Basketball
Basketball stats
The tool for those who build their own bet. Filter and find your value.
Filter by points for and against, pace, gap to the line and recent form. The tool for those who build their own basketball bet with data. How our model works → Points and pace in basketball: why scoring a lot isn't playing well →
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Formula 1
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| ⓘ | Date | League | Teams | Points F|A Last 5 ⓘ | Points F|A Last 10 ⓘ | 3-pt F|A ⓘ | FT F|A ⓘ | Est. total ⓘ | Line O/U ⓘ | Diff. ⓘ | Over/Under ⓘ | Est. result ⓘ | Diff. ⓘ | Hand. line ⓘ | Odds ⓘ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 14/08, 14:00View analysis ↗ | Rwanda National League Women | The Hoops BBC (W) | 57.2 | 56.2 | 63.1 | 61.2 | 6.3 | 4.5 | 8.5 | 11 | 119.6 | 116.5 | 3.1 | – / – | 58 | 2.5 | +3.5 | 2.30 | |
| Kepler (W) | 58.2 | 51 | 62.5 | 52.4 | 5 | 5.4 | 10.2 | 8.2 | 62 | 1.55 | |||||||||
| 14/08, 14:30View analysis ↗ | Vietnam VBA | Hanoi Buffaloes | 106.2 | 90.8 | 100.5 | 87.9 | 10.2 | 6.6 | 15.2 | 12.9 | 177.7 | 176.5 | 1.2 | – / – | 92 | 16.4 | -16.5 | 1.04 | |
| Cantho Catfish | 82.8 | 79.4 | 83.7 | 83.3 | 7.8 | 7.3 | 12.2 | 9.1 | 86 | 8.75 | |||||||||
| 14/08, 16:30View analysis ↗ | Rwanda National League Women | APR (W) | 81.2 | 65.2 | 76.3 | 64.9 | 7.8 | 7.6 | 13.6 | 12.2 | 143.7 | 142.5 | 1.2 | – / – | 69 | 5.4 | +6.5 | 2.90 | |
| REG (W) | 82.6 | 70.2 | 84.7 | 61.5 | 8.3 | 8.3 | 12.5 | 14.8 | 75 | 1.36 | |||||||||
| 14/08, 18:00View analysis ↗ | Uganda NBL Women | KCCA Leopards (W) | 68 | 58.4 | 60.8 | 57.1 | 6.1 | 5.4 | 12.1 | 9.8 | 117.8 | 119.5 | 1.75 | – / – | 55 | 5.8 | +7.5 | 3.25 | |
| UCU Lady Canons (W) | 69.4 | 52 | 69.2 | 48.4 | 8.9 | 5 | 9.3 | 12 | 63 | 1.30 | |||||||||
| 14/08, 19:00View analysis ↗ | Rwanda National League | Patriots BC | 72.2 | 68.8 | 82.6 | 71.6 | 5.8 | 8.4 | 16.4 | 8.7 | 158 | 150.5 | 7.5 | – / – | 81 | 5.8 | -5.5 | 1.43 | |
| Rwanda Energy Group | 75.8 | 75.6 | 81.5 | 80.3 | 8.1 | 6.2 | 11.3 | 16.7 | 77 | 2.65 | |||||||||
| 14/08, 20:00View analysis ↗ | Uganda NBL | City Oilers | 70.4 | 67 | 71.7 | 60 | 5.4 | 5.4 | 14.2 | 12.2 | 138.3 | 139.5 | 1.2 | – / – | 67 | 0.4 | +1.5 | 1.87 | |
| Nam Blazers | 83.6 | 68.4 | 83.4 | 61.5 | 9.3 | 5.6 | 16.1 | 9.3 | 72 | 1.80 | |||||||||
| 14/08, 21:30View analysis ↗ | Rwanda National League | APR BBC | 87.6 | 87.8 | 93 | 80.1 | 12.3 | 8.8 | 15.8 | 13.8 | 173.4 | 172.5 | 0.9 | – / – | 89 | 2.8 | -2.5 | 1.65 | |
| Tigers | 87.8 | 87.6 | 89.1 | 84.6 | 9.2 | 8.9 | 12.7 | 15.4 | 85 | 2.12 | |||||||||
| 15/08, 00:00View analysis ↗ | Brazil Camp.Carioca U22 | Flamengo U22 | 82.6 | 74.6 | 81.8 | 69.1 | 7.4 | 6.3 | 13.6 | 11.4 | 144 | 157.5 | 13.5 | – / – | 73 | 4.6 | -4.5 | 1.50 | |
| Botafogo RJ U22 | 72 | 66.2 | 73.2 | 63.9 | 7.7 | 5.7 | 14.3 | 12.6 | 71 | 2.50 | |||||||||
| 15/08, 00:30View analysis ↗ | Brazil Paulista Women | SESI/Araraquara (W) | 69.6 | 65.4 | 63.3 | 65.3 | 4.3 | 7.7 | 14.1 | 10.3 | 132.9 | 131.5 | 1.4 | – / – | 66 | 7.3 | – | – | |
| Santo Andre (W) | 70.2 | 75 | 67.8 | 69.4 | 7.4 | 6 | 11 | 10.9 | 67 | – | |||||||||
| 15/08, 01:00View analysis ↗ | Paraguay Primera | Olimpia Kings | 71.4 | 76.6 | 79.9 | 68.7 | 7.9 | 7.4 | 11.2 | 14.1 | 159.4 | 157.5 | 1.85 | – / – | 83 | 9.9 | -9.5 | 1.22 | |
| Felix Perez Cardozo | 78 | 91.8 | 84.5 | 85.6 | 8.7 | 9.8 | 13.6 | 14.7 | 77 | 3.90 | |||||||||
| 15/08, 01:15View analysis ↗ | Uruguay Liga de Ascenso | Sayago | 68 | 73.8 | 73.7 | 71.2 | 7.1 | 10.3 | 11.2 | 9.9 | 151.8 | 154 | 2.2 | – / – | 77 | 5.8 | – | – | |
| Urupan de Pando | 75.6 | 87.4 | 77.8 | 80.9 | 8.6 | 9.5 | 12.2 | 15.9 | 75 | – | |||||||||
| 15/08, 01:15View analysis ↗ | Uruguay Liga de Ascenso | Verdirrojo | 80.8 | 70.6 | 77.2 | 71.8 | 6.6 | 6.7 | 15 | 9.7 | 146 | 145 | 0.95 | – / – | 74 | 5 | – | – | |
| Stockolmo | 77.4 | 72.2 | 72.8 | 70.1 | 9.1 | 8.4 | 11 | 10.4 | 72 | – | |||||||||
| 15/08, 01:15View analysis ↗ | Uruguay Liga de Ascenso | Tabare | 81.2 | 89 | 77.7 | 79.5 | 9.1 | 9.1 | 11.9 | 12.4 | 154.4 | 156 | 1.6 | – / – | 76 | 0.7 | – | – | |
| Lagomar | 77.4 | 72.6 | 76.4 | 75.2 | 5.3 | 8.4 | 14.7 | 14.4 | 78 | – | |||||||||
| 15/08, 02:00View analysis ↗ | Puerto Rico Superior Nacional | Vaqueros de Bayamon | 98.6 | 87.8 | 90.8 | 83.3 | 9.5 | 9.5 | 14.8 | 14.1 | 178.1 | 173.5 | 4.55 | – / – | 90 | 4.6 | -5 | 1.53 | |
| Aguada Santeros | 91.4 | 92.4 | 92.6 | 89.4 | 9.1 | 8.6 | 15.1 | 15.6 | 88 | 2.40 | |||||||||
| 15/08, 02:00View analysis ↗ | Chile LNB | CD Espanol Talca | 75 | 90.8 | 75.9 | 95 | 9.3 | 10.4 | 10.6 | 13.5 | 171.7 | 174.5 | 2.85 | 35% / 65% | 77 | 6.2 | +24.5 | – | |
| CDU Concepcion | 88 | 75.4 | 95.3 | 77.1 | 10.3 | 8.2 | 15.9 | 13.7 | 95 | – | |||||||||
| 15/08, 13:10View analysis ↗ | Australia NBL1 West | Rockingham Flames | 107 | 85.8 | 100.6 | 86.3 | 10.6 | 11 | 9.6 | 10.7 | 187.6 | 187 | 0.55 | – / – | 93 | 2.8 | – | – | |
| Geraldton Buccaneers | 95.4 | 88.6 | 102 | 86.2 | 12 | 10.5 | 14.9 | 12.2 | 94 | – | |||||||||
| 15/08, 23:00View analysis ↗ | Brazil Paulista 1 Div. | Mogi das Cruzes | 91.8 | 77 | 84.9 | 80.8 | 12 | 9.8 | 12.6 | 14 | 159.2 | 150.5 | 8.7 | – / – | 82 | 9.4 | – | – | |
| Bauru | 73.2 | 66.8 | 73.8 | 78.9 | 6.4 | 8.7 | 12.3 | 13.8 | 77 | – | |||||||||
| 16/08, 00:30View analysis ↗ | Uruguay Liga Women | Club Yale Women | 45.6 | 85.2 | 52.2 | 72.2 | 6.2 | 7.2 | 8.3 | 9.4 | 119.3 | 125.5 | 6.2 | – / – | 55 | 3.9 | – | – | |
| Lagomar (W) | 60.6 | 57 | 56.2 | 58 | 5.6 | 6.6 | 7.9 | 8.6 | 64 | – | |||||||||
| 16/08, 01:30View analysis ↗ | Uruguay Liga Women | Aguada (W) | 69.8 | 67.2 | 74 | 70 | 7.2 | 7 | 12.6 | 13 | 139.1 | 139 | 0.1 | – / – | 70 | 4.3 | – | – | |
| Urunday Universitario (W) | 69 | 63.6 | 67.3 | 66.9 | 8.6 | 7 | 12.2 | 11.9 | 69 | – | |||||||||
| 16/08, 02:30View analysis ↗ | Chile LNB | Espanol Osorno | 82.8 | 82 | 85.2 | 83.4 | 7.1 | 7.4 | 15.2 | 13.6 | 168.5 | 160 | 8.45 | 80% / 20% | 84 | 8.6 | – | – | |
| Las Animas | 83.8 | 83.4 | 85.6 | 82.7 | 8.1 | 7.3 | 19.4 | 14.6 | 85 | – |
Frequently asked questions
What does Over/Under points mean?
It is the game's total points against a line. Cross each team's pace and recent points for/against.
How does BetsTalent calculate probabilities?
With an in-house model: opponent-adjusted Elo and, in football, Poisson/Dixon-Coles with per-team attack and defence. In tennis, Elo by surface. No raw averages.