Goalkeeper data analysis: Nikita Haikin – FK Bodø/Glimt 2021

On day 17 of Blomgas, I bring you a goalkeeper analysis. I’ve had a look at the Norwegian Eliteserien 2021 and looked at the goalkeepers’ performances. In this analysis, I will have a closer look at FK Bodø/Glimt’s goalkeeper Nikita Haikin, in their championship-winning season.

The data comes from Wyscout.

In my data, only players are concluded who have played on the goalkeeper position and have played over 600 minutes. This leaves me with 21 players. In this analysis, I will use data to look at how well Haikin has performed.

In the image below you see a radar with the percentile ranks. Based on the data in the metrics they say in which percentile rank a certain player is compared to his peers.

Conceded goals per 90
In this metric, we look at how many goals per 90 have been conceded. This is linked with the number of shots and the dominance of the game, but how higher the percentile, the lower the quality in terms of this radar. Haikin has 0,57 goals conceded per 90, which is the lowest of the league and therefor he is performing as one of the best in this particular metric.

Expected goals against per 90
In this metric, we look at the likelihood that a shot is converted into a goal. The number of xGA measures the quality of a shot and how many conceded goals per 90 we can expect. The xGA per 90 is 0,91, meaning that less than 1 goal per 90 is meant to be a goal. Again, this is the lowest in the league and therefore he is performing as the best in this particular metric.

Prevented goals per 90
In this metric, we look at the two metrics above and combine them. How many goals were expected to go in and how may actually did go in. Extract the conceded goals from the expected goals and you get a positive or negative result. Haikin has a positive result of +0,158 – meaning that he prevented more goals than one would expect. He is in the 90th percentile for this metrics, as one player has done better.

Shots against per 90
In this metric, we look at the shots conceded per 90 minutes. We can’t really blaim this on goalkeeper, as the defence needs to deal with this and prevent them, but it gives us an indication of how many shots have been faced and that’s important when we look at expected goals against. Haikin faces 3,36 shots per 90 which gets him into the 10th percentile: he doesn’t face many shots in comparison to his peers.

Clean sheets per 90
In this metric, we look at the number of games, the goalkeeper has had a clean sheet: no goals conceded. It does tell us about the state of defending. Many clean sheets do indicate draws and/or wins, and no losses. That’s a positive thing. Haikin has 13 clean sheets and that’s the most of all, hence his 99th percentile ranking.

Save rate, %
In this metric we look at the number of shots faced and how many shots of those have been saved. It obviously is linked to the conceded goals, but it also tells us more than just shots against per 90, because the goalkeeper is actually involved in the saving. Haikin has a save rate of 77,67% when facing 3,36 shots per 90. He is the best in the league with this percentage and that’s why he is in the 99th percentile ranking.

Exits per 90
In this metric, we look at the number of times the goalkeeper leaves his line to claim or punch a ball after a high cross or long aerial pass. It shows us the commitment to get to the ball and the willingness to clear danger. Haikin has 1,24 exits per 90, which means he is in the 35th percentile compared to his peers. Not the best, but again the notion that not every team they play against, will play a high cross and FK Bodø/Glimt is a very dominant side in most games.

Aerial duels per 90
In this metric, we look at the number of aerial duels played per game by the goalkeepers. Obviously here are linked with the exits per 90. Hakin has 0,33 aerial duels per 90, in which he is in a duel with an attacker of the opposition. In this metric, he is in the 35th percentile. Again, we have to take into consideration the team Haikin is playing in and the opposition they receive.

In this short analysis, I’ve tried to illustrate what you can do with goalkeeper data and how to look closer to this in analysis. Goalkeeper analysis is more complex as the data is very much subjective and technical analysis is needed, but this gives an indicatio to what you can do with data.

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