football_analytics
worldcup
football_analytics | worldcup | |
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5 | 6 | |
1,715 | 168 | |
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7.2 | 6.5 | |
17 days ago | 10 months ago | |
Jupyter Notebook | HTML | |
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football_analytics
- Football Analytics Bible: A collection of projects, data, and analysis
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The Goalkeepers with the most Saves in the Top-5-Leagues since 1999/00
Just wondering, because I found this recently and thought about starting getting into football analytics
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[OptaJoe]2009 - Arsenal have won a Premier League game they were losing at half-time outside of London for the first time since December 2009 (2-1 at Liverpool). Temperament.
You can check statsbomb open data but you will to preprocess it from json to sql. They have great course and articles about analyzing the data. Another good reading is awasome-football . They provide list of resources to get data. But the most comprehensive and recommended resources eddwebster's guide. He worked for city football group and his repository updated frequently.
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Pra quem gosta de análise de dados no futebol
Segue o link do repositório: https://github.com/eddwebster/football_analytics
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Weekly Open Thread - General Discussion
I found a great collection for anyone who's interested in football analytics
worldcup
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Generate Data Warehouse
Hi guys, I have a school project for building a Data warehouse using an open-source dataset. I currently dive into one dataset which is The Fjelstul World Cup Database (Github: https://github.com/jfjelstul/worldcup). This dataset has multiple tables which combine a variety of properties. It's hard to figure out the whole following process to build a Dataware house from scratch. I just get some ideas and make out a sample of this. Can you guys help me examine that? What are the best ways to build Fact and Dimension tables from this generous dataset? What properties and table I should put in that case?
- Where to find database of World Cup penalty statistics? Including penalties awarded and the score line of when this happened
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[OC] Brazil and Argentina are the top goal-scorers in World Cup history.
Source: Fjelstul World Cup Database
- Ask about Day 5 of #25daysofDAXFridays
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Announcing the 25 days of DAX Fridays! second edition!
let Source = Web.BrowserContents("https://github.com/jfjelstul/worldcup/tree/master/data-csv"), #"Extracted Table From Html" = Html.Table( Source, {{"FileName", ".js-navigation-open.Link\-\-primary"}}, [RowSelector = ".Box-row + *"] ), fxCSVs = (FileName as text) as table => let Source = Csv.Document( Web.Contents( "https://raw.githubusercontent.com/jfjelstul/worldcup/master/data-csv/" & FileName ), [Delimiter = ",", Encoding = 65001, QuoteStyle = QuoteStyle.None] ), #"Promoted Headers" = Table.PromoteHeaders(Source, [PromoteAllScalars = true]) in #"Promoted Headers", #"Invoked Custom Function" = Table.AddColumn( #"Extracted Table From Html", "CSV_Data", each fxCSVs([FileName]) ) in #"Invoked Custom Function"
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Ask about Day 1 of #25daysofDAXFridays
= Csv.Document(Web.Contents("https://github.com/jfjelstul/worldcup/blob/master/data-csv/award_winners.csv"),[Delimiter=",", Encoding=65001, QuoteStyle=QuoteStyle.None])
What are some alternatives?
open-data - Free football data from StatsBomb
qcoder - Lightweight package to do qualitative coding
project - Predict how many points an European football team will end the season with, according to the characteristics of its players. Project for the Big Data Computing course at Sapienza University of Rome (2021-22)
sofifa-web-scraper - It has over 18k detailed players info and stats from EA FC 24 scrapped from SoFIFA.com.
understatr - fetch understat data
sports-analytics - Data collection, processing, visualization, modeling, and ideation in the space of sports analytics
soccerdata - ⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.
EA-FC-24-Automated-SBC-Solving - EA FC 24 Automated SBC Solving using Integer Programming ⚽
opendata - SkillCorner Open Data with 9 matches of broadcast tracking data.
socceraction - Convert soccer event stream data to SPADL and value player actions using VAEP or xT
football-crunching - Analysis and datasets about football (soccer)