Our model prediction (Glicko-2)
PropickAI model Β· comparison with the market line (no margin)
2 Sakatsume H β 61%
Pure model vs market (2 Β· Sakatsume H): model 48% Β· market 61% Ξ β13 pp model estimates below the market
Model estimate: win Wang Xiyu 39.4%, win Sakatsume H 60.6%. Model favourite β Sakatsume H.
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 Sakatsume H.
For reference
Odds source: Fonbet. This is the fair probability after removing the bookmaker margin from the odds β reference information, not a prediction or a betting recommendation.
For reference
β odds shortened (money on this outcome), β drifted (line weakened). For reference, not a betting recommendation.
Model consensus
Modeli dayut edinyy signal. Takie matchi my pomechaem kak bolee silnye.
Head-to-head and form stats
Head-to-head and recent form per sports statistics β for reference.
AI overview
AI analysis:1/7 ready Β· Still preparing:DeepSeek, ChatGPT, Claude, Qwen, Kimi, GLM 5.2
| AI | 1 | 2 | Score | Total games | Bet |
|---|---|---|---|---|---|
| Google AI | 35% | 65% | 0:2 | Under 22.5 |
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.
Best value: no value found
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 | Betcity | Fonbet |
|---|---|---|
| — | 2.30 43.5% | |
| — | 2.15 46.5% | |
| 2.02 49.5% | — | |
| 1.79 55.9% | — | |
| — | 2.50 40.0% | |
| — | 2.70 37.0% | |
| — | 2.95 33.9% | |
| — | 1.55 64.5% | |
| — | 1.63 61.4% | |
| — | 1.78 56.2% | |
| — | 2.00 50.0% | |
| — | 2.45 40.8% | |
| — | 3.05 32.8% | |
| — | 1.47 68.0% | |
| — | 1.40 71.4% | |
| 1.80 55.6% | 1.35 74.1% | |
| 2.02 49.5% | — |
| Outcome | Betcity | Fonbet |
|---|---|---|
| Over 18.5 | — | 1.35 74.1% |
| Over 19.5 | — | 1.50 66.7% |
| Over 20.5 | — | 1.68 59.5% |
| Over 21.5 | 1.88 53.2% | 1.90 52.6% |
| Over 22.5 | — | 2.10 47.6% |
| Over 23.5 | — | 2.35 42.6% |
| Over 24.5 | — | 2.45 40.8% |
| Over 25.5 | — | 2.75 36.4% |
| Under 18.5 | — | 3.00 33.3% |
| Under 19.5 | — | 2.45 40.8% |
| Under 20.5 | — | 2.05 48.8% |
| Under 21.5 | 1.92 52.1% | 1.90 52.6% |
| Under 22.5 | — | 1.65 60.6% |
| Under 23.5 | — | 1.53 65.4% |
| Under 24.5 | — | 1.48 67.6% |
| Under 25.5 | — | 1.40 71.4% |
| Outcome | Betcity | Fonbet | Leon |
|---|---|---|---|
| 2.50 40.0% | 2.45 40.8% | 2.48 40.3% | |
| 1.53 65.4% | 1.55 64.5% | 1.52 65.8% |
| Bookmaker | 1 | 2 |
|---|---|---|
| Pari | 3.2 | 1.35 |
| Winline | 2.4 | 1.53 |
| Fonbet | 3.2 | 1.35 |
| Betcity | 3.2 | 1.35 |
Wang Xiyu
Kyrstya S. π·π΄
Starodubtseva Yu. πΊπ¦
Baptist Kh. πΊπΈ
Kovinich D. (Cher)
Kudermetova P. πΊπΏ
Sakatsume H
Rybakina E. π°πΏ
Ruze G. π·π΄
Tomlyanovich A. π¦πΊ
Serra S. π¦π·
Navarro E. πΊπΈ
Full head-to-head historyWang Xiyu - Sakatsume H
The Wang Xiyu - Sakatsume H breakdown — outcomes, probabilities, risks and history — is available after a free sign-in.