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2011-12 Superliga Season

198 games

Final

Champion

Nordsjaelland

68 points · 1st Title

Relegated

HB Koge

19 pts

Lyngby · 28 pts

Biggest Overachiever

Nordsjaelland

15.87 points above expected

68 points · 52.13 expected points

Biggest Disappointment

Odense

13.38 points below expected

34 points · 47.38 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 Nordsjaelland Champion 33 21 5 7 68 49 22 +27 52.13 +15.87
2 FC Copenhagen 33 19 9 5 66 55 26 +29 62.39 +3.61
3 Midtjylland 33 17 7 9 58 50 40 +10 49.27 +8.73
4 Horsens 33 17 6 10 57 53 39 +14 48.26 +8.74
5 Aarhus GF 33 12 12 9 48 47 40 +7 47.79 +0.21
6 Sonderjyske 33 11 11 11 44 48 51 -3 39.49 +4.51
7 Aalborg 33 12 8 13 44 42 48 -6 45.92 -1.92
8 Silkeborg 33 11 10 12 43 51 47 +4 45.16 -2.16
9 Brondby 33 9 9 15 36 35 46 -11 45.37 -9.37
10 Odense 33 8 10 15 34 46 50 -4 47.38 -13.38
11 Lyngby Relegated 33 8 4 21 28 32 60 -28 33.31 -5.31
12 HB Koge Relegated 33 4 7 22 19 32 71 -39 27.68 -8.68

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
Nordsjaelland 1805 68 52.13 +15.87 98.8% 24 40 47 52 57 64 81
FC Copenhagen 1797 66 62.39 +3.61 71.3% 32 50 58 62 67 74 90
Midtjylland 1733 58 49.27 +8.73 89.3% 23 37 44 49 54 61 78
Horsens 1720 57 48.26 +8.74 89.3% 22 36 43 48 53 61 76
Aarhus GF 1667 48 47.79 +0.21 53.8% 22 36 43 48 53 60 74
Silkeborg 1652 43 45.16 -2.16 41.6% 14 33 40 45 50 57 72
Sonderjyske 1646 44 39.49 +4.51 76.6% 13 28 35 39 44 51 67
Odense 1614 34 47.38 -13.38 3.8% 22 36 42 47 52 60 74
Aalborg 1585 44 45.92 -1.92 42.3% 21 34 41 46 51 58 72
Brondby 1582 36 45.37 -9.37 11.0% 19 34 40 45 50 57 73
Lyngby 1490 28 33.31 -5.31 24.9% 11 22 29 33 38 45 61
HB Koge 1452 19 27.68 -8.68 10.0% 6 17 23 27 32 39 53

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 AG BRO FC HK HOR LYN MID NOR ODE SIL SON
Aalborg —
1-1-1
4.21
1-2-0
3.83
0-1-2
2.55
2-1-0
5.58
1-1-1
3.59
1-0-2
5.68
2-0-1
4.07
0-0-3
3.89
3-0-0
4.01
1-1-1
3.97
0-1-2
4.59
Aarhus GF
1-1-1
4.01
 —
1-2-0
4.57
0-3-0
2.80
3-0-0
5.90
1-0-2
3.80
2-1-0
5.48
2-0-1
4.10
1-1-1
3.87
1-2-0
4.35
0-1-2
4.13
0-1-2
4.90
Brondby
0-2-1
4.39
0-2-1
3.65
 —
1-0-2
2.77
1-2-0
5.83
0-0-3
4.25
2-0-1
5.47
0-0-3
3.58
1-0-2
3.00
1-1-1
3.86
2-0-1
4.04
1-2-0
4.54
FC Copenhagen
2-1-0
5.72
0-3-0
5.45
2-0-1
5.48
 —
3-0-0
6.52
2-0-1
5.31
3-0-0
6.25
1-1-1
5.39
1-0-2
5.25
1-2-0
5.50
2-1-0
5.74
2-1-0
5.78
HB Koge
0-1-2
2.68
0-0-3
2.38
0-2-1
2.44
0-0-3
1.84
 —
1-0-2
2.45
0-1-2
3.48
0-1-2
2.52
0-0-3
2.31
1-1-1
2.29
2-0-1
2.59
0-1-2
2.63
Horsens
1-1-1
4.63
2-0-1
4.43
3-0-0
3.97
1-0-2
2.93
2-0-1
5.84
 —
1-2-0
5.27
1-0-2
4.00
0-1-2
3.76
2-0-1
4.37
1-2-0
4.74
3-0-0
4.27
Lyngby
2-0-1
2.58
0-1-2
2.78
1-0-2
2.78
0-0-3
2.06
2-1-0
4.75
0-2-1
2.98
 —
1-0-2
2.62
1-0-2
2.41
1-0-2
2.76
0-0-3
3.53
0-0-3
3.95
Midtjylland
1-0-2
4.14
1-0-2
4.12
3-0-0
4.64
1-1-1
2.86
2-1-0
5.77
2-0-1
4.22
2-0-1
5.65
 —
1-2-0
3.86
3-0-0
4.06
0-1-2
4.68
1-2-0
5.16
Nordsjaelland
3-0-0
4.33
1-1-1
4.36
2-0-1
5.24
2-0-1
2.99
3-0-0
5.99
2-1-0
4.46
2-0-1
5.88
0-2-1
4.36
 —
1-1-1
4.55
3-0-0
4.59
2-0-1
5.48
Odense
0-0-3
4.20
0-2-1
3.87
1-1-1
4.36
0-2-1
2.77
1-1-1
5.99
1-0-2
3.85
2-0-1
5.48
0-0-3
4.17
1-1-1
3.70
 —
1-2-0
4.12
1-1-1
4.82
Silkeborg
1-1-1
4.24
2-1-0
4.09
1-0-2
4.18
0-1-2
2.53
1-0-2
5.68
0-2-1
3.49
3-0-0
4.70
2-1-0
3.54
0-0-3
3.63
0-2-1
4.11
 —
1-2-0
4.99
Sonderjyske
2-1-0
3.64
2-1-0
3.34
0-2-1
3.69
0-1-2
2.50
2-1-0
5.63
0-0-3
3.95
3-0-0
4.27
0-2-1
3.08
1-0-2
2.77
1-1-1
3.41
0-2-1
3.24
 —

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 0.69 +15.6
Allowed 0.91 -10.7
Differential 0.93 +7.2

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
06.57%7.58%6.82%1.77%1.01%1.01%24.75%
17.58%13.13%9.60%4.55%1.77%0.25%36.87%
26.82%9.60%4.04%1.26%1.52%—23.23%
31.77%4.55%1.26%1.01%0.25%0.25%9.09%
41.01%1.77%1.52%0.25%——4.55%
5+1.01%0.25%—0.25%——1.52%
Total24.75%36.87%23.23%9.09%4.55%1.52%100%

Summary Statistics

Scored Allowed Difference
Mean 1.36 1.36 +0.00
SD 1.17 1.17 1.73
CV 0.86 0.86 —
Max 5 5 +5
Min 0 0 -5

Games Played: 198

↓ Scored | Allowed →012345+Total
03.03%6.06%9.09%3.03%—3.03%24.24%
112.12%15.15%12.12%———39.39%
23.03%12.12%3.03%3.03%3.03%—24.24%
3—6.06%—3.03%——9.09%
4—3.03%————3.03%
5+———————
Total18.18%42.42%24.24%9.09%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.45 -0.18
SD 1.04 1.18 1.63
CV 0.82 0.81 —
Max 4 5 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
015.15%—6.06%———21.21%
13.03%18.18%6.06%12.12%——39.39%
212.12%9.09%3.03%———24.24%
33.03%3.03%———3.03%9.09%
4——3.03%———3.03%
5+—3.03%————3.03%
Total33.33%33.33%18.18%12.12%—3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.42 1.21 +0.21
SD 1.20 1.22 1.60
CV 0.84 1.01 —
Max 5 5 +4
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%15.15%9.09%———33.33%
112.12%9.09%12.12%3.03%3.03%3.03%42.42%
2—9.09%6.06%———15.15%
3——3.03%3.03%——6.06%
4———————
5+3.03%—————3.03%
Total24.24%33.33%30.30%6.06%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.39 -0.33
SD 1.12 1.20 1.57
CV 1.05 0.86 —
Max 5 5 +5
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%6.06%3.03%———21.21%
16.06%9.09%3.03%3.03%——21.21%
215.15%15.15%6.06%———36.36%
36.06%9.09%————15.15%
4——3.03%———3.03%
5+3.03%—————3.03%
Total42.42%39.39%15.15%3.03%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.67 0.79 +0.88
SD 1.24 0.82 1.49
CV 0.74 1.04 —
Max 5 3 +5
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%3.03%15.15%3.03%—6.06%30.30%
13.03%15.15%15.15%12.12%6.06%—51.52%
2—3.03%3.03%3.03%3.03%—12.12%
33.03%—————3.03%
4——3.03%———3.03%
5+———————
Total9.09%21.21%36.36%18.18%9.09%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 0.97 2.15 -1.18
SD 0.92 1.30 1.70
CV 0.95 0.61 —
Max 4 5 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%9.09%6.06%6.06%——24.24%
112.12%12.12%6.06%—3.03%—33.33%
26.06%9.09%————15.15%
33.03%9.09%—3.03%——15.15%
4—6.06%—3.03%——9.09%
5+3.03%—————3.03%
Total27.27%45.45%12.12%12.12%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.61 1.18 +0.42
SD 1.41 1.07 1.89
CV 0.88 0.91 —
Max 5 4 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%12.12%6.06%6.06%9.09%—36.36%
19.09%6.06%18.18%9.09%——42.42%
2—6.06%3.03%3.03%——12.12%
3—3.03%3.03%———6.06%
4—3.03%————3.03%
5+———————
Total12.12%30.30%30.30%18.18%9.09%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.97 1.82 -0.85
SD 1.02 1.16 1.70
CV 1.05 0.64 —
Max 4 4 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%3.03%6.06%———15.15%
19.09%12.12%9.09%3.03%3.03%—36.36%
212.12%18.18%3.03%—3.03%—36.36%
3——6.06%———6.06%
4—6.06%————6.06%
5+———————
Total27.27%39.39%24.24%3.03%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.52 1.21 +0.30
SD 1.03 1.08 1.49
CV 0.68 0.89 —
Max 4 4 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%9.09%6.06%———21.21%
115.15%9.09%6.06%———30.30%
224.24%12.12%————36.36%
33.03%3.03%————6.06%
43.03%—————3.03%
5+———3.03%——3.03%
Total51.52%33.33%12.12%3.03%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.48 0.67 +0.82
SD 1.18 0.82 1.42
CV 0.79 1.22 —
Max 5 3 +4
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%12.12%3.03%———24.24%
13.03%12.12%12.12%3.03%3.03%—33.33%
23.03%6.06%9.09%3.03%6.06%—27.27%
3—6.06%——3.03%—9.09%
46.06%—————6.06%
5+———————
Total21.21%36.36%24.24%6.06%12.12%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.52 -0.12
SD 1.14 1.25 1.60
CV 0.82 0.83 —
Max 4 4 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%9.09%—3.03%——15.15%
1—21.21%15.15%6.06%——42.42%
26.06%9.09%6.06%3.03%——24.24%
33.03%3.03%3.03%———9.09%
4—3.03%6.06%———9.09%
5+———————
Total12.12%45.45%30.30%12.12%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.55 1.42 +0.12
SD 1.15 0.87 1.45
CV 0.74 0.61 —
Max 4 3 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%12.12%—3.03%3.03%30.30%
16.06%18.18%—3.03%3.03%—30.30%
2—6.06%6.06%—3.03%—15.15%
3—12.12%—3.03%——15.15%
43.03%—3.03%———6.06%
5+3.03%—————3.03%
Total18.18%42.42%21.21%6.06%9.09%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.55 -0.09
SD 1.39 1.30 2.10
CV 0.96 0.84 —
Max 5 5 +5
Min 0 0 -5

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 Nordsjaelland 68 52.13 +15.87
2 Horsens 57 48.26 +8.74
3 Midtjylland 58 49.27 +8.73
4 Sonderjyske 44 39.49 +4.51
5 FC Copenhagen 66 62.39 +3.61

Biggest Disappointments

# Team Actual Sim vsSim
1 Odense 34 47.38 -13.38
2 Brondby 36 45.37 -9.37
3 HB Koge 19 27.68 -8.68
4 Lyngby 28 33.31 -5.31
5 Silkeborg 43 45.16 -2.16

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 Sonderjyske 3 Mar 24 – Apr 5 1 in 142
2 FC Copenhagen 8 Jul 30 – Sep 24 1 in 121
3 Aarhus GF 4 Aug 29 – Sep 24 1 in 43
4 Nordsjaelland 5 Apr 15 – May 5 1 in 38
5 Midtjylland 4 Sep 18 – Oct 16 1 in 35

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Odense 5 Mar 10 – Apr 6 1 in 427
2 HB Koge 5 Jul 17 – Aug 14 1 in 40
3 Aalborg 3 Sep 11 – Sep 26 1 in 35
4 Brondby 4 May 6 – May 23 1 in 34
5 Lyngby 5 Apr 15 – May 5 1 in 21

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Aarhus GF 11 Aug 15 – Nov 7 1 in 102
2 Silkeborg 8 Sep 18 – Nov 21 1 in 81
3 Sonderjyske 7 Mar 24 – Apr 29 1 in 61
4 Aalborg 7 Jul 17 – Aug 27 1 in 28
5 Midtjylland 8 Apr 1 – May 7 1 in 17

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Odense 13 Mar 5 – May 14 1 in 338
2 Silkeborg 7 Jul 23 – Sep 10 1 in 24
3 FC Copenhagen 4 May 2 – May 20 1 in 22
4 Midtjylland 4 Oct 23 – Nov 20 1 in 17
5 HB Koge 13 Aug 27 – Mar 4 1 in 17

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
Nordsjaelland10.68%21.46%16.86%13.80%10.52%8.90%6.92%4.97%3.19%1.82%0.76%0.12%
FC Copenhagen66.60%17.28%7.28%3.98%2.17%1.24%0.85%0.40%0.13%0.05%0.02%—
Midtjylland5.69%12.94%14.32%12.85%12.50%11.05%9.53%8.13%6.53%4.33%1.72%0.41%
Horsens4.37%11.50%12.20%12.66%12.21%11.66%10.18%9.14%7.67%5.34%2.54%0.53%
Aarhus GF3.53%9.96%11.92%12.05%12.55%11.89%10.76%9.93%8.24%6.05%2.54%0.58%
Sonderjyske0.29%1.09%2.26%3.50%4.96%6.34%9.21%12.30%17.55%20.78%15.81%5.91%
Aalborg2.09%6.39%8.90%9.66%10.74%11.92%12.23%11.95%11.66%9.01%4.50%0.95%
Silkeborg1.73%5.59%8.04%9.52%10.66%11.17%12.56%12.85%11.54%10.00%5.05%1.29%
Brondby1.88%5.04%7.71%9.57%10.29%11.89%12.34%12.39%12.20%10.59%4.90%1.20%
Odense3.11%8.57%10.21%11.81%12.18%11.92%11.59%10.80%9.36%6.61%3.15%0.69%
Lyngby0.03%0.17%0.30%0.56%1.05%1.68%3.16%5.72%8.96%17.95%37.38%23.04%
HB Koge—0.01%—0.04%0.17%0.34%0.67%1.42%2.97%7.47%21.63%65.28%

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
+10.61%
Slight Edge
42.93%24.75%32.32%
Elo Value
Home Edge: 36.99 Elo pts.
199 Elo
0.005 goals per Elo point
0500
Scoring Tilt
Expected
+0.17 goals
Neutral
-2+0.19+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
2.2
Top-Heavy
124610
Champion Preseason Odds
11%
Nordsjaelland, 2nd of 12
LongshotFavorite
Title Margin
Expected
0.06/gm
Photo Finish
00.210.5/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 5.75 * Some Luck: 5.75 to 8.62 * Lucky: 8.62 to 11.49 * Wild Swing: 11.49 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 1.59 * Close: 1.59 to 2.38 * Off: 2.38 to 3.18 * Way Off: 3.18 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 0.53 * A Surprise: 0.53 to 0.84 * Several Surprises: 0.84 to 1.16 * Many Surprises: 1.16 and up.
Luck Spread
Expected
8.25 points
Some Luck
07.1818
Average Finish Error
Expected
1.00
Pinpoint
01.994
Biggest Overachiever
Expected 95.83%
98.77%
Nordsjaelland
50100
Biggest Underachiever
Expected 4.17%
3.75%
Odense
050
Season Outliers
Expected
2 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
0 of 2
As Expected
00.52

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
0.18
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.74
Strong Separation
01.003
Interquartile Edge
69%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline
88%
Strong Edge
50%90%100%
Close Games
Expected
62%
Very Frequent
0%61%100%
Blowouts
Expected
12%
Occasional
0%15%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
0.61
Predictable
00.622
Matchup Imbalance
0.30
Lopsided
00.10.180.280.5
Strangeness
Expected
1.32
Wilder Than Modeled
01.002
Repeatability
0.29
Weak Carryover
00.30.60.851
Upset Rate
Expected
25%
As Expected
0%26%50%
Clear Favorite Upset Rate
Expected
21%
As Expected
0%22%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 0.24 * Well Above Noise: 0.24 and up.
Probability calibration
1.00
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.03
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.034
Well Within Noise
00.1200.3

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 99.98% 0.02%
Nordsjaelland 99.12% 0.88%
Midtjylland 97.87% 2.13%
Horsens 96.93% 3.07%
Aarhus GF 96.88% 3.12%
Odense 96.16% 3.84%
Aalborg 94.55% 5.45%
Brondby 93.90% 6.10%
Silkeborg 93.66% 6.34%
Sonderjyske 78.28% 21.72%
Lyngby 39.58% 60.42%
HB Koge 13.09% 86.91%

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
2011-07-16 Nordsjaelland W 2-0 1681 1631 48.70% 25.61% 25.69% +14.3 3
2011-07-16 @ Odense L 0-2 1631 1681 25.69% 25.61% 48.70% -14.3 0
2011-07-17 Aalborg D 2-2 1676 1636 47.52% 25.73% 26.75% -0.8 1
2011-07-17 @ Brondby D 2-2 1636 1676 26.75% 25.73% 47.52% +0.9 1
2011-07-17 FC Copenhagen L 0-2 1621 1720 28.63% 25.92% 45.45% -15.6 0
2011-07-17 @ Sonderjyske W 2-0 1720 1621 45.45% 25.92% 28.63% +15.6 3
2011-07-17 HB Koge W 3-0 1624 1601 45.31% 25.93% 28.76% +22.7 3
2011-07-17 @ Horsens L 0-3 1601 1624 28.76% 25.93% 45.31% -22.7 0
2011-07-17 Silkeborg L 1-2 1662 1637 45.53% 25.91% 28.56% -11.1 0
2011-07-17 @ Midtjylland W 2-1 1637 1662 28.56% 25.91% 45.53% +11.1 3
2011-07-18 Lyngby W 2-1 1635 1618 44.43% 26.00% 29.58% +8.0 3
2011-07-18 @ Aarhus GF L 1-2 1618 1635 29.58% 26.00% 44.43% -8.0 0
2011-07-23 Brondby L 0-1 1648 1675 38.24% 26.24% 35.52% -10.3 3
2011-07-23 @ Silkeborg W 1-0 1675 1648 35.52% 26.24% 38.24% +10.3 4
2011-07-23 Odense D 2-2 1736 1696 47.44% 25.74% 26.81% -0.9 4
2011-07-23 @ FC Copenhagen D 2-2 1696 1736 26.81% 25.74% 47.44% +0.8 4
2011-07-24 Aarhus GF W 2-1 1636 1643 41.20% 26.17% 32.64% +8.6 4
2011-07-24 @ Aalborg L 1-2 1643 1636 32.64% 26.17% 41.20% -8.6 3
2011-07-24 Horsens D 1-1 1617 1647 37.89% 26.24% 35.87% -0.1 1
2011-07-24 @ Nordsjaelland D 1-1 1647 1617 35.87% 26.24% 37.89% +0.1 4
2011-07-24 Sonderjyske L 0-1 1610 1606 42.61% 26.10% 31.29% -11.2 0
2011-07-24 @ Lyngby W 1-0 1606 1610 31.29% 26.10% 42.61% +11.2 3
2011-07-25 Midtjylland L 2-3 1578 1651 31.86% 26.13% 42.01% -8.0 0
2011-07-25 @ HB Koge W 3-2 1651 1578 42.01% 26.13% 31.86% +8.0 3
2011-07-30 Nordsjaelland W 2-0 1735 1617 56.67% 24.29% 19.04% +11.0 7
2011-07-30 @ FC Copenhagen L 0-2 1617 1735 19.04% 24.29% 56.67% -11.0 1
2011-07-30 Odense D 2-2 1634 1697 33.34% 26.19% 40.47% +0.3 4
2011-07-30 @ Aarhus GF D 2-2 1697 1634 40.47% 26.19% 33.34% -0.3 5
2011-07-31 HB Koge W 3-1 1598 1570 45.95% 25.88% 28.17% +13.3 3
2011-07-31 @ Lyngby L 1-3 1570 1598 28.17% 25.88% 45.95% -13.3 0
2011-07-31 Horsens L 1-4 1686 1647 47.24% 25.76% 27.00% -28.1 4
2011-07-31 @ Brondby W 4-1 1647 1686 27.00% 25.76% 47.24% +28.1 7
2011-07-31 Sonderjyske D 1-1 1638 1617 44.88% 25.96% 29.16% -0.9 4
2011-07-31 @ Silkeborg D 1-1 1617 1638 29.16% 25.96% 44.88% +0.9 4
2011-08-01 Midtjylland W 1-0 1645 1659 40.11% 26.20% 33.68% +9.4 7
2011-08-01 @ Aalborg L 0-1 1659 1645 33.68% 26.20% 40.11% -9.4 3
2011-08-06 Aalborg D 3-3 1675 1654 44.92% 25.96% 29.12% -0.5 8
2011-08-06 @ Horsens D 3-3 1654 1675 29.12% 25.96% 44.92% +0.5 8
2011-08-06 Aarhus GF W 3-1 1618 1635 39.78% 26.21% 34.01% +15.4 7
2011-08-06 @ Sonderjyske L 1-3 1635 1618 34.01% 26.21% 39.78% -15.4 4
2011-08-07 Brondby W 2-1 1696 1658 47.24% 25.76% 27.00% +7.4 8
2011-08-07 @ Odense L 1-2 1658 1696 27.00% 25.76% 47.24% -7.4 4
2011-08-07 FC Copenhagen L 2-4 1556 1746 19.26% 24.35% 56.40% -8.6 0
2011-08-07 @ HB Koge W 4-2 1746 1556 56.40% 24.35% 19.26% +8.6 10
2011-08-07 Lyngby W 2-1 1650 1612 47.17% 25.77% 27.06% +7.4 6
2011-08-07 @ Midtjylland L 1-2 1612 1650 27.06% 25.77% 47.17% -7.4 3
2011-08-07 Silkeborg W 2-1 1606 1637 37.76% 26.24% 36.00% +9.3 4
2011-08-07 @ Nordsjaelland L 1-2 1637 1606 36.00% 26.24% 37.76% -9.3 4
2011-08-13 Midtjylland W 2-0 1755 1657 54.36% 24.76% 20.88% +11.9 13
2011-08-13 @ FC Copenhagen L 0-2 1657 1755 20.88% 24.76% 54.36% -11.9 6
2011-08-13 Odense W 2-1 1655 1704 35.20% 26.23% 38.56% +9.8 11
2011-08-13 @ Aalborg L 1-2 1704 1655 38.56% 26.23% 35.20% -9.8 8
2011-08-14 HB Koge W 2-0 1615 1548 50.84% 25.33% 23.82% +13.4 7
2011-08-14 @ Nordsjaelland L 0-2 1548 1615 23.82% 25.33% 50.84% -13.4 0
2011-08-14 Horsens D 1-1 1604 1675 32.25% 26.15% 41.60% +0.5 4
2011-08-14 @ Lyngby D 1-1 1675 1604 41.60% 26.15% 32.25% -0.5 9
2011-08-14 Sonderjyske D 2-2 1650 1633 44.38% 26.00% 29.62% -0.6 5
2011-08-14 @ Brondby D 2-2 1633 1650 29.62% 26.00% 44.38% +0.6 8
2011-08-15 Aarhus GF D 1-1 1628 1619 43.25% 26.07% 30.68% -0.7 5
2011-08-15 @ Silkeborg D 1-1 1619 1628 30.68% 26.07% 43.25% +0.7 5
2011-08-20 FC Copenhagen L 0-1 1674 1767 29.43% 25.99% 44.58% -8.4 9
2011-08-20 @ Horsens W 1-0 1767 1674 44.58% 25.99% 29.43% +8.4 16
2011-08-20 Lyngby W 3-1 1694 1605 53.41% 24.93% 21.66% +10.7 11
2011-08-20 @ Odense L 1-3 1605 1694 21.66% 24.93% 53.41% -10.7 4
2011-08-21 Brondby D 0-0 1620 1650 37.90% 26.24% 35.86% -0.1 6
2011-08-21 @ Aarhus GF D 0-0 1650 1620 35.86% 26.24% 37.90% +0.1 6
2011-08-21 Nordsjaelland W 2-1 1645 1629 44.36% 26.00% 29.64% +8.0 9
2011-08-21 @ Midtjylland L 1-2 1629 1645 29.64% 26.00% 44.36% -8.0 7
2011-08-21 Silkeborg W 3-0 1534 1627 29.43% 25.99% 44.59% +31.8 3
2011-08-21 @ HB Koge L 0-3 1627 1534 44.59% 25.99% 29.43% -31.8 5
2011-08-22 Aalborg D 0-0 1634 1665 37.77% 26.24% 35.98% -0.1 9
2011-08-22 @ Sonderjyske D 0-0 1665 1634 35.98% 26.24% 37.77% +0.1 12
2011-08-27 Aalborg L 1-4 1566 1665 28.68% 25.92% 45.40% -19.1 3
2011-08-27 @ HB Koge W 4-1 1665 1566 45.40% 25.92% 28.68% +19.1 15
2011-08-28 Brondby W 2-1 1653 1650 42.59% 26.11% 31.31% +8.4 12
2011-08-28 @ Midtjylland L 1-2 1650 1653 31.31% 26.11% 42.59% -8.3 6
2011-08-28 Lyngby W 4-0 1621 1594 45.66% 25.90% 28.43% +29.4 10
2011-08-28 @ Nordsjaelland L 0-4 1594 1621 28.43% 25.90% 45.66% -29.4 4
2011-08-28 Silkeborg W 2-1 1775 1595 62.94% 22.59% 14.46% +4.2 19
2011-08-28 @ FC Copenhagen L 1-2 1595 1775 14.46% 22.59% 62.94% -4.2 5
2011-08-28 Sonderjyske L 2-4 1705 1634 51.25% 25.28% 23.48% -19.0 11
2011-08-28 @ Odense W 4-2 1634 1705 23.48% 25.28% 51.25% +19.1 12
2011-08-29 Aarhus GF L 0-3 1666 1620 48.20% 25.66% 26.14% -33.9 9
2011-08-29 @ Horsens W 3-0 1620 1666 26.14% 25.66% 48.20% +33.9 9
2011-09-10 FC Copenhagen L 0-1 1565 1779 17.24% 23.72% 59.04% -5.3 4
2011-09-10 @ Lyngby W 1-0 1779 1565 59.04% 23.72% 17.24% +5.3 22
2011-09-10 Odense L 1-3 1591 1686 29.14% 25.96% 44.89% -13.7 5
2011-09-10 @ Silkeborg W 3-1 1686 1591 44.89% 25.96% 29.14% +13.7 14
2011-09-11 HB Koge W 5-0 1641 1547 54.00% 24.83% 21.17% +28.3 9
2011-09-11 @ Brondby L 0-5 1547 1641 21.17% 24.83% 54.00% -28.3 3
2011-09-11 Horsens L 1-3 1653 1632 44.93% 25.96% 29.11% -19.1 12
2011-09-11 @ Sonderjyske W 3-1 1632 1653 29.11% 25.96% 44.93% +19.1 12
2011-09-11 Nordsjaelland L 1-2 1684 1650 46.62% 25.82% 27.56% -11.3 15
2011-09-11 @ Aalborg W 2-1 1650 1684 27.56% 25.82% 46.62% +11.4 13
2011-09-12 Midtjylland W 4-2 1654 1662 40.96% 26.18% 32.86% +13.4 12
2011-09-12 @ Aarhus GF L 2-4 1662 1654 32.86% 26.18% 40.96% -13.4 12
2011-09-17 Aarhus GF L 0-2 1519 1667 23.14% 25.22% 51.65% -13.1 3
2011-09-17 @ HB Koge W 2-0 1667 1519 51.65% 25.22% 23.14% +13.0 15
2011-09-18 Aalborg W 2-0 1785 1673 56.01% 24.43% 19.56% +11.2 25
2011-09-18 @ FC Copenhagen L 0-2 1673 1785 19.56% 24.43% 56.01% -11.3 15
2011-09-18 Brondby W 2-0 1661 1670 40.95% 26.18% 32.88% +17.3 16
2011-09-18 @ Nordsjaelland L 0-2 1670 1661 32.88% 26.18% 40.95% -17.3 9
2011-09-18 Silkeborg L 0-2 1559 1577 39.62% 26.21% 34.16% -20.0 4
2011-09-18 @ Lyngby W 2-0 1577 1559 34.16% 26.21% 39.62% +20.0 8
2011-09-18 Sonderjyske W 2-0 1648 1634 44.06% 26.02% 29.92% +16.1 15
2011-09-18 @ Midtjylland L 0-2 1634 1648 29.92% 26.02% 44.06% -16.1 12
2011-09-19 Odense W 4-3 1651 1699 35.28% 26.24% 38.49% +9.0 15
2011-09-19 @ Horsens L 3-4 1699 1651 38.49% 26.24% 35.28% -9.0 14
2011-09-24 FC Copenhagen L 1-2 1652 1796 23.61% 25.30% 51.10% -6.6 9
2011-09-24 @ Brondby W 2-1 1796 1652 51.10% 25.30% 23.61% +6.7 28
2011-09-24 Nordsjaelland W 1-0 1680 1679 42.27% 26.12% 31.61% +8.9 18
2011-09-24 @ Aarhus GF L 0-1 1679 1680 31.61% 26.12% 42.27% -8.9 16
2011-09-25 HB Koge D 0-0 1618 1506 55.98% 24.44% 19.58% -2.3 13
2011-09-25 @ Sonderjyske D 0-0 1506 1618 19.58% 24.44% 55.98% +2.3 4
2011-09-25 Horsens D 1-1 1597 1660 33.26% 26.19% 40.55% +0.4 9
2011-09-25 @ Silkeborg D 1-1 1660 1597 40.55% 26.19% 33.26% -0.4 16
2011-09-25 Midtjylland L 1-4 1690 1664 45.57% 25.91% 28.52% -27.3 14
2011-09-25 @ Odense W 4-1 1664 1690 28.52% 25.91% 45.57% +27.3 18
2011-09-26 Lyngby L 1-2 1661 1540 57.06% 24.20% 18.74% -13.5 15
2011-09-26 @ Aalborg W 2-1 1540 1661 18.74% 24.20% 57.06% +13.5 7
2011-10-01 Aalborg D 1-1 1598 1648 35.00% 26.23% 38.77% +0.2 10
2011-10-01 @ Silkeborg D 1-1 1648 1598 38.77% 26.23% 35.00% -0.2 16
2011-10-02 Aarhus GF D 1-1 1802 1689 56.16% 24.40% 19.44% -2.1 29
2011-10-02 @ FC Copenhagen D 1-1 1689 1802 19.44% 24.40% 56.16% +2.1 19
2011-10-02 HB Koge W 2-1 1663 1508 60.48% 23.33% 16.18% +4.7 17
2011-10-02 @ Odense L 1-2 1508 1663 16.18% 23.33% 60.48% -4.7 4
2011-10-02 Lyngby W 1-0 1646 1553 53.83% 24.86% 21.32% +6.5 12
2011-10-02 @ Brondby L 0-1 1553 1646 21.32% 24.86% 53.83% -6.5 7
2011-10-02 Sonderjyske W 1-0 1670 1615 49.25% 25.54% 25.21% +7.4 19
2011-10-02 @ Nordsjaelland L 0-1 1615 1670 25.21% 25.54% 49.25% -7.4 13
2011-10-03 Horsens W 1-0 1692 1660 46.39% 25.84% 27.77% +8.1 21
2011-10-03 @ Midtjylland L 0-1 1660 1692 27.77% 25.84% 46.39% -8.1 16
2011-10-15 Aalborg W 1-0 1677 1648 46.08% 25.87% 28.05% +8.1 22
2011-10-15 @ Nordsjaelland L 0-1 1648 1677 28.05% 25.87% 46.08% -8.1 16
2011-10-16 Brondby W 1-0 1700 1652 48.39% 25.64% 25.97% +7.6 24
2011-10-16 @ Midtjylland L 0-1 1652 1700 25.97% 25.64% 48.39% -7.6 12
2011-10-16 Odense D 0-0 1691 1668 45.26% 25.94% 28.80% -1.0 20
2011-10-16 @ Aarhus GF D 0-0 1668 1691 28.80% 25.94% 45.26% +1.0 18
2011-10-16 Silkeborg L 2-3 1547 1598 34.87% 26.23% 38.90% -8.6 7
2011-10-16 @ Lyngby W 3-2 1598 1547 38.90% 26.23% 34.87% +8.6 13
2011-10-16 Sonderjyske L 1-3 1504 1608 27.96% 25.86% 46.17% -13.2 4
2011-10-16 @ HB Koge W 3-1 1608 1504 46.17% 25.86% 27.96% +13.2 16
2011-10-17 FC Copenhagen W 2-0 1652 1800 23.06% 25.20% 51.73% +24.8 19
2011-10-17 @ Horsens L 0-2 1800 1652 51.73% 25.20% 23.06% -24.8 29
2011-10-22 Aarhus GF D 1-1 1538 1690 22.73% 25.14% 52.13% +1.6 8
2011-10-22 @ Lyngby D 1-1 1690 1538 52.13% 25.14% 22.73% -1.6 21
2011-10-23 Brondby W 2-1 1606 1644 36.71% 26.25% 37.05% +9.5 16
2011-10-23 @ Silkeborg L 1-2 1644 1606 37.05% 26.25% 36.71% -9.5 12
2011-10-23 Horsens L 1-4 1621 1676 34.31% 26.22% 39.48% -21.9 16
2011-10-23 @ Sonderjyske W 4-1 1676 1621 39.48% 26.22% 34.31% +21.9 22
2011-10-23 Midtjylland D 1-1 1490 1707 17.03% 23.65% 59.31% +2.5 5
2011-10-23 @ HB Koge D 1-1 1707 1490 59.31% 23.65% 17.03% -2.5 25
2011-10-23 Odense W 2-1 1639 1669 38.00% 26.24% 35.76% +9.2 19
2011-10-23 @ Aalborg L 1-2 1669 1639 35.76% 26.24% 38.00% -9.2 18
2011-10-24 Nordsjaelland L 1-3 1776 1685 53.54% 24.91% 21.55% -22.1 29
2011-10-24 @ FC Copenhagen W 3-1 1685 1776 21.55% 24.91% 53.54% +22.1 25
2011-10-29 Silkeborg D 1-1 1698 1616 52.64% 25.06% 22.30% -1.7 23
2011-10-29 @ Horsens D 1-1 1616 1698 22.30% 25.06% 52.64% +1.7 17
2011-10-30 Aalborg D 1-1 1635 1649 40.19% 26.20% 33.61% -0.3 13
2011-10-30 @ Brondby D 1-1 1649 1635 33.61% 26.20% 40.19% +0.3 20
2011-10-30 FC Copenhagen L 1-3 1659 1753 29.22% 25.97% 44.81% -13.7 18
2011-10-30 @ Odense W 3-1 1753 1659 44.81% 25.97% 29.22% +13.7 32
2011-10-30 HB Koge W 2-0 1688 1493 64.41% 22.10% 13.49% +7.8 24
2011-10-30 @ Aarhus GF L 0-2 1493 1688 13.49% 22.10% 64.41% -7.8 5
2011-10-30 Lyngby L 0-1 1708 1540 61.79% 22.95% 15.26% -15.3 25
2011-10-30 @ Nordsjaelland W 1-0 1540 1708 15.26% 22.95% 61.79% +15.3 11
2011-10-31 Sonderjyske D 1-1 1705 1599 55.31% 24.58% 20.12% -2.0 26
2011-10-31 @ Midtjylland D 1-1 1599 1705 20.12% 24.58% 55.31% +2.0 17
2011-11-05 Horsens W 2-0 1649 1697 35.38% 26.24% 38.39% +19.5 23
2011-11-05 @ Aalborg L 0-2 1697 1649 38.39% 26.24% 35.38% -19.5 23
2011-11-06 Brondby D 0-0 1646 1635 43.59% 26.05% 30.36% -0.8 19
2011-11-06 @ Odense D 0-0 1635 1646 30.36% 26.05% 43.59% +0.8 14
2011-11-06 Lyngby W 3-0 1767 1555 65.89% 21.57% 12.54% +10.6 35
2011-11-06 @ FC Copenhagen L 0-3 1555 1767 12.54% 21.57% 65.89% -10.6 11
2011-11-06 Midtjylland W 4-1 1618 1703 30.31% 26.05% 43.65% +26.4 20
2011-11-06 @ Silkeborg L 1-4 1703 1618 43.65% 26.05% 30.31% -26.4 26
2011-11-06 Nordsjaelland L 0-2 1485 1692 17.80% 23.91% 58.29% -10.3 5
2011-11-06 @ HB Koge W 2-0 1692 1485 58.29% 23.91% 17.80% +10.3 28
2011-11-07 Aarhus GF D 1-1 1601 1696 29.09% 25.96% 44.95% +0.8 18
2011-11-07 @ Sonderjyske D 1-1 1696 1601 44.95% 25.96% 29.09% -0.9 25
2011-11-19 Odense L 0-1 1677 1645 46.41% 25.84% 27.75% -12.0 23
2011-11-19 @ Horsens W 1-0 1645 1677 27.75% 25.84% 46.41% +12.0 22
2011-11-20 Aalborg L 1-3 1677 1669 43.19% 26.07% 30.74% -18.5 26
2011-11-20 @ Midtjylland W 3-1 1669 1677 30.74% 26.07% 43.19% +18.5 26
2011-11-20 FC Copenhagen W 2-1 1635 1778 23.73% 25.32% 50.95% +12.2 17
2011-11-20 @ Brondby L 1-2 1778 1635 50.95% 25.32% 23.73% -12.2 35
2011-11-20 HB Koge D 2-2 1544 1475 51.13% 25.29% 23.57% -1.2 12
2011-11-20 @ Lyngby D 2-2 1475 1544 23.57% 25.29% 51.13% +1.2 6
2011-11-20 Sonderjyske W 2-0 1702 1602 54.71% 24.69% 20.60% +11.8 31
2011-11-20 @ Nordsjaelland L 0-2 1602 1702 20.60% 24.69% 54.71% -11.8 18
2011-11-21 Silkeborg L 0-2 1695 1644 48.88% 25.59% 25.53% -23.6 25
2011-11-21 @ Aarhus GF W 2-0 1644 1695 25.53% 25.59% 48.88% +23.6 23
2011-11-26 Midtjylland L 2-3 1657 1658 41.93% 26.14% 31.94% -9.9 22
2011-11-26 @ Odense W 3-2 1658 1657 31.94% 26.14% 41.93% +9.9 29
2011-11-27 Aarhus GF L 0-2 1687 1672 44.16% 26.01% 29.83% -21.7 26
2011-11-27 @ Aalborg W 2-0 1672 1687 29.83% 26.01% 44.16% +21.7 28
2011-11-27 HB Koge W 2-1 1765 1476 72.23% 18.87% 8.90% +2.5 38
2011-11-27 @ FC Copenhagen L 1-2 1476 1765 8.90% 18.87% 72.23% -2.5 6
2011-11-27 Lyngby W 3-1 1590 1543 48.31% 25.65% 26.04% +12.5 21
2011-11-27 @ Sonderjyske L 1-3 1543 1590 26.04% 25.65% 48.31% -12.5 12
2011-11-27 Nordsjaelland L 1-2 1668 1714 35.48% 26.24% 38.28% -9.2 23
2011-11-27 @ Silkeborg W 2-1 1714 1668 38.28% 26.24% 35.48% +9.2 34
2011-11-28 Horsens L 0-1 1648 1665 39.67% 26.21% 34.12% -10.6 17
2011-11-28 @ Brondby W 1-0 1665 1648 34.12% 26.21% 39.67% +10.6 26
2011-12-03 Aalborg W 4-2 1658 1665 41.13% 26.17% 32.70% +13.4 26
2011-12-03 @ Silkeborg L 2-4 1665 1658 32.70% 26.17% 41.13% -13.4 26
2011-12-04 Aarhus GF D 0-0 1768 1694 51.69% 25.21% 23.10% -1.8 39
2011-12-04 @ FC Copenhagen D 0-0 1694 1768 23.10% 25.21% 51.69% +1.8 29
2011-12-04 Brondby D 1-1 1473 1637 21.58% 24.91% 53.51% +1.8 7
2011-12-04 @ HB Koge D 1-1 1637 1473 53.51% 24.91% 21.58% -1.8 18
2011-12-04 Horsens L 1-2 1531 1676 23.46% 25.27% 51.27% -6.6 12
2011-12-04 @ Lyngby W 2-1 1676 1531 51.27% 25.27% 23.46% +6.6 29
2011-12-04 Midtjylland D 0-0 1723 1668 49.38% 25.53% 25.09% -1.5 35
2011-12-04 @ Nordsjaelland D 0-0 1668 1723 25.09% 25.53% 49.38% +1.5 30
2011-12-05 Odense L 0-4 1603 1647 35.84% 26.24% 37.91% -35.1 21
2011-12-05 @ Sonderjyske W 4-0 1647 1603 37.91% 26.24% 35.84% +35.1 25
2012-03-03 Nordsjaelland D 1-1 1695 1722 38.36% 26.24% 35.40% -0.2 30
2012-03-03 @ Aarhus GF D 1-1 1722 1695 35.40% 26.24% 38.36% +0.1 36
2012-03-04 FC Copenhagen D 1-1 1652 1766 26.80% 25.74% 47.46% +1.1 27
2012-03-04 @ Aalborg D 1-1 1766 1652 47.46% 25.74% 26.80% -1.1 40
2012-03-04 HB Koge W 2-1 1682 1475 65.45% 21.73% 12.81% +3.7 32
2012-03-04 @ Horsens L 1-2 1475 1682 12.81% 21.73% 65.45% -3.7 7
2012-03-04 Lyngby L 1-2 1669 1524 59.54% 23.59% 16.87% -14.0 30
2012-03-04 @ Midtjylland W 2-1 1524 1669 16.87% 23.59% 59.54% +14.0 15
2012-03-04 Sonderjyske W 1-0 1635 1568 50.87% 25.33% 23.80% +7.1 21
2012-03-04 @ Brondby L 0-1 1568 1635 23.80% 25.33% 50.87% -7.1 21
2012-03-05 Silkeborg D 2-2 1682 1672 43.51% 26.05% 30.43% -0.5 26
2012-03-05 @ Odense D 2-2 1672 1682 30.43% 26.05% 43.51% +0.5 27
2012-03-10 Nordsjaelland L 0-1 1682 1722 36.37% 26.25% 37.39% -9.9 26
2012-03-10 @ Odense W 1-0 1722 1682 37.39% 26.25% 36.37% +9.9 39
2012-03-11 Aarhus GF D 0-0 1642 1695 34.64% 26.22% 39.13% +0.3 22
2012-03-11 @ Brondby D 0-0 1695 1642 39.13% 26.22% 34.64% -0.3 31
2012-03-11 HB Koge L 0-1 1672 1471 64.88% 21.94% 13.18% -16.0 27
2012-03-11 @ Silkeborg W 1-0 1471 1672 13.18% 21.94% 64.88% +16.0 10
2012-03-11 Lyngby W 1-0 1653 1538 56.32% 24.37% 19.32% +5.9 30
2012-03-11 @ Aalborg L 0-1 1538 1653 19.32% 24.37% 56.32% -5.9 15
2012-03-11 Sonderjyske W 2-0 1765 1561 65.21% 21.82% 12.97% +7.5 43
2012-03-11 @ FC Copenhagen L 0-2 1561 1765 12.97% 21.82% 65.21% -7.5 21
2012-03-12 Horsens W 4-1 1655 1686 37.80% 26.24% 35.96% +22.7 33
2012-03-12 @ Midtjylland L 1-4 1686 1655 35.96% 26.24% 37.80% -22.7 32
2012-03-17 Horsens L 1-3 1695 1663 46.33% 25.85% 27.82% -19.6 31
2012-03-17 @ Aarhus GF W 3-1 1663 1695 27.82% 25.85% 46.33% +19.6 35
2012-03-18 Brondby L 1-2 1732 1643 53.45% 24.92% 21.63% -12.7 39
2012-03-18 @ Nordsjaelland W 2-1 1643 1732 21.63% 24.92% 53.45% +12.7 25
2012-03-18 Midtjylland D 0-0 1773 1678 54.03% 24.82% 21.15% -2.1 44
2012-03-18 @ FC Copenhagen D 0-0 1678 1773 21.15% 24.82% 54.03% +2.1 34
2012-03-18 Odense W 1-0 1532 1672 24.03% 25.37% 50.60% +12.9 18
2012-03-18 @ Lyngby L 0-1 1672 1532 50.60% 25.37% 24.03% -12.9 26
2012-03-18 Silkeborg L 2-4 1553 1656 28.10% 25.87% 46.02% -11.9 21
2012-03-18 @ Sonderjyske W 4-2 1656 1553 46.02% 25.87% 28.10% +11.9 30
2012-03-19 Aalborg D 1-1 1487 1659 20.85% 24.75% 54.40% +1.9 11
2012-03-19 @ HB Koge D 1-1 1659 1487 54.40% 24.75% 20.85% -1.9 31
2012-03-24 Sonderjyske L 1-2 1657 1541 56.43% 24.34% 19.23% -13.4 31
2012-03-24 @ Aalborg W 2-1 1541 1657 19.23% 24.34% 56.43% +13.4 24
2012-03-25 FC Copenhagen D 0-0 1668 1770 28.20% 25.88% 45.91% +1.1 31
2012-03-25 @ Silkeborg D 0-0 1770 1668 45.91% 25.88% 28.20% -1.1 45
2012-03-25 HB Koge L 2-4 1659 1489 61.95% 22.91% 15.15% -22.5 26
2012-03-25 @ Odense W 4-2 1489 1659 15.15% 22.91% 61.95% +22.5 14
2012-03-25 Lyngby W 2-1 1655 1545 55.81% 24.47% 19.72% +5.7 28
2012-03-25 @ Brondby L 1-2 1545 1655 19.72% 24.47% 55.81% -5.7 18
2012-03-25 Nordsjaelland L 0-2 1683 1719 36.96% 26.25% 36.80% -18.9 35
2012-03-25 @ Horsens W 2-0 1719 1683 36.80% 26.25% 36.96% +18.9 42
2012-03-26 Aarhus GF L 0-2 1680 1675 42.77% 26.10% 31.14% -21.2 34
2012-03-26 @ Midtjylland W 2-0 1675 1680 31.14% 26.10% 42.77% +21.2 34
2012-03-31 Aalborg W 1-0 1664 1644 44.84% 25.97% 29.20% +8.4 38
2012-03-31 @ Horsens L 0-1 1644 1664 29.20% 25.97% 44.84% -8.4 31
2012-04-01 FC Copenhagen L 1-3 1539 1769 16.09% 23.30% 60.61% -8.1 18
2012-04-01 @ Lyngby W 3-1 1769 1539 60.61% 23.30% 16.09% +8.1 48
2012-04-01 HB Koge W 2-0 1738 1512 67.14% 21.09% 11.77% +6.8 45
2012-04-01 @ Nordsjaelland L 0-2 1512 1738 11.77% 21.09% 67.14% -6.8 14
2012-04-01 Odense W 1-0 1661 1636 45.43% 25.92% 28.65% +8.3 31
2012-04-01 @ Brondby L 0-1 1636 1661 28.65% 25.92% 45.43% -8.3 26
2012-04-01 Silkeborg D 2-2 1659 1669 40.69% 26.18% 33.12% -0.3 35
2012-04-01 @ Midtjylland D 2-2 1669 1659 33.12% 26.18% 40.69% +0.3 32
2012-04-02 Sonderjyske L 1-3 1697 1554 59.20% 23.68% 17.12% -24.1 34
2012-04-02 @ Aarhus GF W 3-1 1554 1697 17.12% 23.68% 59.20% +24.1 27
2012-04-04 Midtjylland L 1-2 1635 1659 38.80% 26.23% 34.97% -9.8 31
2012-04-04 @ Aalborg W 2-1 1659 1635 34.97% 26.23% 38.80% +9.8 38
2012-04-05 Aarhus GF W 2-1 1669 1672 41.69% 26.15% 32.16% +8.5 35
2012-04-05 @ Silkeborg L 1-2 1672 1669 32.16% 26.15% 41.69% -8.5 34
2012-04-05 Brondby W 3-1 1778 1669 55.58% 24.52% 19.90% +9.9 51
2012-04-05 @ FC Copenhagen L 1-3 1669 1778 19.90% 24.52% 55.58% -9.9 31
2012-04-05 Lyngby L 1-4 1505 1531 38.38% 26.24% 35.39% -23.8 14
2012-04-05 @ HB Koge W 4-1 1531 1505 35.39% 26.24% 38.38% +23.9 21
2012-04-05 Nordsjaelland W 1-0 1579 1745 21.34% 24.86% 53.80% +13.6 30
2012-04-05 @ Sonderjyske L 0-1 1745 1579 53.80% 24.86% 21.34% -13.6 45
2012-04-06 Horsens L 0-1 1628 1672 35.84% 26.24% 37.92% -9.8 26
2012-04-06 @ Odense W 1-0 1672 1628 37.92% 26.24% 35.84% +9.8 41
2012-04-08 Nordsjaelland D 1-1 1669 1731 33.27% 26.19% 40.54% +0.4 39
2012-04-08 @ Midtjylland D 1-1 1731 1669 40.54% 26.19% 33.27% -0.4 46
2012-04-08 Silkeborg W 3-1 1625 1678 34.67% 26.23% 39.10% +17.1 34
2012-04-08 @ Aalborg L 1-3 1678 1625 39.10% 26.23% 34.67% -17.1 35
2012-04-09 FC Copenhagen D 0-0 1664 1787 25.75% 25.61% 48.64% +1.4 35
2012-04-09 @ Aarhus GF D 0-0 1787 1664 48.64% 25.61% 25.75% -1.4 52
2012-04-09 HB Koge D 1-1 1659 1481 62.80% 22.64% 14.56% -2.9 32
2012-04-09 @ Brondby D 1-1 1481 1659 14.56% 22.64% 62.80% +2.8 15
2012-04-09 Lyngby D 0-0 1682 1555 57.62% 24.07% 18.31% -2.5 42
2012-04-09 @ Horsens D 0-0 1555 1682 18.31% 24.07% 57.62% +2.5 22
2012-04-09 Sonderjyske D 1-1 1618 1592 45.60% 25.91% 28.49% -0.9 27
2012-04-09 @ Odense D 1-1 1592 1618 28.49% 25.91% 45.60% +0.9 31
2012-04-14 Odense W 2-0 1669 1617 48.90% 25.58% 25.51% +14.2 42
2012-04-14 @ Midtjylland L 0-2 1617 1669 25.51% 25.58% 48.90% -14.2 27
2012-04-15 Brondby W 2-0 1680 1657 45.20% 25.94% 28.86% +15.7 45
2012-04-15 @ Horsens L 0-2 1657 1680 28.86% 25.94% 45.20% -15.7 32
2012-04-15 FC Copenhagen L 0-5 1484 1786 11.68% 21.04% 67.28% -15.8 15
2012-04-15 @ HB Koge W 5-0 1786 1484 67.28% 21.04% 11.68% +15.8 55
2012-04-15 Silkeborg W 2-1 1731 1661 51.17% 25.29% 23.54% +6.6 49
2012-04-15 @ Nordsjaelland L 1-2 1661 1731 23.54% 25.29% 51.17% -6.6 35
2012-04-15 Sonderjyske L 0-4 1558 1593 37.11% 26.25% 36.65% -36.0 22
2012-04-15 @ Lyngby W 4-0 1593 1558 36.65% 26.25% 37.11% +36.0 34
2012-04-16 Aalborg D 1-1 1665 1643 45.16% 25.94% 28.90% -0.9 36
2012-04-16 @ Aarhus GF D 1-1 1643 1665 28.90% 25.94% 45.16% +0.9 35
2012-04-21 Nordsjaelland L 0-2 1643 1738 29.20% 25.97% 44.83% -15.8 35
2012-04-21 @ Aalborg W 2-0 1738 1643 44.83% 25.97% 29.20% +15.8 52
2012-04-22 HB Koge W 2-1 1629 1468 61.12% 23.15% 15.73% +4.6 37
2012-04-22 @ Sonderjyske L 1-2 1468 1629 15.73% 23.15% 61.12% -4.6 15
2012-04-22 Horsens W 2-1 1802 1695 55.40% 24.56% 20.04% +5.8 58
2012-04-22 @ FC Copenhagen L 1-2 1695 1802 20.04% 24.56% 55.40% -5.8 45
2012-04-22 Lyngby W 3-0 1654 1522 58.22% 23.93% 17.86% +15.0 38
2012-04-22 @ Silkeborg L 0-3 1522 1654 17.86% 23.93% 58.22% -15.0 22
2012-04-22 Midtjylland L 0-2 1641 1683 36.12% 26.24% 37.64% -18.6 32
2012-04-22 @ Brondby W 2-0 1683 1641 37.64% 26.24% 36.12% +18.6 45
2012-04-23 Aarhus GF L 1-2 1603 1664 33.48% 26.20% 40.33% -8.8 27
2012-04-23 @ Odense W 2-1 1664 1603 40.33% 26.20% 33.48% +8.8 39
2012-04-28 Aarhus GF W 5-3 1753 1673 52.39% 25.10% 22.51% +9.3 55
2012-04-28 @ Nordsjaelland L 3-5 1673 1753 22.51% 25.10% 52.39% -9.3 39
2012-04-29 Aalborg W 3-0 1808 1628 62.94% 22.59% 14.46% +12.2 61
2012-04-29 @ FC Copenhagen L 0-3 1628 1808 14.46% 22.59% 62.94% -12.2 35
2012-04-29 Brondby D 3-3 1634 1622 43.66% 26.05% 30.30% -0.5 38
2012-04-29 @ Sonderjyske D 3-3 1622 1634 30.30% 26.05% 43.66% +0.5 33
2012-04-29 Horsens W 2-1 1464 1689 16.37% 23.41% 60.22% +14.1 18
2012-04-29 @ HB Koge L 1-2 1689 1464 60.22% 23.41% 16.37% -14.1 45
2012-04-29 Midtjylland L 1-2 1507 1702 18.79% 24.22% 57.00% -5.4 22
2012-04-29 @ Lyngby W 2-1 1702 1507 57.00% 24.22% 18.79% +5.4 48
2012-04-30 Odense D 1-1 1669 1594 51.75% 25.20% 23.04% -1.6 39
2012-04-30 @ Silkeborg D 1-1 1594 1669 23.04% 25.20% 51.75% +1.6 28
2012-05-02 FC Copenhagen W 1-0 1763 1820 34.06% 26.21% 39.72% +10.6 58
2012-05-02 @ Nordsjaelland L 0-1 1820 1763 39.72% 26.21% 34.06% -10.6 61
2012-05-02 Lyngby W 2-1 1664 1501 61.27% 23.11% 15.62% +4.6 42
2012-05-02 @ Aarhus GF L 1-2 1501 1664 15.62% 23.11% 61.27% -4.5 22
2012-05-03 Aalborg L 1-2 1596 1615 39.38% 26.22% 34.40% -9.9 28
2012-05-03 @ Odense W 2-1 1615 1596 34.40% 26.22% 39.38% +9.9 38
2012-05-03 HB Koge W 2-1 1707 1478 67.40% 20.99% 11.61% +3.3 51
2012-05-03 @ Midtjylland L 1-2 1478 1707 11.61% 20.99% 67.40% -3.4 18
2012-05-03 Silkeborg W 3-2 1623 1668 35.74% 26.24% 38.02% +9.2 36
2012-05-03 @ Brondby L 2-3 1668 1623 38.02% 26.24% 35.74% -9.2 39
2012-05-03 Sonderjyske W 5-0 1675 1633 47.68% 25.72% 26.60% +34.3 48
2012-05-03 @ Horsens L 0-5 1633 1675 26.60% 25.72% 47.68% -34.3 38
2012-05-05 Nordsjaelland L 0-2 1497 1773 13.07% 21.88% 65.05% -7.6 22
2012-05-05 @ Lyngby W 2-0 1773 1497 65.05% 21.88% 13.07% +7.6 61
2012-05-06 Aarhus GF L 1-3 1474 1668 18.87% 24.24% 56.89% -9.4 18
2012-05-06 @ HB Koge W 3-1 1668 1474 56.89% 24.24% 18.87% +9.4 45
2012-05-06 Brondby W 1-0 1625 1632 41.18% 26.17% 32.65% +9.2 41
2012-05-06 @ Aalborg L 0-1 1632 1625 32.65% 26.17% 41.18% -9.2 36
2012-05-06 Horsens L 0-1 1659 1710 34.87% 26.23% 38.90% -9.6 39
2012-05-06 @ Silkeborg W 1-0 1710 1659 38.90% 26.23% 34.87% +9.6 51
2012-05-06 Odense D 1-1 1809 1586 66.85% 21.21% 11.94% -3.3 62
2012-05-06 @ FC Copenhagen D 1-1 1586 1809 11.94% 21.21% 66.85% +3.3 29
2012-05-07 Midtjylland D 1-1 1599 1711 27.12% 25.78% 47.11% +1.1 39
2012-05-07 @ Sonderjyske D 1-1 1711 1599 47.11% 25.78% 27.12% -1.1 52
2012-05-12 Midtjylland W 2-1 1719 1709 43.43% 26.06% 30.51% +8.2 54
2012-05-12 @ Horsens L 1-2 1709 1719 30.51% 26.06% 43.43% -8.2 52
2012-05-13 Aalborg W 3-2 1489 1634 23.41% 25.27% 51.32% +11.7 25
2012-05-13 @ Lyngby L 2-3 1634 1489 51.32% 25.27% 23.41% -11.7 41
2012-05-13 Brondby W 5-1 1678 1623 49.33% 25.53% 25.14% +22.2 48
2012-05-13 @ Aarhus GF L 1-5 1623 1678 25.14% 25.53% 49.33% -22.2 36
2012-05-13 FC Copenhagen D 2-2 1600 1806 17.91% 23.95% 58.14% +1.7 40
2012-05-13 @ Sonderjyske D 2-2 1806 1600 58.14% 23.95% 17.91% -1.7 63
2012-05-13 Silkeborg L 1-3 1465 1649 19.73% 24.48% 55.79% -9.8 18
2012-05-13 @ HB Koge W 3-1 1649 1465 55.79% 24.48% 19.73% +9.8 42
2012-05-14 Odense D 0-0 1781 1589 64.04% 22.23% 13.73% -3.3 62
2012-05-14 @ Nordsjaelland D 0-0 1589 1781 13.73% 22.23% 64.04% +3.3 30
2012-05-20 Aarhus GF W 3-1 1727 1700 45.79% 25.89% 28.31% +13.4 57
2012-05-20 @ Horsens L 1-3 1700 1727 28.31% 25.89% 45.79% -13.4 48
2012-05-20 FC Copenhagen W 1-0 1701 1804 28.15% 25.88% 45.98% +11.9 55
2012-05-20 @ Midtjylland L 0-1 1804 1701 45.98% 25.88% 28.15% -11.9 63
2012-05-20 HB Koge W 1-0 1623 1455 61.77% 22.96% 15.27% +4.7 44
2012-05-20 @ Aalborg L 0-1 1455 1623 15.27% 22.96% 61.77% -4.7 18
2012-05-20 Lyngby W 4-0 1593 1501 53.73% 24.87% 21.39% +23.1 33
2012-05-20 @ Odense L 0-4 1501 1593 21.39% 24.87% 53.73% -23.1 25
2012-05-20 Nordsjaelland L 0-1 1601 1778 20.35% 24.63% 55.01% -6.2 36
2012-05-20 @ Brondby W 1-0 1778 1601 55.01% 24.63% 20.35% +6.2 65
2012-05-20 Sonderjyske D 1-1 1659 1602 49.55% 25.50% 24.94% -1.4 43
2012-05-20 @ Silkeborg D 1-1 1602 1659 24.94% 25.50% 49.55% +1.4 41
2012-05-23 Aalborg W 5-0 1603 1628 38.69% 26.23% 35.08% +42.6 44
2012-05-23 @ Sonderjyske L 0-5 1628 1603 35.08% 26.23% 38.69% -42.6 44
2012-05-23 Brondby W 1-0 1478 1594 26.52% 25.71% 47.77% +12.3 28
2012-05-23 @ Lyngby L 0-1 1594 1478 47.77% 25.71% 26.52% -12.3 36
2012-05-23 Horsens W 3-0 1784 1741 47.81% 25.71% 26.49% +21.2 68
2012-05-23 @ Nordsjaelland L 0-3 1741 1784 26.49% 25.71% 47.81% -21.2 57
2012-05-23 Midtjylland L 0-2 1687 1713 38.37% 26.24% 35.40% -19.5 48
2012-05-23 @ Aarhus GF W 2-0 1713 1687 35.40% 26.24% 38.37% +19.5 58
2012-05-23 Odense D 1-1 1450 1616 21.43% 24.88% 53.69% +1.8 19
2012-05-23 @ HB Koge D 1-1 1616 1450 53.69% 24.88% 21.43% -1.8 34
2012-05-23 Silkeborg W 2-1 1792 1657 58.46% 23.87% 17.67% +5.1 66
2012-05-23 @ FC Copenhagen L 1-2 1657 1792 17.67% 23.87% 58.46% -5.1 43

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 2012-03-11 13.18% HB Koge 1471 1 @ Silkeborg 1672 0
2 2012-03-25 15.15% HB Koge 1489 4 @ Odense 1659 2
3 2011-10-30 15.26% Lyngby 1540 1 @ Nordsjaelland 1708 0
4 2012-04-29 16.37% @ HB Koge 1464 2 Horsens 1689 1
5 2012-03-04 16.87% Lyngby 1524 2 @ Midtjylland 1669 1
6 2012-04-02 17.12% Sonderjyske 1554 3 @ Aarhus GF 1697 1
7 2011-09-26 18.74% Lyngby 1540 2 @ Aalborg 1661 1
8 2012-03-24 19.23% Sonderjyske 1541 2 @ Aalborg 1657 1
9 2012-04-05 21.34% @ Sonderjyske 1579 1 Nordsjaelland 1745 0
10 2011-10-24 21.55% Nordsjaelland 1685 3 @ FC Copenhagen 1776 1
11 2012-03-18 21.63% Brondby 1643 2 @ Nordsjaelland 1732 1
12 2011-10-17 23.06% @ Horsens 1652 2 FC Copenhagen 1800 0
13 2012-05-13 23.41% @ Lyngby 1489 3 Aalborg 1634 2
14 2011-08-28 23.48% Sonderjyske 1634 4 @ Odense 1705 2
15 2011-11-20 23.73% @ Brondby 1635 2 FC Copenhagen 1778 1
16 2012-03-18 24.03% @ Lyngby 1532 1 Odense 1672 0
17 2011-11-21 25.53% Silkeborg 1644 2 @ Aarhus GF 1695 0
18 2011-08-29 26.14% Aarhus GF 1620 3 @ Horsens 1666 0
19 2012-05-23 26.52% @ Lyngby 1478 1 Brondby 1594 0
20 2011-07-31 27.00% Horsens 1647 4 @ Brondby 1686 1
21 2011-09-11 27.56% Nordsjaelland 1650 2 @ Aalborg 1684 1
22 2011-11-19 27.75% Odense 1645 1 @ Horsens 1677 0
23 2012-03-17 27.82% Horsens 1663 3 @ Aarhus GF 1695 1
24 2012-05-20 28.15% @ Midtjylland 1701 1 FC Copenhagen 1804 0
25 2011-09-25 28.52% Midtjylland 1664 4 @ Odense 1690 1

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 2012-05-23 42.59 @ Sonderjyske 5 1603 38.69% Aalborg 0 1628 35.08% 26.23%
2 2012-04-15 36.03 Sonderjyske 4 1593 36.65% @ Lyngby 0 1558 37.11% 26.25%
3 2011-12-05 35.12 Odense 4 1647 37.91% @ Sonderjyske 0 1603 35.84% 26.24%
4 2012-05-03 34.32 @ Horsens 5 1675 47.68% Sonderjyske 0 1633 26.60% 25.72%
5 2011-08-29 33.90 Aarhus GF 3 1620 26.14% @ Horsens 0 1666 48.20% 25.66%
6 2011-08-21 31.80 @ HB Koge 3 1534 29.43% Silkeborg 0 1627 44.59% 25.99%
7 2011-08-28 29.38 @ Nordsjaelland 4 1621 45.66% Lyngby 0 1594 28.43% 25.90%
8 2011-09-11 28.26 @ Brondby 5 1641 54.00% HB Koge 0 1547 21.17% 24.83%
9 2011-07-31 28.11 Horsens 4 1647 27.00% @ Brondby 1 1686 47.24% 25.76%
10 2011-09-25 27.29 Midtjylland 4 1664 28.52% @ Odense 1 1690 45.57% 25.91%
11 2011-11-06 26.36 @ Silkeborg 4 1618 30.31% Midtjylland 1 1703 43.65% 26.05%
12 2011-10-17 24.78 @ Horsens 2 1652 23.06% FC Copenhagen 0 1800 51.73% 25.20%
13 2012-04-02 24.13 Sonderjyske 3 1554 17.12% @ Aarhus GF 1 1697 59.20% 23.68%
14 2012-04-05 23.85 Lyngby 4 1531 35.39% @ HB Koge 1 1505 38.38% 26.24%
15 2011-11-21 23.62 Silkeborg 2 1644 25.53% @ Aarhus GF 0 1695 48.88% 25.59%
16 2012-05-20 23.15 @ Odense 4 1593 53.73% Lyngby 0 1501 21.39% 24.87%
17 2012-03-12 22.72 @ Midtjylland 4 1655 37.80% Horsens 1 1686 35.96% 26.24%
18 2011-07-17 22.70 @ Horsens 3 1624 45.31% HB Koge 0 1601 28.76% 25.93%
19 2012-03-25 22.45 HB Koge 4 1489 15.15% @ Odense 2 1659 61.95% 22.91%
20 2012-05-13 22.15 @ Aarhus GF 5 1678 49.33% Brondby 1 1623 25.14% 25.53%
21 2011-10-24 22.10 Nordsjaelland 3 1685 21.55% @ FC Copenhagen 1 1776 53.54% 24.91%
22 2011-10-23 21.94 Horsens 4 1676 39.48% @ Sonderjyske 1 1621 34.31% 26.22%
23 2011-11-27 21.72 Aarhus GF 2 1672 29.83% @ Aalborg 0 1687 44.16% 26.01%
24 2012-05-23 21.24 @ Nordsjaelland 3 1784 47.81% Horsens 0 1741 26.49% 25.71%
25 2012-03-26 21.17 Aarhus GF 2 1675 31.14% @ Midtjylland 0 1680 42.77% 26.10%