Officiating intelligence for the third team on the field.

EPL officiating research

Ranked Premier League officiating patterns from the Ref Watch dataset, with effect sizes, sample sizes, and links to evidence.

6 high-confidence findings

Games analyzed: 3,800
referees included: 48
Seasons covered: 2016–2026 (10 seasons)
Analysis generated: 2026-09-30T00:31:17.847Z
Methods: Methodology

Showing 2016-2026

Andre Marriner runs 2.9 fewer fouls than league average

Sample: 164 games • Data maturity: High

18.6fouls per game

-2.9 vs 21.5 league avg

Official 18.6 per gameLeague avg 21.5

18.6
fouls per game: -2.9vs 21.5 league avg; 56.7%
Over benchmark: 2.8 goals; 3
Avg combined total goals: +0.2vs league

Whistle pace compares fouls volume to the league average in this dataset. High or low foul counts do not automatically predict scoring or spread outcomes. Sample depth is strong (100+ games in this finding).

View evidence

High-confidence findings

#2
League trend
2025-26 vs 2024-25: league scoring and whistle context
2.8 goals2025-26 avg total
380 games
Sample: 760 games • Data maturity: High
League scoring held steady year over year (2024-25 to 2025-26).
View evidence
#3
Ref outlier
Michael Salisbury runs +0.5 on combined scoring
+0.5Scoring delta
vs 2.8 league avg
LowerLeague avgHigher
Sample: 61 games • Data maturity: High
Michael Salisbury's 61 games average 3.3 combined points (65.6% over 2.8), one of the largest scoring deltas in the pool.
View evidence
#4
Ref outlier
Sam Barrott leads the pool on over frequency
66.1%Over benchmark
62 games
0%50% neutral100%
Sample: 62 games • Data maturity: High
66.1% of Sam Barrott's 62 games finish over 2.8 combined total goals, 16.1 pts from a neutral 50% baseline.
View evidence
#5
Whistle extreme
David Coote foul pace outlier
23.5Fouls
+2.0 vs 21.5
Official 23.5 per gameLeague avg 21.5
Sample: 112 games • Data maturity: High
David Coote: 23.5 fouls/match.
View evidence
#6
Ref outlier
Robert Madley leads the pool on under frequency
36.0%Under benchmark
50 games
0%50% neutral100%
Sample: 50 games • Data maturity: High
36.0% of Robert Madley's 50 games finish under 2.8 combined total goals, 14.0 pts from a neutral 50% baseline.
View evidence

These are descriptive historical associations. They do not establish causation or predict individual games.

← EPL games

Officiating intelligence for the third team on the field.

EPL officiating research

Ranked Premier League officiating patterns from the Ref Watch dataset, with effect sizes, sample sizes, and links to evidence.

6 high-confidence findings

Games analyzed: 3,800
referees included: 48
Seasons covered: 2016–2026 (10 seasons)
Analysis generated: 2026-09-30T00:31:17.847Z
Methods: Methodology

Showing 2016-2026

More in this league

League baseline

2.8 combined goals21.6 cards shown per gamebenchmark 2.5 (O/U comparison threshold (matches observed average in this scope))

Whistle extreme