Indian Wells CA, U.S.A. Hard Masters 1000 Round of 128

Reilly Opelka vs Ethan Quinn: AI Prediction | Games, Spread, Aces & Double Faults

Reilly Opelka

Rank: #69
61%
VS

Ethan Quinn

Rank: #72
39%
Expected Total Games: 25.3
Predicted Winner: Reilly Opelka

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Player Metrics

Reilly Opelka

Form Index: 44.3
ELO Rating: 872.5
Glicko2 Rating: 1537.3
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 7.5
Clay: 6.2
Grass: 8.1
Serve Rating: 95.8
Return Rating: 12.2

Ethan Quinn

Form Index: 38.8
ELO Rating: 822.5
Glicko2 Rating: 1536.2
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 7.8
Clay: 7.7
Grass: 6.1
Serve Rating: 96.4
Return Rating: 88.3

Recent Matches

Reilly Opelka

Ethan Quinn

  • Last Match: vs Rafael Jodar (0-2) hard Delray Beach 78 min
  • 2nd Last Match: vs Marin Cilic (0-2) hard Dallas 97 min
  • 3rd Last Match: vs Trevor Svajda (2-0) hard Dallas 106 min
  • 4th Last Match: vs Jakub Mensik (0-3) hard Australian Open 174 min
  • 5th Last Match: vs Hubert Hurkacz (3-0) hard Australian Open 174 min

Head-to-Head (Last 2 Seasons)

0
Reilly Opelka
vs
0
Ethan Quinn
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At Indian Wells (hard, Round of 128, Masters 1000), Reilly Opelka meets Ethan Quinn in a matchup between two big servers and contrasting return profiles. The model favors Reilly Opelka to win (60.55% vs 39.45% for Quinn) with an expected total of about 25.3 games in the match.

Match Analysis

Opelka enters ranked 69 with a form index of 44.26 and an Elo of 872.47; Quinn is close in the rankings at 72 with a form index of 38.81 and a lower Elo of 822.51. Neither player carries tournament fatigue into this encounter. Surface strength indices on hard court are virtually identical (Opelka 7.48, Quinn 7.78). Serve metrics are similar — Opelka’s mean serve index is 95.77 and Quinn’s 96.38, so there’s no meaningful serve-index gap to note. By contrast, the return profile is a clear divider: Quinn’s mean return index sits at 88.30 versus Opelka’s 12.15, a large difference that will be central to how rallies develop. Recent form tells a complementary story. Opelka has two wins and one tight five-set loss in his last three hard‑court outings, including a long Australian Open match (174 minutes) versus Alejandro Davidovich Fokina and a straight-sets victory earlier in the same event. Quinn’s last three matches show one win and two straight-set defeats; his victories and losses have also come on hard courts, with recent defeats to higher-ranked opponents and a 78– to 97–minute range in match durations. These patterns underline Opelka’s marginal edge in resilience and Elo, while Quinn’s return ability could create pressure in short windows.

Total Games Predictions

🎾
Expected Total Games in Match 25.3 Most likely outcome: 25 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Reilly Opelka versus Ethan Quinn. 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 Reilly Opelka versus Ethan Quinn. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Reilly Opelka - Ethan Quinn) +0.7 Most likely spread: 0 (even number of games won)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Reilly Opelka versus Ethan Quinn. Positive values indicate Reilly Opelka winning more games, negative values indicate Ethan Quinn winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Reilly Opelka versus Ethan Quinn. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this match is high: the model forecasts about 19.38 total aces and expected double faults around 5.72. On medium‑pace hard courts, that predicted aces total aligns with two big servers producing frequent free points but not the extreme ace counts seen on grass. Because serve ratings are nearly identical, neither player alone fully accounts for the high predicted aces; instead, both servers should contribute. The double faults prediction suggests moderate risk on second serves, typical for an aggressive serving matchup.
🎯
Expected Total Aces 19.4 Most likely: 19 aces
Expected Total Double Faults 5.7 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Reilly Opelka versus Ethan Quinn. 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 Reilly Opelka versus Ethan Quinn. 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 Reilly Opelka versus Ethan Quinn. 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 Reilly Opelka versus Ethan Quinn. The curve shows the cumulative probability for each double faults threshold.

Final Prediction

Opelka’s higher Elo and marginally better form give him the edge in the model, but the real hinge will be how Quinn’s elite return index converts opportunities against two very strong servers. Keep an eye on return games early — break opportunities there will likely decide the contest.

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