60.0% | 51.7% | +8.3 |
| Samuel Barrott | 55 | 14 | 0.255 | 8 | 6 | 57.1% | 50.7% | +6.4 |
| Thomas Bramall | 39 | 12 | 0.308 | 7 | 5 | 58.3% | 54.7% | +3.6 |
| Darren England | 49 | 9 | 0.184 | 5 | 4 | 55.6% | 52.2% | +3.4 |
| J Smith small sample | 7 | 2 | 0.286 | 1 | 1 | 50.0% | 46.7% | +3.3 |
| Michael Salisbury | 39 | 21 | 0.538 | 12 | 9 | 57.1% | 55.2% | +1.9 |
| Tony Harrington | 39 | 11 | 0.282 | 6 | 5 | 54.5% | 52.9% | +1.6 |
| Paul Tierney | 30 | 6 | 0.200 | 3 | 3 | 50.0% | 49.7% | +0.3 |
| John Brooks | 49 | 14 | 0.286 | 7 | 7 | 50.0% | 50.9% | -0.9 |
| Craig Pawson | 58 | 17 | 0.293 | 8 | 9 | 47.1% | 50.3% | -3.2 |
| Peter Bankes | 54 | 13 | 0.241 | 6 | 7 | 46.2% | 51.6% | -5.4 |
| Anthony Taylor | 79 | 27 | 0.342 | 12 | 15 | 44.4% | 50.1% | -5.7 |
| Stuart Attwell | 54 | 11 | 0.204 | 5 | 6 | 45.5% | 54.8% | -9.3 |
| Andrew Kitchen small sample | 5 | 0 | 0.000 | 0 | 0 | — | 57.4% | — |
| G Scott small sample | 6 | 0 | 0.000 | 0 | 0 | — | 59.3% | — |
Methodology
Penalty data sourced from FBref (PKatt column) and joined to our match dataset via date + team name. Home Pen% = share of that referee's penalties awarded to the home team. Expected% = average home possession across that referee's matches (a proxy for attacking intent). Bias = Home Pen% − Expected%. A positive bias means home teams received more penalties than their possession share would predict. Referees with fewer than 5 total penalties are flagged as small sample. Possession data from FBref.
Penalty data sourced from FBref (PKatt column) and joined to our match dataset via date + team name. Home Pen% = share of that referee's penalties awarded to the home team. Expected% = average home possession across that referee's matches (a proxy for attacking intent). Bias = Home Pen% − Expected%. A positive bias means home teams received more penalties than their possession share would predict. Referees with fewer than 5 total penalties are flagged as small sample. Possession data from FBref.