We import all our data from fbref™
Listed below are excel or CSV files that contain ready-made striped data.
I exclusively use this data to perform our data analysis.
Customised Data File - Top 35 u23 forwards with a Transfermarkt™ value of less than £10 Million (35u10 data)
This large customised Database is a culmination of hours of work where I scouted and selected the top 35 u23 forward prospects in Europe's top 5 leagues, and compared their shooting, passing, defensive and in-possession ability. The data also includes the new weighted scores for each of the above 4 subsets.
The data has all been adjusted to per/90 and is ready to use.
Please note that all data is correct as of December 2020
Premier league Cumulative
This file contains in-depth data that combines data from the defending, in-possession, passing and shooting files for all premier league players in 20/21. The data has all been adjusted to per/90 and is ready to use. The data also includes the new weighted scores for each of the above 4 subsets.
Please note that all data is correct as of January 2021
Premier League Defending
This file contains in-depth data on defensive actions from all premier league players in 20/21. The data has all been adjusted to per/90 and is ready to use - we have also edited the data to include aerial duels and their win percentage as we feel this is also a large part of defending.
Please note that all data is correct as of January 2021
Explaining the weighted scores
My weighted scores use an algorithm created to help provide a summary of the data used in one concise value for each field of football. The values contain many different stats weighted as per my personal belief of their importance, for example tackle success rate for a defender will have more of an influence on ratings than the total tackles made. The value does not necessarily have a set maximum value, however, any score in the region of 100+ should be considered exceptional. Moreover, to ensure the values are spread over the region of 0-100 in the data visualisations, I usually take percentile ranks in the required data set - this ensures more tailor made comparisons. In addition, in the Premier League cumulative file, I have manually edited the algorithm such that all the scores are in the 0-99 range, and the very few outliers can easily be assumed as having a score of 99 - hence when comparing the Premier League weighted scores against the weighted scores in any other data set, the results will not be fair and it is best to primarily compare scores only between players in the same database.