Montpellier France Hard Atp 250 Round of 16

Martin Damm vs Roberto Bautista Agut: AI Prediction | Games, Spread, Aces & Double Faults

Martin Damm

Rank: #177
48%
VS

Roberto Bautista Agut

Rank: #91
52%
Expected Total Games: 22.6
Predicted Winner: Roberto Bautista Agut

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Player Metrics

Martin Damm

Form Index: 63.3
ELO Rating: 442.4
Glicko2 Rating: 1534.5
Current Fatigue (minutes): 374.0
Surface Strength:
Hard: 4.2
Clay: 2.9
Grass: 2.8
Serve Rating: 58.4
Return Rating: 14.8

Roberto Bautista Agut

Form Index: 27.1
ELO Rating: 616.1
Glicko2 Rating: 1604.3
Current Fatigue (minutes): 168.0
Surface Strength:
Hard: 6.3
Clay: 7.2
Grass: 8.0
Serve Rating: 97.6
Return Rating: 94.5

Recent Matches

Martin Damm

  • Last Match: vs Hubert Hurkacz (2-0) hard Montpellier 92 min
  • 2nd Last Match: vs Clement Tabur (2-1) hard Montpellier 173 min
  • 3rd Last Match: vs Matteo Martineau (2-0) hard Montpellier 109 min
  • 4th Last Match: vs Gilles Arnaud Bailly (2-0) hard Australian Open 174 min
  • 5th Last Match: vs Valentin Vacherot (0-3) hard Australian Open 174 min

Roberto Bautista Agut

Head-to-Head (Last 2 Seasons)

0
Martin Damm
vs
0
Roberto Bautista Agut
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

This round-of-16 match in Montpellier, France is on indoor hard courts at an ATP 250-level event. The model favors Roberto Bautista Agut to win, with a 51.59% probability versus Martin Damm at 48.41%, and it projects a relatively short match of about 22.63 total games.

Match Analysis

Martin Damm (rank 177) arrives with a higher proprietary form index (63.28) and an Elo of 442.39. His surface strength index (4.19) and mean return index (14.77) are modest, while his mean serve index (58.39) is reasonable for this level. Damm has logged 374 minutes on court in the tournament so far, indicating significant recent court time. He has won his three matches in Montpellier (against Hurkacz, Tabur and Martineau), including a long 173-minute match, showing match resilience over successive rounds. Roberto Bautista Agut (rank 91) carries a stronger Elo (616.13) but a lower form index (27.07). His surface strength index (6.33) is slightly higher than Damm’s. There is a large gap in serve ability: Bautista’s mean serve index is 97.62 versus Damm’s 58.39 (a difference >5 points), and an even larger gap in return index (94.54 vs 14.77). Bautista has played 168 minutes in the event and has mixed recent results—he won his most recent Montpellier match over O’Connell but lost earlier hard-court matches in the season’s lead-up—so his match sharpness is variable compared with Damm’s hot streak.

Total Games Predictions

🎾
Expected Total Games in Match 22.6 Most likely outcome: 22 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Martin Damm versus Roberto Bautista Agut. 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 Martin Damm versus Roberto Bautista Agut. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Martin Damm - Roberto Bautista Agut) +1.8 Most likely spread: +2 (Martin Damm wins 2 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Martin Damm versus Roberto Bautista Agut. Positive values indicate Martin Damm winning more games, negative values indicate Roberto Bautista Agut winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Martin Damm versus Roberto Bautista Agut. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

This aces prediction expects about 15.91 total aces in the match, reflecting a medium-paced hard court where aces are moderate compared with grass or clay. The predicted aces figure is boosted by Bautista’s substantially higher serve index, which should raise the overall ace count. For double faults prediction, the model forecasts expected double faults around 5.94; Bautista’s strong serve profile suggests fewer DF contribution relative to total aces.
🎯
Expected Total Aces 15.9 Most likely: 15 aces
Expected Total Double Faults 5.9 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Martin Damm versus Roberto Bautista Agut. 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 Martin Damm versus Roberto Bautista Agut. 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 Martin Damm versus Roberto Bautista Agut. Clay surface matches tend to produce more double faults due to fatigue in longer rallies.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Martin Damm versus Roberto Bautista Agut. The curve shows the cumulative probability for each double faults threshold.

Final Prediction

Bautista Agut’s higher Elo and markedly superior serve and return indices give him a narrow edge despite Damm’s recent wins and higher form index. The key factor to watch is Bautista’s serving efficiency—if he converts free points with aces and limits double faults, he should tip the balance.

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