Rame A. 🇫🇷 - Noha Akugue N
About the athletes
Our model prediction (Glicko-2)
PropickAI model · comparison with the market line (no margin)
2 Noha Akugue N — 72%
Pure model vs market (2 · Noha Akugue N): model 53% · market 93% Δ −40 pp model estimates below the market
Model estimate: win Rame A. 🇫🇷 28.1%, win Noha Akugue N 71.9%. Model favourite — Noha Akugue N.
Informational estimate, not a betting recommendation.
Math-model prediction
AI match prediction Rame A. 🇫🇷 - Noha Akugue N 13 июля 2026
Tennis math modelBased on the collected prematch data, the favourite looks like Noha Akugue N.
- Win odds (Fonbet): 1 14.00 / 2 1.01
- Glicko: Rame A. 🇫🇷 28.1% / Noha Akugue N 71.9%
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
Head-to-head and recent form per sports statistics — for reference.
Rame A. 🇫🇷 - Noha Akugue N
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 |
|---|---|---|---|
| П1 +3.5 | — | — | 2.05 48.8% |
| П1 +4.5 | 1.97 50.8% | 2.03 49.3% | 2.25 44.4% |
| П1 +5.5 | 1.71 58.5% | 1.70 58.8% | 10.00 10.0% |
| П1 +6.5 | — | — | 7.40 13.5% |
| П2 +3.5 | — | — | 1.68 59.5% |
| П2 +4.5 | — | — | 1.57 63.7% |
| П2 +5.5 | — | — | 1.02 98.0% |
| П2 +6.5 | — | — | 1.05 95.2% |
| П2 +7.5 | — | — | 2.55 39.2% |
| П2 +8.5 | — | — | 3.10 32.3% |
| П2 -4.5 | 1.76 56.8% | 1.70 58.8% | — |
| П2 -5.5 | 2.05 48.8% | 2.02 49.5% | — |
Total
| Outcome | Baltbet | Betcity | Fonbet |
|---|---|---|---|
| ТБ 15.5 | — | — | 1.43 69.9% |
| ТБ 16.5 | — | — | 1.42 70.4% |
| ТБ 17.5 | — | — | 1.40 71.4% |
| ТБ 18.5 | — | — | 2.20 45.5% |
| ТБ 19.5 | 1.76 56.8% | 1.78 56.2% | 6.30 15.9% |
| ТБ 20.5 | 1.95 51.3% | 1.94 51.6% | 10.50 9.5% |
| ТБ 21.5 | — | — | 1.90 52.6% |
| ТБ 22.5 | — | — | 1.95 51.3% |
| ТБ 23.5 | — | — | 1.75 57.1% |
| ТБ 24.5 | — | — | 1.72 58.1% |
| ТМ 19.5 | 1.97 50.8% | 1.92 52.1% | — |
| ТМ 20.5 | 1.78 56.2% | 1.76 56.8% | — |
Outcome (1X2)
| Outcome | Baltbet | Betcity | Fonbet | Leon |
|---|---|---|---|---|
| П1 | 3.60 27.8% | 3.80 26.3% | 14.00 7.1% | 3.45 29.0% |
| П2 | 1.26 79.4% | 1.22 82.0% | 1.01 99.0% | 1.25 80.0% |
Джонс Ф. (Вел)
Хвалинска М. (Пол)
Noha Akugue N
Краус С. (Авт)
Full head-to-head historyRame A. 🇫🇷 - Noha Akugue N