BiscuitChaserFC

Following my first tutorial loading R and importing StatsBomb data to plot passes in a specific FAWSL match I've had loads of good feedback! ( Tutorial One ) There seems to be a general appetite for a second part how the plots can be progressed and further information added - so lets give it a go! As always, I will caveat that I'm no expert in R and have been self teaching since Christmas 2019 - as such I'm presenting something that works for me but may not be the *entirely* correct way of doing things! Anyway,  below was the final pass plot we ended up with after the first tutorial. Great that we've plotted the passes, but what can we learn from it? What could a practical application be if we wanted coaches/scouts to take away insight? Looking at below, for me, the plot infers a high density of passes on the right wing in the final third with regular crosses (in this specific match!) along side regular passing actions in the Left Centre Back location. This is...

As always, I should caveat that I'm not an expert either in football or programming...I started learning R in December and have gradually reached a 'mildly competent' level. This will go through installing R, loading the StatsBomb data, then plotting a pass map - something like this: Anyway, away we go. Thing number 1 - install R. There are two things to load...the R 'base' and Rstudio. You can download Rstudio here: https://rstudio.com/products/rstudio/download/ The first 3 minutes of the below shows the process: https://www.youtube.com/watch?v=BuaTLZyg0xs&list=PL6cDc8Xxld162nSsZ14bQnFn1cYStsrtk&index=2&t=0s That is now hopefully R loaded. Open Rstudio and you should be greeted with something like this: Press the arrow areas to reveal: Under the 'Packages' tab select 'install' and search 'devtools'..install package. Repeat the previous step however search 'tidyverse'. Next steps are to load in th...

Since first writing about Oxford's search for Right Back in January I've had a feeling that whilst the steps are logical, they could probably be better. Ram Srinivas outlined a famework on the Purefitbaw podcast  that led to me creating the first piece, but also thinking how it could be improved. I started researching further and found this piece  - it relates to NBA but why not adapt and see if this can be applied to football also? On first reading, I didn't have a clue what was going on so attempted to break down each element and see if this had a logical, football implication. This lead me to Will Gurpinar-Morgan's 2+2=11  blog and initially presented a process at Opta in  2015  and further presented this year. (You should follow his work and watch his presentations!) This could provide a blueprint within recruitment when sourcing players of a specific skillset to fulfil a specific role within the squad. In Oxford's example Chris Cadden was a cre...

Since the last blog I have listened to the @PureFitbaw  podcast which features Ram Srnivas who works in player recruitment. He outlined a basic methodology around recruitment, the use of data and traditional scouting methods. I will look to apply this here (on a very basic level!) Now Cadden has departed, Oxford are left with Sam Long. On the surface Long has different attributes to Cadden, however that doesn't diminish the impact Long could make (this will mainly look in League 1&2). Firstly establishing Oxford's playing style. ( Some boring stuff: I normalised the team data for the individual metrics on a scale 0-1 - the deep purple = in a higher percentile compared to the other teams. For example, looking at the first 'Crosses P90' column, it is clear Rochdale are the lowest rank in the League. In comparison, Portsmouth are the highest. In the PPDA (Passes Allowed Per Defensive Action) metric a lower rank = a high pressing team. Ipswich are the fore runn...

Welcome to BiscuitChaserFC. This could be great, or it could be another thing I start but don't quite follow through with. It could be stat-sy, could be Oxford related, could document my trip through football analytics...anyway toughest bit is to start, right!? Anyway, as its January and we all get excited about transfers I thought it might be interesting to take a look at the Oxford squad and answer a few questions: How does the squad currently look? What are the issues? Where can improvement be made in this transfer window and future? Average age based on Transfermarkt data Looking at the above it documents the average age of each squad in League One (A word of caution - Transfermarkt have Oxford's squad at 26 players including Kevin Berkoe, Sam Allardyce and Oussama Zamouri (who today left the club)). Oxford have on average the 7th youngest squad - a few players bring this average up, however Oxford sit amongst teams in Peterborough who have a strong recruitm...