Siauliai — Cluj-Napoca
☆ Save matchModel prediction for 14 October
In short
Cluj-Napoca are slightly stronger: 55% against 45%.
The model expects a score around 85:87 — 172 points in total.
Over 171.5 points (incl. overtime) — 50%.
Why
- Team strength against the league average: Siauliai −6.8, Cluj-Napoca −2.6 points in regulation.
Probabilities
| Expected points (incl. overtime): Siauliai — Cluj-Napoca | 85.3–87.0 | |
| Total over 171.5 (incl. OT) | 50% | |
| Total under 171.5 (incl. OT) | 50% |
223 more model lines in Premium
All totals and handicaps, team totals, the regulation 1X2, the teams’ offence and defence, every factor and how the estimate moved before kick-off.
- All handicaps
- All totals
- Siauliai points
- Cluj-Napoca points
- Regulation 1X2
- Offence and defence strength
Form
- 07.10Venezia98:92
- 30.09away · Maxima Roma55:89
- 17.03away · Bahcesehir Kol.72:75
- 11.03away · Buducnost100:82
- 11.02Aris111:92
Head to head
No previous meetings in the data.
Table
Group B
| # | Team | W | L | PCT | GB |
|---|---|---|---|---|---|
| 1, Playoffs | Venezia | 1 | 1 | .500 | — |
| 2, Playoffs | Maxima Roma | 1 | 1 | .500 | — |
| 3, Playoffs | London Lions | 1 | 1 | .500 | — |
| 4, Playoffs | Turk Telekom | 1 | 1 | .500 | — |
| 5 | Tenerife | 1 | 1 | .500 | — |
| 6 | Siauliai | 1 | 1 | .500 | — |
| 7 | Frankfurt | 1 | 1 | .500 | — |
| 8 | Cluj-Napoca | 1 | 1 | .500 | — |
EuroCup on the same day
- 36642The model's most likely outcome: 2Model's score: —162.4
- 55451The model's most likely outcome: 1Model's score: —170.0
- 64361The model's most likely outcome: 1Model's score: —167.2
- 34662The model's most likely outcome: 2Model's score: —172.1
- 49512The model's most likely outcome: 2Model's score: —170.2
- 54461The model's most likely outcome: 1Model's score: —169.1
- 22782The model's most likely outcome: 2Model's score: —170.2
- 47532The model's most likely outcome: 2Model's score: —164.9
This is the model’s statistical estimate, not a recommendation. An outcome at 55% will not happen in roughly 45 matches out of 100. How to read probabilities →