AI & machine learning · Python
Build an AI tennis scout that shows where every fact came from
Combine match context and player history into a cited scout card. Let AI select the evidence while code owns the numbers, timestamps and source links.
CrawlPlant guides
Good data.
Something worth building.
Practical projects with real data, readable Python and charts that show their sources. Start with our tennis data lab: nine ways to connect a season, a match and a single point.
9 hands-on tutorials4 tennis Actors15 original figures
Start here · AI + evidence
An AI tennis scout
that shows its sources.
Connect match context and player history. Build an evidence ledger, let AI select the useful facts, and keep every source attached.
Build the scoutTennis data lab
From season to single point.
Choose a project. Every guide includes code, a worked example and the limits of the evidence.
AI & machine learning · Python
Ask your tennis dataset a question: AI chooses the filters, Python does the counting
Build a bounded natural-language tennis analyst with a validated query plan, an honest sample-size chart and a handoff to player history.
AI & machine learning · Python
Turn a tennis final into an illustrated AI recap, with receipts for the pressure games
Combine a match lookup with game-level points, calculate the pressure events, and let an AI editor select a small set of verifiable recap facts.
AI & machine learning · Python
Your first tennis prediction model should have a baseline it can lose to
Turn a winner-first tennis dataset into an outcome-independent modelling table, hold out later tournament weeks and compare logistic regression with overall Elo.
Tennis data · Python
Your tennis CSV should not stop at last season: build an updating ATP/WTA dataset
Keep a familiar tennis CSV layout, update it without duplicate matches, then identify the matches worth studying point by point.
Tennis data · Python
One tennis rivalry, three different stories: build a surface-aware H2H card
Turn tennis match history into a rivalry card, keep player identity stable, and add pre-match context without confusing snapshots with history.
Tennis data · Python
A 6–2 set can hide five break points: draw a tennis pressure map in Python
Revisit the 2024 Wimbledon final game by game, distinguish break-point opportunities from pressure games, and connect a scoreline to its point history.
Tennis data · Python
When tennis Elo and the market disagree: build a research shortlist, not a magic pick
Compare pre-match Elo with margin-adjusted market probability, plot the largest disagreements, and investigate them through player history.
Tennis data · Python
From 233 tennis matches to one pressure game: connect four Actors into a research workflow
Join a tennis match dataset to point streams by stable IDs, measure coverage, and build a small evidence-backed match research report.