Erel Ya. 🇹🇷 - Pavlovich L. 🇫🇷
About the athletes
Our model prediction (Glicko-2)
1 Erel Ya. 🇹🇷 — 51%
Pure model vs market (1 · Erel Ya. 🇹🇷): model 61% · market 49% Δ +12 pp model estimates above the market
Model estimate: win Erel Ya. 🇹🇷 50.5%, win Pavlovich L. 🇫🇷 49.5%. Model favourite — Erel Ya. 🇹🇷.
Informational estimate, not a betting recommendation.
Independent AI-agent assessment from our data (model, market line, form, H2H)
- • Эрель Я
- • (Тур) — Павлович Л
- • (Фра) (теннис)
- • Эрель Я
- • (Тур): форма ВВВВВ (5-0)
- • Павлович Л
- • (Фра): форма ПВПВП (2-3)
- • линия на пик П1 1.88→1.90 (удлинилась — рынок дрейфует против)
- • Модель ставит на Эрель Я
- • (Тур): вероятность 51% против 53% по линии (кэф 1.89)
- ✓ перевеса над линией нет (-2 пп) — прогноз информационный.
Analytical AI-agent assessment, not a betting recommendation.
Math-model prediction
AI match prediction Erel Ya. 🇹🇷 - Pavlovich L. 🇫🇷 14 июля 2026
Tennis math modelBased on the collected prematch data, the favourite looks like Pavlovich L. 🇫🇷.
- Win odds (Fonbet): 1 1.90 / 2 1.85
- Glicko: Erel Ya. 🇹🇷 50.5% / Pavlovich L. 🇫🇷 49.5%
For reference
Fair probability (no margin)
Probability excluding the bookmaker margin — for reference, not a betting recommendation.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
Line movement
How the odds changed from opening to the current line — for reference, not a betting recommendation.↓ odds shortened (money on this outcome), ↑ drifted (line weakened). For reference, not a betting recommendation.
Head-to-head and form stats
Head-to-head and form
Team form
no data
Head-to-head and recent form per sports statistics — for reference.
Erel Ya. 🇹🇷 - Pavlovich L. 🇫🇷
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.
Handicap
| Outcome | Baltbet | Betcity | Fonbet | Leon |
|---|---|---|---|---|
| П1 +0.5 | 1.83 54.6% | — | 1.80 55.6% | 1.83 54.6% |
| П1 +1.5 | 1.86 53.8% | 1.70 58.8% | 1.68 59.5% | — |
| П1 +2.5 | — | — | 1.68 59.5% | — |
| П1 -0.5 | — | — | 1.95 51.3% | — |
| П1 -1.5 | — | — | 2.10 47.6% | — |
| П2 +0.5 | — | — | 1.90 52.6% | — |
| П2 +1.5 | — | — | 2.05 48.8% | — |
| П2 +2.5 | — | — | 2.05 48.8% | — |
| П2 -0.5 | 1.89 52.9% | — | 1.75 57.1% | 1.91 52.4% |
| П2 -1.5 | 1.86 53.8% | 2.02 49.5% | 1.65 60.6% | — |
Total
| Outcome | Baltbet | Betcity | Fonbet |
|---|---|---|---|
| ТБ 20.5 | — | — | 1.50 66.7% |
| ТБ 21.5 | 1.76 56.8% | 1.73 57.8% | 1.55 64.5% |
| ТБ 22.5 | 1.91 52.4% | 1.85 54.1% | 1.78 56.2% |
| ТБ 23.5 | — | — | 2.00 50.0% |
| ТБ 24.5 | — | — | 2.05 48.8% |
| ТБ 25.5 | — | — | 2.25 44.4% |
| ТМ 20.5 | — | — | 2.40 41.7% |
| ТМ 21.5 | 1.97 50.8% | 2.00 50.0% | 2.30 43.5% |
| ТМ 22.5 | 1.81 55.3% | 1.85 54.1% | 1.92 52.1% |
| ТМ 23.5 | — | — | 1.72 58.1% |
Outcome (1X2)
| Outcome | Baltbet | Betcity | Fonbet | Leon |
|---|---|---|---|---|
| П1 | 1.88 53.2% | 1.90 52.6% | 1.90 52.6% | 1.87 53.5% |
| П2 | 1.84 54.4% | 1.79 55.9% | 1.85 54.1% | 1.83 54.6% |
Радулов И. (Бол)
Edengren K. (Шве)
Pavlovich L. 🇫🇷
Дроге Т. (Фра)
Сантильян А. (Япо)
Галан Д. Э. (Кол)
Full head-to-head historyErel Ya. 🇹🇷 - Pavlovich L. 🇫🇷