analytics

Reflections from my first FPL season

If you ask any Fantasy Premier League (FPL) player on Twitter about what word has been beaten to death last season, they’d likely respond with “optimal”. I must admit that I played a part in starting or fuelling more than my fair share of these discussions… There are optimal ways to play FPL. — Sertalp B. Çay (@sertalpbilal) March 29, 2021 It might come as a suprise to some that I had never heard of FPL before August of 2020, just a week before I went on vacation.

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Rocket League as a Sports Analytics Sandbox

Taking a serious interest in sports analytics was probably the best thing I did during the pandemic. Not only is it fun to play with and analyze, but it’s also easy to make connections with ongoing events while also providing you with a broader understanding of the sports. There are, however, a few roadblocks. Reaching to the data, especially on-pitch data, is very difficult. You can find summarized stats but more granular specifics such as tracking data is treated as a premium commodity and understandably so.

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Hindsight Optimization for FPL

This season certainly proved how random FPL could get, full of difficult decisions and regret. Every GW, we’d look at our team and wish that we’d that shiny player everyone else had. Sometimes Bruno, sometimes Gundogan, and sometimes Martinez. Week after week we were filled with regret after not buying (or worse: benching) that player. Of course with hindsight being 20/20, it’s easy to see what you missed. But what if you could get the ‘Almanac’ just like in Back to the Future 2 and know how every week would play out?

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Using Optimization Modeling for Expected Threat

If you know little about football analytics, I can safely assume that you have heard of expected goals (xG). For those who don’t know, xG is a metric showing the probability of a shot to be successful with the information we have, such as position, body part, and defender positions.1 Another of such metrics is expected assists (xA) which can measure the probability that a pass leads to a goal.

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O-Ring Optimization for FPL

“The Numbers Game”1 is a great read for anyone interested in football (soccer) analytics. The book covers a wide range of events where numbers give insights to football professionals on topics like possession, short/long passes, and team evaluation. I have recently read the section about the “O-Ring theory”, which brought a couple of new ideas regarding FPL. O-Ring theory says that a team (or a system) is as strong as its weakest link.

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On the meaning of optimal in FPL

The amount of available content for Fantasy Premier League (FPL) is unbelivable and hard to follow. Among all, one of my favorite resources is the “Corridor of Uncertainty” podcast as they focus on modeling and analytics part of FPL. Their guest in the latest episode was Abdul Rehman (FPL Salah), who is a well-known manager in the FPL community. I truly enjoyed their discussion and noticed that the word “optimal” is thrown around quite a bit.

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On FPL, Optimization, and Ownership Weights

Robert Cialdini mentions scarcity as one of the 6 principles of persuasion. The nature of seeking something of great interest is embedded inside all of us. Our first reaction when we see other people do something is to follow them. Even though it does not make too much sense, we follow the herd even in a competitive game, like Fantasy Premier League. Last week’s (GW11) unfortunate gold rush to Jota proved that we fear being left out.

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Notes from FPL Gameweek 2 and Optimization

I am playing Fantasy Premier League this seasons for the first time and I can already tell you that it is frustrating, despite using a mathematical model. Even though I put no manual input of my own (all decisions are up to the mathematical model), I am watching almost all EPL games to improve the model and I can say that it is very addictive. Growing up, I never liked watching live sports that much.

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