tara-nguyen/english-premier-league-random-forest-analysis
Random forest analysis of match statistics and team performances in five seasons of the English Premier League (EPL)
This project helps soccer analysts and enthusiasts understand the factors that truly determine match outcomes in the English Premier League. By analyzing five seasons of match statistics, it identifies key performance indicators, like goals scored by each team and the first scorer, that are highly predictive of a game's result. This is for anyone looking to gain deeper insights into EPL team performance and game dynamics.
No commits in the last 6 months.
Use this if you are a soccer analyst, sports journalist, or passionate fan wanting to understand which match statistics are most crucial for predicting Premier League game results.
Not ideal if you're looking for real-time betting predictions or an analysis of current season performance, as the data covers seasons up to 2019/2020.
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/perception/tara-nguyen/english-premier-league-random-forest-analysis"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
scrapy/scrapy
Scrapy, a fast high-level web crawling & scraping framework for Python.
Altimis/Scweet
A simple and unlimited twitter scraper : scrape tweets, likes, retweets, following, followers,...
lexiforest/curl_cffi
Python binding for curl-impersonate fork via cffi. A http client that can impersonate browser...
plabayo/rama
modular service framework to move and transform network packets
scrapinghub/spidermon
Scrapy Extension for monitoring spiders execution.