The football environment in Poland reflects steady growth in quality and depth. The Division 1 is widely recognized for the level of competition it consistently delivers. We analyze team performance using a combination of form, trends, and match data. As the season progresses, trends begin to define team strengths and weaknesses.
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 33 | ||||
| Puszcza LKS Lodz 2026-05-18 |
DWDWL
DWWWL |
X2 | 1:0 |
69.71%
|
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 32 | ||||
| Odra Opole Grodzisk M. 2026-05-11 |
LLDWW
LLDLL |
1X | 3:1 |
66.08%
|
| Slask Wroclaw LKS Lodz 2026-05-11 |
WWDWW
WWWLW |
X2 | 2:2 |
60.93%
|
| Pruszkow Polonia Bytom 2026-05-09 |
LDDLW
WWLLD |
X2 | 1:4 |
61.46%
|
| Stal Mielec Puszcza 2026-05-09 |
LLLWW
WDWLW |
1X | 1:1 |
52.5%
|
| Wieczysta Krakow Legnica 2026-05-09 |
WWWDW
WLLWD |
1X | 0:1 |
91.46%
|
| Wisla Chrobry Glogow 2026-05-08 |
WDDDW
WLWLD |
1 | 2:0 |
59.27%
|
| Round 31 | ||||
| Polonia Bytom Polonia Warszawa 2026-05-04 |
WLLDD
WWLL |
1X | 3:2 |
65.39%
|
| Ruch Chorzow Odra Opole 2026-05-03 |
DDLD
LDWWD |
1 DNB | 2:0 |
59.6%
|
| Chrobry Glogow Tychy 2026-05-03 |
LWLD
LWWLD |
1X | 3:2 |
76.46%
|
| S. Rzeszow Wisla 2026-05-03 |
LLLLW
DDDW |
2 DNB | 1:2 |
80.92%
|
| Grodzisk M. Wieczysta Krakow 2026-05-02 |
DLL
WWDWL |
2 DNB | 1:4 |
58.26%
|
| Legnica Stal Mielec 2026-05-02 |
LLWD
LLWW |
X2 | 1:0 |
92.02%
|
| LKS Lodz Pogon Siedlce 2026-05-02 |
WLWDD
WWLLL |
Handicap 2 (0:2) | 4:0 |
50.69%
|
| Puszcza Pruszkow 2026-05-01 |
DWLW
DDLW |
X2 | 1:0 |
54.16%
|
| Leczna Slask Wroclaw 2026-05-01 |
DWWLW
WDWWD |
2 DNB | 0:4 |
65.57%
|
Our methodology
Our Division 1 predictions are built using a data-driven approach based on statistical modeling. Techniques such as Linear Regression help capture underlying trends in match data. Key variables include goal-scoring efficiency, defensive strength, and recent form. The result is a more consistent and data-backed match analysis.
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