Saturday, 29/08/2026 at 19:00
Full timeAkhmat Grozny 3:3 Krylya Sovetov Samara
Akhmat Grozny were the model's likeliest winner before kick-off at 50%. It finished 3–3.
The model against the result
- Akhmat Grozny
- 50%
- Draw
- 28% What happened
- Krylya Sovetov Samara
- 21%
Data coverage Both teams have the full 20-match model window available.
Recent form
1.16 xG created 1.43 xGA
- D 0.62 created, 2.25 conceded against Baltika Kaliningrad
- L 0.60 created, 2.00 conceded against Zenit St. Petersburg
- W 2.03 created, 1.07 conceded against Pari Nizhny Novgorod
- D 0.97 created, 0.66 conceded against Dinamo Makhachkala
- D 0.86 created, 1.15 conceded against FC Sochi
- D 1.87 created, 1.44 conceded against Lokomotiv Moscow
1.84 xG created 1.71 xGA
- D 0.90 created, 0.17 conceded against CSKA Moscow
- L 0.82 created, 2.96 conceded against FC Sochi
- W 2.91 created, 1.37 conceded against Lokomotiv Moscow
- W 1.11 created, 1.52 conceded against FC Spartak Moscow
- L 1.04 created, 2.22 conceded against Orenburg
- W 4.23 created, 2.02 conceded against Akron Togliatti
xG created xG conceded (xGA) W / D / L: the match result
Head to head
Pre-match model & market record
2 opportunities flagged2 won0 lost
- Won
- Won
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| Draw | 3.67 | +3.9% | Won |
| Over 2.5 goals | 1.94 | +3.4% | Won |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Akhmat Grozny | 50.5% | 50.6% | −0.1 pp | 1.98 |
| Draw | 28.3% | 26.2% | +2.1 pp | 3.53 |
| Krylya Sovetov Samara | 21.2% | 23.3% | −2.0 pp | 4.71 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Over 2.5 goals | 53.2% | 49.8% | +3.5 pp | 1.88 |
| Under 2.5 goals | 46.8% | 50.2% | −3.5 pp | 2.14 |
Prices and probabilities are the ones stored before kick-off; nothing here is recalculated. Edge is the model's probability times the price, minus one, so a flagged outcome that lost is the ordinary case rather than a contradiction.
Model details
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- Fit window
- the last 20 matches, recency weighted (a match 107 days old counts half)
- Akhmat Grozny sample
- 20 matches
- Krylya Sovetov Samara sample
- 20 matches
- Computed
- 9 hours before kick-off
- Prices taken
- 9 hours before kick-off
Limitations
The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.