P. Badosa vs M. Sherif — prediction
›Ranking: #141 vs #129
›Recent form: 3/10 in recent matches
›Head-to-head: 1-0 in favor
›Model 56% vs market 65% → the model sees it as less likely than the odds
Badosa carries a substantial across-the-board level advantage: her Elo rating of 1763 sits 170 points above Sherif's 1593, and her baseline win rate of 53% dwarfs Sherif's 13%. This is the largest single driver behind the model's lean toward Badosa.
Ranking tells a different story — Sherif (#129) actually sits ahead of Badosa (#141) — but the scale of the Elo and baseline gaps outweighs that modest ranking edge for Sherif.
The service numbers point to a tight exchange rather than a mismatch. Badosa's 60% serve-points-won projects against Sherif's 50% return, a 10-point hold margin.
Sherif's own serve (57%) against Badosa's 45% return produces a slightly larger 12-point margin, giving Sherif a marginal edge on the serve/return numbers taken alone.
Both players arrive on identical 9-match win streaks (LWWWWWWWWW), so current form does not separate them. The single prior meeting went to Badosa in 2023, but with only one data point the head-to-head carries limited predictive weight.
Rest is also equal: both played one day ago and have logged 9 matches in the last 14 days, meaning any fatigue from deep runs at Iasi cuts both ways rather than favoring either side.
The model prices Badosa at 56% to win, while the market (via 1.54 odds) implies 65% — a notable gap that produces a -14% expected value on backing the favorite at this price.
In practical terms, the market is more convinced of Badosa's dominance than the level, serve/return, and form data support here. Being favorite is not the same as having value: on this pricing, backing Badosa is a negative-EV proposition by the model's own read.
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.