Fantasy-Premier-League

A FPL library that gets all the basic stats for each player, gw-specific data for each player and season history of each player

How to CIte this dataset?

BibTeX:

@misc{anand2016fantasypremierleague,
  title = {{FPL Historical Dataset}},
  author = {Anand, Vaastav},
  year = {2022},
  howpublished = {Retrieved August 2022 from \url{https://github.com/vaastav/Fantasy-Premier-League/}}
}

Acknowledgement

• rin-hairie for adding master team lists and merge scripts
• ergest for adding merged_gw.csv files for 2016-17 and 2017-18 seasons
• BDooley11 for providing top managers script
• speeder1987 for providing 2018/19 fixtures.csv file
• ravgeetdhillon for github actions automation for data update
• kz4killua for fixing GW37 data for the 21-22 season
• SaintJuniper for id-dictionary update for the 21-22 season

FAQ

Data Structure

The data folder contains the data from past seasons as well as the current season. It is structured as follows:

• season/cleaned_players.csv : The overview stats for the season
• season/gws/gw_number.csv : GW-specific stats for the particular season
• season/gws/merged_gws.csv : GW-by-GW stats for each player in a single file
• season/players/player_name/gws.csv : GW-by-GW stats for that specific player
• season/players/player_name/history.csv : Prior seasons history stats for that specific player.

Player Position Data

In players_raw.csv, element_type is the field that corresponds to the position. 1 = GK 2 = DEF 3 = MID 4 = FWD

Errata

• GW35 expected points data is wrong (all values are 0).

Contributing

• If you feel like there is some data that is missing which you would like to see, then please feel free to create a PR or create an issue highlighting what is missing and what you would like to be added
• If you have access to old data (pre-2016) then please feel free to create Pull Requests adding the data to the repo or create an issue with links to old data and I will add them myself.

Using

If you use data from here for your website or blog posts, then I would humbly request that you please add a link back to this repo as the data source (and I would in turn add a link to your post/site as a notable usage of this repo).

Downloading Your Team Data

You can download the data for your team by executing the following steps:

python teams_scraper.py <team_id>
#Eg: python teams_scraper.py 4582

This will create a new folder called "team_<team_id>_data18-19" with individual files of all the important data

Notable Usages of this Repository

• Analysing Fantasy Premier League data in R Course by Arif P. Sulistiono

• Point Predictor via Random Forests by Francesco Barbara

• Money (Foot)Ball – how will our virtual football team selected entirely by Machine Learning compete in the big leagues?

• An introduction to SQL using FPL data by Liam Connors

• Hindsight Optimization for FPL by Sertalp B. Cay

• Data Science to get top 1% on return to FPL by James Asher

• FPLDASH: A customizable Fantasy Premier League Dashboard by Jin Hyun Cheong

• How to win at Fantasy Football with Splunk and Machine Learning by Rupert Truman

• 2019-20 Winner Joshua Bull's Oxford Maths Public Lecture

• 2019-20 Lottery Analysis by @theFPLKiwi

• Fantasy Nutmeg Website by code247

• Fantasy Premier League 19/20, a review by Hersh Dhillon

• Visualisasi Data: Fantasy Premier League 19/20 by Erwindra Rusli

• Machine Learning Model by pratz

• xA vs xG for Attacking Midfielders/Forwards by u/JLane1996

• Expected Goals vs Actual Goals for Manchester United by u/JLane1996

• Tableau Viz by u/richkelana

• Top Players against GW13 rival by u/LiuSiuMing

• Captaincy Choice GW4 2019-20 post by Matthew Barnfield

• Building a dataset for Fantasy Premier League analysis by djfinnoy

• Value in FPL 2019-20 Report by Who Got The Assist?

• Talisman Theory 2018-19 Report by Who Got The Assist?

• Historical Analyses in fplscrapR by Rasmus Chrisentsen

• Linearly Optimising Fantasy Premier League Teams by Joseph O'Connor

• How to Win at Fantasy Premier league using Deep learning by Paul Solomon

• graphql API by u/jeppews

• FPL modeling and prediction by @alsgregory

• FPL.co.id Talismans by @FPL_COID

• Leicester City Brendan Rodgers Impact Analysis on twitter by @neilswmurrayFPL

• Stat Analysis on twitter by @StatOnScout

• Arsenal-Chelsea LinkedIn article by Velko Kamenov

• Form vs Fixture Medium article by JinHyunCheong

• Visualization by u/dkattir

• Visualization by u/Dray11

• Visualization website by @antoniaelek

• FPL Captain Classifier by Raghunandh GS

• My Personal Blog

• FPL.cool