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1. Division

1. Division

Danimarca  · Season 2026/27
2026/27 2025/26
50.00%
1X2 accuracy · 14 predictions (3 months)
Matchday 1 of 22 5%

League Table

12 Teams
# Team P W D L GF–GA GD Pts Form
1 FC Fredericia — Champion 1 1 0 0 3–0 +3 3
V
2 Aarhus Fremad 1 1 0 0 2–1 +1 3
V
3 Aalborg 1 1 0 0 1–0 +1 3
V
4 Vejle 1 0 1 0 2–2 +0 1
P
5 Hvidovre 1 0 1 0 2–2 +0 1
P
6 AB Copenhagen 1 0 1 0 2–2 +0 1
P
7 Vendsyssel FF 1 0 1 0 2–2 +0 1
P
8 Esbjerg 1 0 1 0 1–1 +0 1
P
9 Kolding IF 1 0 1 0 1–1 +0 1
P
10 Hobro 1 0 0 1 1–2 -1 0
S
11 Hillerød 1 0 0 1 0–1 -1 0
S
12 HB Koge 1 0 0 1 0–3 -3 0
S
1 FC Fredericia — Champion 1 1 0 0 3–0 +3 3
V
2 Aalborg 1 1 0 0 1–0 +1 3
V
3 Vejle 1 0 1 0 2–2 +0 1
P
4 Hvidovre 1 0 1 0 2–2 +0 1
P
5 Esbjerg 1 0 1 0 1–1 +0 1
P
6 Hobro 1 0 0 1 1–2 -1 0
S
1 Aarhus Fremad — Champion 1 1 0 0 2–1 +1 3
V
2 AB Copenhagen 1 0 1 0 2–2 +0 1
P
3 Vendsyssel FF 1 0 1 0 2–2 +0 1
P
4 Kolding IF 1 0 1 0 1–1 +0 1
P
5 Hillerød 1 0 0 1 0–1 -1 0
S
6 HB Koge 1 0 0 1 0–3 -3 0
S
Champion

End of season projections

Monte Carlo simulation · 10,000 simulated seasons · updated 29 Jul 2026
Champion
# Team Zone probability Projected Pts Schedule Trend
1 FC Fredericia
36 (9–62)
pos. ~3.9°
C10 · T11
ELO 1503
▼0%
2 Aarhus Fremad
36 (14–58)
pos. ~3.7°
C11 · T10
ELO 1496
▲0%
3 Aalborg
32 (13–55)
pos. ~5.5°
C10 · T11
ELO 1499
▲1%
4 Vejle
27 (7–51)
pos. ~8.0°
C10 · T11
ELO 1507
▲0%
5 Hvidovre
29 (7–55)
pos. ~7.0°
C10 · T11
ELO 1500
▼0%
6 AB Copenhagen
31 (8–53)
pos. ~6.4°
C11 · T10
ELO 1503
▲0%
7 Vendsyssel FF
31 (10–52)
pos. ~6.4°
C11 · T10
ELO 1500
·
8 Esbjerg
31 (10–56)
pos. ~6.2°
C10 · T11
ELO 1498
▼0%
9 Kolding IF
29 (7–50)
pos. ~7.3°
C11 · T10
ELO 1501
▼0%
10 Hobro
28 (8–51)
pos. ~7.8°
C10 · T11
ELO 1499
·
11 Hillerød
28 (7–49)
pos. ~7.7°
C11 · T10
ELO 1500
▲0%
12 HB Koge
27 (7–49)
pos. ~8.2°
C11 · T10
ELO 1503
▼0%
% = probability of reaching that zone or better. Each sparkline shows the trend of the most relevant probability for each team over the last 12 daily simulations.

Model & advanced data

Model calibration for this league
Probability band Sample Expected (mid) Actual Δ
50–60%% 3 55.00% 0.0% -55.00%
60–70%% 6 65.00% 50.0% -15.00%
70–100%% 10 85.00% 80.0% -5.00%
Based on 19 verified predictions · Δ ≤ 5% = excellent calibration
Frequently Asked Questions
What predictions are available for 1. Division?
For 1. Division, ForzaPitch provides 1X2 win probabilities, expected goals (xG), Over 1.5 and Over 2.5 signals and season projections for title, European qualification and relegation per team.
How accurate are predictions for 1. Division?
Accuracy for 1. Division is tracked match by match and shown on this page. The model is calibrated specifically for 1. Division using per-league historical data.
How are 1. Division season projections calculated?
Season projections use 10,000 Monte Carlo simulations of the remaining fixtures, sampling from match probability distributions to estimate title, Champions League, Europa League and relegation probabilities per team.