Cincinnati OH, U.S.A. Hard Masters 1000 Quarterfinals

Tommy Paul vs Flavio Cobolli: AI Prediction | Games, Spread, Aces & Double Faults

Tommy Paul

Rank: #24
53%
VS

Flavio Cobolli

Rank: #10
47%
Expected Total Games: 23.6
Predicted Winner: Tommy Paul

Why the Model Favors Tommy Paul

The factors that drove this prediction, measured in win-probability points.

Recent record by level +4.6 Tommy Paul
Surface fit +3.1 Tommy Paul
Age +2.2 Flavio Cobolli
Overall strength +2.1 Flavio Cobolli
Serve & return game +0.9 Tommy Paul

Starting from an even matchup, these factors move the model to 53% for Tommy Paul. Computed with gradient-based attribution on our neural network, not editorial opinion. How to read this →

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Player Metrics

Tommy Paul

Form Index: 62.8
ELO Rating: 1854.3
Glicko2 Rating: 1880.7
Current Fatigue (minutes): 465.0
Surface Strength:
Hard: 39.9
Clay: 37.5
Grass: 22.0
Serve Rating: 96.8
Return Rating: 91.5

Flavio Cobolli

Form Index: 67.6
ELO Rating: 1902.8
Glicko2 Rating: 1857.0
Current Fatigue (minutes): 420.0
Surface Strength:
Hard: 30.1
Clay: 37.7
Grass: 33.1
Serve Rating: 94.8
Return Rating: 86.6

Recent Matches

Tommy Paul

Flavio Cobolli

Head-to-Head (Last 2 Seasons)

0
Tommy Paul
vs
0
Flavio Cobolli
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

Cincinnati quarterfinals on hard courts at a Masters 1000 event sets up Tommy Paul against Flavio Cobolli. The model projects Tommy Paul to win with a 53.17% probability, while Flavio Cobolli is at 46.83%. The match is expected to be relatively short by set count, with a predicted total of 23.56 games.

Match Analysis

The model’s edge for Tommy Paul comes mainly from recent results at this level and a better fit to the surface. Paul’s recent string includes three consecutive hard court wins at Cincinnati, including victories over Alexander Zverev and Hubert Hurkacz, and his recent match lengths reflect heavy, competitive matches that the model rewarded. Paul’s surface strength index is 39.93, higher than Cobolli’s 30.13, which helps explain the surface fit advantage. The model also assigned a small serve and return tilt to Paul, supported by his mean serve index of 96.76 and mean return index of 91.48 versus Cobolli’s 94.77 and 86.60. Cobolli’s edge comes from overall strength and age adjustments in the model. He enters this match ranked 10 with an Elo of 1902.75 and a form index of 67.58, slightly better than Paul’s rank of 24, Elo 1854.32, and form index 62.80. Cobolli has also won three straight matches at Cincinnati, including a win over Miomir Kecmanovic, with cumulative minutes slightly lower than Paul’s, reflecting less tournament fatigue (Cobolli 420 minutes, Paul 465 minutes). Those factors pushed a few percentage points toward Cobolli despite Paul’s surface and recent-level advantages.

Total Games Predictions

🎾
Expected Total Games in Match 23.6 Most likely outcome: 23 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Tommy Paul versus Flavio Cobolli. The X-axis shows possible total games values and the Y-axis shows the predicted probability percentage for each outcome.
Cumulative Probability (CDF)

Probability of total games ≤ X

Cumulative distribution function chart for total games in Tommy Paul versus Flavio Cobolli. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Tommy Paul - Flavio Cobolli) -0.1 Most likely spread: -1 (Flavio Cobolli wins 1 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Tommy Paul versus Flavio Cobolli. Positive values indicate Tommy Paul winning more games, negative values indicate Flavio Cobolli winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Tommy Paul versus Flavio Cobolli. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this hard court match is modest. The model’s predicted aces total is 12.07, and the expected double faults total is 4.43. Hard courts tend to produce a moderate number of aces compared with grass and clay. There is no significant gap in serve ratings large enough to expect a dramatic skew in the predicted aces between the two players.
🎯
Expected Total Aces 12.1 Most likely: 12 aces
Expected Total Double Faults 4.4 Most likely: 4 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Tommy Paul versus Flavio Cobolli. Higher ace counts are more likely on faster surfaces like grass.
Cumulative Probability (CDF)

Probability of aces ≤ X

Cumulative distribution function chart for total aces in Tommy Paul versus Flavio Cobolli. The curve shows the cumulative probability for each aces threshold.

Double Faults Probability Distribution

Distribution

Probability of each double fault count outcome

Probability distribution chart for double faults in Tommy Paul versus Flavio Cobolli. The chart shows the predicted probability for each double-fault count.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Tommy Paul versus Flavio Cobolli. The curve shows the cumulative probability for each double faults threshold.

🎯 Match Format Predictions

Tiebreak Likelihood

Probability that any tiebreak is played in this match

35.0% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Tommy Paul's perspective)

2-0 Most likely set score (32.4%)
Probability distribution of the final set score from Tommy Paul's perspective. Format: BO3.

Final Prediction

Paul’s slight predicted edge is driven chiefly by recent record by level and better surface fit. Watch return intensity and early break points, as these elements could decide a tight match that the numbers expect to be short on games.

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