N. Osaka vs E. Cocciaretto — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Strong heat: warm air speeds the ball up and physical wear tells in long matches.
Dry air: the ball travels normally.
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: #14 vs #46 (better ranked)
›Head-to-head: 1-0 in favor
›Model 74% vs market 86% → the model sees it as less likely than the odds
›Recent form: 8/10 in recent matches
›More rested: 24d vs opponent's 2d
!Returning from a long layoff (24d) — possible rustiness
The numbers point firmly toward Osaka on pure level: an Elo gap of 1882 to 1674, a ranking spread of #14 to #46, and a baseline win rate of 72% against Cocciaretto's 46%. These are not marginal differences — they reflect a substantial gap in overall match quality that should show up across most facets of play, not just one or two stats.
This gap is reinforced by the serve and return numbers below, which suggest the class difference isn't just theoretical ranking noise but grounded in tangible in-match performance splits.
Osaka holds a real edge on both serving (68% vs 58%) and returning (46% vs 41%), meaning she should be competitive on both her own and Cocciaretto's service games — a double advantage that is hard for the opponent to overcome structurally.
The hot, dry conditions (31°C, 43% humidity, light 6 km/h wind) tend to speed up the court and ball, which generally benefits the stronger server. Given Osaka's clear serve advantage, this weather profile should reinforce rather than offset her existing edge.
Osaka's 8-2 record over her last 10 matches, including two wins over Sabalenka (Elo 2044), shows she can beat top-tier opposition. But she is currently on a 2-match losing streak, which tempers the form narrative somewhat. Cocciaretto, by contrast, is just 4-6 over her last 10 but arrives on a 2-match winning streak.
Rest cuts both ways: Osaka's 24 days off could mean rust after a long layoff, while Cocciaretto's heavier recent workload (2 matches in the last 14 days, only 2 days since her last one) could mean tired legs by the later sets. Neither risk is quantified beyond these raw numbers, so this factor is best treated as a wash rather than a clear tilt.
The model rates Osaka's win probability at 74%, notably below the market's implied 86% (odds of 1.16). That gap translates to an expected value of -14.4% at these odds — a clear sign that, even though Osaka is the deserved favorite on level, form, and conditions, the market is pricing her even more heavily than the model's own estimate.
Being the stronger player is not the same as being a value bet. Here, backing Osaka at 1.16 means paying a premium beyond what the model itself projects, so this is a case where the favorite is likely to win more often than not, but the price offers no edge — if anything, a modest negative one.
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.