Premier League Data Collection Project
Budget: €6 – €12 EUR
I’m ready to hand you an exact, exhaustive list of metrics—everything from goals, xG and xGA to corners, cards, possession, injury reports and confirmed line-ups—then rely on you to track down each figure for the English Premier League across the last three seasons (2020/21, 2021/22, 2022/23).
Key sources like FBref and SoccerStats can be used to ensure top-notch accuracy. Your role is to source the numbers from these reliable outlets, verify them against multiple references where possible, remove inconsistencies or duplicates, and return a single, tidy dataset in either Excel or CSV. I’ll be using this file as the foundation for a larger betting-analytics model focusing on high-hit-rate value bets. Every cell must be accurate, and every column clearly labeled.
Deliverables:
• Clean, complete dataset covering every stat in my upcoming list, one row per match.
• Consistent column names, data types, and date formats.
• Brief data-quality note highlighting any gaps you were unable to verify.
If you’re meticulous about data hygiene, comfortable scraping or manually logging harder-to-find items such as injury status using the said sources, and happy to follow step-by-step instructions tied to overall project milestones, this first task should be straightforward and lead to more work as the model expands.
Key sources like FBref and SoccerStats can be used to ensure top-notch accuracy. Your role is to source the numbers from these reliable outlets, verify them against multiple references where possible, remove inconsistencies or duplicates, and return a single, tidy dataset in either Excel or CSV. I’ll be using this file as the foundation for a larger betting-analytics model focusing on high-hit-rate value bets. Every cell must be accurate, and every column clearly labeled.
Deliverables:
• Clean, complete dataset covering every stat in my upcoming list, one row per match.
• Consistent column names, data types, and date formats.
• Brief data-quality note highlighting any gaps you were unable to verify.
If you’re meticulous about data hygiene, comfortable scraping or manually logging harder-to-find items such as injury status using the said sources, and happy to follow step-by-step instructions tied to overall project milestones, this first task should be straightforward and lead to more work as the model expands.
Related categories:
Data Entry
Excel
Web Scraping
Data Mining
Data Scraping
Data Analysis
Data Collection
Data Management