A. Rublev vs A. Pellegrino — prediction
Slow court, high bounce: longer points, rewards whoever holds up from the baseline.
Warm: the ball flies a little more and fitness counts.
Humid air: the ball loses some speed.
Light wind: no noticeable effect.
Surface feeds the model (surface specialization is one of its factors). Weather and altitude are context we publish for you — they do NOT move the probability.
›Ranking: #13 vs #124 (better ranked)
›Recent form: 6/10 in recent matches
›More rested: 17d vs opponent's 2d
!Coming off 3 losses in a row
The ranking and Elo numbers tell a straightforward story: Rublev (#13, Elo 1966) sits far above Pellegrino (#124, Elo 1877), and the baseline model reflects that with a 58% to 50% split in service-point efficiency. This is the foundation of Rublev's favorite status — a substantial quality difference that should show up over the course of a best-of-three or best-of-five match, assuming no external disruption.
The picture is less one-sided once you look at return numbers. Rublev's serve (64%) is only marginally ahead of Pellegrino's (61%), but Pellegrino's return production (36%) is far stronger than Rublev's (23%). That means Pellegrino, despite the ranking gap, is statistically live to generate break chances — a detail that tightens the match more than the level gap alone suggests.
Recent form cuts against the favorite: Rublev has dropped his last three matches, even though his season includes notable wins (Davidovich Fokina, Buse). Pellegrino, by contrast, is 6-4 in his last ten with a modest one-match win streak, suggesting he's playing with some rhythm.
Rest works the other way. Rublev is fully recovered — 17 days since his last match and none in the past two weeks — while Pellegrino has played three matches in 14 days on just two days' rest. That workload could blunt his physical edge in longer exchanges, offsetting some of his return-game advantage.
The model rates Rublev at 76% versus a market-implied 72% (odds 1.38), producing a 5.5% expected-value edge. That's a modest gap, not a mispriced line — the model is essentially in line with the market's own assessment of a clear favorite.
This is a case where being the favorite doesn't guarantee value beyond what's already priced in. The rest advantage and class gap support Rublev, but his three-match losing streak and Pellegrino's superior return numbers are real counterweights. Treat the edge as a small one, not a lock.
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.