D. Merida Aguilar vs K. Jacquet — prediction
›Ranking: #82 vs #130 (better ranked)
›Recent form: 6/10 in recent matches
›On a streak: 5 wins in a row
›Match-sharp: 5 matches in the last 2 weeks
›Model 65% vs market 70% → the model sees it as less likely than the odds
Merida's Elo (1938) sits 58 points above Jacquet's (1880), and his #82 ranking versus #130 reinforces that gap, all consistent with his 63% baseline performance level. This is the model's strongest and most reliable signal in the match.
Momentum adds to the picture: Merida has won five straight, including victories over players rated 1935 and 1903 Elo, both above his own current level. Jacquet, by contrast, has dropped two of his last three and enters on a one-match losing streak, a shift in trajectory that supports the favorite's edge.
On paper, the serve numbers are close: Jacquet holds a marginal edge at 66% of serve points won compared to Merida's 65%. That one-point gap is not decisive on its own.
The separator is the return column, where Merida's 40% versus Jacquet's 38% suggests he converts more return points into pressure. In a match between two similarly strong servers, that two-point return advantage is where Merida's edge is most likely to show up on the scoreboard.
Merida has been busier, playing 5 matches in the last 14 days against Jacquet's 3, and both players reached a tour final within the last two to three days (Umag for Merida, Estoril for Jacquet). This shared fatigue context cuts both ways and should not be read as decisively favoring either side.
Days since last match are close (3 vs 2), so neither player has a clear rest advantage; the congestion is roughly symmetric, making this a secondary factor rather than a deciding one.
The model gives Merida a 65% win probability, but the market is pricing him at an implied 72% (odds of 1.39). That gap produces a -10.1% expected value on the favorite, meaning the price already exceeds what the data-driven edge supports.
Being the stronger player by ranking, Elo, form and return numbers does not automatically make his price good value. Here, the market has moved further than the model's own estimate, so backing Merida at 1.39 is a negative-EV proposition based on this method — the case for the favorite as a player is real, but the price does not currently offer value.
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.