The standard of football in Belarus keeps improving year after year. The Vysshaya Liga continues to attract interest for its competitive balance and structure. We focus on relevant data points to help you understand how teams are performing.
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 7 | ||||
| Naftan BATE 2026-05-10 |
LDLLL
LWLLW |
X2 |
92.55%
|
|
| ML Vitebsk Dnepr Mogilev 2026-05-10 |
WLDWL
DLDWL |
1 |
68.04%
|
|
| Dynamo Brest Din. Minsk 2026-05-10 |
WDWWL
LWWDW |
X2 |
88.65%
|
|
| Slavia Mozyr FC Minsk 2026-05-09 |
DLDLL
WWLLW |
X2 | 1:2 |
68.74%
|
| Belshina Vitebsk 2026-05-09 |
LLLLL
DDWWL |
2 DNB | 1:0 |
90.02%
|
| Zhodino Neman 2026-05-09 |
DDDLW
WDWWW |
X2 | 1:0 |
84.69%
|
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 6 | ||||
| Vitebsk Slavia Mozyr 2026-05-03 |
DWWL
LDLLD |
1X | 0:0 |
63.8%
|
| BATE Dynamo Brest 2026-05-03 |
WLLWL
DWWLL |
Handicap 1 (2:0) | 0:3 |
85.99%
|
| Din. Minsk ML Vitebsk 2026-05-03 |
WWDWW
LDWLW |
1X | 2:3 |
74.4%
|
| Dnepr Mogilev Baranovici 2026-05-02 |
LDWLD
LLLLL |
1 DNB | 0:0 |
97.5%
|
| Neman Belshina 2026-05-02 |
DWWWD
LLLLW |
1 | 2:1 |
97.88%
|
| FC Gomel Zhodino 2026-05-02 |
WWWL
DDLWL |
1X | 1:1 |
89.57%
|
| Arsenal Dzerzhinsk Isloch 2026-05-01 |
DWDWD
WDLDW |
X2 | 2:2 |
67.62%
|
| FC Minsk Naftan 2026-05-01 |
WLLWD
DLLLD |
1 | 4:2 |
89.09%
|
| Round 5 | ||||
| Isloch Dnepr Mogilev 2026-04-26 |
DLDWL
DWLD |
1 DNB | 2:1 |
74.32%
|
| Belshina FC Gomel 2026-04-26 |
LLLW
WWL |
2 | 0:2 |
95.89%
|
| Zhodino Arsenal Dzerzhinsk 2026-04-26 |
DLWLL
WDWDL |
1 | 3:3 |
67.42%
|
| Naftan Vitebsk 2026-04-25 |
LLLD
WWL |
2 DNB | 1:1 |
93.7%
|
| Baranovici Din. Minsk 2026-04-25 |
LLLL
DWWWW |
2 | 2:3 |
99.11%
|
| ML Vitebsk Dynamo Brest 2026-04-25 |
WLWDW
WWLLL |
1 | 0:0 |
95.06%
|
| Slavia Mozyr Neman 2026-04-24 |
LLDW
WWWDW |
X2 | 0:0 |
95.48%
|
| FC Minsk BATE 2026-04-24 |
LLWD
LWLW |
X2 | 1:0 |
76.85%
|
Our methodology
Our system generates Vysshaya Liga predictions through data analysis and performance tracking. Linear Regression forms part of the framework used to analyze match data. We analyze factors such as scoring trends, defensive records, and match consistency. This helps present each match from a data-informed perspective.
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