Stop bunching

At the end of last season Ram (@rramesss), Kev (@swansanalytics) and Matt (@PannasNutmegs) and I (@sbunching) decided to combine some of the work we've been doing recently into a case study. We decided to analyse a single Championship club, using data to pick out their playing style, identify players that may need replacing and use data and scouting to suggest realistic replacements. This is a very in-depth document, actually edited down significantly believe it or not, but hopefully, it will give a good insight into the type of work that we can produce. We would love to help clubs that don't already have an analytics department (perhaps at lower levels) turn the data they do hold into something useful for their recruitment teams or coaches. If that sounds like you then please get in touch. Enjoy! https://docs.google.com/document/d/e/2PACX-1vTwOtPflkpuJo_p-kZd1uJElyP18vzjvO8kDQnsd1UxqSgzZaWIy2F2VdAxhbDR72sWSU4Au5XKuwUt/pub

I've been looking more at progressive passes and what it might tell us about spotting players of high potential early on in their career. Original article here Progressive passes, as defined by Wyscout, are forward passes that are 30m long when the pass starts in the team's own half or at least 10m in length in the opponent's half. So far I've only looked at the volume of progressive passing. This has been because I cannot filter the data on the player ranking section of Wyscout other than by age. If I choose per 90 statistics a lot of players with a tiny number of minutes show up and push other players off the results screen (limited to 30). However, my suspicion has been that by using the volume of passes I am effectively looking at young players who played a lot. Young players who play a lot of games in lower divisions will get picked up by bigger teams. So maybe progressive passing isn't the great stat that I keep saying it is? How about I loo