Now that the FPL season has come to an end, people may want to take a break or review how their season went. One aspect of the game people may consider if they analyse their decisions is chip strategy. Due to the large number of double gameweeks and the extra Free Hit Chip, there were… Continue reading FPL Chip Analysis
On The Beach – Update
After posting my analysis of on the beach teams last week, some people on twitter (@theFPLkiwi and @CoalportGlen) pointed out that by only looking at teams with less than 55 points, I was introducing bias into the analysis by removing teams who may have been ‘on the beach’, won lots of games and ended up… Continue reading On The Beach – Update
On The Beach
As the Premier League season draws to a close, some teams will have too many points to get relegated but not enough to challenge for Europe. It’s arguable that as these teams have ‘little to play for’, their players won’t be as motivated as usual which will lead to worse results. These teams are deemed… Continue reading On The Beach
Secret xG Data
Most people use data from Fbref (Statsbomb) or Understat to assist their FPL decisions. However, an underlooked source of data is the FiveThirtyEight website. FiveThirtyEight use data to analyse sports, politics and science. With regards to football, they are well-known for their predictions on every tournament imaginable, from the Champions league to League two. It’s… Continue reading Secret xG Data
R Code to Scrape xG Data From Fbref
I have recently talked about the best data sources for xG and the best ways to use xG data. In this post I’m providing the R code I use which: Scrapes non-penalty xG data (npxG) and expected assist (xA) data for all the players in the Premier League Scrapes npxG for and against data for… Continue reading R Code to Scrape xG Data From Fbref
xG Data Sources for FPL
Below are advantages and disadvantages of xG data sources one can use for FPL. Why xG and expected assists (xA) are better stats than goals and assists has been widely discussed. For example, Michael Caley (@MC_of_A) has done a lot of work on the benefits of xG: https://cartilagefreecaptain.sbnation.com/2014/2/28/5452786/shot-matrix-tottenham-hotspur-stats-analysis-expected-goals This twitter thread is another explanation on… Continue reading xG Data Sources for FPL
Finding West Ham a Striker
Since Sebastian Haller’s departure to Ajax in the January transfer window, West Ham’s only senior striker has been Michail Antonio. Combined with the fact that Antonio has only played in around half of all games due to injuries, it’s no surprise that West Ham are keen to sign a striker. This article identifies players West… Continue reading Finding West Ham a Striker
AC Milan: A Data-Driven Analysis
This post is using data to create an ‘opposition’ report on AC Milan. The aim of this is to use data to deliver clear insights on how Milan play, in order to help teams prepare for games against Milan. In a real-life scenario, this should definitely be accompanied by video analysis to verify that the… Continue reading AC Milan: A Data-Driven Analysis
Off The Ball Runs
I used a sample of tracking data from Metrica sports and resources from Laurie Shaw (@EightyFivePoint) to build a model to identify and estimate the value added of off the ball runs (tracking data records a player’s position on the pitch at frequent intervals). Why is this useful? It’s main use would be to identify… Continue reading Off The Ball Runs
My Fantasy Football Model
With the Premier league season currently on hold, I thought now would be the ideal time to talk about the fantasy football model I made this season. Last season, I chose my players based on expected goals and fixtures, so a model that combined these to provide points predictions for each player seemed like the… Continue reading My Fantasy Football Model
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