A. Potapova vs V. Williams — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Surface feeds the model — surface specialization is one of its factors.
›Ranking: #28 vs #471 (better ranked)
Potapova (#28) sits far above Williams (#471) in the rankings, a gap the model reflects directly: Potapova's baseline win rate is 61% compared with just 8% for Williams.
This baseline advantage, before any other adjustment, already signals a lopsided match on paper and forms the backbone of the model's 87% probability for Potapova.
Beyond the ranking gap, Potapova's own service and return numbers reinforce her edge: she wins 56% of service points and 36% of return points, both solid marks for a player at her level.
Her recent form, 7 wins in her last 10 matches, adds a short-term boost, though no equivalent numbers exist for Williams to allow a direct comparison.
The one caution here is Potapova's return from a 29-day layoff, flagged as a risk of possible rustiness. Layoffs of this length can affect timing and rhythm, especially early in a match.
The data gives no indication of how significant this effect might be for Potapova specifically, so it should be read as a mild caveat rather than a quantified drag on her chances.
The model's 87% probability for Potapova matches the market-implied probability from the 1.15 odds, also 87%. That leaves an expected value of just 0.4%, essentially negligible.
This is a case where the favorite is heavily backed by the data, but the market has already priced in her ranking, baseline, and form advantages — backing her at these odds offers no meaningful edge over the market's own assessment.
Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). The model ≈ the market on average; the odds already capture almost all the edge. 18+ · gamble responsibly.