AI verdict
Model consensus and the Glicko-2 rating lean to Wong C. Full breakdown below.
Picks locked before kickoff results verified after public accuracy log →
| Muller A | Wong C | |
|---|---|---|
| Win % | 51.1% | 53.6% |
| Hard % | 48.6% | 57.1% |
| Clay % | 54.9% | 39.1% |
| Grass % | 30% | 36.8% |
| Deciding set % | 57.7% | 52.4% |
| Tie-breaks % | 48.2% | 59.6% |
| Titles (total) | 4 | 1 |
| Last 10 | LLWWLLLLLL | LWWLWWWLWL |
Source: scorego-app.com
| Muller A | Wong C | |
|---|---|---|
| Aces per match | 3.00 | 9.70 |
| Double faults per match | 1.71 | 2.43 |
| Breaks per match | 2.1 | 1.87 |
Source:tennisstats.com (per-match averages)
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Win Percentage 2026 Calendar Year | 25.0% 1 / 4 Matches | 62.2% 28 / 45 Matches |
| Win Percentage Last 12 Months | 33.3% 6 / 18 Matches | 61.2% 41 / 67 Matches |
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Win Percentage 2026 Calendar Year | 45.0% 9 / 20 Matches | 40.0% 2 / 5 Matches |
| Win Percentage Last 12 Months | 45.0% 9 / 20 Matches | 40.0% 2 / 5 Matches |
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Win Percentage 2026 Calendar Year | N/A 0 / 0 Matches | 25.0% 1 / 4 Matches |
| Win Percentage Last 12 Months | N/A 0 / 0 Matches | 25.0% 1 / 4 Matches |
Source:tennisstats.com
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| H2H wins | 0 (0%) | 0 (0%) |
| Sets | 0 (0%) | 0 (0%) |
| Wins this year | 37.9% 11 / 29 Matches | 55.4% 31 / 56 Matches |
| Wins in 12 mo. | 37.2% 16 / 43 Matches | 57.0% 45 / 79 Matches |
| Current rank | 136 | 93 |
Source: tennisstats.com
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Prize money (career) | $2,210,035 USD | $268,667 USD |
| Rating | 136 | 93 |
| Age | 29 | 22 |
| Height | 1.83m | 1.91m |
| Weight | 75kg | 80kg |
| Playing hand | Right-handed | Right-handed |
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Match Wins | 38 % | 55 % |
| Match Wins (3 Sets) | 42 % | 57 % |
| Match Wins (5 Sets) | 33 % | 0 % |
| Wins in Straight Sets | 24 % | 39 % |
| Wins From Behind | 14 % | 17 % |
| Won At Least 1 Set | 52 % | 79 % |
| Set 1 Win | 31 % | 59 % |
| Set 2 Win | 45 % | 59 % |
Source:tennisstats.com
| Alexandre Muller | Chak Lam Coleman Wong | |
|---|---|---|
| Aces | 0 | 0 |
| Double Faults | 0 | 0 |
| 1st serve percentage | 100% | 0% |
| 1st serve points won | 100% (1/1) | 0% (0/0) |
| 2nd serve points won | 0% (0/0) | 0% (0/0) |
| Break Points Saved | 0/0 | 0/0 |
| 1st return points won | 0% (0/0) | 0% (0/1) |
| 2nd return points won | 0% (0/0) | 0% (0/0) |
| Break Points Converted | 0/0 | 0/0 |
| Service Points Won | 100% (1/1) | 0% (0/0) |
| Return Points Won | 0% (0/0) | 0% (0/1) |
| Total Points Won | 100% (1/1) | 0% (0/1) |
| Last 10 balls | 1 | 0 |
| Match points saved | 0 | 0 |
| Service games won | 0% (0/0) | 0% (0/0) |
| Return games won | 0% (0/0) | 0% (0/0) |
| Total games won | 0% (0/0) | 0% (0/0) |
Source:tennisstats.com
Outcome percentages for totals and props: values for each player and a match-total column.
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Average Games in a Set | 9.72 | 10.07 | 9.9 |
| Over 6.5 | 100 % | 100 % | 100 % |
| Over 7.5 | 96 % | 93 % | 95 % |
| Over 8.5 | 75 % | 81 % | 78 % |
| Over 9.5 | 67 % | 52 % | 60 % |
| Over 10.5 | 29 % | 30 % | 30 % |
| Over 11.5 | 29 % | 30 % | 30 % |
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Aces Per Match | 3.00 | 9.70 | 12.70 |
| Most Aces in a match | 33 % | 85 % | N/A |
| 1+ | 83 % | 98 % | 99 % |
| 2+ | 71 % | 98 % | 99 % |
| 3+ | 54 % | 98 % | 91 % |
| 4+ | 33 % | 96 % | 87 % |
| 5+ | 25 % | 91 % | 85 % |
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Breaks Per Match | 2.1 | 1.87 | 3.97 |
| Over 0.5 | 63 % | 98 % | 100 % |
| Over 1.5 | 63 % | 15 % | 100 % |
| Over 2.5 | 63 % | 9 % | 81 % |
| Over 3.5 | 58 % | 7 % | 79 % |
| Over 4.5 | 0 % | 2 % | 27 % |
| Over 5.5 | 0 % | 0 % | 6 % |
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Tie Breaks Per Match | 0.33 | 0.43 | 0.38 |
| Over 0.5 | 29 % | 37 % | 33 % |
| Over 1.5 | 4 % | 6 % | 5 % |
| Under 0.5 | 71 % | 63 % | 33 % |
| Under 1.5 | 96 % | 94 % | 5 % |
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Double Faults Per Match | 1.71 | 2.43 | 4.14 |
| Over 0.5 (1+) | 67 % | 83 % | 98 % |
| Over 1.5 (2+) | 50 % | 63 % | 90 % |
| Over 2.5 (3+) | 21 % | 39 % | 68 % |
| Over 3.5 (4+) | 17 % | 24 % | 53 % |
| Over 4.5 (5+) | 13 % | 17 % | 45 % |
| Over 5.5 (6+) | 4 % | 11 % | 27 % |
| Alexandre Muller | Chak Lam Coleman Wong | Match total | |
|---|---|---|---|
| Net Points Won Per Match | 6 | 7.9 | 13.9 |
| Over 4.5 (5+) | 73 % | 81 % | 77 % |
| Over 5.5 (6+) | 53 % | 71 % | 62 % |
| Over 6.5 (7+) | 47 % | 67 % | 57 % |
| Over 7.5 (8+) | 33 % | 60 % | 47 % |
| Over 8.5 (9+) | 20 % | 45 % | 33 % |
| Over 9.5 (10+) | 13 % | 40 % | 27 % |
Source:tennisstats.com
Muller A face Wong C on August 19, 2026 in the ATP Challenger Cancun, Mexico Men Singles.
PropickAI's Glicko-2 model gives the home side 34% to win. Below: team form, head-to-head history, bookmaker odds and the full PropickAI AI breakdown.
Our model prediction (Glicko-2)
PropickAI model · comparison with the market line (no margin)
2 Wong C — 66%
Model estimate: win Muller A 34.5%, win Wong C 65.5%. Model favourite — Wong C.
Informational estimate, not a betting recommendation.
Independent AI-agent assessment from our data (model, market line, form, H2H)
Analytical AI-agent assessment, not a betting recommendation.
Math-model prediction
Based on the collected prematch data, the favourite looks like Wong C.
For reference
Odds source: consensus of 4 books (Baltbet, Kambi BetMGM, Kambi Unibet, Leon). This is the fair probability after removing the bookmaker margin from the odds — reference information, not a prediction or a betting recommendation.
Model consensus
Modeli dayut edinyy signal. Takie matchi my pomechaem kak bolee silnye.
Market consensus
Consensus probability with the bookmaker margin removed; the number on the right is the best available odds. For reference only, not a bet.
AI overview
AI analysis:1/7 ready · Still preparing:DeepSeek, ChatGPT, Claude, Qwen, Kimi, GLM 5.2
The upcoming round of 32 match at the Cancún Country Open in Mexico pairs world No. 136 Alexandre Müller against the rising world No. 93 Chak Lam Coleman Wong. This hard-court match presents an intriguing contrast between Müller's experience and Wong's stellar 2026 hard-court breakthrough.
Current Form and Rankings
Alexandre Müller (France): Currently struggling with a LLWWL form curve. Müller has seen his ranking drop outside the top 100 to No. 136. His hard-court performances have lacked consistency, often succumbing to unforced errors during protracted baseline rallies.
Chak Lam Coleman Wong (Hong Kong): Currently riding a strong WLWWW momentum shift. He recently broke into the ATP Top 100 for the first time, demonstrating excellent hard-court aptitude through deep runs like his recent ATP 250 semifinal in Los Cabos. He arrives sharp after standard qualifying and main draw battles at the Cincinnati Masters.
Head-to-Head (H2H) & Match Conditions
There are no previous official head-to-head encounters between Alexandre Müller and Coleman Wong. The surface in Cancún is standard outdoor hard court, which naturally gives an upper hand to Wong. Wong’s baseline aggression and powerful serve have excelled in the high humidity and bouncy conditions of Latin American hard-court tournaments this season.
Injuries, Suspensions, and Line-Ups
Both players enter this tournament fully healthy with no reported physical restrictions, injuries, or suspensions. Both are highly motivated; Müller needs points desperately to salvage his ranking, while Wong is eager to cement his newly earned status as a top-100 player.
Market and Model Analysis Divergence
The analytical model assigns a narrow 47% win probability to Müller and 53% to Wong. However, my analysis slightly adjusts this gap to P1 40% / P2 60%. The justification for this divergence lies in the hyper-specific hard-court metric tracking: Wong boasts a 61.5% win rate on outdoor hard courts this year and has scored massive confidence-boosting wins over top-tier opponents like Jiří Lehečka. Müller's current technical slump and vulnerabilities on quick surfaces make Wong a more decisive favorite than a simple Glicko rating suggests.
Total Games and Exact Score Forecast
Given both players possess solid hold percentages—with Wong holding serve 77.1% of the time this year—this match should feature highly competitive sets. A standard line of Over 22.5 games is heavily anticipated, as a single tiebreak or a close three-setter is highly probable. The most realistic exact score scenario is a 1:2 win for Wong, as Müller's experience should allow him to snatch a set before Wong's superior physical stamina dominates the deciding frame.
Brief Conclusion (The Main Bet)
The definitive recommendation is to back Chak Lam Coleman Wong to win (P2). His upward career trajectory, phenomenal 2026 hard-court metrics, and recent high-level match practice in Cincinnati make him the clear pick to outlast the out-of-form Frenchman.
| AI | 1 | 2 | Score | Total games | Bet |
|---|---|---|---|---|---|
| Google AI | 40% | 60% | 1:2 | Over 22.5 | Away Win (P2) |
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V baze uchteny nedavnie matchi oboikh uchastnikov.
We mark in green only strong signals where the model passed our publication filter. The other rows are for audit and training.
Tennis math model. Tennis without draws: the base signal comes from player rating, surface, form, serve/return and tournament fatigue. For live logic the set state and who is serving matter more than the overall points score.
Glicko-2 is a team-strength rating: it weighs the line, history and consistency, but is not a guarantee.
Model = Glicko + Elo strength prior (heuristic, historical calibration in progress). Glicko34.5% · +Elo prior (weight0.25).
Tennis without draws: the base signal comes from player rating, surface, form, serve/return and tournament fatigue. For live logic the set state and who is serving matter more than the overall points score.
Betting notes are built from the line, market and our math model: take a signal only when the model and market agree.
| Outcome | Baltbet | Leon |
|---|---|---|
| 1.86 53.8% | 1.84 54.4% | |
| 1.86 53.8% | 1.89 52.9% |
| Outcome | Baltbet | Kambi BetMGM |
|---|---|---|
| Over 2.5 | — | 2.45 40.8% |
| Over 8.5 | — | 1.22 82.0% |
| Over 9.5 | — | 1.71 58.5% |
| Over 10.5 | — | 3.00 33.3% |
| Over 21.5 | 1.76 56.8% | 1.66 60.2% |
| Over 22.5 | 1.94 51.6% | 1.92 52.1% |
| Over 23.5 | — | 2.18 45.9% |
| Under 2.5 | — | 1.50 66.7% |
| Under 8.5 | — | 4.00 25.0% |
| Under 9.5 | — | 2.07 48.3% |
| Under 10.5 | — | 1.35 74.1% |
| Under 21.5 | 1.97 50.8% | 2.10 47.6% |
| Under 22.5 | 1.79 55.9% | 1.80 55.6% |
| Under 23.5 | — | 1.62 61.7% |
| Outcome | Baltbet | Kambi BetMGM | Kambi Unibet | Leon |
|---|---|---|---|---|
| 3.05 32.8% | 2.85 35.1% | 2.85 35.1% | 2.80 35.7% | |
| 1.34 74.6% | 1.41 70.9% | 1.41 70.9% | 1.38 72.5% |
Muller A
Den Ouden G. 🇳🇱
Chekkinato M. 🇮🇹
Napolitano S. 🇮🇹
Navone M. 🇦🇷
Wong C
Virtanen O. 🇫🇮
Gea A. 🇫🇷
Bruksbi Dzh. 🇺🇸
Lekhechka I. 🇨🇿
Blanch Dar. 🇺🇸
The Muller A - Wong C breakdown — outcomes, probabilities, risks and history — is available after a free sign-in.
By the PropickAI model, Wong C is favoured — about 66% win probability.
The consensus of 7 AI models and the Glicko-2 rating leans to Wong C. Full probabilities and bookmaker odds are shown on this page.
August 19, 2026.