The football environment in Sweden reflects steady growth in quality and depth. Within this structure, the Division 1 delivers regular high-level matchups. Each prediction is built around form, consistency, and key statistical indicators. Across the season, these patterns reveal consistency and performance levels.
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 21 | ||||
| Umea FC Stockholm Internazionale 2026-09-13 |
WWDLL
WWLWW |
2 |
90.57%
|
|
| AFC Eskilstuna Pitea 2026-09-13 |
WWWLW
WLDLD |
1 |
95.26%
|
|
| Karlbergs Arlanda 2026-09-12 |
LDLWW
LWWLL |
1X | 1:0 |
87.11%
|
| FBK Karlstad Vasalund 2026-09-12 |
WWLWW
LLWLD |
X2 | 2:1 |
50%
|
| Gefle Jarfalla 2026-09-12 |
LDWWL
LLLLL |
1 DNB | 3:1 |
98.47%
|
| Stocksund Karlstad 2026-09-12 |
LLLLW
LDLLL |
2 DNB | 2:1 |
72.63%
|
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 20 | ||||
| Vasalund Enkoping SK 2026-09-06 |
LWLDW
LDLLW |
1 DNB | 2:3 |
88.76%
|
| Arlanda Umea FC 2026-09-06 |
WWLLD
WDLLL |
1 DNB | 1:2 |
67.56%
|
| Pitea Karlbergs 2026-09-06 |
LDLDD
DLWWL |
X2 | 3:0 |
94.44%
|
| Stockholm Internazionale Hammarby TFF 2026-09-05 |
WLWWL
DDLDW |
1X | 3:0 |
59.34%
|
| Jarfalla FBK Karlstad 2026-09-05 |
LLLLL
WLWWD |
X2 | 0:3 |
96.66%
|
| Karlstad AFC Eskilstuna 2026-09-05 |
DLLLW
WWLWW |
Handicap 2 (0:2) | 1:2 |
93.16%
|
| Sollentuna Gefle 2026-09-05 |
LWLWL
DWWLW |
X2 | 1:0 |
91.12%
|
| Round 19 | ||||
| Hammarby TFF Karlbergs 2026-08-31 |
DLDW
LWWLW |
Handicap 2 (0:2) | 0:0 |
76.6%
|
| Enkoping SK Stockholm Internazionale 2026-08-30 |
DLLWL
LWWLW |
2 | 0:3 |
78.58%
|
| FBK Karlstad Pitea 2026-08-30 |
LWWDL
DLDDL |
1 | 4:3 |
82.25%
|
| Umea FC Vasalund 2026-08-30 |
DLLL
WLDWD |
X2 | 3:2 |
90.89%
|
| AFC Eskilstuna Sollentuna 2026-08-29 |
WLWWW
WLWLD |
1 DNB | 2:1 |
93.09%
|
| Gefle Karlstad 2026-08-29 |
WWLW
LLLWW |
1X | 2:2 |
90.06%
|
| Jarfalla Assyriska FF 2026-08-29 |
LLLL
LWWW |
X2 | 0:2 |
99.77%
|
| Stocksund Arlanda 2026-08-29 |
LLWL
WLLDL |
X2 | 2:3 |
54.98%
|
Our methodology
Our approach to Division 1 predictions relies on statistical models and performance data. We rely on established statistical methods like Linear Regression for evaluation. We evaluate performance using a combination of offensive and defensive data. This helps present each match from a data-informed perspective.
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