A sample pre-match analysis report in Elite Football using Fbref Data

Let’s imagine Scunthorpe united in the premier league and are about to play Everton in the upcoming fixture. Assuming that all of their players are available for selection, the manager has asked to put my analytical hat on and produce a report that summarises the following:

- What are the main characteristics of Everton’s play?

• Dangerous/important players at Everton and what do they contribute?
• How have they set up in recent games?
• Are there any weaknesses we can exploit?
• How do they press?
• Is there anything else we should know about them?

I’m looking to use Fbref data and have data engineered all the games of Everton in the 20/21 season hoping I can unearth some actionable insights.

1. Who are the Dangerous/important players at Everton and what do they contribute?

Identifying key contributors to attacking threat through metrics xG,xA

The above image gives an easy indication that James Rodriguez and Dominic Calvert are probably the most dangerous players. But why have I included Richarlison and Iwobi? Let’s discuss.

Firstly, Dominic Calvert-Lewin (DCL)is having probably one of his best seasons as a toffee.

Higher Likelihood of scoring for every shot taken

By looking at his xG/Shot ratio, we can conclude that DCL will most likely take shots when he’s closer to goal to have clear-scoring opportunities. Perhaps, a box striker or more of a central striker (Poacher).

Secondly, the Progressive Carries into Box shows that DCL will most likely carry the ball into the box amongst other players if he does receive the ball outside the box in the final third.

Carries into Box/Progressive Carries

Thirdly, DCL receives ball mostly in the penalty area, with some team interaction in the final third.

James Rodriguez

Shot creating Actions is a good indicator that James Rodriguez is involved in actions leading shots

Penalty Area Passes is a good indicator that James Rodriguez maximises his involvement in Forward passes into Final Third and Penalty Area

Check for Correlation

19 out of 22 attacking variables chosen were highly correlated i.e. James Rodrigues will have better stats than others in similar (all) variables so no point overestimating stats.

Method Chosen: Correlation > 0.70 and a Variance Inflation Factor >10

Attacking Contributions from other players

2) How have they set up in recent games?

3) Pressure Intensity Per Area as a percentage(%)

4) How do they press?

Final Recommendations

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