D. Merida Aguilar vs T. Droguet — prediction
Slow court, high bounce: longer points, rewards whoever holds up from the baseline.
Strong heat: warm air speeds the ball up and physical wear tells in long matches.
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: #84 vs #116 (better ranked)
›Model 53% vs market 61% → the model sees it as less likely than the odds
›Recent form: 5/10 in recent matches
›On a streak: 2 wins in a row
Merida Aguilar holds the better ATP ranking (#84 vs #116) and a positive ranking trend (+2 vs -3), which is why he is nominally the favorite. But Droguet's Elo rating (1937) sits above Merida Aguilar's (1905), and the baseline model gives Droguet a 58% underlying win rate against Merida Aguilar's 46% — a 12-point gap that reflects deeper, longer-window performance data than the ranking snapshot alone.
This tension between ranking and Elo/baseline is the core of the match: the ranking says one thing, the more granular models say another, and the calibrated 53%-47% split for Merida Aguilar reflects that conflict rather than a clean edge.
Recent form clearly favors Droguet. He has won 8 of his last 10 matches, including wins over A. Blockx (Elo 1998) and G. Heide (Elo 1907) — both notably higher-rated than Merida Aguilar's own best recent win, P. Llamas Ruiz (Elo 1903). Merida Aguilar, by contrast, is just 5-5 over the same span, with a run of four straight losses noted as an explicit risk factor.
Both players are on a 2-match winning streak right now, so the short-term momentum is currently aligned, but the broader 10-match sample tilts meaningfully toward Droguet in both quantity and quality of wins.
The rest picture is the clearest factor working in Merida Aguilar's favor. Droguet has played 7 matches in the last 14 days compared to just 2 for Merida Aguilar, even though both are coming off a single day of rest. That workload gap can translate into accumulated physical fatigue over a best-of-three or best-of-five format, partially offsetting Droguet's edge in Elo and form.
Conditions are hot and humid (30°C, 65% humidity, 13 km/h wind), which tends to lengthen rallies and reward return skill and physical endurance. However, the serve and return numbers for both players are almost identical — 63% vs 64% on serve, 37% vs 38% on return — so these conditions do not create a decisive mechanical advantage for either side; Droguet's marginal statistical edge is too small to lean on heavily.
The model rates Merida Aguilar at 53% to win, while the market price of 1.64 implies a much higher 61% probability. That gap produces a -12.5% expected value on backing the favorite, meaning the market is pricing Merida Aguilar as safer than the model's factor-based read supports.
This is a case where being the favorite does not equal having betting value: the model, calibrated to roughly 65% out-of-sample accuracy, sees a closer contest than the odds suggest, driven mainly by Droguet's better Elo, better recent form, and a virtually even serve/return profile. There is no value signal here to act on.
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.