Gstaad Switzerland Clay Atp 250 Quarterfinals

Raphael Collignon vs Valentin Vacherot: AI Prediction | Games, Spread, Aces & Double Faults

Raphael Collignon

Rank: #42
38%
VS

Valentin Vacherot

Rank: #21
62%
Expected Total Games: 26.6
Predicted Winner: Valentin Vacherot

Why the Model Favors Valentin Vacherot

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

Recent record by level +7.1 Valentin Vacherot
Surface fit +4.4 Valentin Vacherot
Recent form +3.2 Raphael Collignon
Serve & return game +2.6 Valentin Vacherot
Overall strength +1.6 Valentin Vacherot

Starting from an even matchup, these factors move the model to 62% for Valentin Vacherot. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Raphael Collignon

Form Index: 47.6
ELO Rating: 1696.0
Glicko2 Rating: 1747.2
Current Fatigue (minutes): 286.0
Surface Strength:
Hard: 23.4
Clay: 19.3
Grass: 8.9
Serve Rating: 96.4
Return Rating: 92.1

Valentin Vacherot

Form Index: 63.5
ELO Rating: 1808.8
Glicko2 Rating: 1795.1
Current Fatigue (minutes): 129.0
Surface Strength:
Hard: 35.3
Clay: 32.7
Grass: 16.6
Serve Rating: 96.7
Return Rating: 87.1

Recent Matches

Raphael Collignon

Valentin Vacherot

  • Last Match: vs Yannick Hanfmann (2-1) clay Gstaad 129 min
  • 2nd Last Match: vs Thomas Faurel (3-1) clay Roland Garros 174 min
  • 3rd Last Match: vs Emilio Nava (1-2) clay Madrid 179 min
  • 4th Last Match: vs Carlos Alcaraz (0-2) clay Monte Carlo 84 min
  • 5th Last Match: vs Alex de Minaur (2-1) clay Monte Carlo 144 min

Head-to-Head (Last 2 Seasons)

0
Raphael Collignon
vs
0
Valentin Vacherot
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

Quarterfinals in Gstaad, on slow Swiss clay, produce an intriguing clay-court matchup in this 250-level event. The model favors Valentin Vacherot to win (61.72%) over Raphael Collignon (38.28%), with a projected 26.65 total games in the match.

Match Analysis

The model’s edge for Vacherot comes mainly from recent record at similar levels and better surface fit. Recent-record-by-level contributes +7.1 points to Vacherot: he arrives having won on clay in both Roland Garros and Gstaad rounds, while his overall clay match experience this season looks deeper. Surface-fit adds another +4.4 toward Vacherot and that is reflected in the surface strength indices — Vacherot 32.71 versus Collignon 19.34 — indicating Vacherot is more comfortable on clay. Overall strength (+1.6) also leans to Vacherot: he’s ranked 21 with a 1808.8 Elo, compared with Collignon at 42 and a 1696.0 Elo. That said, Collignon has pushed back in-form signals that account for a +3.2 tilt in his favor: his recent tournament form in Gstaad is strong, with straight-sets win over Lorenzo Sonego and a three-set victory over Timofey Skatov before reaching this round. Fatigue is a clear contrast — Collignon has logged 286 minutes in this event versus Vacherot’s 129 — which may blunt Collignon’s mid-match legs. Serve numbers are effectively even (mean serve indices 96.45 vs 96.66), so no large serving advantage is expected, but Collignon holds a slightly better mean return (92.15 vs 87.11), a difference just over 5 points that could be decisive in the crucible of clay breaks. Recent three-match form: Collignon 2–1 (two Gstaad wins, prior loss on grass), Vacherot 2–1 (Gstaad and Roland Garros wins, one clay loss in Madrid).

Total Games Predictions

🎾
Expected Total Games in Match 26.6 Most likely outcome: 26 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Raphael Collignon versus Valentin Vacherot. 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 Raphael Collignon versus Valentin Vacherot. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Raphael Collignon - Valentin Vacherot) -1.4 Most likely spread: -2 (Valentin Vacherot wins 2 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Raphael Collignon versus Valentin Vacherot. Positive values indicate Raphael Collignon winning more games, negative values indicate Valentin Vacherot winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Raphael Collignon versus Valentin Vacherot. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction sits at 13.26 for the match and the predicted double faults total is 6.94. On slow clay, expected aces are suppressed and predicted aces reflect that; expected double faults can rise as matches wear on, especially given Collignon’s heavier minutes. Neither player has a significantly higher serve rating to push aces well above the projection, so the serve contest should be more about placement than sheer pace.
🎯
Expected Total Aces 13.3 Most likely: 13 aces
Expected Total Double Faults 6.9 Most likely: 6 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Raphael Collignon versus Valentin Vacherot. 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 Raphael Collignon versus Valentin Vacherot. 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 Raphael Collignon versus Valentin Vacherot. 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 Raphael Collignon versus Valentin Vacherot. 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

47.4% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Raphael Collignon's perspective)

0-2 Most likely set score (34.9%)
Probability distribution of the final set score from Raphael Collignon's perspective. Format: BO3.

Final Prediction

Vacherot’s edge is driven primarily by recent record at this level and better clay fit. Watch Collignon’s return pressure early and whether accumulated fatigue increases his error count — that will likely decide if Vacherot can convert the model’s projected advantage into a win.

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