Norway football continues to grow in competitiveness and talent. The Division 2 provides a platform where tactical approaches and squad depth are tested. We evaluate fixtures using structured data and observable performance trends. This helps build a clearer picture of how teams perform over time.
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 18 | ||||
| Sandviken Eik-Tonsberg 2026-09-05 |
DDLLW
LLLLL |
1 DNB | 2:0 |
84.98%
|
| Mjondalen Jerv 2026-09-05 |
LLWWL
WDWLL |
X2 | 0:3 |
65%
|
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 17 | ||||
| Bjarg Mjondalen 2026-08-30 |
WDLWL
LWWLW |
1 DNB | 1:0 |
54.98%
|
| Eik-Tonsberg Sotra 2026-08-30 |
LLLLL
WWWL |
2 | 1:3 |
95.89%
|
| Jerv Pors 2026-08-29 |
DWLL
WDLDW |
1 |
54.08%
|
|
| Round 16 | ||||
| Vidar Arendal 2026-08-15 |
LWL
WLW |
2 DNB |
94.15%
|
|
| Mjondalen Eik-Tonsberg 2026-08-15 |
WLW
LLL |
1 |
73.1%
|
|
| Lysekloster Kvik Halden 2026-08-15 |
LLW
LWL |
2 DNB |
79.14%
|
|
| Notodden Brattvag 2026-08-15 |
WWW
WDL |
1X |
85.34%
|
|
Our methodology
Our system generates Division 2 predictions through data analysis and performance tracking. Linear Regression forms part of the framework used to analyze match data. Metrics such as goals scored, goals conceded, and team form are central to the analysis. This provides a structured and objective view of each matchup.
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