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
Tag: data science
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
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
Predicting Titanic Survivors
Kaggle is a website which hosts machine learning competitions. I recently completed the Titanic competition on Kaggle. The task was to predict who died and who survived on the Titanic, given data on approximately 900 passengers. I did this by using a random forest model to classify the passengers. I managed to correctly classify 74%… Continue reading Predicting Titanic Survivors
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