Our model prediction (Glicko-2)
PropickAI model · comparison with the market line (no margin)
1 Reberg M. Kh. 🇩🇪 — 61%
Pure model vs market (1 · Reberg M. Kh. 🇩🇪): model 47% · market 7% Δ +40 pp model estimates above the market
Model estimate: win Reberg M. Kh. 🇩🇪 61.2%, win Khusto G. I. 🇦🇷 38.8%. Model favourite — Reberg M. Kh. 🇩🇪.
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 Khusto G. I. 🇦🇷.
For reference
Odds source: Fonbet. This is the fair probability after removing the bookmaker margin from the odds — reference information, not a prediction or a betting recommendation.
For reference
↓ odds shortened (money on this outcome), ↑ drifted (line weakened). For reference, not a betting recommendation.
Model consensus
Модели дают единый сигнал. Такие матчи мы помечаем как более сильные.
Head-to-head and form stats
Head-to-head and recent form per sports statistics — for reference.
AI overview
AI analysis:7/7 ready
AI consensus:1
| AI | 1 | 2 | Score | Total games | Bet |
|---|---|---|---|---|---|
| Google AI | 63% | 37% | 2:0 | ТБ 22.5 | 1 |
| DeepSeek | 60% | 40% | 2:1 | ТБ 22.5 | П1 |
| ChatGPT | 64% | 36% | 2:0 | ТМ 22.5 | Реберг поб |
| Claude | 35% | 65% | 2:0 (Хусто) | ТМ 22.5 | П2 — победа Хусто |
| Qwen | 63% | 37% | 2:1 | ТБ 22.5 | Победа Реберга М. Х. (П1) |
| Kimi | 62% | 38% | 2:0 | ТМ 22.5 | П1 (Реберг) |
| GLM 5.2 | 63% | 37% | — | ТБ 22.5 | по форме: Реберг показывает прогрессирующую форму на грунтовых челленджерах в июле, одержав две уверенные победы над соперниками из топ-300, включая победу в трёх сетах над опытным Яном Чоински |
В базе учтены недавние матчи обоих участников.
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 - рейтинговая модель силы: сравнивает линию, историю и стабильность, но не дает гарантий.
Best value: value не найден
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 | Betcity | Fonbet |
|---|---|---|---|
| П1 -0.5 | — | — | 1.92 52.1% |
| П1 -2.5 | 1.81 55.3% | 1.70 58.8% | — |
| П1 -3.5 | 1.94 51.6% | — | — |
| П2 +0.5 | — | — | 1.90 52.6% |
| П2 +1.5 | — | — | 2.02 49.5% |
| П2 +2.5 | 1.91 52.4% | 2.02 49.5% | 1.45 69.0% |
| П2 +3.5 | 1.79 55.9% | — | 1.01 99.0% |
| П2 +4.5 | — | — | 1.05 95.2% |
| П2 +5.5 | — | — | 2.20 45.5% |
| П2 -0.5 | — | — | 1.78 56.2% |
| П2 -1.5 | — | — | 1.90 52.6% |
| П2 -2.5 | — | — | 1.72 58.1% |
| П2 -3.5 | — | — | 1.77 56.5% |
| П2 -4.5 | — | — | 1.52 65.8% |
| Outcome | Baltbet | Betcity | Fonbet |
|---|---|---|---|
| ТБ 19.5 | — | — | 5.90 17.0% |
| ТБ 20.5 | — | — | 1.70 58.8% |
| ТБ 21.5 | 1.83 54.6% | 1.84 54.4% | 6.80 14.7% |
| ТБ 22.5 | 1.97 50.8% | — | 1.92 52.1% |
| ТБ 23.5 | — | — | 2.02 49.5% |
| ТБ 24.5 | — | — | 1.95 51.3% |
| ТБ 25.5 | — | — | 1.85 54.1% |
| ТБ 26.5 | — | — | 1.95 51.3% |
| ТБ 27.5 | — | — | 1.72 58.1% |
| ТБ 28.5 | — | — | 1.90 52.6% |
| ТМ 19.5 | — | — | 1.08 92.6% |
| ТМ 20.5 | — | — | 2.02 49.5% |
| ТМ 21.5 | 1.89 52.9% | 1.86 53.8% | — |
| ТМ 22.5 | 1.76 56.8% | — | — |
| Outcome | Baltbet | Betcity | Fonbet | Leon |
|---|---|---|---|---|
| П1 | 1.49 67.1% | 1.47 68.0% | 13.00 7.7% | 1.47 68.0% |
| П2 | 2.47 40.5% | 2.48 40.3% | 1.01 99.0% | 2.49 40.2% |
Reberg M. Kh. 🇩🇪
Ян Чоински (Вел)
Kouame M. (Фра)
Pieri S. (Ита)
Khusto G. I. 🇦🇷
Milic O. (Сер)
Гима С. (Рум)
Full head-to-head historyReberg M. Kh. 🇩🇪 - Khusto G. I. 🇦🇷