Wimbledon Great Britain Grass Grand Slam Round of 16

Roman Safiullin vs Novak Djokovic: AI Prediction | Games, Spread, Aces & Double Faults

Roman Safiullin

Rank: #132
24%
VS

Novak Djokovic

Rank: #7
76%
Expected Total Games: 39.4
Predicted Winner: Novak Djokovic

Why the Model Favors Novak Djokovic

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

Surface fit +9.2 Novak Djokovic
Overall strength +7.1 Novak Djokovic
Fatigue & recent workload +4.8 Novak Djokovic
Overall record & opposition quality +2.7 Novak Djokovic
Recent form +2.7 Roman Safiullin

Starting from an even matchup, these factors move the model to 76% for Novak Djokovic. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Roman Safiullin

Form Index: 96.2
ELO Rating: 1825.0
Glicko2 Rating: 1818.6
Current Fatigue (minutes): 1044.0
Surface Strength:
Hard: 16.1
Clay: 17.2
Grass: 24.6
Serve Rating: 96.1
Return Rating: 92.5

Novak Djokovic

Form Index: 55.5
ELO Rating: 2036.1
Glicko2 Rating: 1995.5
Current Fatigue (minutes): 522.0
Surface Strength:
Hard: 57.1
Clay: 41.0
Grass: 52.3
Serve Rating: 96.6
Return Rating: 89.0

Recent Matches

Roman Safiullin

  • Last Match: vs Joao Fonseca (3-0) grass Wimbledon 174 min
  • 2nd Last Match: vs Botic van de Zandschulp (1-3) grass Wimbledon 174 min
  • 3rd Last Match: vs Andrey Rublev (3-2) grass Wimbledon 174 min
  • 4th Last Match: vs Jerome Kym (3-2) grass Wimbledon 174 min
  • 5th Last Match: vs Kimmer Coppejans (2-0) grass Wimbledon 174 min

Novak Djokovic

Head-to-Head (Last 2 Seasons)

0
Roman Safiullin
vs
0
Novak Djokovic
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At Wimbledon in London, the round-of-16 clash on grass pits Roman Safiullin against Novak Djokovic in a Grand Slam night-session spotlight. The model favors Djokovic as the likely winner — Djokovic 76.24%, Safiullin 23.76% — with a projected total of about 39.4 games in the match.

Match Analysis

The model’s edge for Djokovic comes mainly from surface fit and overall strength. On paper Djokovic’s grass credentials show through: his Elo sits at 2036 versus Safiullin’s 1825, and his surface strength index (52.34) is markedly higher than Safiullin’s (24.61), which is the single largest driver in the prediction. That advantage is compounded by Djokovic’s higher standing in the rankings (No. 7 versus No. 132) and the model also rewards his overall season strength. Fatigue and recent workload further tilt the scales toward Djokovic — he has logged 522 minutes at the tournament compared with Safiullin’s 1,044 minutes, so Djokovic should be the fresher player going into this tie. Safiullin’s case rests largely on recent form: his form index (96.18) outstrips Djokovic’s (55.49), which is why the model still gives him a roughly one-in-four upset chance. Serve profiles are almost identical in the underlying indices (mean serve ~96 for both), so expect service potency from both men rather than a clear serving mismatch; return indices are close enough that no major gap is flagged. Over their last three matches at Wimbledon both players have advanced comfortably — Djokovic with straight and four-set wins (including Tsitsipas), Safiullin with a notable five-set win earlier and a straight-sets victory in his most recent match — suggesting momentum but also workload differences.

Total Games Predictions

🎾
Expected Total Games in Match 39.4 Most likely outcome: 39 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Roman Safiullin versus Novak Djokovic. 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 Roman Safiullin versus Novak Djokovic. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Roman Safiullin - Novak Djokovic) -3.5 Most likely spread: -4 (Novak Djokovic wins 4 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Roman Safiullin versus Novak Djokovic. Positive values indicate Roman Safiullin winning more games, negative values indicate Novak Djokovic winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Roman Safiullin versus Novak Djokovic. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this grass match is high: the predicted aces total is 23.55, and the double faults prediction sits at an expected double faults total of 7.49. Grass typically inflates ace counts, and with both players registering very similar high serve indices, the predicted aces are likely to be shared between them rather than dominated by one server.
🎯
Expected Total Aces 23.6 Most likely: 23 aces
Expected Total Double Faults 7.5 Most likely: 7 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Roman Safiullin versus Novak Djokovic. 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 Roman Safiullin versus Novak Djokovic. 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 Roman Safiullin versus Novak Djokovic. 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 Roman Safiullin versus Novak Djokovic. 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

60.4% Predicted: Tiebreak likely

Exact Score Distribution BO5

Probability of each set-by-set outcome (Roman Safiullin's perspective)

0-3 Most likely set score (43.6%)
Probability distribution of the final set score from Roman Safiullin's perspective. Format: BO5.

Final Prediction

Djokovic’s edge is primarily driven by surface fit, reinforced by superior overall strength and a lighter workload. The key factor to watch is fatigue: Safiullin’s impressive form has carried him deep, but maintaining that level against Djokovic on grass with a heavier minute load will determine whether an upset is possible.

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