Skip to main content

Oxford United Squad Assessment 2020

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 recruitment focus and Coventry who have established a successful category 2 academy. 

So Oxford have a pretty young squad, but do they play?

I initially saw the below via Tom Worville and Ryo Nakagawra. These have been widely reproduced but I haven't seen too many in League One!

The below is useful:

1 - to document squad building, where potential issues possibly lie ahead of time
2 - to see where the share of minutes go. Who are the mainstays, who play a reduced role.

Squad share of minutes played in League One 2019/2020. Data: Wyscout

Oxford have a clear starting 9 players contributing over 70% of the available minutes in league One so far this season.

Eastwood
Cadden // Dickie // Mousinho // Ruffels
Brannagan // Gorrin
Fosu // Henry

This leaves the striker position rotated between Mackie and Taylor in addition to the third midfield spot filled by Baptiste (more recently) or previously, Woodburn. Prior to injury Eastwood would be up with Ruffels with 100%.

This pretty much tallies with what would be considered Oxford's strongest 11.

You can break the above into 3 areas:

1) Oxford have a core of the starting 11 (Brannagan, Cadden, Dickie, Gorrin, Ruffels, Fosu) who are either in their prime or will be within the next year contributing big minutes and playing regularly.

2) The 30+ gang. Eastwood, Mousinho, Henry, Mackie. Being 30 as a keeper isn't a huge issue, Mousinho has been reborn this season after looking to possibly move into coaching in the summer, Henry has signed a new contract and Mackie raked up plenty of minutes following an injury to Taylor. This is one to keep an eye on over the next couple of windows

3) The up and comers. Baptiste, Sykes, Moore (plus, to a lesser extent, Agyei and Hanson) show where our recruitment focus has been in previous windows. Yet to grab big minutes, you can see how this crop could be integrated into the starting 11. Currently they are having to capitalise on injuries or sub appearances, however you can make a good case for Baptiste being a constant in the side along with Moore and Sykes.

The problem:
Squad depth! Oxford have 21 players that have featured in the league with:

Currently Injured - Eastwood, Woodburn, Forde
Returning from injury - Hall, Hanson
Recalled - Cadden

Remove the above from our initial 21 and Oxford have a *fit squad of 17 going into the promotion run in. This represents obvious issues, mainly, can our core of players sustain such high minute contributions?

It's pretty clear what this squad needs.
1 - Right back - Long can step in but profiles very differently to Cadden. A permanent first choice RB should be the priority.

2 - Midfield - options are needed. Outside of Gorrin/Brannagan/Baptiste options are pretty light.

3 - Winger(s) - Robinson loves pacey wingers. We certainly need at least one to push Fosu. Fosu is playing more than he has previously in his career and whilst starting on fire has tapered over the weeks. We don't have the competition in attacking areas as we do in defence.

4 - Striker - everyone wants strikers but going into the last few month with Taylor and Mackie could be an issue.

Luckily, Robinson has highlighted all of the above...

Comments

Popular posts from this blog

Getting started in R with StatsBomb Data

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...

Shot Maps In R using StatsBomb Data

Im not sure if anyone is following these, but I will do one more and see what happens! I have covered some passing based stuff, I thought it might be useful to look into shots. Therefore, the rough plan for this piece: 1) Total player xG in the WSL for this season 2) Find the top 9 players based on xG 3) Plot all shots taken including xG 4) Add labels 5) Plot the shot map of the 9 players against one another As always, my coding is in the learning stage so this isn't a definitive way...just something that works for me and might help others! Anyway, load in this seasons WSL data as we have previously. We want to extract 3 things from the data - the number of shots, numbers of goals and total xG (initially including penalties) To start - tallying player shots: player_shots<-StatsBombData%>%   filter(type.name == "Shot")%>% ##filter all shots in StatsBombData   group_by(player.name)%>% ##group by player   tally(name = "total_shots"...

Using Wyscout in R

It's pretty clear that within a football setting, clubs are largely using the same data. Most clubs will be using Wyscout/Instat...others may have access to StatsBomb and Metrica. None the less, data quality discussion aside, Wyscout is used predominantly to quickly gain an overview of players (both from a video and data perspective). This dovetails with people up-skilling through the lockdown, taking various courses and becoming increasingly proficient in languages such as R and Python. This is a big asset within football! Those that have read previously know that I am self teaching R and sharing any learnings that may be of interest around football analytics to others. By no means am I an authority on this, I've just found something that works, that might help others...I'm always happy to be corrected! Anyway, the aim is to: - Download Wyscout data - Import into R - Clean the headers - Re-format the data from "wide" to "long" format - Some e...