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2006-07 Superliga Season

198 games

Final

Champion

FC Copenhagen

76 points · 6th Title

Last Title: 2005-06

Relegated

Silkeborg

22 pts

Vejle BK · 25 pts

Biggest Overachiever

FC Copenhagen

11.48 points above expected

76 points · 64.52 expected points

Biggest Disappointment

Silkeborg

9.74 points below expected

22 points · 31.74 expected points

League Table

The final standings for the season. vsSim shows actual points minus the simulation's mean — positive means the team overachieved against the model, negative means they underperformed.

# Team GP W D L Pts GF GA GD SimPts vsSim
1 FC Copenhagen Champion 33 23 7 3 76 60 23 +37 64.52 +11.48
2 Midtjylland 33 18 9 6 63 58 39 +19 54.31 +8.69
3 Aalborg 33 18 7 8 61 55 35 +20 51.36 +9.64
4 Odense 33 17 7 9 58 46 36 +10 54.37 +3.63
5 Nordsjaelland 33 16 9 8 57 67 39 +28 51.52 +5.48
6 Brondby 33 13 10 10 49 50 38 +12 53.81 -4.81
7 Esbjerg 33 10 10 13 40 46 51 -5 45.08 -5.08
8 Randers 33 10 8 15 38 41 53 -12 36.55 +1.45
9 Viborg 33 8 5 20 29 34 64 -30 37.66 -8.66
10 Horsens 33 6 10 17 28 29 53 -24 36.03 -8.03
11 Vejle BK Relegated 33 6 7 20 25 35 64 -29 28.98 -3.98
12 Silkeborg Relegated 33 5 7 21 22 34 60 -26 31.74 -9.74

Going into Phase 2, the championship group halved its Phase 1 points (rounded up); the relegation group kept its full Phase 1 points. Each group then played its own round-robin to determine final standings.

Form

Each team's 5-game rolling points-per-game across the season. Hot streaks push above the dashed 1.5 PPG reference line; cold spells drop below. Each team gets a distinct color; the legend below the plot lets you read off which line is which. (First 4 games of each team have no rolling window, so the lines start at game 5.)

League Race

Cumulative points across the season for each team. Highlighted teams are drawn in color (top finishers for the Title Race, bottom finishers for the Relegation Race); the rest of the league appears in light gray as context. Switch views with the buttons below.

Season Summary

Every team's regular-season finish compared against 100,000 simulations. Click any column header to sort. Luck is the team's actual points minus the sim's mean — positive means the team beat the model. Percentile is where the actual result fell in the team's sim distribution (e.g. 90% = the team did this well or better in only 10% of sims).

Team Elo Points Avg Luck Percentile Min 5th Q1 Median Q3 95th Max
FC Copenhagen 1825 76 64.52 +11.48 95.9% 40 53 60 65 69 76 89
Nordsjaelland 1738 57 51.52 +5.48 79.1% 25 40 47 51 56 64 79
Aalborg 1718 61 51.36 +9.64 92.0% 26 39 46 51 56 63 79
Midtjylland 1712 63 54.31 +8.69 89.8% 26 42 49 54 59 66 81
Odense 1682 58 54.37 +3.63 70.9% 28 42 49 54 59 67 80
Brondby 1663 49 53.81 -4.81 28.1% 27 42 49 54 59 66 84
Esbjerg 1593 40 45.08 -5.08 26.2% 19 33 40 45 50 57 73
Randers 1542 38 36.55 +1.45 61.9% 12 25 32 36 41 48 63
Vejle BK 1511 25 28.98 -3.98 31.4% 5 19 24 29 33 40 56
Silkeborg 1509 22 31.74 -9.74 8.2% 9 21 27 32 36 43 59
Viborg 1489 29 37.66 -8.66 11.7% 13 27 33 38 42 49 68
Horsens 1486 28 36.03 -8.03 14.0% 12 25 31 36 41 48 63

Head-to-Head

Each cell shows a team's record in that matchup (row vs column, formatted W-D-L) with the model's expected points on the line below. Navy-tinted cells mean the team beat the model's expectations by more than one point in that matchup; gold-tinted cells mean they fell short by the same margin.

Beat expectations Fell short Within expectations
Team AAL BRO ESB FC HOR MID NOR ODE RAN SIL VB VIB
Aalborg —
2-1-0
3.82
3-0-0
4.70
2-0-1
2.70
2-1-0
5.40
0-0-3
3.67
0-2-1
4.39
1-1-1
4.22
1-1-1
5.80
3-0-0
5.60
2-1-0
5.95
2-0-1
5.11
Brondby
0-1-2
4.42
 —
2-1-0
5.16
0-0-3
2.93
2-1-0
5.74
0-2-1
4.17
2-1-0
4.10
1-1-1
3.78
1-1-1
5.57
1-1-1
6.12
2-0-1
6.25
2-1-0
5.57
Esbjerg
0-0-3
3.56
0-1-2
3.10
 —
1-2-0
2.45
0-2-1
4.93
2-0-1
3.06
1-1-1
3.93
1-1-1
3.30
1-0-2
4.87
2-0-1
5.37
1-1-1
5.74
1-2-0
4.81
FC Copenhagen
1-0-2
5.57
3-0-0
5.33
0-2-1
5.87
 —
3-0-0
6.18
2-1-0
4.96
2-1-0
5.54
1-2-0
5.30
3-0-0
6.58
3-0-0
6.41
2-1-0
6.65
3-0-0
6.18
Horsens
0-1-2
2.86
0-1-2
2.54
1-2-0
3.32
0-0-3
2.16
 —
1-1-1
2.41
0-1-2
2.68
0-0-3
2.83
1-0-2
4.13
2-1-0
4.35
0-2-1
4.78
1-1-1
4.02
Midtjylland
3-0-0
4.56
1-2-0
4.08
1-0-2
5.20
0-1-2
3.28
1-1-1
5.88
 —
1-2-0
4.28
1-1-1
3.78
2-1-0
5.80
3-0-0
5.96
2-1-0
6.03
3-0-0
5.40
Nordsjaelland
1-2-0
3.85
0-1-2
4.14
1-1-1
4.31
0-1-2
2.73
2-1-0
5.59
0-2-1
3.95
 —
2-0-1
3.76
3-0-0
5.45
2-1-0
5.85
2-0-1
6.22
3-0-0
5.67
Odense
1-1-1
4.02
1-1-1
4.45
1-1-1
4.94
0-2-1
2.95
3-0-0
5.44
1-1-1
4.45
1-0-2
4.48
 —
1-1-1
5.81
3-0-0
6.08
3-0-0
5.96
2-0-1
5.87
Randers
1-1-1
2.50
1-1-1
2.70
2-0-1
3.37
0-0-3
1.78
2-0-1
4.10
0-1-2
2.48
0-0-3
2.82
1-1-1
2.48
 —
0-3-0
4.84
2-0-1
5.26
1-1-1
4.10
Silkeborg
0-0-3
2.67
1-1-1
2.19
1-0-2
2.89
0-0-3
1.96
0-1-2
3.89
0-0-3
2.35
0-1-2
2.44
0-0-3
2.23
0-3-0
3.40
 —
2-1-0
4.29
1-0-2
3.45
Vejle BK
0-1-2
2.35
1-0-2
2.08
1-1-1
2.55
0-1-2
1.73
1-2-0
3.46
0-1-2
2.29
1-0-2
2.10
0-0-3
2.36
1-0-2
2.99
0-1-2
3.95
 —
1-0-2
3.21
Viborg
1-0-2
3.14
0-1-2
2.70
0-2-1
3.43
0-0-3
2.16
1-1-1
4.21
0-0-3
2.90
0-0-3
2.61
1-0-2
2.43
1-1-1
4.14
2-0-1
4.80
2-0-1
5.04
 —

Points vs. Goals Scored, Allowed, and Differential

Points plotted against goals scored, allowed, and differential. Use the buttons to switch views; hover a team for exact values. The table gives each fit's R² and slope (the change in points per 10 goals).

Fit Metrics

R² Slope
Scored 0.79 +13.0
Allowed 0.92 -12.9
Differential 0.94 +7.1

Scoreline Distribution

Percentage of games ending with each combination of team-goals (rows) and opponent-goals (columns). The diagonal shows draws; cells below the diagonal are wins from the row team's perspective, cells above are losses. Marginal totals on the right and bottom show how often each goal count occurred regardless of opponent. Use the picker to switch between the league-wide view and any individual team.

↓ Scored | Allowed →012345+Total
05.56%7.58%6.31%3.03%1.77%0.25%24.49%
17.58%13.13%8.59%4.55%1.26%0.51%35.61%
26.31%8.59%4.55%2.27%1.01%0.25%22.98%
33.03%4.55%2.27%1.01%—0.25%11.11%
41.77%1.26%1.01%——0.25%4.29%
5+0.25%0.51%0.25%0.25%0.25%—1.52%
Total24.49%35.61%22.98%11.11%4.29%1.52%100%

Summary Statistics

Scored Allowed Difference
Mean 1.40 1.40 +0.00
SD 1.20 1.20 1.76
CV 0.85 0.85 —
Max 6 6 +5
Min 0 0 -5

Games Played: 198

↓ Scored | Allowed →012345+Total
03.03%9.09%6.06%3.03%3.03%—24.24%
13.03%18.18%3.03%———24.24%
218.18%12.12%————30.30%
3—6.06%3.03%———9.09%
46.06%3.03%————9.09%
5+————3.03%—3.03%
Total30.30%48.48%12.12%3.03%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.67 1.06 +0.61
SD 1.45 1.06 1.84
CV 0.87 1.00 —
Max 6 4 +4
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%9.09%3.03%3.03%——18.18%
13.03%21.21%6.06%6.06%——36.36%
29.09%9.09%3.03%3.03%——24.24%
39.09%6.06%—3.03%——18.18%
43.03%—————3.03%
5+———————
Total27.27%45.45%12.12%15.15%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.52 1.15 +0.36
SD 1.09 1.00 1.67
CV 0.72 0.87 —
Max 4 3 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%3.03%9.09%6.06%——24.24%
16.06%15.15%9.09%6.06%——36.36%
23.03%9.09%6.06%3.03%——21.21%
33.03%3.03%—3.03%—3.03%12.12%
43.03%—3.03%———6.06%
5+———————
Total21.21%30.30%27.27%18.18%—3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.55 -0.15
SD 1.17 1.20 1.66
CV 0.84 0.78 —
Max 4 5 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%—3.03%———12.12%
127.27%6.06%6.06%———39.39%
23.03%6.06%6.06%———15.15%
36.06%15.15%————21.21%
43.03%6.06%3.03%———12.12%
5+———————
Total48.48%33.33%18.18%———100%

Summary Statistics

Scored Allowed Difference
Mean 1.82 0.70 +1.12
SD 1.26 0.77 1.32
CV 0.69 1.10 —
Max 4 2 +4
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%12.12%9.09%3.03%6.06%—42.42%
13.03%9.09%9.09%6.06%3.03%—30.30%
23.03%9.09%9.09%3.03%——24.24%
3—3.03%————3.03%
4———————
5+———————
Total18.18%33.33%27.27%12.12%9.09%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.88 1.61 -0.73
SD 0.89 1.20 1.51
CV 1.02 0.75 —
Max 3 4 +2
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%3.03%—3.03%——9.09%
115.15%12.12%6.06%—3.03%—36.36%
26.06%12.12%12.12%—3.03%—33.33%
33.03%12.12%————15.15%
4—3.03%————3.03%
5+——3.03%———3.03%
Total27.27%42.42%21.21%3.03%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.76 1.18 +0.58
SD 1.12 1.07 1.52
CV 0.64 0.91 —
Max 5 4 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%9.09%3.03%———15.15%
19.09%18.18%6.06%—3.03%—36.36%
23.03%6.06%3.03%3.03%——15.15%
36.06%—3.03%3.03%——12.12%
43.03%3.03%3.03%———9.09%
5+3.03%6.06%—3.03%——12.12%
Total27.27%42.42%18.18%9.09%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.03 1.18 +0.85
SD 1.69 1.04 1.95
CV 0.83 0.88 —
Max 6 4 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%3.03%3.03%——18.18%
112.12%12.12%6.06%3.03%——33.33%
215.15%15.15%3.03%3.03%3.03%—39.39%
3—6.06%3.03%———9.09%
4———————
5+———————
Total33.33%39.39%15.15%9.09%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.09 +0.30
SD 0.90 1.07 1.38
CV 0.65 0.98 —
Max 3 4 +2
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%6.06%3.03%3.03%—3.03%24.24%
13.03%15.15%18.18%3.03%—3.03%42.42%
26.06%9.09%—3.03%3.03%—21.21%
3—3.03%6.06%———9.09%
43.03%—————3.03%
5+———————
Total21.21%33.33%27.27%9.09%3.03%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.24 1.61 -0.36
SD 1.03 1.43 1.85
CV 0.83 0.89 —
Max 4 6 +4
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%15.15%12.12%———33.33%
1—15.15%15.15%12.12%3.03%3.03%48.48%
23.03%3.03%————6.06%
33.03%—3.03%———6.06%
4——3.03%——3.03%6.06%
5+———————
Total12.12%33.33%33.33%12.12%3.03%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.03 1.82 -0.79
SD 1.10 1.36 1.47
CV 1.07 0.75 —
Max 4 6 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%9.09%9.09%6.06%9.09%—39.39%
13.03%6.06%15.15%3.03%——27.27%
23.03%3.03%6.06%3.03%3.03%3.03%21.21%
36.06%—3.03%3.03%——12.12%
4———————
5+———————
Total18.18%18.18%33.33%15.15%12.12%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.94 -0.88
SD 1.06 1.37 1.80
CV 1.00 0.71 —
Max 3 5 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
0—9.09%15.15%6.06%3.03%—33.33%
16.06%9.09%3.03%15.15%3.03%—36.36%
23.03%9.09%6.06%6.06%——24.24%
3——6.06%———6.06%
4———————
5+———————
Total9.09%27.27%30.30%27.27%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.03 1.94 -0.91
SD 0.92 1.09 1.51
CV 0.89 0.56 —
Max 3 4 +2
Min 0 0 -4

Games Played: 33

Home-Field Advantage Edge

The simulation applies the same home-field boost to every game across the league, so the per-game home win probabilities bake in the model's idea of HFA. For each team, we sum expected points at home and compare to actual home points, and the same on the road. The bar shows (home points above expected) minus (away points above expected). A tall positive bar means the team's home/road split exceeded what the model predicted — a real fortress effect. A tall negative bar means the reverse: they played worse at home or better on the road than expected.

Top Overachievers & Disappointments

Teams that most beat — or most fell short of — their simulated point projections. A positive vsSim means the team accumulated more points than the model expected on average; a negative one means fewer.

Biggest Overachievers

# Team Actual Sim vsSim
1 FC Copenhagen 76 64.52 +11.48
2 Aalborg 61 51.36 +9.64
3 Midtjylland 63 54.31 +8.69
4 Nordsjaelland 57 51.52 +5.48
5 Odense 58 54.37 +3.63

Biggest Disappointments

# Team Actual Sim vsSim
1 Silkeborg 22 31.74 -9.74
2 Viborg 29 37.66 -8.66
3 Horsens 28 36.03 -8.03
4 Esbjerg 40 45.08 -5.08
5 Brondby 49 53.81 -4.81

Top Streaks

Ranked by model unlikelihood — the product of pregame W/D/L probabilities over the games in each team's streak. A short streak by a poor team can outrank a longer one by a strong team since the poor team's per-game probabilities were lower going in. Unbeaten counts W or D consecutively; Winless counts L or D consecutively.

Most Unlikely Winning Streaks

# Team Games Dates Probability
1 Midtjylland 6 Oct 15 – Nov 12 1 in 153
2 Esbjerg 2 May 24 – May 27 1 in 65
3 FC Copenhagen 7 Mar 31 – Apr 29 1 in 39
4 Odense 4 Aug 20 – Sep 17 1 in 35
5 Vejle BK 2 Oct 22 – Oct 25 1 in 31

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Vejle BK 9 Jul 19 – Sep 16 1 in 466
2 Silkeborg 7 Oct 22 – Mar 11 1 in 86
3 Odense 3 May 20 – May 27 1 in 61
4 Nordsjaelland 3 Oct 22 – Oct 28 1 in 48
5 Viborg 5 Apr 18 – May 9 1 in 31

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 FC Copenhagen 21 Sep 9 – Apr 29 1 in 124
2 Midtjylland 13 Oct 1 – Apr 5 1 in 96
3 Odense 10 Aug 2 – Oct 15 1 in 44
4 Aalborg 9 Apr 9 – May 19 1 in 32
5 Brondby 9 Jul 19 – Sep 24 1 in 18

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Brondby 8 Sep 24 – Nov 5 1 in 96
2 Esbjerg 10 Nov 19 – Apr 29 1 in 80
3 Vejle BK 12 Jul 19 – Oct 15 1 in 28
4 Silkeborg 11 Sep 24 – Mar 11 1 in 16
5 Aalborg 4 Sep 9 – Sep 30 1 in 13

Finish Position Heatmap

Each cell is the probability — across 100,000 simulations — that the team (row) finished at that position (column). Rows are sorted by actual finish (champion at top, bottom of the table at the bottom).

Team123456789101112
FC Copenhagen62.66%19.49%9.41%4.76%2.27%0.95%0.29%0.14%0.03%———
Midtjylland9.00%19.13%18.61%17.44%13.72%10.96%6.43%2.87%1.14%0.52%0.15%0.03%
Aalborg4.59%11.75%14.60%16.15%17.10%15.37%10.35%5.78%2.59%1.24%0.41%0.07%
Odense9.58%17.65%17.99%16.67%14.33%11.79%7.12%2.94%1.27%0.42%0.20%0.04%
Nordsjaelland5.42%12.03%14.81%16.51%16.55%14.78%10.58%5.42%2.62%0.87%0.32%0.09%
Brondby7.86%16.93%17.71%16.75%15.64%11.97%7.69%3.37%1.31%0.59%0.13%0.05%
Esbjerg0.79%2.47%5.07%7.79%11.51%17.14%21.88%15.14%9.24%5.45%2.57%0.95%
Randers0.01%0.19%0.55%1.09%2.31%4.84%10.04%17.43%20.36%19.12%15.35%8.71%
Viborg0.05%0.24%0.70%1.48%3.29%5.60%10.87%18.97%19.71%17.95%13.65%7.49%
Horsens0.04%0.12%0.39%1.05%2.14%4.49%8.86%15.81%19.11%20.22%17.44%10.33%
Vejle BK——0.03%0.10%0.29%0.63%1.95%4.64%8.89%14.50%23.93%45.04%
Silkeborg——0.13%0.21%0.85%1.48%3.94%7.49%13.73%19.12%25.85%27.20%

Points Required Per Position

The empirical CDF of simulated point totals per finishing position. Each curve shows, for one position (1st, 2nd, ..., last), the spread of point totals teams accumulated across simulations. Reading the curve at the 50% mark gives the median points typically needed to finish at that position. Steep curves mean the position is tightly clustered around a particular point range; shallow curves mean the position came with a wide variety of point totals.

Points Totals in Context

How did each team's actual results compare to their simulated points, Elo rating, average opponent Elo, and percentile within simulated outcomes? Use the buttons to switch between views. In each chart, dashed crosshairs at the league means split the plot into four quadrants: pastel green (team did well, model agreed), pastel red (team did poorly, model agreed), and pastel yellow (model and reality disagreed).

Season Trends

How each metric evolved across the season - Elo rating, actual and projected points, title/promotion probability, and relegation probability - day by day.

Edges & Scoring

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Home Edge
Share of matches won by the home team minus the share won by the away team.
No Edge: under 5% * Slight Edge: 5% to 15% * Clear Edge: 15% to 25% * Strong Edge: 25% and up.
Elo Value
Number of Elo rating points one goal is worth. A team this many Elo points better than another is expected to win by one goal on a neutral field.
Scoring Tilt
Average home goals minus average away goals per match. The gold line is the home goals edge implied by the scoring value of an Elo point and the home-field Elo bonus.
Road-Tilted: under -0.2 * Neutral: -0.2 to 0.5 * Home-Tilted: 0.5 to 1.2 * Strong Home: 1.2 and up.
Home Edge
HomeDrawAway
+10.10%
Slight Edge
42.93%24.24%32.83%
Elo Value
Home Edge: 35.21 Elo pts.
205 Elo
0.005 goals per Elo point
0600
Scoring Tilt
Expected
+0.20 goals
Neutral
-2+0.17+2

Title Race

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Title-Race Openness
Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 4 * Open: 4 to 6 * Wide Open: 6 and up.
Champion Preseason Odds
Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd * Middle of the Pack: 3rd to 6th * Longshot: 7th or lower.
Title Margin
Points-per-game gap between the champion and the runner-up. Shown per game so it reads the same across long and short seasons. The gold line is the winning margin the model expected, so a dot to the right means a more one-sided race than projected. A title won on goal difference shows 0.00.
Photo Finish: under 0.15 * Tight Race: 0.15 to 0.4 * Comfortable: 0.4 to 0.75 * Runaway: 0.75 and up.
Title-Race Openness
2.4
Top-Heavy
124610
Champion Preseason Odds
63%
FC Copenhagen, 1st of 12
LongshotFavorite
Title Margin
Expected
0.39/gm
Tight Race
00.190.6/gm

Simulation-Based Surprises

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Luck Spread
Standard deviation of the gap between each team's actual points and their simulated average points. The gold line is the spread the model expected from chance alone.
As Expected: under 5.66 * Some Luck: 5.66 to 8.49 * Lucky: 8.49 to 11.32 * Wild Swing: 11.32 and up.
Average Finish Error
Average gap between where each team was projected to finish and where they actually finished in the table.
Pinpoint: under 1.23 * Close: 1.23 to 1.84 * Off: 1.84 to 2.46 * Way Off: 2.46 and up.
Biggest Overachiever
The team that finished highest inside its own range of simulated outcomes. The gold line is where the top team in a league of 12 typically lands.
Biggest Underachiever
The team that finished lowest inside its own range of simulated outcomes. The gold line is where the bottom team in a league of 12 typically lands.
Season Outliers
Number of teams that finished above the 95th or below the 5th percentile of their own simulated range. Even a well-calibrated model expects about 10% of teams in the extremes.
Minimal Outliers: under 12 * As Expected: 12 to 19.2 * Several Outliers: 19.2 to 26.4 * Many Outliers: 26.4 and up.
Unexpected Relegations
Number of teams that were actually relegated but were not in the model's projected bottom field of the same size. The gold line is how many the model expected to miss on average.
As Expected: under 0.78 * A Surprise: 0.78 to 1.25 * Several Surprises: 1.25 to 1.72 * Many Surprises: 1.72 and up.
Luck Spread
Expected
7.33 points
Some Luck
07.0818
Average Finish Error
Expected
1.00
Pinpoint
01.544
Biggest Overachiever
Expected 95.83%
95.86%
FC Copenhagen
50100
Biggest Underachiever
Expected 4.17%
8.16%
Silkeborg
050
Season Outliers
Expected
1 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
0 of 2
As Expected
00.82

Parity

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Gini Index
How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.
Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully
How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge
Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst
Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts
Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.21
Top-Heavy
00.120.180.260.5
Noll-Scully
Coin-flip
2.04
Strong Separation
01.003
Interquartile Edge
76%
Clear Edge
50%60%70%80%100%
Best vs. Worst
Baseline
88%
Strong Edge
50%91%100%
Close Games
Expected
61%
Very Frequent
0%61%100%
Blowouts
Expected
14%
Frequent
0%16%100%

Predictability

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Brier Score
How close the pregame probabilities landed to the actual result, averaged over the season. Confident, correct calls are rewarded most; confident misses are punished most. Lower is better; since draws are possible, a score under 0.66 beats guessing the base rate.
Highly Predictable: under 0.56 * Predictable: 0.56 to 0.62 * Hard to Predict: 0.62 to 0.66 * Coin-Flip: 0.66 and up.
Matchup Imbalance
How lopsided the matchups were on paper, averaging the gap between the two win probabilities over their sum. 0 means every match was a toss-up; 1 means every match was a heavy favorite against a big underdog.
Very Even: under 0.1 * Slight Separation: 0.1 to 0.18 * Notable Separation: 0.18 to 0.28 * Lopsided: 0.28 and up.
Strangeness
How wild the final table was versus what the model expected. A value of 1 means teams landed about one standard deviation from their projections on average. Above 1 is a stranger season; below 1 hugged the projections.
Very Predictable: under 0.8 * As Expected: 0.8 to 1.1 * Wilder Than Modeled: 1.1 to 1.4 * Chaotic: 1.4 and up.
Repeatability
How closely the final table order matched the preseason Elo order, by Spearman rank correlation. Higher means last season's ratings strongly predicted this season's finish. Shows N/A for an inaugural season.
Weak Carryover: under 0.3 * Some Carryover: 0.3 to 0.6 * Strong Carryover: 0.6 to 0.85 * Near-Lock: 0.85 and up.
Upset Rate
Share of matches the underdog won. The gold line is how often the model expected underdogs to win; a dot to the right means upsets ran hotter than expected.
Chalky: under 25% * As Expected: 25% to 33% * Upset-Prone: 33% to 42% * Very Upset-Prone: 42% and up.
Clear Favorite Upset Rate
Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 15% * As Expected: 15% to 25% * Shaky Favorites: 25% to 35% * Very Shaky: 35% and up.
Brier Score
Expected
0.58
Predictable
00.602
Matchup Imbalance
0.36
Lopsided
00.10.180.280.5
Strangeness
Expected
1.08
As Expected
01.002
Repeatability
0.64
Strong Carryover
00.30.60.851
Upset Rate
Expected
21%
Chalky
0%24%50%
Clear Favorite Upset Rate
Expected
18%
As Expected
0%21%50%

Calibration

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Probability calibration
An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope
Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE)
The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.12 * Near Noise Ceiling: 0.12 to 0.18 * Above Noise: 0.18 to 0.23 * Well Above Noise: 0.23 and up.
Probability calibration
0.90
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.12
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.071
Well Within Noise
00.1170.3

Next-Season Status

Across 100,000 regular-season simulations, the probability of each team's next-season status. Columns appear in best-to-worst outcome order: promotion-positive on the left, relegation-positive on the right. Cells with darker shading indicate higher likelihood.

Team Same level Direct relegation
FC Copenhagen 100% —
Brondby 99.82% 0.18%
Midtjylland 99.82% 0.18%
Odense 99.76% 0.24%
Nordsjaelland 99.59% 0.41%
Aalborg 99.52% 0.48%
Esbjerg 96.48% 3.52%
Viborg 78.86% 21.14%
Randers 75.94% 24.06%
Horsens 72.23% 27.77%
Silkeborg 46.95% 53.05%
Vejle BK 31.03% 68.97%

Overall Game Log

Summary of every completed game this season. Sort any column by clicking its header.

Date Opponent Score Pre Elo Opp Elo Win % Tie % Loss % Elo Δ Points
2006-07-19 FC Copenhagen L 0-1 1592 1695 28.09% 25.33% 46.58% -8.1 0
2006-07-19 @ Horsens W 1-0 1695 1592 46.58% 25.33% 28.09% +8.1 3
2006-07-19 Midtjylland D 1-1 1665 1620 48.06% 25.20% 26.74% -1.2 1
2006-07-19 @ Odense D 1-1 1620 1665 26.74% 25.20% 48.06% +1.2 1
2006-07-19 Randers W 5-0 1595 1534 50.16% 24.97% 24.87% +32.3 3
2006-07-19 @ Nordsjaelland L 0-5 1534 1595 24.87% 24.97% 50.16% -32.3 0
2006-07-19 Silkeborg W 2-1 1630 1591 47.24% 25.28% 27.49% +7.5 3
2006-07-19 @ Esbjerg L 1-2 1591 1630 27.49% 25.28% 47.24% -7.5 0
2006-07-19 Vejle BK W 2-1 1675 1576 54.64% 24.31% 21.05% +6.0 3
2006-07-19 @ Brondby L 1-2 1576 1675 21.05% 24.31% 54.64% -6.0 0
2006-07-19 Viborg W 3-1 1645 1651 41.27% 25.64% 33.09% +15.1 3
2006-07-19 @ Aalborg L 1-3 1651 1645 33.09% 25.64% 41.27% -15.0 0
2006-07-22 FC Copenhagen L 1-4 1584 1703 26.24% 25.14% 48.61% -17.7 0
2006-07-22 @ Silkeborg W 4-1 1703 1584 48.61% 25.14% 26.24% +17.7 6
2006-07-23 Aalborg L 1-2 1637 1660 38.86% 25.69% 35.44% -9.8 3
2006-07-23 @ Esbjerg W 2-1 1660 1637 35.44% 25.69% 38.86% +9.8 6
2006-07-23 Horsens W 1-0 1501 1584 30.73% 25.53% 43.74% +11.4 3
2006-07-23 @ Randers L 0-1 1584 1501 43.74% 25.53% 30.73% -11.4 0
2006-07-23 Midtjylland L 0-1 1636 1621 44.16% 25.50% 30.34% -11.5 0
2006-07-23 @ Viborg W 1-0 1621 1636 30.34% 25.50% 44.16% +11.5 4
2006-07-23 Nordsjaelland W 2-1 1681 1627 49.17% 25.08% 25.75% +7.1 6
2006-07-23 @ Brondby L 1-2 1627 1681 25.75% 25.08% 49.17% -7.1 3
2006-07-29 Esbjerg L 0-2 1664 1627 47.00% 25.30% 27.71% -22.8 1
2006-07-29 @ Odense W 2-0 1627 1664 27.71% 25.30% 47.00% +22.8 6
2006-07-30 Brondby D 1-1 1633 1688 34.37% 25.67% 39.96% +0.3 5
2006-07-30 @ Midtjylland D 1-1 1688 1633 39.96% 25.67% 34.37% -0.3 7
2006-07-30 Silkeborg W 1-0 1620 1566 49.23% 25.08% 25.69% +7.5 6
2006-07-30 @ Nordsjaelland L 0-1 1566 1620 25.69% 25.08% 49.23% -7.5 0
2006-07-30 Vejle BK W 4-0 1670 1570 54.79% 24.28% 20.93% +22.6 9
2006-07-30 @ Aalborg L 0-4 1570 1670 20.93% 24.28% 54.79% -22.6 0
2006-07-30 Viborg D 2-2 1572 1625 34.66% 25.68% 39.66% +0.2 1
2006-07-30 @ Horsens D 2-2 1625 1572 39.66% 25.68% 34.66% -0.2 1
2006-08-02 Odense L 1-3 1547 1641 29.25% 25.43% 45.32% -13.7 0
2006-08-02 @ Vejle BK W 3-1 1641 1547 45.32% 25.43% 29.25% +13.7 4
2006-08-05 FC Copenhagen L 1-3 1625 1721 28.97% 25.41% 45.62% -13.6 1
2006-08-05 @ Viborg W 3-1 1721 1625 45.62% 25.41% 28.97% +13.6 9
2006-08-05 Horsens W 3-0 1688 1572 56.42% 23.97% 19.61% +16.3 10
2006-08-05 @ Brondby L 0-3 1572 1688 19.61% 23.97% 56.42% -16.3 1
2006-08-06 Aalborg L 0-2 1559 1693 24.63% 24.94% 50.44% -13.7 0
2006-08-06 @ Silkeborg W 2-0 1693 1559 50.44% 24.94% 24.63% +13.7 12
2006-08-06 Midtjylland L 2-5 1533 1633 28.53% 25.37% 46.10% -16.4 0
2006-08-06 @ Vejle BK W 5-2 1633 1533 46.10% 25.37% 28.53% +16.4 8
2006-08-06 Nordsjaelland L 3-5 1650 1628 45.16% 25.44% 29.40% -16.2 6
2006-08-06 @ Esbjerg W 5-3 1628 1650 29.40% 25.44% 45.16% +16.2 9
2006-08-06 Randers D 1-1 1655 1513 59.25% 23.34% 17.41% -2.4 5
2006-08-06 @ Odense D 1-1 1513 1655 17.41% 23.34% 59.25% +2.4 4
2006-08-12 Aalborg W 1-0 1650 1706 34.11% 25.67% 40.22% +10.7 11
2006-08-12 @ Midtjylland L 0-1 1706 1650 40.22% 25.67% 34.11% -10.7 12
2006-08-13 Brondby D 1-1 1515 1704 19.34% 23.90% 56.76% +2.2 5
2006-08-13 @ Randers D 1-1 1704 1515 56.76% 23.90% 19.34% -2.2 11
2006-08-13 Esbjerg D 1-1 1556 1634 31.28% 25.56% 43.16% +0.6 2
2006-08-13 @ Horsens D 1-1 1634 1556 43.16% 25.56% 31.28% -0.6 7
2006-08-13 Odense D 1-1 1735 1652 52.68% 24.63% 22.69% -1.7 10
2006-08-13 @ FC Copenhagen D 1-1 1652 1735 22.69% 24.63% 52.68% +1.7 6
2006-08-13 Silkeborg L 2-3 1611 1545 50.74% 24.90% 24.36% -11.5 1
2006-08-13 @ Viborg W 3-2 1545 1611 24.36% 24.90% 50.74% +11.5 3
2006-08-13 Vejle BK W 1-0 1644 1517 57.68% 23.70% 18.61% +5.7 12
2006-08-13 @ Nordsjaelland L 0-1 1517 1644 18.61% 23.70% 57.68% -5.7 0
2006-08-19 FC Copenhagen L 0-4 1511 1733 16.70% 23.10% 60.20% -18.3 0
2006-08-19 @ Vejle BK W 4-0 1733 1511 60.20% 23.10% 16.70% +18.3 13
2006-08-20 Horsens L 0-2 1556 1557 42.10% 25.61% 32.30% -20.9 3
2006-08-20 @ Silkeborg W 2-0 1557 1556 32.30% 25.61% 42.10% +20.9 5
2006-08-20 Midtjylland W 4-2 1633 1660 38.33% 25.70% 35.97% +14.3 10
2006-08-20 @ Esbjerg L 2-4 1660 1633 35.97% 25.70% 38.33% -14.3 11
2006-08-20 Nordsjaelland W 2-1 1654 1650 42.72% 25.58% 31.70% +8.4 9
2006-08-20 @ Odense L 1-2 1650 1654 31.70% 25.58% 42.72% -8.4 12
2006-08-20 Randers W 2-1 1696 1517 62.86% 22.36% 14.78% +4.3 15
2006-08-20 @ Aalborg L 1-2 1517 1696 14.78% 22.36% 62.86% -4.3 5
2006-08-20 Viborg W 3-0 1702 1600 54.96% 24.25% 20.79% +17.2 14
2006-08-20 @ Brondby L 0-3 1600 1702 20.79% 24.25% 54.96% -17.2 1
2006-08-27 Aalborg L 0-2 1751 1700 48.88% 25.12% 26.01% -23.6 13
2006-08-27 @ FC Copenhagen W 2-0 1700 1751 26.01% 25.12% 48.88% +23.6 18
2006-08-27 Esbjerg W 3-1 1513 1648 24.56% 24.93% 50.52% +21.0 8
2006-08-27 @ Randers L 1-3 1648 1513 50.52% 24.93% 24.56% -21.0 10
2006-08-27 Odense L 0-2 1578 1662 30.41% 25.51% 44.08% -16.3 5
2006-08-27 @ Horsens W 2-0 1662 1578 44.08% 25.51% 30.41% +16.3 12
2006-08-27 Vejle BK W 1-0 1582 1493 53.52% 24.50% 21.98% +6.6 4
2006-08-27 @ Viborg L 0-1 1493 1582 21.98% 24.50% 53.52% -6.6 0
2006-09-09 Brondby D 1-1 1724 1719 42.77% 25.58% 31.66% -0.6 19
2006-09-09 @ Aalborg D 1-1 1719 1724 31.66% 25.58% 42.77% +0.6 15
2006-09-09 FC Copenhagen D 2-2 1627 1728 28.41% 25.36% 46.23% +0.7 11
2006-09-09 @ Esbjerg D 2-2 1728 1627 46.23% 25.36% 28.41% -0.7 14
2006-09-10 Horsens D 0-0 1641 1561 52.39% 24.67% 22.94% -1.9 13
2006-09-10 @ Nordsjaelland D 0-0 1561 1641 22.94% 24.67% 52.39% +1.8 6
2006-09-10 Midtjylland L 0-2 1536 1646 27.29% 25.26% 47.45% -14.9 3
2006-09-10 @ Silkeborg W 2-0 1646 1536 47.45% 25.26% 27.29% +14.9 14
2006-09-10 Vejle BK W 2-1 1534 1486 48.44% 25.16% 26.40% +7.3 11
2006-09-10 @ Randers L 1-2 1486 1534 26.40% 25.16% 48.44% -7.3 0
2006-09-10 Viborg W 2-0 1679 1589 53.52% 24.49% 21.98% +12.4 15
2006-09-10 @ Odense L 0-2 1589 1679 21.98% 24.49% 53.52% -12.4 4
2006-09-16 Silkeborg L 2-4 1479 1521 36.22% 25.70% 38.08% -14.4 0
2006-09-16 @ Vejle BK W 4-2 1521 1479 38.08% 25.70% 36.22% +14.4 6
2006-09-17 Esbjerg W 2-0 1720 1627 53.81% 24.45% 21.74% +12.3 18
2006-09-17 @ Brondby L 0-2 1627 1720 21.74% 24.45% 53.81% -12.3 11
2006-09-17 Horsens L 1-2 1661 1563 54.47% 24.34% 21.19% -12.9 14
2006-09-17 @ Midtjylland W 2-1 1563 1661 21.19% 24.34% 54.47% +13.0 9
2006-09-17 Nordsjaelland W 1-0 1727 1639 53.30% 24.53% 22.17% +6.6 17
2006-09-17 @ FC Copenhagen L 0-1 1639 1727 22.17% 24.53% 53.30% -6.6 13
2006-09-17 Odense L 0-1 1723 1691 46.42% 25.35% 28.23% -12.0 19
2006-09-17 @ Aalborg W 1-0 1691 1723 28.23% 25.35% 46.42% +12.0 18
2006-09-17 Randers W 3-2 1577 1541 46.86% 25.31% 27.83% +7.2 7
2006-09-17 @ Viborg L 2-3 1541 1577 27.83% 25.31% 46.86% -7.2 11
2006-09-23 Aalborg D 0-0 1576 1711 24.53% 24.92% 50.55% +1.6 10
2006-09-23 @ Horsens D 0-0 1711 1576 50.55% 24.92% 24.53% -1.6 20
2006-09-23 Midtjylland W 2-1 1734 1648 53.06% 24.57% 22.37% +6.3 20
2006-09-23 @ FC Copenhagen L 1-2 1648 1734 22.37% 24.57% 53.06% -6.3 14
2006-09-24 Brondby D 2-2 1703 1732 38.06% 25.70% 36.24% -0.1 19
2006-09-24 @ Odense D 2-2 1732 1703 36.24% 25.70% 38.06% +0.1 19
2006-09-24 Silkeborg D 0-0 1534 1535 41.97% 25.61% 32.42% -0.6 12
2006-09-24 @ Randers D 0-0 1535 1534 32.42% 25.61% 41.97% +0.6 7
2006-09-24 Vejle BK D 3-3 1615 1465 60.12% 23.12% 16.76% -1.6 12
2006-09-24 @ Esbjerg D 3-3 1465 1615 16.76% 23.12% 60.12% +1.6 1
2006-09-24 Viborg W 2-0 1633 1584 48.59% 25.15% 26.27% +14.5 16
2006-09-24 @ Nordsjaelland L 0-2 1584 1633 26.27% 25.15% 48.59% -14.5 7
2006-09-30 Nordsjaelland L 0-3 1709 1647 50.27% 24.96% 24.77% -35.1 20
2006-09-30 @ Aalborg W 3-0 1647 1709 24.77% 24.96% 50.27% +35.1 19
2006-10-01 Brondby W 1-0 1740 1732 43.21% 25.56% 31.23% +8.8 23
2006-10-01 @ FC Copenhagen L 0-1 1732 1740 31.23% 25.56% 43.21% -8.8 19
2006-10-01 Esbjerg L 0-4 1569 1614 35.86% 25.70% 38.44% -35.0 7
2006-10-01 @ Viborg W 4-0 1614 1569 38.44% 25.70% 35.86% +35.0 15
2006-10-01 Horsens D 2-2 1466 1578 27.16% 25.24% 47.59% +0.8 2
2006-10-01 @ Vejle BK D 2-2 1578 1466 47.59% 25.24% 27.16% -0.8 11
2006-10-01 Odense L 0-1 1536 1703 21.29% 24.36% 54.36% -6.4 7
2006-10-01 @ Silkeborg W 1-0 1703 1536 54.36% 24.36% 21.29% +6.4 22
2006-10-01 Randers W 2-1 1642 1533 55.64% 24.12% 20.24% +5.8 17
2006-10-01 @ Midtjylland L 1-2 1533 1642 20.24% 24.12% 55.64% -5.8 12
2006-10-04 Nordsjaelland D 2-2 1647 1682 37.21% 25.71% 37.08% +0.0 18
2006-10-04 @ Midtjylland D 2-2 1682 1647 37.08% 25.71% 37.21% +0.0 20
2006-10-14 FC Copenhagen L 0-2 1528 1749 16.75% 23.12% 60.13% -9.7 12
2006-10-14 @ Randers W 2-0 1749 1528 60.13% 23.12% 16.75% +9.7 26
2006-10-15 Aalborg L 0-2 1649 1674 38.50% 25.70% 35.81% -19.5 15
2006-10-15 @ Esbjerg W 2-0 1674 1649 35.81% 25.70% 38.50% +19.5 23
2006-10-15 Horsens W 2-0 1709 1577 58.27% 23.57% 18.16% +10.5 25
2006-10-15 @ Odense L 0-2 1577 1709 18.16% 23.57% 58.27% -10.5 11
2006-10-15 Midtjylland L 1-3 1723 1647 51.89% 24.74% 23.37% -21.5 19
2006-10-15 @ Brondby W 3-1 1647 1723 23.37% 24.74% 51.89% +21.5 21
2006-10-15 Silkeborg W 5-1 1682 1529 60.36% 23.06% 16.58% +15.2 23
2006-10-15 @ Nordsjaelland L 1-5 1529 1682 16.58% 23.06% 60.36% -15.2 7
2006-10-15 Vejle BK W 2-1 1534 1467 50.87% 24.88% 24.25% +6.8 10
2006-10-15 @ Viborg L 1-2 1467 1534 24.25% 24.88% 50.87% -6.8 2
2006-10-18 Silkeborg D 1-1 1702 1514 63.69% 22.10% 14.20% -2.9 20
2006-10-18 @ Brondby D 1-1 1514 1702 14.20% 22.10% 63.69% +2.9 8
2006-10-21 Brondby D 0-0 1566 1699 24.82% 24.96% 50.21% +1.6 12
2006-10-21 @ Horsens D 0-0 1699 1566 50.21% 24.96% 24.82% -1.6 21
2006-10-22 Esbjerg L 1-2 1517 1629 27.09% 25.24% 47.67% -7.4 8
2006-10-22 @ Silkeborg W 2-1 1629 1517 47.67% 25.24% 27.09% +7.4 18
2006-10-22 Nordsjaelland W 3-2 1460 1697 15.59% 22.69% 61.72% +13.7 5
2006-10-22 @ Vejle BK L 2-3 1697 1460 61.72% 22.69% 15.59% -13.7 23
2006-10-22 Odense W 3-0 1669 1720 34.93% 25.69% 39.38% +28.8 24
2006-10-22 @ Midtjylland L 0-3 1720 1669 39.38% 25.69% 34.93% -28.8 25
2006-10-22 Randers L 0-4 1694 1518 62.60% 22.44% 14.96% -55.5 23
2006-10-22 @ Aalborg W 4-0 1518 1694 14.96% 22.44% 62.60% +55.5 15
2006-10-22 Viborg W 3-0 1758 1541 66.37% 21.20% 12.43% +10.4 29
2006-10-22 @ FC Copenhagen L 0-3 1541 1758 12.43% 21.20% 66.37% -10.4 10
2006-10-25 Aalborg L 1-2 1697 1638 49.82% 25.01% 25.17% -12.0 21
2006-10-25 @ Brondby W 2-1 1638 1697 25.17% 25.01% 49.82% +12.0 26
2006-10-25 Esbjerg D 1-1 1568 1637 32.52% 25.62% 41.87% +0.5 13
2006-10-25 @ Horsens D 1-1 1637 1568 41.87% 25.62% 32.52% -0.5 19
2006-10-25 FC Copenhagen D 0-0 1691 1769 31.31% 25.56% 43.13% +0.7 26
2006-10-25 @ Odense D 0-0 1769 1691 43.13% 25.56% 31.31% -0.7 30
2006-10-25 Midtjylland L 1-4 1684 1698 40.16% 25.67% 34.17% -24.6 23
2006-10-25 @ Nordsjaelland W 4-1 1698 1684 34.17% 25.67% 40.16% +24.6 27
2006-10-25 Vejle BK L 0-1 1573 1474 54.66% 24.30% 21.03% -13.8 15
2006-10-25 @ Randers W 1-0 1474 1573 21.03% 24.30% 54.66% +13.8 8
2006-10-25 Viborg L 1-2 1510 1531 39.18% 25.69% 35.13% -9.9 8
2006-10-25 @ Silkeborg W 2-1 1531 1510 35.13% 25.69% 39.18% +9.9 13
2006-10-28 Nordsjaelland W 1-0 1636 1659 38.90% 25.69% 35.41% +9.7 22
2006-10-28 @ Esbjerg L 0-1 1659 1636 35.41% 25.69% 38.90% -9.7 23
2006-10-29 Brondby W 1-0 1692 1685 43.02% 25.57% 31.41% +8.8 29
2006-10-29 @ Odense L 0-1 1685 1692 31.41% 25.57% 43.02% -8.8 21
2006-10-29 Horsens W 1-0 1722 1568 60.46% 23.04% 16.51% +5.1 30
2006-10-29 @ Midtjylland L 0-1 1568 1722 16.51% 23.04% 60.46% -5.1 13
2006-10-29 Randers D 1-1 1540 1560 39.43% 25.68% 34.89% -0.2 14
2006-10-29 @ Viborg D 1-1 1560 1540 34.89% 25.68% 39.43% +0.2 16
2006-10-29 Silkeborg W 1-0 1650 1500 60.13% 23.12% 16.75% +5.1 29
2006-10-29 @ Aalborg L 0-1 1500 1650 16.75% 23.12% 60.13% -5.1 8
2006-10-29 Vejle BK W 3-0 1768 1488 71.50% 19.12% 9.38% +7.7 33
2006-10-29 @ FC Copenhagen L 0-3 1488 1768 9.38% 19.12% 71.50% -7.7 8
2006-11-04 Aalborg D 1-1 1649 1656 41.26% 25.64% 33.10% -0.4 24
2006-11-04 @ Nordsjaelland D 1-1 1656 1649 33.10% 25.64% 41.26% +0.4 30
2006-11-05 Brondby W 3-1 1776 1676 54.67% 24.30% 21.03% +10.4 36
2006-11-05 @ FC Copenhagen L 1-3 1676 1776 21.03% 24.30% 54.67% -10.3 21
2006-11-05 Esbjerg W 3-2 1560 1646 30.29% 25.50% 44.21% +10.3 19
2006-11-05 @ Randers L 2-3 1646 1560 44.21% 25.50% 30.29% -10.3 22
2006-11-05 Horsens W 1-0 1540 1563 38.88% 25.69% 35.43% +9.7 17
2006-11-05 @ Viborg L 0-1 1563 1540 35.43% 25.69% 38.88% -9.7 13
2006-11-05 Midtjylland L 0-1 1495 1727 15.89% 22.81% 61.29% -4.9 8
2006-11-05 @ Silkeborg W 1-0 1727 1495 61.29% 22.81% 15.89% +4.9 33
2006-11-05 Odense L 1-2 1480 1701 16.79% 23.13% 60.08% -4.8 8
2006-11-05 @ Vejle BK W 2-1 1701 1480 60.08% 23.13% 16.79% +4.9 32
2006-11-11 Silkeborg W 3-1 1666 1490 62.63% 22.43% 14.94% +7.5 24
2006-11-11 @ Brondby L 1-3 1490 1666 14.94% 22.43% 62.63% -7.5 8
2006-11-12 FC Copenhagen L 0-1 1656 1786 25.05% 24.99% 49.96% -7.4 30
2006-11-12 @ Aalborg W 1-0 1786 1656 49.96% 24.99% 25.05% +7.4 39
2006-11-12 Nordsjaelland L 0-1 1705 1649 49.55% 25.04% 25.41% -12.7 32
2006-11-12 @ Odense W 1-0 1649 1705 25.41% 25.04% 49.55% +12.6 27
2006-11-12 Randers W 2-1 1554 1570 39.80% 25.68% 34.52% +9.0 16
2006-11-12 @ Horsens L 1-2 1570 1554 34.52% 25.68% 39.80% -9.0 19
2006-11-12 Vejle BK W 1-0 1635 1475 61.09% 22.87% 16.04% +4.9 25
2006-11-12 @ Esbjerg L 0-1 1475 1635 16.04% 22.87% 61.09% -4.9 8
2006-11-12 Viborg W 3-1 1732 1550 63.21% 22.25% 14.54% +7.3 36
2006-11-12 @ Midtjylland L 1-3 1550 1732 14.54% 22.25% 63.21% -7.3 17
2006-11-18 Midtjylland D 2-2 1794 1740 49.23% 25.08% 25.69% -1.0 40
2006-11-18 @ FC Copenhagen D 2-2 1740 1794 25.69% 25.08% 49.23% +1.0 37
2006-11-19 Aalborg D 1-1 1470 1649 20.27% 24.13% 55.60% +2.0 9
2006-11-19 @ Vejle BK D 1-1 1649 1470 55.60% 24.13% 20.27% -2.0 31
2006-11-19 Brondby W 2-0 1561 1673 27.09% 25.24% 47.68% +23.1 22
2006-11-19 @ Randers L 0-2 1673 1561 47.68% 25.24% 27.09% -23.1 24
2006-11-19 Esbjerg D 1-1 1543 1640 28.80% 25.39% 45.80% +0.9 18
2006-11-19 @ Viborg D 1-1 1640 1543 45.80% 25.39% 28.80% -0.9 26
2006-11-19 Horsens W 4-0 1662 1563 54.59% 24.31% 21.09% +22.7 30
2006-11-19 @ Nordsjaelland L 0-4 1563 1662 21.09% 24.31% 54.59% -22.7 16
2006-11-19 Odense L 1-3 1482 1693 17.55% 23.39% 59.06% -8.8 8
2006-11-19 @ Silkeborg W 3-1 1693 1482 59.06% 23.39% 17.55% +8.8 35
2006-11-26 Randers W 2-1 1793 1584 65.57% 21.48% 12.95% +3.7 43
2006-11-26 @ FC Copenhagen L 1-2 1584 1793 12.95% 21.48% 65.57% -3.8 22
2007-03-10 Vejle BK D 2-2 1741 1472 70.56% 19.53% 9.90% -2.7 38
2007-03-10 @ Midtjylland D 2-2 1472 1741 9.90% 19.53% 70.56% +2.7 10
2007-03-11 FC Copenhagen D 0-0 1639 1796 22.29% 24.55% 53.16% +2.0 27
2007-03-11 @ Esbjerg D 0-0 1796 1639 53.16% 24.55% 22.29% -1.9 44
2007-03-11 Nordsjaelland W 2-0 1650 1684 37.33% 25.70% 36.97% +18.9 27
2007-03-11 @ Brondby L 0-2 1684 1650 36.97% 25.70% 37.33% -18.9 30
2007-03-11 Randers L 1-2 1702 1581 57.03% 23.84% 19.12% -13.5 35
2007-03-11 @ Odense W 2-1 1581 1702 19.12% 23.84% 57.03% +13.5 25
2007-03-11 Silkeborg W 2-1 1540 1473 50.77% 24.89% 24.34% +6.8 19
2007-03-11 @ Horsens L 1-2 1473 1540 24.34% 24.89% 50.77% -6.8 8
2007-03-11 Viborg L 0-2 1647 1544 55.05% 24.23% 20.72% -26.1 31
2007-03-11 @ Aalborg W 2-0 1544 1647 20.72% 24.23% 55.05% +26.1 21
2007-03-17 Silkeborg L 0-2 1475 1467 43.25% 25.55% 31.19% -21.3 10
2007-03-17 @ Vejle BK W 2-0 1467 1475 31.19% 25.55% 43.25% +21.3 11
2007-03-18 Brondby D 1-1 1570 1669 28.59% 25.38% 46.04% +1.0 22
2007-03-18 @ Viborg D 1-1 1669 1570 46.04% 25.38% 28.59% -1.0 28
2007-03-18 Horsens W 4-0 1620 1547 51.65% 24.78% 23.57% +25.0 34
2007-03-18 @ Aalborg L 0-4 1547 1620 23.57% 24.78% 51.65% -25.0 19
2007-03-18 Midtjylland D 0-0 1594 1738 23.61% 24.78% 51.60% +1.8 26
2007-03-18 @ Randers D 0-0 1738 1594 51.60% 24.78% 23.61% -1.8 39
2007-03-18 Nordsjaelland D 1-1 1794 1665 57.89% 23.66% 18.45% -2.3 45
2007-03-18 @ FC Copenhagen D 1-1 1665 1794 18.45% 23.66% 57.89% +2.3 31
2007-03-18 Odense L 1-2 1641 1688 35.52% 25.69% 38.79% -9.2 27
2007-03-18 @ Esbjerg W 2-1 1688 1641 38.79% 25.69% 35.52% +9.2 38
2007-03-31 FC Copenhagen L 1-3 1522 1792 13.43% 21.73% 64.84% -6.7 19
2007-03-31 @ Horsens W 3-1 1792 1522 64.84% 21.73% 13.43% +6.7 48
2007-04-01 Aalborg D 1-1 1697 1645 48.96% 25.11% 25.94% -1.3 39
2007-04-01 @ Odense D 1-1 1645 1697 25.94% 25.11% 48.96% +1.3 35
2007-04-01 Esbjerg W 3-1 1736 1632 55.15% 24.21% 20.64% +10.2 42
2007-04-01 @ Midtjylland L 1-3 1632 1736 20.64% 24.21% 55.15% -10.2 27
2007-04-01 Randers D 0-0 1488 1596 27.59% 25.29% 47.12% +1.2 12
2007-04-01 @ Silkeborg D 0-0 1596 1488 47.12% 25.29% 27.59% -1.2 27
2007-04-01 Vejle BK W 4-0 1668 1454 66.13% 21.28% 12.59% +13.8 31
2007-04-01 @ Brondby L 0-4 1454 1668 12.59% 21.28% 66.13% -13.8 10
2007-04-01 Viborg W 4-1 1668 1571 54.38% 24.35% 21.27% +14.8 34
2007-04-01 @ Nordsjaelland L 1-4 1571 1668 21.27% 24.35% 54.38% -14.8 22
2007-04-05 Brondby D 1-1 1622 1682 33.68% 25.66% 40.67% +0.4 28
2007-04-05 @ Esbjerg D 1-1 1682 1622 40.67% 25.66% 33.68% -0.4 32
2007-04-05 Horsens D 0-0 1440 1515 31.67% 25.58% 42.75% +0.7 11
2007-04-05 @ Vejle BK D 0-0 1515 1440 42.75% 25.58% 31.67% -0.7 20
2007-04-05 Midtjylland L 0-2 1647 1746 28.59% 25.38% 46.04% -15.5 35
2007-04-05 @ Aalborg W 2-0 1746 1647 46.04% 25.38% 28.59% +15.5 45
2007-04-05 Nordsjaelland L 1-6 1595 1682 30.03% 25.48% 44.48% -31.2 27
2007-04-05 @ Randers W 6-1 1682 1595 44.48% 25.48% 30.03% +31.2 37
2007-04-05 Odense L 0-2 1556 1696 23.99% 24.84% 51.17% -13.4 22
2007-04-05 @ Viborg W 2-0 1696 1556 51.17% 24.84% 23.99% +13.4 42
2007-04-05 Silkeborg W 3-1 1799 1489 73.66% 18.11% 8.23% +4.0 51
2007-04-05 @ FC Copenhagen L 1-3 1489 1799 8.23% 18.11% 73.66% -4.0 12
2007-04-08 Randers W 3-0 1682 1563 56.74% 23.90% 19.35% +16.1 35
2007-04-08 @ Brondby L 0-3 1563 1682 19.35% 23.90% 56.74% -16.1 27
2007-04-09 Aalborg L 4-6 1485 1631 23.38% 24.74% 51.88% -9.3 12
2007-04-09 @ Silkeborg W 6-4 1631 1485 51.88% 24.74% 23.38% +9.3 38
2007-04-09 Esbjerg D 1-1 1714 1622 53.71% 24.46% 21.82% -1.8 38
2007-04-09 @ Nordsjaelland D 1-1 1622 1714 21.82% 24.46% 53.71% +1.8 29
2007-04-09 FC Copenhagen L 1-4 1762 1803 36.31% 25.70% 37.99% -22.8 45
2007-04-09 @ Midtjylland W 4-1 1803 1762 37.99% 25.70% 36.31% +22.8 54
2007-04-09 Vejle BK W 3-2 1709 1441 70.61% 19.51% 9.88% +2.7 45
2007-04-09 @ Odense L 2-3 1441 1709 9.88% 19.51% 70.61% -2.7 11
2007-04-09 Viborg W 3-1 1514 1542 38.15% 25.70% 36.15% +16.1 23
2007-04-09 @ Horsens L 1-3 1542 1514 36.15% 25.70% 38.15% -16.1 22
2007-04-14 Brondby W 3-2 1641 1698 34.05% 25.67% 40.29% +9.6 41
2007-04-14 @ Aalborg L 2-3 1698 1641 40.29% 25.67% 34.05% -9.6 35
2007-04-15 Horsens L 0-1 1624 1530 54.02% 24.41% 21.56% -13.6 29
2007-04-15 @ Esbjerg W 1-0 1530 1624 21.56% 24.41% 54.02% +13.6 26
2007-04-15 Nordsjaelland D 1-1 1739 1712 45.77% 25.40% 28.83% -0.9 46
2007-04-15 @ Midtjylland D 1-1 1712 1739 28.83% 25.40% 45.77% +0.9 39
2007-04-15 Odense W 4-2 1826 1712 56.23% 24.01% 19.76% +8.8 57
2007-04-15 @ FC Copenhagen L 2-4 1712 1826 19.76% 24.01% 56.23% -8.8 45
2007-04-15 Randers L 0-2 1438 1547 27.40% 25.27% 47.33% -15.0 11
2007-04-15 @ Vejle BK W 2-0 1547 1438 47.33% 25.27% 27.40% +15.0 30
2007-04-15 Silkeborg W 2-1 1526 1476 48.78% 25.13% 26.09% +7.2 25
2007-04-15 @ Viborg L 1-2 1476 1526 26.09% 25.13% 48.78% -7.2 12
2007-04-18 Aalborg D 1-1 1562 1650 30.04% 25.48% 44.48% +0.8 31
2007-04-18 @ Randers D 1-1 1650 1562 44.48% 25.48% 30.04% -0.8 42
2007-04-18 Esbjerg D 0-0 1703 1611 53.88% 24.44% 21.68% -2.0 46
2007-04-18 @ Odense D 0-0 1611 1703 21.68% 24.44% 53.88% +2.1 30
2007-04-18 FC Copenhagen L 0-1 1713 1834 26.00% 25.12% 48.88% -7.6 39
2007-04-18 @ Nordsjaelland W 1-0 1834 1713 48.88% 25.12% 26.00% +7.6 60
2007-04-18 Midtjylland D 2-2 1544 1738 18.90% 23.78% 57.32% +1.6 27
2007-04-18 @ Horsens D 2-2 1738 1544 57.32% 23.78% 18.90% -1.7 47
2007-04-18 Vejle BK D 1-1 1469 1423 48.21% 25.18% 26.61% -1.2 13
2007-04-18 @ Silkeborg D 1-1 1423 1469 26.61% 25.18% 48.21% +1.2 12
2007-04-18 Viborg W 3-1 1688 1534 60.54% 23.02% 16.45% +8.2 38
2007-04-18 @ Brondby L 1-3 1534 1688 16.45% 23.02% 60.54% -8.2 25
2007-04-21 Randers W 2-1 1736 1563 62.35% 22.51% 15.14% +4.4 50
2007-04-21 @ Midtjylland L 1-2 1563 1736 15.14% 22.51% 62.35% -4.4 31
2007-04-22 Aalborg L 0-2 1525 1649 25.74% 25.08% 49.18% -14.2 25
2007-04-22 @ Viborg W 2-0 1649 1525 49.18% 25.08% 25.74% +14.2 45
2007-04-22 Brondby W 3-0 1424 1696 13.31% 21.67% 65.01% +43.9 15
2007-04-22 @ Vejle BK L 0-3 1696 1424 65.01% 21.67% 13.31% -43.9 38
2007-04-22 Horsens W 3-1 1842 1546 72.70% 18.57% 8.74% +4.2 63
2007-04-22 @ FC Copenhagen L 1-3 1546 1842 8.74% 18.57% 72.70% -4.2 27
2007-04-22 Odense W 2-1 1705 1701 42.66% 25.58% 31.76% +8.4 42
2007-04-22 @ Nordsjaelland L 1-2 1701 1705 31.76% 25.58% 42.66% -8.4 46
2007-04-22 Silkeborg L 0-3 1613 1468 59.57% 23.26% 17.17% -40.7 30
2007-04-22 @ Esbjerg W 3-0 1468 1613 17.17% 23.26% 59.57% +40.7 16
2007-04-28 Midtjylland W 1-0 1693 1741 35.34% 25.69% 38.96% +10.4 49
2007-04-28 @ Odense L 0-1 1741 1693 38.96% 25.69% 35.34% -10.4 50
2007-04-29 Esbjerg W 2-1 1653 1572 52.47% 24.66% 22.87% +6.4 41
2007-04-29 @ Brondby L 1-2 1572 1653 22.87% 24.66% 52.47% -6.4 30
2007-04-29 FC Copenhagen L 0-1 1508 1846 9.94% 19.56% 70.51% -3.0 16
2007-04-29 @ Silkeborg W 1-0 1846 1508 70.51% 19.56% 9.94% +3.0 66
2007-04-29 Nordsjaelland L 2-3 1541 1714 20.82% 24.26% 54.92% -5.6 27
2007-04-29 @ Horsens W 3-2 1714 1541 54.92% 24.26% 20.82% +5.6 45
2007-04-29 Vejle BK W 2-0 1664 1468 64.43% 21.86% 13.70% +7.9 48
2007-04-29 @ Aalborg L 0-2 1468 1664 13.70% 21.86% 64.43% -8.0 15
2007-04-29 Viborg W 3-2 1559 1511 48.43% 25.16% 26.41% +6.9 34
2007-04-29 @ Randers L 2-3 1511 1559 26.41% 25.16% 48.43% -6.9 25
2007-05-05 Aalborg L 1-2 1849 1671 62.78% 22.38% 14.84% -14.7 66
2007-05-05 @ FC Copenhagen W 2-1 1671 1849 14.84% 22.38% 62.78% +14.7 51
2007-05-06 Brondby D 3-3 1719 1659 50.00% 24.99% 25.01% -0.9 46
2007-05-06 @ Nordsjaelland D 3-3 1659 1719 25.01% 24.99% 50.00% +0.9 42
2007-05-06 Odense L 1-2 1536 1703 21.26% 24.35% 54.39% -6.0 27
2007-05-06 @ Horsens W 2-1 1703 1536 54.39% 24.35% 21.26% +6.0 52
2007-05-06 Randers W 3-1 1566 1566 42.11% 25.61% 32.28% +14.8 33
2007-05-06 @ Esbjerg L 1-3 1566 1566 32.28% 25.61% 42.11% -14.8 34
2007-05-06 Silkeborg W 3-1 1730 1505 67.03% 20.95% 12.01% +6.0 53
2007-05-06 @ Midtjylland L 1-3 1505 1730 12.01% 20.95% 67.03% -6.0 16
2007-05-06 Viborg W 2-0 1460 1504 35.87% 25.70% 38.43% +19.5 18
2007-05-06 @ Vejle BK L 0-2 1504 1460 38.43% 25.70% 35.87% -19.5 25
2007-05-09 Esbjerg W 3-0 1479 1580 28.42% 25.36% 46.21% +32.7 21
2007-05-09 @ Vejle BK L 0-3 1580 1479 46.21% 25.36% 28.42% -32.7 33
2007-05-09 FC Copenhagen L 0-1 1660 1835 20.60% 24.21% 55.19% -6.2 42
2007-05-09 @ Brondby W 1-0 1835 1660 55.19% 24.21% 20.60% +6.2 69
2007-05-09 Horsens D 1-1 1499 1530 37.83% 25.70% 36.47% -0.1 17
2007-05-09 @ Silkeborg D 1-1 1530 1499 36.47% 25.70% 37.83% +0.1 28
2007-05-09 Midtjylland L 0-1 1485 1736 14.61% 22.29% 63.10% -4.5 25
2007-05-09 @ Viborg W 1-0 1736 1485 63.10% 22.29% 14.61% +4.5 56
2007-05-09 Nordsjaelland D 1-1 1686 1718 37.58% 25.70% 36.72% -0.1 52
2007-05-09 @ Aalborg D 1-1 1718 1686 36.72% 25.70% 37.58% +0.1 47
2007-05-09 Odense L 1-2 1551 1709 22.13% 24.52% 53.34% -6.2 34
2007-05-09 @ Randers W 2-1 1709 1551 53.34% 24.52% 22.13% +6.3 55
2007-05-12 Brondby D 1-1 1741 1654 53.24% 24.54% 22.22% -1.8 57
2007-05-12 @ Midtjylland D 1-1 1654 1741 22.22% 24.54% 53.24% +1.8 43
2007-05-13 Aalborg L 1-4 1530 1686 22.34% 24.56% 53.09% -15.4 28
2007-05-13 @ Horsens W 4-1 1686 1530 53.09% 24.56% 22.34% +15.4 55
2007-05-13 Randers W 1-0 1841 1545 72.68% 18.57% 8.74% +2.6 72
2007-05-13 @ FC Copenhagen L 0-1 1545 1841 8.74% 18.57% 72.68% -2.6 34
2007-05-13 Silkeborg W 2-0 1716 1499 66.28% 21.23% 12.49% +7.2 58
2007-05-13 @ Odense L 0-2 1499 1716 12.49% 21.23% 66.28% -7.2 17
2007-05-13 Vejle BK W 3-0 1718 1512 65.39% 21.54% 13.06% +11.0 50
2007-05-13 @ Nordsjaelland L 0-3 1512 1718 13.06% 21.54% 65.39% -11.0 21
2007-05-13 Viborg D 2-2 1548 1480 50.89% 24.88% 24.24% -1.1 34
2007-05-13 @ Esbjerg D 2-2 1480 1548 24.24% 24.88% 50.89% +1.1 26
2007-05-19 Esbjerg W 2-0 1702 1547 60.57% 23.01% 16.43% +9.5 58
2007-05-19 @ Aalborg L 0-2 1547 1702 16.43% 23.01% 60.57% -9.5 34
2007-05-20 FC Copenhagen L 0-1 1481 1843 8.93% 18.73% 72.34% -2.7 26
2007-05-20 @ Viborg W 1-0 1843 1481 72.34% 18.73% 8.93% +2.7 75
2007-05-20 Horsens W 2-1 1542 1514 45.85% 25.39% 28.76% +7.8 37
2007-05-20 @ Randers L 1-2 1514 1542 28.76% 25.39% 45.85% -7.8 28
2007-05-20 Midtjylland L 1-2 1501 1739 15.54% 22.67% 61.79% -4.5 21
2007-05-20 @ Vejle BK W 2-1 1739 1501 61.79% 22.67% 15.54% +4.5 60
2007-05-20 Nordsjaelland D 1-1 1492 1729 15.57% 22.69% 61.75% +2.7 18
2007-05-20 @ Silkeborg D 1-1 1729 1492 61.75% 22.69% 15.57% -2.7 51
2007-05-20 Odense W 1-0 1655 1723 32.69% 25.62% 41.69% +11.0 46
2007-05-20 @ Brondby L 0-1 1723 1655 41.69% 25.62% 32.69% -11.0 58
2007-05-24 Aalborg W 2-1 1744 1711 46.49% 25.34% 28.17% +7.7 63
2007-05-24 @ Midtjylland L 1-2 1711 1744 28.17% 25.34% 46.49% -7.7 58
2007-05-24 Brondby W 2-1 1495 1666 20.87% 24.27% 54.87% +13.0 21
2007-05-24 @ Silkeborg L 1-2 1666 1495 54.87% 24.27% 20.87% -13.0 46
2007-05-24 Esbjerg L 1-2 1846 1537 73.61% 18.13% 8.25% -16.7 75
2007-05-24 @ FC Copenhagen W 2-1 1537 1846 8.25% 18.13% 73.61% +16.7 37
2007-05-24 Randers W 4-2 1727 1550 62.70% 22.41% 14.89% +6.7 54
2007-05-24 @ Nordsjaelland L 2-4 1550 1727 14.89% 22.41% 62.70% -6.7 37
2007-05-24 Vejle BK L 1-2 1507 1497 43.47% 25.54% 30.99% -10.7 28
2007-05-24 @ Horsens W 2-1 1497 1507 30.99% 25.54% 43.47% +10.7 24
2007-05-24 Viborg L 2-3 1712 1479 67.71% 20.70% 11.59% -14.8 58
2007-05-24 @ Odense W 3-2 1479 1712 11.59% 20.70% 67.71% +14.8 29
2007-05-27 FC Copenhagen D 0-0 1507 1829 10.67% 20.09% 69.24% +3.9 25
2007-05-27 @ Vejle BK D 0-0 1829 1507 69.24% 20.09% 10.67% -3.9 76
2007-05-27 Horsens W 2-0 1653 1496 60.82% 22.94% 16.24% +9.4 49
2007-05-27 @ Brondby L 0-2 1496 1653 16.24% 22.94% 60.82% -9.4 28
2007-05-27 Midtjylland W 3-0 1554 1751 18.61% 23.70% 57.69% +39.5 40
2007-05-27 @ Esbjerg L 0-3 1751 1554 57.69% 23.70% 18.61% -39.5 63
2007-05-27 Nordsjaelland L 1-2 1494 1733 15.40% 22.62% 61.98% -4.5 29
2007-05-27 @ Viborg W 2-1 1733 1494 61.98% 22.62% 15.40% +4.5 57
2007-05-27 Odense W 3-1 1703 1697 43.00% 25.57% 31.44% +14.5 61
2007-05-27 @ Aalborg L 1-3 1697 1703 31.44% 25.57% 43.00% -14.5 58
2007-05-27 Silkeborg D 1-1 1543 1508 46.85% 25.31% 27.84% -1.0 38
2007-05-27 @ Randers D 1-1 1508 1543 27.84% 25.31% 46.85% +1.0 22

Biggest Upsets

The 25 games where the underdog won despite the lowest pregame win probability. Underdog Win % is the winner's pregame chance of winning the game (lower = bigger upset). @ before a team name indicates the away side. An asterisk (*) after the date marks a playoff game.

# Date Underdog Win % Winning Team Losing Team
Team Elo Score Team Elo Score
1 2007-05-24 8.25% Esbjerg 1537 2 @ FC Copenhagen 1846 1
2 2007-05-24 11.59% Viborg 1479 3 @ Odense 1712 2
3 2007-04-22 13.31% @ Vejle BK 1424 3 Brondby 1696 0
4 2007-05-05 14.84% Aalborg 1671 2 @ FC Copenhagen 1849 1
5 2006-10-22 14.96% Randers 1518 4 @ Aalborg 1694 0
6 2006-10-22 15.59% @ Vejle BK 1460 3 Nordsjaelland 1697 2
7 2007-04-22 17.17% Silkeborg 1468 3 @ Esbjerg 1613 0
8 2007-05-27 18.61% @ Esbjerg 1554 3 Midtjylland 1751 0
9 2007-03-11 19.12% Randers 1581 2 @ Odense 1702 1
10 2007-03-11 20.72% Viborg 1544 2 @ Aalborg 1647 0
11 2007-05-24 20.87% @ Silkeborg 1495 2 Brondby 1666 1
12 2006-10-25 21.03% Vejle BK 1474 1 @ Randers 1573 0
13 2006-09-17 21.19% Horsens 1563 2 @ Midtjylland 1661 1
14 2007-04-15 21.56% Horsens 1530 1 @ Esbjerg 1624 0
15 2006-10-15 23.37% Midtjylland 1647 3 @ Brondby 1723 1
16 2006-08-13 24.36% Silkeborg 1545 3 @ Viborg 1611 2
17 2006-08-27 24.56% @ Randers 1513 3 Esbjerg 1648 1
18 2006-09-30 24.77% Nordsjaelland 1647 3 @ Aalborg 1709 0
19 2006-10-25 25.17% Aalborg 1638 2 @ Brondby 1697 1
20 2006-11-12 25.41% Nordsjaelland 1649 1 @ Odense 1705 0
21 2006-08-27 26.01% Aalborg 1700 2 @ FC Copenhagen 1751 0
22 2006-11-19 27.09% @ Randers 1561 2 Brondby 1673 0
23 2006-07-29 27.71% Esbjerg 1627 2 @ Odense 1664 0
24 2006-09-17 28.23% Odense 1691 1 @ Aalborg 1723 0
25 2007-05-09 28.42% @ Vejle BK 1479 3 Esbjerg 1580 0

Biggest Elo Changes

The 25 games that resulted in the largest shift in Elo rating.

# Date Elo Δ Winning Team Losing Team Tie %
Team Score Elo Win % Team Score Elo Win %
1 2006-10-22 55.49 Randers 4 1518 14.96% @ Aalborg 0 1694 62.60% 22.44%
2 2007-04-22 43.88 @ Vejle BK 3 1424 13.31% Brondby 0 1696 65.01% 21.67%
3 2007-04-22 40.67 Silkeborg 3 1468 17.17% @ Esbjerg 0 1613 59.57% 23.26%
4 2007-05-27 39.54 @ Esbjerg 3 1554 18.61% Midtjylland 0 1751 57.69% 23.70%
5 2006-09-30 35.08 Nordsjaelland 3 1647 24.77% @ Aalborg 0 1709 50.27% 24.96%
6 2006-10-01 35.04 Esbjerg 4 1614 38.44% @ Viborg 0 1569 35.86% 25.70%
7 2007-05-09 32.68 @ Vejle BK 3 1479 28.42% Esbjerg 0 1580 46.21% 25.36%
8 2006-07-19 32.32 @ Nordsjaelland 5 1595 50.16% Randers 0 1534 24.87% 24.97%
9 2007-04-05 31.20 Nordsjaelland 6 1682 44.48% @ Randers 1 1595 30.03% 25.48%
10 2006-10-22 28.78 @ Midtjylland 3 1669 34.93% Odense 0 1720 39.38% 25.69%
11 2007-03-11 26.13 Viborg 2 1544 20.72% @ Aalborg 0 1647 55.05% 24.23%
12 2007-03-18 25.05 @ Aalborg 4 1620 51.65% Horsens 0 1547 23.57% 24.78%
13 2006-10-25 24.64 Midtjylland 4 1698 34.17% @ Nordsjaelland 1 1684 40.16% 25.67%
14 2006-08-27 23.58 Aalborg 2 1700 26.01% @ FC Copenhagen 0 1751 48.88% 25.12%
15 2006-11-19 23.09 @ Randers 2 1561 27.09% Brondby 0 1673 47.68% 25.24%
16 2007-04-09 22.83 FC Copenhagen 4 1803 37.99% @ Midtjylland 1 1762 36.31% 25.70%
17 2006-07-29 22.82 Esbjerg 2 1627 27.71% @ Odense 0 1664 47.00% 25.30%
18 2006-11-19 22.74 @ Nordsjaelland 4 1662 54.59% Horsens 0 1563 21.09% 24.31%
19 2006-07-30 22.58 @ Aalborg 4 1670 54.79% Vejle BK 0 1570 20.93% 24.28%
20 2006-10-15 21.49 Midtjylland 3 1647 23.37% @ Brondby 1 1723 51.89% 24.74%
21 2007-03-17 21.32 Silkeborg 2 1467 31.19% @ Vejle BK 0 1475 43.25% 25.55%
22 2006-08-27 21.00 @ Randers 3 1513 24.56% Esbjerg 1 1648 50.52% 24.93%
23 2006-08-20 20.87 Horsens 2 1557 32.30% @ Silkeborg 0 1556 42.10% 25.61%
24 2006-10-15 19.48 Aalborg 2 1674 35.81% @ Esbjerg 0 1649 38.50% 25.70%
25 2007-05-06 19.45 @ Vejle BK 2 1460 35.87% Viborg 0 1504 38.43% 25.70%