Football data analyst — Turin, IT
I'm a data analyst at Math&Sport, where we support DAZN Italy's and others stakeholders. On the side I write The Cutback, where I publish recruitment-style research — transfer corridor analysis, player profiling, and metrics built from event data — with every methodology open for inspection.
Where I'm headed
My day job is data analysis. My goal is a first role in recruitment analytics — and rather than wait for the job to learn the work, I've spent the last seasons publishing the work itself: scouting briefs, transfer-corridor models, role clustering, custom metrics, my own opinions on actual transfer and recommended ones with my data. Everything on this page is open, reproducible, and ready to be challenged.
Selected work — The Cutback
An atomic VAEP-based pipeline across six seasons of event data, measuring transfer success rates corridor by corridor — which origin leagues make adaptation easiest, and which don't.
A complete mock recruitment process: team similarity to shortlist target leagues, corridor risk, heatmaps and passing-skill profiling — from Stiller to Camavinga, Fernandes and Avdullahu.
A scouting brief built the way a club would commission it: define the profile, filter candidates across leagues, and land on a recommendation backed by metrics.
Technical work
Each notebook and metric below maps onto a stage of the recruitment workflow. Together they're the toolkit I'd bring to a club on day one.
Stage 1 — Define the role
Grouping players into data-defined roles — the position feature behind any profiling system.
Stage 2 — Pick the market
Rating stylistic closeness between clubs to identify the leagues where a target is most likely to translate.
Stage 3 — Evaluate players
A metric to rate defending from event data — methodology, validation, application.
Estimating composure under pressure without pressure-event data.
An acceleration estimate from event data, validated against Gradient Sport's physical tracking output.
Two competing proxies for a quality traditional stats miss — scouting dribblers without tracking data.
About
I read the game through data, but my first training was in people: an MA in Cultural Anthropology from the University of Turin still shapes how I interpret collective behaviour on the pitch — and how I write about it for the analysts, scouts and editors who read The Cutback.
At Math&Sport I work with aggregated and event data daily in a production environment, turning it into insight for multiple ends.
Fluent
Event data — six seasons of metric building, profiling and analysis on top of it
Working
Tracking data — worked with the limits of what's publicly available (in progress)
Stack
Python · pandas · scikit-learn · Streamlit · VAEP & xG modelling · data viz
Languages
Italian (native) · English (professional)