Who is the Premier League’s Number One Bogey Referee?

Everyone has heard of a bogey team. It’s generally used to describe a team that, for whatever reason, tends to perform poorly against a particular opponent - even if, on paper, they are deemed winnable games. In the mid to late 2000s, Bolton were well known as a bogey team for Arsenal under Sam Allardyce, due to the blend of directness, physicality and technical ability his side possessed. Stoke City under Tony Pulis were also a bogey team for Arsène Wenger, which is partly why the coined phrase “a cold, rainy night in Stoke” became so prominent in football pop culture.

Of course, Arsenal aren’t the only team to have ever had a bogey team, but their relationships with those teams serve as one of the clearest examples of the term in its most extreme form.

But what about bogey referees? What about the teams that seem to get unfavourable results, decisions and disciplinary outcomes depending on who is officiating? Well, if that’s something that interests you, then you’re in luck. AceOdds have delved into the data to see which referee brings the bad luck for each Premier League team, based on combined data from the 2024/25 and 2025/26 seasons.

AceOdds created a Bogey Score using points per game earned, alongside fouls per game, yellow cards, red cards and penalties conceded. The team used Min–Max scaling, where the minimum value for a team was set to 0 and the maximum to 1. A weighted bogey score was then calculated for each team–referee combination using a sum of the normalised metrics. The formula assigned weights as follows:

- 25% to inverted points per game
- 10% to fouls per game
- 15% to yellow cards per game
- 25% to total red cards
- 25% to penalties concededThis score was designed to capture both team underperformance and referee harshness, resulting in a single value where higher scores indicate a worse overall experience for the team under that referee.

Simon Hooper is the Premier League’s Number One Bogey Referee

According to the data, Simon Hooper is the number one bogey referee in the league with the highest score of 0.87, and the team that has suffered the most under his watch is Everton. Under Hooper’s stewardship, Everton have earned 0.17 points per game, with a score of 0.66 for fouls per game, 0.64 for yellow cards per game, and one red card and penalty conceded per game. Interestingly, Hooper ties with another referee as the number one bogey referee.

Michael Oliver follows closely with a bogey score of 0.77, and his number one bogey team is Burnley. Oliver ties Hooper as the referee with the most bogey nominations, as he also happens to be the bogey referee for Manchester United and Liverpool, with scores of 0.66 and 0.53 respectively.

Worryingly for Liverpool and Manchester United, Michael Oliver is officiating their game this weekend and the odds of there being over 6 cards in the match is only 12/5 on bet365. If you want to back the data, you can use the bet365 bonus code and cash in on some free bets even if Oliver keeps the cards in his pocket.

When it comes to Chelsea, John Brooks is their bogey referee when it comes to unfavourable results and decisions. He has officiated four Chelsea games and has a bogey score of 0.76. Across the other side of London, Arsenal will be surprised to find out that their bad omen referee is Robert Jones, with a score of 0.73. Meanwhile, Manchester City’s harshest referee is Chris Kavanagh, with a score of 0.61.

To the surprise of many, the referee with the lowest bogey score is none other than Anthony Taylor, who came in 20th with a score of 0.52.

This data piece has been created for entertainment purposes, while also aiming to explore - and perhaps prove or disprove - the theories of fans who, on a weekly basis, feel harshly treated when it comes to officiating in the Premier League.

Methodology

The goal of this project was to identify the “bogey referee” for each football team - the referee under whom a team tends to perform the worst. This analysis combined both team performance metrics and referee behavior metrics using match data from the 2024/25 and 2025/26 seasons.

Match-level referee statistics were collected from multiple CSV files containing information such as the team and referee names, games played, results, points per game, fouls, yellow and red cards, and penalties conceded. These files were combined into a single dataset for analysis.

The data was then cleaned and standardised. Column names were formatted consistently, and metrics were aggregated by team and referee. Per-game statistics such as points, fouls, and yellow cards were averaged, while total counts like red cards and penalties were summed across matches.

To compare referees fairly within each team, the metrics were normalized between 0 and 1 using Min-Max scaling, where the lowest value for a team became 0 and the highest became 1.

Since lower points per game represents worse performance, this metric was inverted after normalization by calculating one minus the normalized value. The metrics normalized included points per game (inverted), fouls per game, yellow cards per game, total red cards, and penalties conceded.

A weighted Bogey Score was then calculated for each team–referee combination using the following formula: 25% inverted points per game, 10% fouls per game, 15% yellow cards per game, 25% total red cards, and 25% penalties conceded. This score reflects both team underperformance and referee harshness, producing a single number where higher values indicate a worse experience for the team under that referee.

Finally, for each team, the referee with the highest Bogey Score was identified as their bogey referee. The analysis also retained scores for all referees, allowing each team’s referees to be ranked from most to least challenging.

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