Player Replacement Finder
Analytical project using machine learning frameworks to find statistically similar players to replace an outgoing player.
Open project →

Shubh Harde
Football Data Analyst
I'm a sports technology student, in love of football and statistics, building xG models, scouting reports and team analyses one match at a time from open football data.
What is xG?
ExplainerEvery shot gets a probability of scoring based on where and how it's taken. Closer and more central means a bigger bubble.
Add every shot up and you get a team's total — chances created, not just shots taken. Values shown are illustrative.
Analytical project using machine learning frameworks to find statistically similar players to replace an outgoing player.
Open project →

How Jan Paul van Hecke is becoming the most important part of the Dutch team Xavi is playing to counter opponents.
Read on Instagram →

Why AC Milan signed Strahinja Pavlović after Euro 2024.
Read on Substack →
I'm Shubh, a student who got hooked on football data by asking simple questions: who actually creates chances, and how would we know? Now I study the game and analyse its numbers. Every project on this page started as one of those questions.
I build everything on open, public data, event feeds, match results, shot maps, and write up what the numbers say and, just as often, what they can't. I'm not here to pretend I have years of club experience; I'm here to show how I think, and to get better fast.
Every number I publish is explainable, reproducible and honest about what it can't tell you. That's how I learn and how I'd want to work with a team.
Capture
Open event & match data, cleaned and time-aligned.
Analyse
xG, xT and data pipelines — built to understand, not to impress.
Share
Write-ups and dashboards anyone can read in a minute.
I'm a student looking for thesis, internships, part time work, or just a good conversation about football data. Tell me what you're working on.