HOW IT WORKS

1 · Surface-aware ratings

Every player gets an Elo rating — a single number for overall strength, plus separate ratings for hard, clay and grass. Tennis is surface-dependent (a great clay player can be ordinary on grass), so we blend a player's surface rating with their overall to judge a specific match. Ratings update after every match, going back 25+ years.

2 · Serve & return

Match results alone miss how a player wins. So we also model the point itself: how often each player lands a first serve, wins behind it, wins behind the second, and how well they return. We adjust each player's serve for the specific returner they're facing.

3 · Putting it together

The ratings give one estimate of who wins; the serve/return model gives another. We blend them, then run the match tens of thousands of times point-by-point to produce the win probability, the likely set scores, and the projected total games. A final calibration step keeps the percentages honest (a 60% really means about 60%).

Win %

The model's estimated chance a player wins the match.

Value

How much more the model expects to win than the best available price pays. +10% value means the odds imply a worse chance than the model believes. It's an estimate of edge, not a guarantee.

Elo

A strength rating updated after every match. Higher is better; the gap between two players' Elos maps to a win probability. ~2000+ is elite.

Serve pts won

Share of points won on serve. The single best summary of serving strength.

1st / 2nd serve won

Win rate behind the first serve vs. the second — separates big-but-risky servers from steady ones.

BP saved / conv.

Break points saved (on serve) and converted (on return) — clutch serving and returning.

Total games

Projected number of games in the match; drives over/under markets.

Closing-line value (CLV)

Whether the price we flagged beat where the market closed. Beating the close is the strongest sign of a real edge — see the Tracker.

We tested the model on 150,000 past matches and against years of closing odds. The honest finding: on the main tours, the betting market's closing line is extremely sharp — our model is good, but it doesn't reliably beat the close head-to-head. Where edge plausibly lives is line-shopping (taking the best price across books) and softer markets.

So we don't claim to print money. Instead the Tracker logs every flagged pick at the price we first saw and grades it against the result and the closing line — a transparent, forward record. The numbers there are the real test, and they're public whether they're good or bad.

Loading the receipts…

We cover ATP & WTA singles — match winner and total games — across hard, clay and grass, for every tour-level event. Ratings are built from 25+ years of results; serve & return splits use a trailing two-year window.

Doubles and live in-play aren't here yet: reliable, current data for them needs a licensed live feed, which is on the roadmap. We'd rather leave a section out than ship stale numbers.