📈 BOROFORM RATINGS & xG FORECAST

The Forecast (Fcst) League position is the position a team should finish at the end of the season. Using past results and statistical analysis of the matches played so far combined with xG and expected results in the remaining fixtures xG data – @infogolapp


👤 BOROFORM PLAYER RATINGS

A players expected rating should be between 60-70%, if higher than 70% then the player makes a positive impact, if lower than 60% then a negative impact is implied.

(Based on current season stats)

1. Stewart Downing 73%
2. Cyrus Christie 71%
3. Adam Clayton 71%
4. Jonny Howson 70%
5. Rudy Gestede 70%
6. Martin Braithwaite 70%
7. Dael Fry 69%
8. Lewis Baker 69%
9. Ryan Shotton 69%
10. Britt Assombalonga 69%
11. Ben Gibson 69%
12. Fabio da Silva 69%
13. Marvin Johnson 68%
14. Adama Traore 68%
15. Darren Randolph 68%
16. Marcus Tavernier 68%
17. Patrick Bamford 68%
18. Grant Leadbitter 68%
19. Adam Forshaw 67%
20. Ashley Fletcher 67%
21. Dani Ayala 67%
22. George Friend 66%
23. Connor Roberts 65%
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RATINGS EXPLANATION

What started out as a way to forecast the top six and to calculate Boro’s finishing position for the 2015/16 Championship season turned into a rather large spreadsheet of team and player data.

After forecasting 4 out of the Championship top six correctly and predicting Boro to finish second in the league, I have found the figures to be relatively reliable so started a project to rate all teams and players using this formula.

In its current form there are ratings based on all positive and negative touches during every match for every player and ratings for all teams from all around the world giving me a base to compare and rate Boro players and Boro team form versus others.

The predictions remained solid on Boro’s return to the Premier League..

So how do we know what is good and what is not?

As for teams, a rating above 80% would mean a team would be capable of competing in top tier football and a rating below 60% would be non league standard. A rating of at least 85% is generally required for survival in the Premier League.

When comparing teams head to head a ratings difference of more than 5% would be an expected win, the closer the teams are rated the tougher the opposition.

What about player ratings?

As for rating players, Opta stats are used and each stat is treated as a positive or a negative to give an overall player rating per 90 minutes play.

For example : a succesful pass is a positive, an unsuccesful one is a negative, shot on target positive, off target negative, and so on with tackles, Clearances, aerial duels etc…

A players expected 90 minute rating should be between 60-70%, if higher than 70% then the player makes a positive impact, if lower than 60% then a negative impact is implied.

All player ratings are taken as an average and then added to the Teams rating (Which is made up of performances against the quality of opposition and results over a two season rolling basis).

I hope this clarifies how the ratings are worked out (I’ve tried not to use too much jargon), If you have any questions feel free to contact me on @boroform , all questions welcome.

🏐 xG explained on the BBC website

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