Karen Khachanov vs Ethan Quinn: AI Prediction | Games, Spread, Aces & Double Faults

The model's edge for Quinn comes mainly from the serve & return game, which swings 10.3 percentage points toward him. Quinn’s mean serve index (94.25) is comparable to Khachanov’s (95.85), so the advantage is not a raw-serving power gap; rather it reflects how Quinn’s serving profile and return matchup on grass interact in the model. Khachanov’s superior mean return index (91.70 vs Quinn’s 84.74) is a notable counterweight — the return gap of nearly 7 points favors Khachanov and helps explain the model also leaning on recent form and overall strength for him. Looking at credentials, Khachanov is the higher-ranked player (18) with a stronger Elo (1690.8) and higher surface strength index on grass (32.78 vs Quinn’s 10.72). His form index (39.83) is better than Quinn’s (28.35), and cumulative fatigue is zero for both entering the match. Recent results show Khachanov with two wins before a five-set loss at Roland Garros, indicating some competitive matches; Quinn arrives on a three-match losing streak, including straight-set defeats on clay. Those form signals move the needle toward Khachanov by about 6.1 points in the model, with overall strength adding another 5.6 points to his chance, while age (favoring the younger Quinn) contributes 4.5 points to Quinn’s side.