Goalkeeping Research

Goalkeeping is a favourite subject here at Differentgame. There isn’t anywhere else you can get long-term contextual statistics on them publicly – even on the great football data websites.

I’ve developed my own shot-stopper statistics and our model has been featured on both the Prozone and OptaPro websites.

I have 6 years worth of Premier League shot-stopping data collated on my Tableau viz

Below is a sample of my research:

The effect of positioning on saves made

The role of luck in shot-stopping

The keeper’s comfort zone

Scouting keepers using data


My keeping model recently featured in Dutch national daily de Volkskrant:

14 Saves in a Match: How Good is Tim Krul?

2 Responses to Goalkeeping Research

  1. schmeet1 says:

    First of all, I love your stuff on this site.

    Is there a worry that when you look at individual keepers save numbers that you don’t have enough samples to have enough certainty to make a judgment that, for example, 75% on the left is worse than 80% on the right.

    For example, if there were 3 shots saved out of 4 on the left then that is 75% but with an error of around 20%
    If 4 shots were saved out of 5 on the right then that is 80% but with an error of around 17%.

    In this case he could infact be better on the left even though the percentage is better on the right.
    75% +/- 20% could be more than 80% +/- 17%

  2. Sample size will always be an issue. I’m actually tidying up my keeper data at present and have just 20 keepers who have made 300+ saves in last 4 yrs of epl.

    I will be writing something on that over summer.

    I also did a piece called ‘funnely old game’ re stat significance with keepers so have a search for that.

    I will revisit that piece after next season with updated no’s as there should be enough to possibly make it more illuminating


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