The pursuit of wisdom in any walk of life quickly reveals that what you think you know is not nearly enough to get you to where you want to go. As I'm starting out in my football scouting journey I challenged myself to reach out to those already working in various roles in football to answer a short list of questions. My goal wasn't to get answers but relevant perspectives on the game within the game.
Here is Riley Wichmann of the:
Here is Riley Wichmann of the:
Back in 2017, I was extremely interested in getting involved in football analytics and my first opportunity came thanks to Dave Willoughby and Stratabet. Stratabet would send free data to bloggers and data analysts to work with, so I began to create various graphics and visualizations using their data and posting them on my twitter account.
My first experience at a professional club came last season as I served as an intern data analyst for the Richmond Kickers where I was able to gain a lot of valuable experience working with the coaches and first team. This eventually turned into a full-time role as their Head Data Analyst.
What attracted you to analytics? What’s more intriguing now names or numbers?
I've been obsessed with statistics since I was a little kid, so much so that I would recreate the UEFA Champions League in my back yard in which I played out the matches myself and kept track of hypothetical scores and stats for the players I pretended to play as. I also loved keeping track of stats for other sports such as baseball, basketball, and football. Metrics like WAR fascinated me, as I loved the idea of being able to quantify player impact with a single number. As I grew up, I began to question some of the methods that were used to draw conclusions about team and player performance, and this eventually led to me get involved with the field myself.
Who/what is the first player/concept you "found"? What caught your eye?
Back in December of 2017 created a list of players that I deemed 'hidden gems' based on my expected goals model. This list included the likes of Tanguy NDombele, Milot Rashica, and Neal Maupay and represented my first attempt at personally scouting football talent using data. Although I didn't achieve anything with the creation of this list itself (many of these players already played for big European clubs at the time), it furthered my belief in the importance of utilizing data to make decisions in football. Nowadays, I use Ball Advancement Rating to measure player impact, a metric I've created based on quantifying the value of every single on-ball action in a match.
Who/what is the player/concept you "missed" on? What did you learn from it?
Due to my relative inexperience in the field, I can't think of a notable player that I was blatantly wrong about up to this point. However, I'm sure I'll have my fair share over the years to come. It's impossible to quantify all the variables that contribute to a player's progression, so player development is naturally nonlinear. One thing I quickly picked up on after being around a club atmosphere is the importance of psychology on a player's development. Sometimes, a player will look outstanding statistically, but unquantifiable factors like mental state may hinder his/her development.
If you could start over what skill would you build on first?
From my experience, being able to effectively communicate the significance of data or a graphic is extremely important when it comes to presenting information to a team. Early on, this was one of my many weaknesses, yet I often was thrown in the deep end when having to present information to players and naturally got better at this the more I did it. Another scenario in which this applies to me is doing podcasts for Clear Data Sports. I often have to pick out significant numbers from a match to point out, and I am only given a limited amount of time to explain why these numbers may be significant in determining the result of a given match. In general, being able to communicate clearly and concisely is an essential skill to have in the field of data analysis.
Do you see player development as more of an art or a science? Is development on the club or the player? Why?
I think there's certainly a lot of science behind the development of players, and it's no coincidence that the usage of data analysis on player fitness has become more and more prevalent over the years. However, as much as player development can be reduced to a science, I believe it's important to regard each player as an individual. If all players were treated the same and ran through the same process, many would burn out before being able to reach their peak.
Some players are simply more mature than others and can be introduced to the first team earlier, while others may need additional development and peak later in their careers. Both player and club hold crucial roles in a given player's development, and sometimes players miss out on opportunities due to being in the wrong situation. In Jadon Sancho's case, his decision to leave Manchester City at the time he did was risky but led to him emerging as one of the world's brightest youngsters.
What is your favorite sports moment? Why?
The 2008 Champions League Final. I was only 7 at the time, and my dad picked me up early from school so we could watch it together. My dad's a huge Chelsea fan, so naturally, I had picked Manchester United to rival him. The 2008 season was the first season I heavily followed EPL and the United side had some of my favorite players to watch from my childhood including Edwin van der Sar, Paul Scholes, Wayne Rooney, and Cristiano Ronaldo.
Ultimately, the result made it even sweeter as John Terry's infamous slip kept United in the penalty shootout and eventually led to their win. I would attribute this match to sealing my love for the sport, as well as sticking with me as one of my earliest childhood memories of football.
What coach/player/team inspires you? Why?
My biggest influence as a data analyst is 11tegen11 on twitter. Prior to the creation of Lucid Analytics, I came across his twitter account and quickly became obsessed with expected goals and his pass map graphic. The pass map graphic itself was actually incredibly influential in pushing me to start learning how to code, as I wanted to learn how to create it myself. Fast forward 3 years later, and I often utilize this graphic at the Richmond Kickers in order to make tactical decisions based on the pass maps generated by us and our opponent.
What advice would you give to someone wanting to get into analytics?
Experience is the best teacher. Up to this point, I'm fully self-taught when it comes to coding and analyzing data. You can take classes all you want, but practicing code on your own is a great way to become a sufficient coder. Through the use of Google, I was able to slowly teach myself R and Excel and over time have been able to turn this into multiple jobs. Luckily, there is tons of free data out there that you can work with. If you're willing to put in the time and practice, anything is possible. Also, starting a blog is a great way to put your work out there for all to see.
What is your favorite app/tool to use (for fun!)?
Although there is more efficient software out there, I absolutely love working in excel!
What other sport/hobby/discipline do you feel improves your work as an analyst? Why?
One of my main hobbies outside of data analysis and coaching is listening to music and collecting records. Music is a huge part of my life and it provides me with a creative outlet that contrasts some of the meticulous tasks I do day-to-day. I could spend long hours working with music on in the background, and it serves as a therapeutic experience for me especially when tasked with stressful or rigorous work. Some of my favorite artists to listen to while I work include Death Grips, Radiohead, and Beach House.
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