Player influence on team goal difference (Premier League)

This blog was written on 26/4/2015, after Round 35 of the Premier League 2015/16.

You know that situation when you leave the pitch when your team is winning 2-1? At the end of the 90 minutes the opponents have turned everything around and won the match 2-3.  Stubborn as you are you tell your manager and teammates that you DID win the game, having left the field in a winning situation.

Taking those situations into account we can calculate the effectivity of each player in his team: how many goals does his team score when he is on the pitch compared to when is not present? And what impact does he have on the total goal difference?

First, a table of the player with the best goal difference when on the pitch this Premier League season (2015/16):

Player goal difference on the pitch
Player goal difference on the pitch

As you can see, the table only includes players of the best 3 teams (highest in the table that is), and only the ones with a lot of minutes played. It would be a bit more fair to take the more responsible metric of goals and goals conceded per 90 minutes. Taking only players with 400+ minutes we’d get the following list:

Player goal difference per 90 minutes
Player goal difference per 90 minutes

 

When we select only players with at least 400 minutes on the pitch and at least 400 on the bench (or in the stands, or on their Playstation at home):

Player impact on goal difference
Player impact on goal difference

The same criteria but then separated for goals scored and goals conceded:

Impact on goals scored by team (per 90 minutes)
Impact on goals scored by team (per 90 minutes). Roles: 1 (GK), 2 (DEF), 3 (MID), 4 (ATT).
Impact on goals conceded by team (per 90 minutes). Roles: 1 (GK), 2 (DEF), 3 (MID), 4 (ATT).
Impact on goals conceded by team (per 90 minutes). Roles: 1 (GK), 2 (DEF), 3 (MID), 4 (ATT).

 

If you want to read more about this, @goalimpact has a lot more to say about it and also has a much more complex and extensive algorithm to calculate player impact.

It also corrects the goal difference for opponent’s strength, something that was not applied to this data.

Note2: all raw data comes from DataFactory.

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