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2009-10 Superliga Season

198 games

Final

Champion

FC Copenhagen

68 points · 8th Title

Last Title: 2008-09

Relegated

HB Koge

19 pts

Aarhus GF · 38 pts

Biggest Overachiever

Sonderjyske

6.39 points above expected

41 points · 34.61 expected points

Biggest Disappointment

HB Koge

8.43 points below expected

19 points · 27.43 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 21 5 7 68 61 22 +39 64.84 +3.16
2 Odense 33 17 8 8 59 46 34 +12 60.84 -1.84
3 Brondby 33 15 7 11 52 57 50 +7 51.35 +0.65
4 Esbjerg 33 13 11 9 50 48 43 +5 44.54 +5.46
5 Aalborg 33 13 9 11 48 36 30 +6 46.34 +1.66
6 Midtjylland 33 14 5 14 47 45 48 -3 46.47 +0.53
7 Nordsjaelland 33 12 7 14 43 40 41 -1 42.05 +0.95
8 Silkeborg 33 12 7 14 43 47 51 -4 46.91 -3.91
9 Sonderjyske 33 11 8 14 41 32 37 -5 34.61 +6.39
10 Randers 33 10 10 13 40 37 43 -6 40.78 -0.78
11 Aarhus GF Relegated 33 10 8 15 38 36 47 -11 42.74 -4.74
12 HB Koge Relegated 33 4 7 22 19 30 69 -39 27.43 -8.43

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 1853 68 64.84 +3.16 68.9% 37 53 60 65 70 76 90
Odense 1782 59 60.84 -1.84 42.8% 32 49 56 61 66 73 84
Brondby 1729 52 51.35 +0.65 55.5% 22 39 46 51 56 64 80
Midtjylland 1698 47 46.47 +0.53 55.5% 22 34 41 46 52 59 76
Aalborg 1691 48 46.34 +1.66 61.9% 22 34 41 46 51 59 75
Randers 1688 40 40.78 -0.78 49.0% 14 29 36 41 46 53 69
Nordsjaelland 1676 43 42.05 +0.95 58.1% 17 30 37 42 47 54 70
Esbjerg 1675 50 44.54 +5.46 79.1% 18 32 40 44 49 57 75
Silkeborg 1650 43 46.91 -3.91 32.6% 18 35 42 47 52 59 73
Aarhus GF 1637 38 42.74 -4.74 28.3% 12 31 38 43 48 55 71
Sonderjyske 1631 41 34.61 +6.39 83.3% 11 23 30 34 40 47 63
HB Koge 1531 19 27.43 -8.43 11.6% 6 17 23 27 32 39 56

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 ESB FC HK MID NOR ODE RAN SIL SON
Aalborg —
1-1-1
4.28
1-0-2
3.52
0-2-1
4.31
1-0-2
2.77
2-1-0
5.60
2-0-1
4.32
2-1-0
4.54
1-1-1
2.88
1-1-1
4.53
1-1-1
4.13
1-1-1
5.36
Aarhus GF
1-1-1
3.99
 —
1-0-2
3.30
1-1-1
3.69
1-1-1
2.27
1-1-1
5.72
0-1-2
4.08
2-0-1
4.07
0-1-2
2.79
1-1-1
4.13
1-1-1
3.85
1-0-2
4.97
Brondby
2-0-1
4.76
2-0-1
4.99
 —
0-1-2
4.73
0-1-2
2.74
2-0-1
6.30
2-1-0
4.70
2-0-1
5.25
1-1-1
3.45
2-1-0
4.71
0-1-2
4.32
2-1-0
5.39
Esbjerg
1-2-0
3.96
1-1-1
4.58
2-1-0
3.54
 —
0-1-2
2.49
3-0-0
5.88
1-1-1
3.72
1-1-1
4.25
0-1-2
2.83
1-1-1
4.64
2-1-0
3.91
1-1-1
4.85
FC Copenhagen
2-0-1
5.57
1-1-1
6.13
2-1-0
5.59
2-1-0
5.88
 —
3-0-0
7.01
2-0-1
5.53
1-0-2
6.04
2-1-0
4.33
2-0-1
6.34
1-1-1
5.96
3-0-0
6.42
HB Koge
0-1-2
2.74
1-1-1
2.63
1-0-2
2.12
0-0-3
2.49
0-0-3
1.54
 —
1-0-2
2.48
0-2-1
2.84
0-0-3
1.74
0-1-2
2.87
0-1-2
2.58
1-1-1
3.38
Midtjylland
1-0-2
3.95
2-1-0
4.19
0-1-2
3.58
1-1-1
4.55
1-0-2
2.79
2-0-1
5.88
 —
1-0-2
4.65
1-1-1
2.73
2-0-1
4.70
2-0-1
4.10
1-1-1
5.33
Nordsjaelland
0-1-2
3.73
1-0-2
4.21
1-0-2
3.05
1-1-1
4.01
2-0-1
2.35
1-2-0
5.48
2-0-1
3.62
 —
0-0-3
2.58
0-3-0
4.36
2-0-1
3.83
2-0-1
4.75
Odense
1-1-1
5.44
2-1-0
5.54
1-1-1
4.84
2-1-0
5.50
0-1-2
3.94
3-0-0
6.76
1-1-1
5.60
3-0-0
5.77
 —
1-1-1
5.80
2-0-1
5.31
1-1-1
6.27
Randers
1-1-1
3.74
1-1-1
4.13
0-1-2
3.58
1-1-1
3.64
1-0-2
2.09
2-1-0
5.45
1-0-2
3.58
0-3-0
3.90
1-1-1
2.56
 —
1-0-2
3.54
1-1-1
4.64
Silkeborg
1-1-1
4.14
1-1-1
4.42
2-1-0
3.94
0-1-2
4.36
1-1-1
2.41
2-1-0
5.78
1-0-2
4.17
1-0-2
4.44
1-0-2
3.00
2-0-1
4.74
 —
0-1-2
5.52
Sonderjyske
1-1-1
2.95
2-0-1
3.32
0-1-2
2.93
1-1-1
3.44
0-0-3
2.02
1-1-1
4.90
1-1-1
2.98
1-0-2
3.53
1-1-1
2.15
1-1-1
3.63
2-1-0
2.81
 —

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 0.66 +10.1
Allowed 0.66 -8.2
Differential 0.96 +6.6

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%9.34%7.83%3.03%1.77%0.51%29.04%
19.34%12.12%7.32%3.54%1.52%0.51%34.34%
27.83%7.32%4.04%1.77%1.01%—21.97%
33.03%3.54%1.77%0.51%—0.25%9.09%
41.77%1.52%1.01%———4.29%
5+0.51%0.51%—0.25%——1.26%
Total29.04%34.34%21.97%9.09%4.29%1.26%100%

Summary Statistics

Scored Allowed Difference
Mean 1.30 1.30 +0.00
SD 1.21 1.21 1.83
CV 0.93 0.93 —
Max 7 7 +6
Min 0 0 -6

Games Played: 198

↓ Scored | Allowed →012345+Total
09.09%6.06%15.15%———30.30%
118.18%18.18%9.09%3.03%——48.48%
26.06%3.03%————9.09%
36.06%—3.03%———9.09%
4———————
5+3.03%—————3.03%
Total42.42%27.27%27.27%3.03%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.09 0.91 +0.18
SD 1.13 0.91 1.65
CV 1.03 1.01 —
Max 5 3 +5
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%12.12%9.09%6.06%—3.03%39.39%
112.12%6.06%9.09%———27.27%
23.03%6.06%9.09%3.03%3.03%—24.24%
3——3.03%———3.03%
43.03%3.03%————6.06%
5+———————
Total27.27%27.27%30.30%9.09%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.09 1.42 -0.33
SD 1.16 1.25 1.76
CV 1.06 0.88 —
Max 4 5 +4
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
0—6.06%9.09%3.03%——18.18%
112.12%15.15%3.03%6.06%3.03%—39.39%
23.03%6.06%6.06%—3.03%—18.18%
3—12.12%————12.12%
4——6.06%———6.06%
5+—3.03%—3.03%——6.06%
Total15.15%42.42%24.24%12.12%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.73 1.52 +0.21
SD 1.57 1.09 1.87
CV 0.91 0.72 —
Max 6 4 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
015.15%6.06%—3.03%6.06%—30.30%
13.03%12.12%9.09%———24.24%
26.06%12.12%3.03%3.03%——24.24%
3——9.09%3.03%——12.12%
46.06%—3.03%———9.09%
5+———————
Total30.30%30.30%24.24%9.09%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.30 +0.15
SD 1.30 1.19 1.75
CV 0.89 0.91 —
Max 4 4 +4
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%9.09%9.09%———24.24%
16.06%9.09%————15.15%
227.27%6.06%—3.03%——36.36%
36.06%3.03%3.03%———12.12%
43.03%3.03%————6.06%
5+3.03%3.03%————6.06%
Total51.52%33.33%12.12%3.03%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.85 0.67 +1.18
SD 1.60 0.82 1.93
CV 0.87 1.22 —
Max 7 3 +6
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%3.03%3.03%6.06%3.03%3.03%24.24%
16.06%15.15%33.33%3.03%3.03%6.06%66.67%
2———3.03%——3.03%
33.03%3.03%————6.06%
4———————
5+———————
Total15.15%21.21%36.36%12.12%6.06%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 0.91 2.09 -1.18
SD 0.72 1.67 1.93
CV 0.80 0.80 —
Max 3 7 +3
Min 0 0 -6

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%9.09%12.12%3.03%3.03%—33.33%
16.06%3.03%3.03%3.03%3.03%—18.18%
29.09%12.12%6.06%3.03%3.03%—33.33%
36.06%—3.03%———9.09%
4—3.03%3.03%———6.06%
5+———————
Total27.27%27.27%27.27%9.09%9.09%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.36 1.45 -0.09
SD 1.22 1.25 1.88
CV 0.89 0.86 —
Max 4 4 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%18.18%9.09%3.03%3.03%—36.36%
19.09%12.12%6.06%———27.27%
212.12%3.03%3.03%———18.18%
36.06%3.03%—3.03%—3.03%15.15%
4—3.03%————3.03%
5+———————
Total30.30%39.39%18.18%6.06%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.21 1.24 -0.03
SD 1.19 1.32 1.81
CV 0.98 1.07 —
Max 4 6 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%6.06%9.09%———18.18%
115.15%12.12%3.03%6.06%——36.36%
29.09%15.15%9.09%———33.33%
33.03%9.09%————12.12%
4———————
5+———————
Total30.30%42.42%21.21%6.06%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.03 +0.36
SD 0.93 0.88 1.39
CV 0.67 0.86 —
Max 3 3 +3
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%9.09%6.06%6.06%——33.33%
16.06%15.15%6.06%6.06%3.03%—36.36%
23.03%9.09%3.03%3.03%——18.18%
3—9.09%————9.09%
43.03%—————3.03%
5+———————
Total24.24%42.42%15.15%15.15%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.12 1.30 -0.18
SD 1.08 1.10 1.63
CV 0.97 0.85 —
Max 4 4 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
0—12.12%3.03%6.06%6.06%—27.27%
16.06%12.12%3.03%3.03%6.06%—30.30%
26.06%6.06%9.09%3.03%——24.24%
36.06%3.03%————9.09%
43.03%6.06%————9.09%
5+———————
Total21.21%39.39%15.15%12.12%12.12%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.42 1.55 -0.12
SD 1.25 1.30 2.16
CV 0.88 0.84 —
Max 4 4 +4
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%15.15%9.09%———33.33%
112.12%15.15%3.03%12.12%——42.42%
29.09%9.09%——3.03%—21.21%
3———————
43.03%—————3.03%
5+———————
Total33.33%39.39%12.12%12.12%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.97 1.12 -0.15
SD 0.92 1.11 1.50
CV 0.95 0.99 —
Max 4 4 +4
Min 0 0 -2

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 Sonderjyske 41 34.61 +6.39
2 Esbjerg 50 44.54 +5.46
3 FC Copenhagen 68 64.84 +3.16
4 Aalborg 48 46.34 +1.66
5 Nordsjaelland 43 42.05 +0.95

Biggest Disappointments

# Team Actual Sim vsSim
1 HB Koge 19 27.43 -8.43
2 Aarhus GF 38 42.74 -4.74
3 Silkeborg 43 46.91 -3.91
4 Odense 59 60.84 -1.84
5 Randers 40 40.78 -0.78

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 Esbjerg 6 Aug 16 – Sep 28 1 in 265
2 Randers 4 Apr 11 – Apr 26 1 in 135
3 Sonderjyske 3 May 3 – May 9 1 in 45
4 Aalborg 4 Aug 2 – Aug 19 1 in 33
5 FC Copenhagen 6 Nov 22 – Mar 21 1 in 28

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Silkeborg 6 Apr 11 – May 6 1 in 632
2 Randers 6 Aug 9 – Sep 20 1 in 105
3 Brondby 4 Nov 8 – Dec 6 1 in 69
4 Esbjerg 4 Mar 21 – Mar 31 1 in 58
5 Midtjylland 4 Aug 17 – Sep 12 1 in 30

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Randers 16 Nov 29 – May 9 1 in 7,625
2 Sonderjyske 5 Nov 22 – Mar 13 1 in 54
3 Aarhus GF 7 Jul 20 – Aug 29 1 in 43
4 Midtjylland 7 Mar 6 – Apr 5 1 in 39
5 Aalborg 8 Mar 21 – Apr 19 1 in 33

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Randers 17 Jul 19 – Nov 29 1 in 1,093
2 Brondby 8 Nov 8 – Mar 25 1 in 154
3 Silkeborg 8 Apr 1 – May 6 1 in 72
4 Odense 5 Mar 29 – Apr 14 1 in 34
5 HB Koge 14 Sep 13 – Mar 21 1 in 25

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 Copenhagen60.43%25.76%7.91%3.22%1.30%0.67%0.41%0.17%0.10%0.03%——
Odense29.79%40.05%15.47%7.17%3.47%2.08%0.97%0.61%0.28%0.09%0.02%—
Brondby4.37%12.82%22.62%17.27%13.29%9.52%7.50%5.34%3.76%2.23%1.10%0.18%
Esbjerg0.68%2.66%8.22%10.69%12.37%13.18%12.62%12.00%11.42%8.71%5.87%1.58%
Aalborg1.31%4.99%10.94%13.30%13.33%13.48%11.84%10.77%8.43%6.57%4.04%1.00%
Midtjylland1.12%4.23%10.77%13.70%13.83%12.70%12.14%10.71%9.02%6.73%3.91%1.14%
Nordsjaelland0.40%1.54%4.40%7.04%8.97%10.74%12.40%13.80%14.28%13.63%9.46%3.34%
Silkeborg1.40%5.01%11.35%13.05%14.09%13.18%11.72%10.85%8.56%6.41%3.41%0.97%
Sonderjyske0.02%0.11%0.60%1.38%2.29%3.64%5.33%7.52%12.17%18.44%30.74%17.76%
Randers0.16%1.08%2.84%5.48%7.68%9.28%11.58%12.82%14.75%16.47%12.83%5.03%
Aarhus GF0.32%1.75%4.81%7.55%9.16%11.15%12.61%13.65%13.89%13.44%8.98%2.69%
HB Koge——0.07%0.15%0.22%0.38%0.88%1.76%3.34%7.25%19.64%66.31%

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
+8.08%
Slight Edge
42.42%23.23%34.34%
Elo Value
Home Edge: 28.14 Elo pts.
205 Elo
0.005 goals per Elo point
0600
Scoring Tilt
Expected
+0.16 goals
Neutral
-2+0.14+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
60%
FC Copenhagen, 1st of 12
LongshotFavorite
Title Margin
Expected
0.27/gm
Tight Race
00.220.5/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 5.84 * Some Luck: 5.84 to 8.76 * Lucky: 8.76 to 11.68 * Wild Swing: 11.68 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 1.41 * Close: 1.41 to 2.12 * Off: 2.12 to 2.83 * Way Off: 2.83 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 0.66 * A Surprise: 0.66 to 1.05 * Several Surprises: 1.05 to 1.44 * Many Surprises: 1.44 and up.
Luck Spread
Expected
4.06 points
As Expected
07.3018
Average Finish Error
Expected
1.33
Pinpoint
01.774
Biggest Overachiever
Expected 95.83%
83.26%
Sonderjyske
50100
Biggest Underachiever
Expected 4.17%
11.58%
HB Koge
050
Season Outliers
Expected
0 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
1 of 2
A Surprise
00.72

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
0.13
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.39
Moderate Separation
01.003
Interquartile Edge
58%
Even
50%60%70%80%100%
Best vs. Worst
Baseline
86%
Strong Edge
50%83%100%
Close Games
Expected
60%
Very Frequent
0%59%100%
Blowouts
Expected
15%
Frequent
0%17%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
0.62
Predictable
00.612
Matchup Imbalance
0.30
Lopsided
00.10.180.280.5
Strangeness
Expected
0.33
Very Predictable
01.002
Repeatability
0.72
Strong Carryover
00.30.60.851
Upset Rate
Expected
30%
As Expected
0%27%50%
Clear Favorite Upset Rate
Expected
24%
As Expected
0%23%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 0.25 * Well Above Noise: 0.25 and up.
Probability calibration
0.02
Miscalibrated
0.010.050.10.51
Calibration slope
Ideal
0.87
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.095
Well Within Noise
00.1230.3

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% —
Odense 99.98% 0.02%
Brondby 98.72% 1.28%
Silkeborg 95.62% 4.38%
Aalborg 94.96% 5.04%
Midtjylland 94.95% 5.05%
Esbjerg 92.55% 7.45%
Aarhus GF 88.33% 11.67%
Nordsjaelland 87.20% 12.80%
Randers 82.14% 17.86%
Sonderjyske 51.50% 48.50%
HB Koge 14.05% 85.95%

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
2009-07-18 Esbjerg D 0-0 1714 1659 49.53% 23.54% 26.94% -0.6 1
2009-07-18 @ Midtjylland D 0-0 1659 1714 26.94% 23.54% 49.53% +0.6 1
2009-07-18 FC Copenhagen W 2-0 1653 1816 22.24% 22.06% 55.70% +11.5 3
2009-07-18 @ Nordsjaelland L 0-2 1816 1653 55.70% 22.06% 22.24% -11.5 0
2009-07-19 Odense D 2-2 1737 1788 34.70% 24.57% 40.73% +0.1 1
2009-07-19 @ Brondby D 2-2 1788 1737 40.73% 24.57% 34.70% -0.1 1
2009-07-19 Randers W 1-0 1599 1688 29.82% 24.09% 46.09% +5.2 3
2009-07-19 @ Sonderjyske L 0-1 1688 1599 46.09% 24.09% 29.82% -5.2 0
2009-07-19 Silkeborg D 1-1 1578 1677 28.70% 23.90% 47.40% +0.5 1
2009-07-19 @ HB Koge D 1-1 1677 1578 47.40% 23.90% 28.70% -0.5 1
2009-07-20 Aalborg W 1-0 1664 1669 41.27% 24.54% 34.19% +4.2 3
2009-07-20 @ Aarhus GF L 0-1 1669 1664 34.19% 24.54% 41.27% -4.2 0
2009-07-25 HB Koge W 7-1 1804 1579 69.75% 16.62% 13.63% +7.2 3
2009-07-25 @ FC Copenhagen L 1-7 1579 1804 13.63% 16.62% 69.75% -7.2 1
2009-07-25 Sonderjyske W 3-1 1788 1604 65.33% 18.59% 16.07% +3.3 4
2009-07-25 @ Odense L 1-3 1604 1788 16.07% 18.59% 65.33% -3.3 3
2009-07-26 Brondby W 2-1 1660 1737 31.34% 24.29% 44.36% +4.8 4
2009-07-26 @ Esbjerg L 1-2 1737 1660 44.36% 24.29% 31.34% -4.8 1
2009-07-26 Midtjylland W 4-0 1677 1713 36.80% 24.64% 38.57% +16.3 4
2009-07-26 @ Silkeborg L 0-4 1713 1677 38.57% 24.64% 36.80% -16.3 1
2009-07-27 Aarhus GF L 2-3 1683 1668 44.05% 24.33% 31.62% -4.5 0
2009-07-27 @ Randers W 3-2 1668 1683 31.62% 24.33% 44.05% +4.5 6
2009-08-01 Esbjerg D 1-1 1600 1664 33.03% 24.46% 42.51% +0.2 4
2009-08-01 @ Sonderjyske D 1-1 1664 1600 42.51% 24.46% 33.03% -0.2 5
2009-08-01 Silkeborg D 1-1 1811 1693 57.66% 21.46% 20.88% -0.9 4
2009-08-01 @ FC Copenhagen D 1-1 1693 1811 20.88% 21.46% 57.66% +0.9 5
2009-08-02 Aalborg L 0-5 1571 1665 29.37% 24.02% 46.61% -16.2 1
2009-08-02 @ HB Koge W 5-0 1665 1571 46.61% 24.02% 29.37% +16.2 3
2009-08-02 Midtjylland W 3-1 1732 1697 46.87% 23.98% 29.15% +6.0 4
2009-08-02 @ Brondby L 1-3 1697 1732 29.15% 23.98% 46.87% -6.0 1
2009-08-02 Randers D 2-2 1665 1678 40.03% 24.60% 35.37% -0.1 4
2009-08-02 @ Nordsjaelland D 2-2 1678 1665 35.37% 24.60% 40.03% +0.1 1
2009-08-03 Odense D 2-2 1673 1791 26.55% 23.44% 50.01% +0.4 7
2009-08-03 @ Aarhus GF D 2-2 1791 1673 50.01% 23.44% 26.55% -0.4 5
2009-08-08 Silkeborg W 3-0 1665 1694 37.76% 24.64% 37.60% +12.2 7
2009-08-08 @ Nordsjaelland L 0-3 1694 1665 37.60% 24.64% 37.76% -12.2 5
2009-08-09 Aalborg L 0-2 1738 1681 49.81% 23.48% 26.71% -10.5 4
2009-08-09 @ Brondby W 2-0 1681 1738 26.71% 23.48% 49.81% +10.5 6
2009-08-09 FC Copenhagen L 0-1 1601 1810 18.43% 20.16% 61.42% -2.4 4
2009-08-09 @ Sonderjyske W 1-0 1810 1601 61.42% 20.16% 18.43% +2.3 7
2009-08-09 HB Koge W 2-1 1673 1555 57.62% 21.47% 20.91% +2.5 10
2009-08-09 @ Aarhus GF L 1-2 1555 1673 20.91% 21.47% 57.62% -2.5 1
2009-08-09 Odense L 1-2 1664 1791 25.70% 23.22% 51.08% -3.1 5
2009-08-09 @ Esbjerg W 2-1 1791 1664 51.08% 23.22% 25.70% +3.1 8
2009-08-09 Randers W 4-1 1691 1678 43.72% 24.36% 31.92% +9.1 4
2009-08-09 @ Midtjylland L 1-4 1678 1691 31.92% 24.36% 43.72% -9.1 1
2009-08-15 Aarhus GF L 0-1 1813 1676 59.95% 20.69% 19.36% -6.5 7
2009-08-15 @ FC Copenhagen W 1-0 1676 1813 19.36% 20.69% 59.95% +6.5 13
2009-08-15 Sonderjyske W 1-0 1691 1598 54.54% 22.38% 23.08% +3.0 9
2009-08-15 @ Aalborg L 0-1 1598 1691 23.08% 22.38% 54.54% -3.0 4
2009-08-16 Brondby L 1-3 1669 1727 33.81% 24.52% 41.68% -6.7 1
2009-08-16 @ Randers W 3-1 1727 1669 41.68% 24.52% 33.81% +6.7 7
2009-08-16 Esbjerg L 2-3 1682 1661 44.89% 24.24% 30.87% -4.6 5
2009-08-16 @ Silkeborg W 3-2 1661 1682 30.87% 24.24% 44.89% +4.6 8
2009-08-16 Nordsjaelland D 1-1 1553 1677 25.95% 23.29% 50.76% +0.6 2
2009-08-16 @ HB Koge D 1-1 1677 1553 50.76% 23.29% 25.95% -0.6 8
2009-08-17 Midtjylland W 1-0 1794 1700 54.63% 22.36% 23.01% +2.9 11
2009-08-17 @ Odense L 0-1 1700 1794 23.01% 22.36% 54.63% -3.0 4
2009-08-19 Nordsjaelland W 1-0 1694 1676 44.53% 24.28% 31.19% +3.9 12
2009-08-19 @ Aalborg L 0-1 1676 1694 31.19% 24.28% 44.53% -3.9 8
2009-08-22 FC Copenhagen L 1-4 1697 1806 27.55% 23.67% 48.78% -8.0 4
2009-08-22 @ Midtjylland W 4-1 1806 1697 48.78% 23.67% 27.55% +8.0 10
2009-08-22 Silkeborg D 2-2 1682 1677 42.65% 24.45% 32.90% -0.2 14
2009-08-22 @ Aarhus GF D 2-2 1677 1682 32.90% 24.45% 42.65% +0.2 6
2009-08-23 Aalborg W 2-0 1666 1698 37.31% 24.64% 38.05% +8.5 11
2009-08-23 @ Esbjerg L 0-2 1698 1666 38.05% 24.64% 37.31% -8.5 12
2009-08-23 HB Koge W 6-1 1734 1553 64.97% 18.75% 16.28% +7.5 10
2009-08-23 @ Brondby L 1-6 1553 1734 16.28% 18.75% 64.97% -7.5 2
2009-08-23 Nordsjaelland W 1-0 1595 1672 31.36% 24.30% 44.35% +5.1 7
2009-08-23 @ Sonderjyske L 0-1 1672 1595 44.35% 24.30% 31.36% -5.1 8
2009-08-24 Randers W 1-0 1797 1663 59.59% 20.82% 19.59% +2.5 14
2009-08-24 @ Odense L 0-1 1663 1797 19.59% 20.82% 59.59% -2.5 1
2009-08-29 Aarhus GF L 0-2 1667 1682 39.90% 24.60% 35.50% -8.8 8
2009-08-29 @ Nordsjaelland W 2-0 1682 1667 35.50% 24.60% 39.90% +8.8 17
2009-08-30 Brondby D 1-1 1814 1742 51.91% 23.04% 25.06% -0.7 11
2009-08-30 @ FC Copenhagen D 1-1 1742 1814 25.06% 23.04% 51.91% +0.7 11
2009-08-30 Esbjerg L 0-1 1660 1674 39.97% 24.60% 35.43% -4.7 1
2009-08-30 @ Randers W 1-0 1674 1660 35.43% 24.60% 39.97% +4.7 14
2009-08-30 Midtjylland W 1-0 1690 1689 42.10% 24.49% 33.41% +4.1 15
2009-08-30 @ Aalborg L 0-1 1689 1690 33.41% 24.49% 42.10% -4.1 4
2009-08-30 Sonderjyske W 1-0 1546 1600 34.25% 24.55% 41.20% +4.8 5
2009-08-30 @ HB Koge L 0-1 1600 1546 41.20% 24.55% 34.25% -4.8 7
2009-08-31 Odense W 3-1 1677 1799 26.20% 23.35% 50.45% +9.2 9
2009-08-31 @ Silkeborg L 1-3 1799 1677 50.45% 23.35% 26.20% -9.2 14
2009-09-12 FC Copenhagen D 1-1 1790 1814 38.61% 24.63% 36.76% -0.0 15
2009-09-12 @ Odense D 1-1 1814 1790 36.76% 24.63% 38.61% +0.0 12
2009-09-12 Nordsjaelland L 0-2 1685 1658 45.67% 24.14% 30.19% -9.8 4
2009-09-12 @ Midtjylland W 2-0 1658 1685 30.19% 24.14% 45.67% +9.8 11
2009-09-13 Aarhus GF W 1-0 1742 1691 49.09% 23.62% 27.29% +3.5 14
2009-09-13 @ Brondby L 0-1 1691 1742 27.29% 23.62% 49.09% -3.5 17
2009-09-13 HB Koge W 3-2 1679 1551 58.88% 21.06% 20.06% +2.3 17
2009-09-13 @ Esbjerg L 2-3 1551 1679 20.06% 21.06% 58.88% -2.3 5
2009-09-13 Sonderjyske D 1-1 1687 1596 54.26% 22.46% 23.28% -0.8 10
2009-09-13 @ Silkeborg D 1-1 1596 1687 23.28% 22.46% 54.26% +0.8 8
2009-09-14 Aalborg L 0-3 1655 1694 36.48% 24.63% 38.89% -12.0 1
2009-09-14 @ Randers W 3-0 1694 1655 38.89% 24.63% 36.48% +12.0 18
2009-09-19 Silkeborg L 0-1 1706 1686 44.78% 24.25% 30.97% -5.1 18
2009-09-19 @ Aalborg W 1-0 1686 1706 30.97% 24.25% 44.78% +5.1 13
2009-09-20 Brondby L 2-4 1596 1746 23.46% 22.52% 54.02% -4.4 8
2009-09-20 @ Sonderjyske W 4-2 1746 1596 54.02% 22.52% 23.46% +4.4 17
2009-09-20 Esbjerg L 0-4 1668 1681 40.14% 24.59% 35.26% -16.8 11
2009-09-20 @ Nordsjaelland W 4-0 1681 1668 35.26% 24.59% 40.14% +16.8 20
2009-09-20 Odense L 1-3 1548 1790 16.23% 18.71% 65.06% -3.3 5
2009-09-20 @ HB Koge W 3-1 1790 1548 65.06% 18.71% 16.23% +3.3 18
2009-09-20 Randers W 3-0 1814 1643 63.79% 19.23% 16.98% +5.9 15
2009-09-20 @ FC Copenhagen L 0-3 1643 1814 16.98% 19.23% 63.79% -5.9 1
2009-09-21 Midtjylland L 2-4 1687 1675 43.70% 24.36% 31.94% -7.3 17
2009-09-21 @ Aarhus GF W 4-2 1675 1687 31.94% 24.36% 43.70% +7.3 7
2009-09-26 Nordsjaelland W 2-0 1793 1651 60.51% 20.49% 19.00% +4.6 21
2009-09-26 @ Odense L 0-2 1651 1793 19.00% 20.49% 60.51% -4.6 11
2009-09-27 Brondby W 4-1 1691 1750 33.67% 24.51% 41.83% +11.2 16
2009-09-27 @ Silkeborg L 1-4 1750 1691 41.83% 24.51% 33.67% -11.2 17
2009-09-27 FC Copenhagen L 1-2 1701 1820 26.51% 23.43% 50.06% -3.2 18
2009-09-27 @ Aalborg W 2-1 1820 1701 50.06% 23.43% 26.51% +3.2 18
2009-09-27 HB Koge D 1-1 1638 1545 54.46% 22.40% 23.14% -0.8 2
2009-09-27 @ Randers D 1-1 1545 1638 23.14% 22.40% 54.46% +0.8 6
2009-09-27 Sonderjyske L 0-2 1682 1592 54.17% 22.48% 23.35% -11.3 7
2009-09-27 @ Midtjylland W 2-0 1592 1682 23.35% 22.48% 54.17% +11.3 11
2009-09-28 Aarhus GF W 3-2 1698 1680 44.51% 24.28% 31.21% +3.5 23
2009-09-28 @ Esbjerg L 2-3 1680 1698 31.21% 24.28% 44.51% -3.5 17
2009-10-03 Sonderjyske W 2-1 1676 1603 51.96% 23.03% 25.01% +3.0 20
2009-10-03 @ Aarhus GF L 1-2 1603 1676 25.01% 23.03% 51.96% -3.0 11
2009-10-04 Esbjerg W 2-1 1823 1701 58.04% 21.34% 20.62% +2.5 21
2009-10-04 @ FC Copenhagen L 1-2 1701 1823 20.62% 21.34% 58.04% -2.5 23
2009-10-04 HB Koge W 2-1 1671 1546 58.53% 21.18% 20.29% +2.5 10
2009-10-04 @ Midtjylland L 1-2 1546 1671 20.29% 21.18% 58.53% -2.5 6
2009-10-04 Nordsjaelland W 6-3 1739 1647 54.39% 22.42% 23.19% +5.5 20
2009-10-04 @ Brondby L 3-6 1647 1739 23.19% 22.42% 54.39% -5.5 11
2009-10-04 Silkeborg L 1-2 1637 1702 32.83% 24.44% 42.73% -3.8 2
2009-10-04 @ Randers W 2-1 1702 1637 42.73% 24.44% 32.83% +3.8 19
2009-10-05 Aalborg W 2-1 1798 1698 55.44% 22.13% 22.43% +2.7 24
2009-10-05 @ Odense L 1-2 1698 1798 22.43% 22.13% 55.44% -2.7 18
2009-10-17 Odense L 0-2 1641 1801 22.53% 22.17% 55.29% -5.4 11
2009-10-17 @ Nordsjaelland W 2-0 1801 1641 55.29% 22.17% 22.53% +5.5 27
2009-10-18 Esbjerg D 2-2 1706 1699 42.97% 24.42% 32.61% -0.2 20
2009-10-18 @ Silkeborg D 2-2 1699 1706 32.61% 24.42% 42.97% +0.2 24
2009-10-18 FC Copenhagen L 0-2 1543 1825 13.83% 16.80% 69.37% -3.2 6
2009-10-18 @ HB Koge W 2-0 1825 1543 69.37% 16.80% 13.83% +3.2 24
2009-10-18 Midtjylland D 1-1 1744 1674 51.65% 23.10% 25.25% -0.6 21
2009-10-18 @ Brondby D 1-1 1674 1744 25.25% 23.10% 51.65% +0.7 11
2009-10-18 Randers D 1-1 1695 1633 50.48% 23.35% 26.17% -0.6 19
2009-10-18 @ Aalborg D 1-1 1633 1695 26.17% 23.35% 50.48% +0.6 3
2009-10-19 Aarhus GF W 1-0 1600 1679 31.09% 24.26% 44.65% +5.1 14
2009-10-19 @ Sonderjyske L 0-1 1679 1600 44.65% 24.26% 31.09% -5.1 20
2009-10-24 Odense D 1-1 1634 1806 21.37% 21.68% 56.95% +0.9 4
2009-10-24 @ Randers D 1-1 1806 1634 56.95% 21.68% 21.37% -0.9 28
2009-10-25 Brondby L 1-2 1694 1744 34.96% 24.58% 40.46% -4.0 19
2009-10-25 @ Aalborg W 2-1 1744 1694 40.46% 24.58% 34.96% +4.0 24
2009-10-25 HB Koge W 2-1 1674 1540 59.59% 20.82% 19.60% +2.4 14
2009-10-25 @ Midtjylland L 1-2 1540 1674 19.60% 20.82% 59.59% -2.4 6
2009-10-25 Silkeborg W 1-0 1828 1706 58.20% 21.29% 20.51% +2.6 27
2009-10-25 @ FC Copenhagen L 0-1 1706 1828 20.51% 21.29% 58.20% -2.6 20
2009-10-25 Sonderjyske W 2-0 1699 1605 54.61% 22.36% 23.03% +5.6 27
2009-10-25 @ Esbjerg L 0-2 1605 1699 23.03% 22.36% 54.61% -5.6 14
2009-10-26 Nordsjaelland L 0-2 1674 1636 47.32% 23.91% 28.76% -10.1 20
2009-10-26 @ Aarhus GF W 2-0 1636 1674 28.76% 23.91% 47.32% +10.1 14
2009-10-31 Midtjylland D 2-2 1664 1677 40.23% 24.59% 35.18% -0.1 21
2009-10-31 @ Aarhus GF D 2-2 1677 1664 35.18% 24.59% 40.23% +0.1 15
2009-11-01 Brondby L 0-1 1646 1748 28.41% 23.85% 47.75% -3.6 14
2009-11-01 @ Nordsjaelland W 1-0 1748 1646 47.75% 23.85% 28.41% +3.6 27
2009-11-01 FC Copenhagen D 0-0 1705 1831 25.72% 23.23% 51.05% +0.7 28
2009-11-01 @ Esbjerg D 0-0 1831 1705 51.05% 23.23% 25.72% -0.7 28
2009-11-01 HB Koge D 0-0 1600 1538 50.51% 23.34% 26.15% -0.7 15
2009-11-01 @ Sonderjyske D 0-0 1538 1600 26.15% 23.34% 50.51% +0.7 7
2009-11-01 Silkeborg L 0-2 1634 1703 32.40% 24.41% 43.19% -7.5 4
2009-11-01 @ Randers W 2-0 1703 1634 43.19% 24.41% 32.40% +7.5 23
2009-11-02 Aalborg D 1-1 1805 1690 57.26% 21.59% 21.16% -0.9 29
2009-11-02 @ Odense D 1-1 1690 1805 21.16% 21.59% 57.26% +0.9 20
2009-11-07 Aarhus GF D 1-1 1538 1664 25.78% 23.24% 50.98% +0.6 8
2009-11-07 @ HB Koge D 1-1 1664 1538 50.98% 23.24% 25.78% -0.6 22
2009-11-07 Odense L 0-1 1711 1804 29.35% 24.01% 46.64% -3.7 23
2009-11-07 @ Silkeborg W 1-0 1804 1711 46.64% 24.01% 29.35% +3.7 32
2009-11-08 Esbjerg L 2-4 1751 1705 48.33% 23.75% 27.92% -8.0 27
2009-11-08 @ Brondby W 4-2 1705 1751 27.92% 23.75% 48.33% +7.9 31
2009-11-08 FC Copenhagen W 1-0 1691 1830 24.42% 22.84% 52.73% +5.8 23
2009-11-08 @ Aalborg L 0-1 1830 1691 52.73% 22.84% 24.42% -5.9 28
2009-11-08 Nordsjaelland L 0-1 1599 1642 35.81% 24.61% 39.57% -4.3 15
2009-11-08 @ Sonderjyske W 1-0 1642 1599 39.57% 24.61% 35.81% +4.3 17
2009-11-08 Randers W 2-1 1677 1627 48.85% 23.66% 27.49% +3.3 18
2009-11-08 @ Midtjylland L 1-2 1627 1677 27.49% 23.66% 48.85% -3.3 4
2009-11-21 Esbjerg W 3-0 1680 1713 37.20% 24.64% 38.16% +12.4 21
2009-11-21 @ Midtjylland L 0-3 1713 1680 38.16% 24.64% 37.20% -12.4 31
2009-11-21 Nordsjaelland L 1-2 1539 1647 27.72% 23.71% 48.57% -3.3 8
2009-11-21 @ HB Koge W 2-1 1647 1539 48.57% 23.71% 27.72% +3.3 20
2009-11-22 Odense L 1-3 1743 1808 32.94% 24.45% 42.61% -6.6 27
2009-11-22 @ Brondby W 3-1 1808 1743 42.61% 24.45% 32.94% +6.6 35
2009-11-22 Randers W 2-0 1825 1624 67.16% 17.80% 15.03% +3.5 31
2009-11-22 @ FC Copenhagen L 0-2 1624 1825 15.03% 17.80% 67.16% -3.5 4
2009-11-22 Sonderjyske L 1-2 1707 1595 56.92% 21.69% 21.39% -5.9 23
2009-11-22 @ Silkeborg W 2-1 1595 1707 21.39% 21.69% 56.92% +5.9 18
2009-11-23 Aarhus GF D 0-0 1697 1664 46.64% 24.01% 29.34% -0.5 24
2009-11-23 @ Aalborg D 0-0 1664 1697 29.34% 24.01% 46.64% +0.5 23
2009-11-28 Aalborg D 1-1 1701 1697 42.60% 24.45% 32.95% -0.2 32
2009-11-28 @ Esbjerg D 1-1 1697 1701 32.95% 24.45% 42.60% +0.2 25
2009-11-29 Brondby W 1-0 1664 1737 31.90% 24.36% 43.74% +5.0 26
2009-11-29 @ Aarhus GF L 0-1 1737 1664 43.74% 24.36% 31.90% -5.0 27
2009-11-29 Midtjylland W 2-0 1828 1692 59.78% 20.75% 19.47% +4.7 34
2009-11-29 @ FC Copenhagen L 0-2 1692 1828 19.47% 20.75% 59.78% -4.7 21
2009-11-29 Silkeborg L 0-1 1650 1701 34.73% 24.57% 40.70% -4.2 20
2009-11-29 @ Nordsjaelland W 1-0 1701 1650 40.70% 24.57% 34.73% +4.2 26
2009-11-29 Sonderjyske D 0-0 1620 1601 44.70% 24.26% 31.05% -0.4 5
2009-11-29 @ Randers D 0-0 1601 1620 31.05% 24.26% 44.70% +0.4 19
2009-11-30 HB Koge W 1-0 1815 1536 74.95% 14.08% 10.97% +1.3 38
2009-11-30 @ Odense L 0-1 1536 1815 10.97% 14.08% 74.95% -1.3 8
2009-12-05 Aalborg W 2-0 1601 1697 29.10% 23.97% 46.93% +10.0 22
2009-12-05 @ Sonderjyske L 0-2 1697 1601 46.93% 23.97% 29.10% -10.0 25
2009-12-06 Brondby W 3-0 1705 1732 38.22% 24.64% 37.14% +12.1 29
2009-12-06 @ Silkeborg L 0-3 1732 1705 37.14% 24.64% 38.22% -12.1 27
2009-12-06 FC Copenhagen L 0-2 1816 1833 39.56% 24.61% 35.83% -8.8 38
2009-12-06 @ Odense W 2-0 1833 1816 35.83% 24.61% 39.56% +8.8 37
2009-12-06 HB Koge W 2-1 1620 1534 53.54% 22.64% 23.82% +2.9 8
2009-12-06 @ Randers L 1-2 1534 1620 23.82% 22.64% 53.54% -2.9 8
2009-12-06 Midtjylland W 3-0 1646 1688 36.02% 24.62% 39.36% +12.7 23
2009-12-06 @ Nordsjaelland L 0-3 1688 1646 39.36% 24.62% 36.02% -12.7 21
2009-12-07 Esbjerg D 1-1 1669 1701 37.45% 24.64% 37.91% +0.0 27
2009-12-07 @ Aarhus GF D 1-1 1701 1669 37.91% 24.64% 37.45% -0.0 33
2010-03-06 Odense D 2-2 1675 1807 25.13% 23.06% 51.81% +0.5 22
2010-03-06 @ Midtjylland D 2-2 1807 1675 51.81% 23.06% 25.13% -0.5 39
2010-03-07 Aarhus GF W 5-0 1842 1669 64.04% 19.13% 16.83% +9.4 40
2010-03-07 @ FC Copenhagen L 0-5 1669 1842 16.83% 19.13% 64.04% -9.4 27
2010-03-07 Randers D 0-0 1701 1623 52.60% 22.88% 24.52% -0.8 34
2010-03-07 @ Esbjerg D 0-0 1623 1701 24.52% 22.88% 52.60% +0.8 9
2010-03-07 Silkeborg L 1-4 1532 1718 20.25% 21.16% 58.59% -6.0 8
2010-03-07 @ HB Koge W 4-1 1718 1532 58.59% 21.16% 20.25% +6.0 32
2010-03-07 Sonderjyske D 1-1 1720 1611 56.45% 21.84% 21.71% -0.9 28
2010-03-07 @ Brondby D 1-1 1611 1720 21.71% 21.84% 56.45% +0.9 23
2010-03-08 Nordsjaelland W 2-1 1687 1659 45.92% 24.11% 29.97% +3.5 28
2010-03-08 @ Aalborg L 1-2 1659 1687 29.97% 24.11% 45.92% -3.5 23
2010-03-13 Sonderjyske D 1-1 1807 1612 66.48% 18.10% 15.42% -1.3 40
2010-03-13 @ Odense D 1-1 1612 1807 15.42% 18.10% 66.48% +1.3 24
2010-03-14 Aalborg W 2-0 1675 1690 39.86% 24.60% 35.53% +8.1 25
2010-03-14 @ Midtjylland L 0-2 1690 1675 35.53% 24.60% 39.86% -8.1 28
2010-03-14 Brondby W 2-0 1851 1719 59.37% 20.89% 19.74% +4.8 43
2010-03-14 @ FC Copenhagen L 0-2 1719 1851 19.74% 20.89% 59.37% -4.8 28
2010-03-14 HB Koge W 2-1 1700 1526 64.26% 19.04% 16.70% +2.0 37
2010-03-14 @ Esbjerg L 1-2 1526 1700 16.70% 19.04% 64.26% -2.0 8
2010-03-14 Nordsjaelland D 0-0 1623 1655 37.46% 24.64% 37.90% +0.0 10
2010-03-14 @ Randers D 0-0 1655 1623 37.90% 24.64% 37.46% -0.0 24
2010-03-15 Silkeborg L 1-2 1660 1724 33.04% 24.46% 42.50% -3.8 27
2010-03-15 @ Aarhus GF W 2-1 1724 1660 42.50% 24.46% 33.04% +3.8 35
2010-03-20 Midtjylland L 0-2 1727 1684 48.06% 23.80% 28.15% -10.2 35
2010-03-20 @ Silkeborg W 2-0 1684 1727 28.15% 23.80% 48.06% +10.2 28
2010-03-21 Aalborg L 0-3 1524 1682 22.59% 22.19% 55.22% -7.9 8
2010-03-21 @ HB Koge W 3-0 1682 1524 55.22% 22.19% 22.59% +7.9 31
2010-03-21 Aarhus GF W 2-0 1805 1656 61.39% 20.17% 18.44% +4.4 43
2010-03-21 @ Odense L 0-2 1656 1805 18.44% 20.17% 61.39% -4.4 27
2010-03-21 Esbjerg W 1-0 1655 1702 35.30% 24.60% 40.10% +4.7 27
2010-03-21 @ Nordsjaelland L 0-1 1702 1655 40.10% 24.60% 35.30% -4.7 37
2010-03-21 FC Copenhagen L 0-2 1613 1856 16.19% 18.68% 65.13% -3.8 24
2010-03-21 @ Sonderjyske W 2-0 1856 1613 65.13% 18.68% 16.19% +3.8 46
2010-03-22 Randers D 1-1 1714 1623 54.19% 22.47% 23.33% -0.8 29
2010-03-22 @ Brondby D 1-1 1623 1714 23.33% 22.47% 54.19% +0.8 11
2010-03-24 Nordsjaelland L 0-2 1860 1660 67.05% 17.85% 15.10% -13.3 46
2010-03-24 @ FC Copenhagen W 2-0 1660 1860 15.10% 17.85% 67.05% +13.3 30
2010-03-24 Silkeborg W 1-0 1690 1717 38.12% 24.64% 37.24% +4.4 34
2010-03-24 @ Aalborg L 0-1 1717 1690 37.24% 24.64% 38.12% -4.4 35
2010-03-25 Aarhus GF W 2-1 1624 1651 38.09% 24.64% 37.27% +4.2 14
2010-03-25 @ Randers L 1-2 1651 1624 37.27% 24.64% 38.09% -4.2 27
2010-03-25 HB Koge L 1-3 1713 1516 66.80% 17.96% 15.24% -11.5 29
2010-03-25 @ Brondby W 3-1 1516 1713 15.24% 17.96% 66.80% +11.5 11
2010-03-25 Odense L 1-2 1697 1810 27.20% 23.60% 49.20% -3.2 37
2010-03-25 @ Esbjerg W 2-1 1810 1697 49.20% 23.60% 27.20% +3.2 46
2010-03-25 Sonderjyske D 0-0 1694 1609 53.40% 22.68% 23.92% -0.8 29
2010-03-25 @ Midtjylland D 0-0 1609 1694 23.92% 22.68% 53.40% +0.8 25
2010-03-27 Aalborg D 1-1 1673 1695 38.91% 24.63% 36.46% -0.0 31
2010-03-27 @ Nordsjaelland D 1-1 1695 1673 36.46% 24.63% 38.91% +0.1 35
2010-03-28 Brondby L 1-3 1610 1702 29.62% 24.06% 46.33% -6.0 25
2010-03-28 @ Sonderjyske W 3-1 1702 1610 46.33% 24.06% 29.62% +6.1 32
2010-03-28 Esbjerg W 4-0 1628 1694 32.81% 24.44% 42.75% +17.7 17
2010-03-28 @ Randers L 0-4 1694 1628 42.75% 24.44% 32.81% -17.7 37
2010-03-28 FC Copenhagen D 0-0 1647 1846 19.23% 20.62% 60.15% +1.2 28
2010-03-28 @ Aarhus GF D 0-0 1846 1647 60.15% 20.62% 19.23% -1.2 47
2010-03-28 HB Koge W 3-0 1713 1527 65.49% 18.53% 15.98% +5.5 38
2010-03-28 @ Silkeborg L 0-3 1527 1713 15.98% 18.53% 65.49% -5.5 11
2010-03-29 Midtjylland L 1-2 1813 1693 57.88% 21.39% 20.73% -6.0 46
2010-03-29 @ Odense W 2-1 1693 1813 20.73% 21.39% 57.88% +5.9 32
2010-03-31 Aarhus GF L 0-4 1676 1648 45.88% 24.12% 30.00% -18.7 37
2010-03-31 @ Esbjerg W 4-0 1648 1676 30.00% 24.12% 45.88% +18.7 31
2010-04-01 Nordsjaelland W 1-0 1699 1673 45.60% 24.15% 30.25% +3.8 35
2010-04-01 @ Midtjylland L 0-1 1673 1699 30.25% 24.15% 45.60% -3.8 31
2010-04-01 Odense W 2-0 1845 1807 47.27% 23.92% 28.81% +6.8 50
2010-04-01 @ FC Copenhagen L 0-2 1807 1845 28.81% 23.92% 47.27% -6.8 46
2010-04-01 Randers L 1-2 1522 1646 25.92% 23.28% 50.80% -3.1 11
2010-04-01 @ HB Koge W 2-1 1646 1522 50.80% 23.28% 25.92% +3.1 20
2010-04-01 Silkeborg D 2-2 1708 1718 40.48% 24.58% 34.94% -0.1 33
2010-04-01 @ Brondby D 2-2 1718 1708 34.94% 24.58% 40.48% +0.1 39
2010-04-02 Sonderjyske D 1-1 1695 1604 54.18% 22.48% 23.34% -0.8 36
2010-04-02 @ Aalborg D 1-1 1604 1695 23.34% 22.48% 54.18% +0.8 26
2010-04-04 Brondby L 1-2 1519 1708 20.01% 21.03% 58.96% -2.4 11
2010-04-04 @ HB Koge W 2-1 1708 1519 58.96% 21.03% 20.01% +2.4 36
2010-04-04 Randers D 0-0 1667 1649 44.49% 24.28% 31.23% -0.4 32
2010-04-04 @ Aarhus GF D 0-0 1649 1667 31.23% 24.28% 44.49% +0.4 21
2010-04-05 Aalborg D 1-1 1718 1694 45.40% 24.18% 30.43% -0.4 40
2010-04-05 @ Silkeborg D 1-1 1694 1718 30.43% 24.18% 45.40% +0.4 37
2010-04-05 Esbjerg D 0-0 1800 1658 60.59% 20.46% 18.95% -1.2 47
2010-04-05 @ Odense D 0-0 1658 1800 18.95% 20.46% 60.59% +1.2 38
2010-04-05 FC Copenhagen L 0-3 1669 1852 20.52% 21.29% 58.19% -7.2 31
2010-04-05 @ Nordsjaelland W 3-0 1852 1669 58.19% 21.29% 20.52% +7.2 53
2010-04-05 Midtjylland L 0-2 1605 1703 28.88% 23.93% 47.19% -6.8 26
2010-04-05 @ Sonderjyske W 2-0 1703 1605 47.19% 23.93% 28.88% +6.8 38
2010-04-10 Aalborg L 0-2 1667 1694 38.05% 24.64% 37.31% -8.5 32
2010-04-10 @ Aarhus GF W 2-0 1694 1667 37.31% 24.64% 38.05% +8.5 40
2010-04-11 Brondby L 0-1 1799 1710 54.01% 22.52% 23.47% -6.0 47
2010-04-11 @ Odense W 1-0 1710 1799 23.47% 22.52% 54.01% +6.0 39
2010-04-11 FC Copenhagen W 1-0 1650 1859 18.44% 20.16% 61.40% +6.6 24
2010-04-11 @ Randers L 0-1 1859 1650 61.40% 20.16% 18.44% -6.6 53
2010-04-11 Midtjylland W 2-1 1659 1709 34.80% 24.57% 40.63% +4.5 41
2010-04-11 @ Esbjerg L 1-2 1709 1659 40.63% 24.57% 34.80% -4.5 38
2010-04-11 Silkeborg W 4-0 1598 1718 26.42% 23.41% 50.17% +20.1 29
2010-04-11 @ Sonderjyske L 0-4 1718 1598 50.17% 23.41% 26.42% -20.1 40
2010-04-12 HB Koge D 1-1 1662 1516 60.98% 20.32% 18.70% -1.1 32
2010-04-12 @ Nordsjaelland D 1-1 1516 1662 18.70% 20.32% 60.98% +1.1 12
2010-04-14 Aarhus GF W 1-0 1705 1658 48.45% 23.73% 27.82% +3.5 41
2010-04-14 @ Midtjylland L 0-1 1658 1705 27.82% 23.73% 48.45% -3.5 32
2010-04-14 Esbjerg W 3-2 1852 1663 65.89% 18.36% 15.75% +1.8 56
2010-04-14 @ FC Copenhagen L 2-3 1663 1852 15.75% 18.36% 65.89% -1.8 41
2010-04-14 Odense W 1-0 1703 1793 29.74% 24.08% 46.19% +5.2 43
2010-04-14 @ Aalborg L 0-1 1793 1703 46.19% 24.08% 29.74% -5.3 47
2010-04-14 Randers L 1-3 1698 1656 47.77% 23.84% 28.39% -8.8 40
2010-04-14 @ Silkeborg W 3-1 1656 1698 28.39% 23.84% 47.77% +8.8 27
2010-04-15 Nordsjaelland L 0-1 1716 1661 49.56% 23.53% 26.91% -5.6 39
2010-04-15 @ Brondby W 1-0 1661 1716 26.91% 23.53% 49.56% +5.6 35
2010-04-15 Sonderjyske L 1-2 1517 1618 28.47% 23.86% 47.67% -3.4 12
2010-04-15 @ HB Koge W 2-1 1618 1517 47.67% 23.86% 28.47% +3.4 32
2010-04-17 FC Copenhagen W 3-2 1708 1854 23.79% 22.64% 53.57% +5.3 44
2010-04-17 @ Midtjylland L 2-3 1854 1708 53.57% 22.64% 23.79% -5.3 56
2010-04-18 Aarhus GF W 1-0 1710 1655 49.65% 23.51% 26.84% +3.4 42
2010-04-18 @ Brondby L 0-1 1655 1710 26.84% 23.51% 49.65% -3.4 32
2010-04-18 Nordsjaelland L 1-4 1689 1666 45.13% 24.21% 30.66% -11.9 40
2010-04-18 @ Silkeborg W 4-1 1666 1689 30.66% 24.21% 45.13% +11.9 38
2010-04-18 Odense L 1-2 1514 1788 14.28% 17.18% 68.54% -1.7 12
2010-04-18 @ HB Koge W 2-1 1788 1514 68.54% 17.18% 14.28% +1.7 50
2010-04-18 Randers L 0-1 1622 1665 35.81% 24.61% 39.58% -4.3 32
2010-04-18 @ Sonderjyske W 1-0 1665 1622 39.58% 24.61% 35.81% +4.3 30
2010-04-19 Esbjerg D 0-0 1708 1662 48.41% 23.74% 27.85% -0.6 44
2010-04-19 @ Aalborg D 0-0 1662 1708 27.85% 23.74% 48.41% +0.6 42
2010-04-24 Silkeborg W 1-0 1789 1677 56.93% 21.69% 21.38% +2.7 53
2010-04-24 @ Odense L 0-1 1677 1789 21.38% 21.69% 56.93% -2.8 40
2010-04-25 Aalborg W 2-0 1849 1707 60.46% 20.51% 19.03% +4.6 59
2010-04-25 @ FC Copenhagen L 0-2 1707 1849 19.03% 20.51% 60.46% -4.6 44
2010-04-25 Brondby D 1-1 1662 1714 34.66% 24.57% 40.77% +0.1 43
2010-04-25 @ Esbjerg D 1-1 1714 1662 40.77% 24.57% 34.66% -0.1 43
2010-04-25 HB Koge L 0-3 1651 1512 60.19% 20.61% 19.21% -17.8 32
2010-04-25 @ Aarhus GF W 3-0 1512 1651 19.21% 20.61% 60.19% +17.8 15
2010-04-25 Sonderjyske W 3-1 1678 1617 50.37% 23.37% 26.26% +5.4 41
2010-04-25 @ Nordsjaelland L 1-3 1617 1678 26.26% 23.37% 50.37% -5.4 32
2010-04-26 Midtjylland W 2-0 1669 1714 35.64% 24.61% 39.76% +8.8 33
2010-04-26 @ Randers L 0-2 1714 1669 39.76% 24.61% 35.64% -8.8 44
2010-05-01 Aarhus GF L 1-4 1674 1633 47.66% 23.86% 28.48% -12.4 40
2010-05-01 @ Silkeborg W 4-1 1633 1674 28.48% 23.86% 47.66% +12.4 35
2010-05-02 Esbjerg L 1-2 1530 1662 25.12% 23.06% 51.83% -3.0 15
2010-05-02 @ HB Koge W 2-1 1662 1530 51.83% 23.06% 25.12% +3.0 46
2010-05-02 FC Copenhagen L 0-2 1714 1854 24.36% 22.82% 52.82% -5.9 43
2010-05-02 @ Brondby W 2-0 1854 1714 52.82% 22.82% 24.36% +5.9 62
2010-05-02 Midtjylland W 3-2 1703 1705 41.67% 24.52% 33.81% +3.7 47
2010-05-02 @ Aalborg L 2-3 1705 1703 33.81% 24.52% 41.67% -3.7 44
2010-05-02 Randers D 1-1 1684 1678 42.79% 24.44% 32.77% -0.2 42
2010-05-02 @ Nordsjaelland D 1-1 1678 1684 32.77% 24.44% 42.79% +0.2 34
2010-05-03 Odense W 2-0 1612 1792 20.72% 21.38% 57.90% +11.9 35
2010-05-03 @ Sonderjyske L 0-2 1792 1612 57.90% 21.38% 20.72% -11.9 53
2010-05-05 Aalborg W 3-1 1678 1707 37.94% 24.64% 37.42% +7.3 37
2010-05-05 @ Randers L 1-3 1707 1678 37.42% 24.64% 37.94% -7.3 47
2010-05-05 Brondby L 2-4 1701 1708 41.06% 24.55% 34.39% -7.0 44
2010-05-05 @ Midtjylland W 4-2 1708 1701 34.39% 24.55% 41.06% +7.0 46
2010-05-05 HB Koge W 4-0 1859 1527 79.58% 11.67% 8.75% +3.6 65
2010-05-05 @ FC Copenhagen L 0-4 1527 1859 8.75% 11.67% 79.58% -3.5 15
2010-05-06 Nordsjaelland W 2-1 1780 1684 54.98% 22.26% 22.76% +2.8 56
2010-05-06 @ Odense L 1-2 1684 1780 22.76% 22.26% 54.98% -2.8 42
2010-05-06 Silkeborg W 4-0 1665 1662 42.44% 24.47% 33.09% +14.5 49
2010-05-06 @ Esbjerg L 0-4 1662 1665 33.09% 24.47% 42.44% -14.5 40
2010-05-06 Sonderjyske L 1-2 1646 1624 45.08% 24.21% 30.71% -4.9 35
2010-05-06 @ Aarhus GF W 2-1 1624 1646 30.71% 24.21% 45.08% +4.9 38
2010-05-09 Aalborg W 2-0 1715 1699 44.15% 24.32% 31.53% +7.3 49
2010-05-09 @ Brondby L 0-2 1699 1715 31.53% 24.32% 44.15% -7.3 47
2010-05-09 Aarhus GF L 0-1 1681 1641 47.51% 23.88% 28.61% -5.4 42
2010-05-09 @ Nordsjaelland W 1-0 1641 1681 28.61% 23.88% 47.51% +5.4 38
2010-05-09 Esbjerg W 1-0 1629 1680 34.74% 24.57% 40.69% +4.8 41
2010-05-09 @ Sonderjyske L 0-1 1680 1629 40.69% 24.57% 34.74% -4.8 49
2010-05-09 FC Copenhagen W 2-0 1647 1863 18.01% 19.90% 62.09% +12.6 43
2010-05-09 @ Silkeborg L 0-2 1863 1647 62.09% 19.90% 18.01% -12.6 65
2010-05-09 Midtjylland W 1-0 1523 1694 21.51% 21.75% 56.74% +6.2 18
2010-05-09 @ HB Koge L 0-1 1694 1523 56.74% 21.75% 21.51% -6.2 44
2010-05-09 Randers L 1-3 1783 1686 55.08% 22.23% 22.69% -9.9 56
2010-05-09 @ Odense W 3-1 1686 1783 22.69% 22.23% 55.08% +9.9 40
2010-05-16 Brondby L 1-3 1695 1722 38.17% 24.64% 37.19% -7.4 40
2010-05-16 @ Randers W 3-1 1722 1695 37.19% 24.64% 38.17% +7.4 52
2010-05-16 HB Koge D 0-0 1692 1530 62.88% 19.60% 17.52% -1.3 48
2010-05-16 @ Aalborg D 0-0 1530 1692 17.52% 19.60% 62.88% +1.3 19
2010-05-16 Nordsjaelland D 3-3 1675 1675 41.91% 24.50% 33.59% -0.1 50
2010-05-16 @ Esbjerg D 3-3 1675 1675 33.59% 24.50% 41.91% +0.1 43
2010-05-16 Odense L 0-3 1646 1773 25.69% 23.22% 51.10% -9.0 38
2010-05-16 @ Aarhus GF W 3-0 1773 1646 51.10% 23.22% 25.69% +8.9 59
2010-05-16 Silkeborg W 3-0 1688 1660 45.90% 24.11% 29.99% +10.2 47
2010-05-16 @ Midtjylland L 0-3 1660 1688 29.99% 24.11% 45.90% -10.2 43
2010-05-16 Sonderjyske W 3-1 1850 1633 68.86% 17.03% 14.10% +2.8 68
2010-05-16 @ FC Copenhagen L 1-3 1633 1850 14.10% 17.03% 68.86% -2.9 41

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 2010-03-24 15.10% Nordsjaelland 1660 2 @ FC Copenhagen 1860 0
2 2010-03-25 15.24% HB Koge 1516 3 @ Brondby 1713 1
3 2010-05-09 18.01% @ Silkeborg 1647 2 FC Copenhagen 1863 0
4 2010-04-11 18.44% @ Randers 1650 1 FC Copenhagen 1859 0
5 2010-04-25 19.21% HB Koge 1512 3 @ Aarhus GF 1651 0
6 2009-08-15 19.36% Aarhus GF 1676 1 @ FC Copenhagen 1813 0
7 2010-05-03 20.72% @ Sonderjyske 1612 2 Odense 1792 0
8 2010-03-29 20.73% Midtjylland 1693 2 @ Odense 1813 1
9 2009-11-22 21.39% Sonderjyske 1595 2 @ Silkeborg 1707 1
10 2010-05-09 21.51% @ HB Koge 1523 1 Midtjylland 1694 0
11 2009-07-18 22.24% @ Nordsjaelland 1653 2 FC Copenhagen 1816 0
12 2010-05-09 22.69% Randers 1686 3 @ Odense 1783 1
13 2009-09-27 23.35% Sonderjyske 1592 2 @ Midtjylland 1682 0
14 2010-04-11 23.47% Brondby 1710 1 @ Odense 1799 0
15 2010-04-17 23.79% @ Midtjylland 1708 3 FC Copenhagen 1854 2
16 2009-11-08 24.42% @ Aalborg 1691 1 FC Copenhagen 1830 0
17 2009-08-31 26.20% @ Silkeborg 1677 3 Odense 1799 1
18 2010-04-11 26.42% @ Sonderjyske 1598 4 Silkeborg 1718 0
19 2009-08-09 26.71% Aalborg 1681 2 @ Brondby 1738 0
20 2010-04-15 26.91% Nordsjaelland 1661 1 @ Brondby 1716 0
21 2009-11-08 27.92% Esbjerg 1705 4 @ Brondby 1751 2
22 2010-03-20 28.15% Midtjylland 1684 2 @ Silkeborg 1727 0
23 2010-04-14 28.39% Randers 1656 3 @ Silkeborg 1698 1
24 2010-05-01 28.48% Aarhus GF 1633 4 @ Silkeborg 1674 1
25 2010-05-09 28.61% Aarhus GF 1641 1 @ Nordsjaelland 1681 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 2010-04-11 20.09 @ Sonderjyske 4 1598 26.42% Silkeborg 0 1718 50.17% 23.41%
2 2010-03-31 18.69 Aarhus GF 4 1648 30.00% @ Esbjerg 0 1676 45.88% 24.12%
3 2010-04-25 17.82 HB Koge 3 1512 19.21% @ Aarhus GF 0 1651 60.19% 20.61%
4 2010-03-28 17.67 @ Randers 4 1628 32.81% Esbjerg 0 1694 42.75% 24.44%
5 2009-09-20 16.83 Esbjerg 4 1681 35.26% @ Nordsjaelland 0 1668 40.14% 24.59%
6 2009-07-26 16.32 @ Silkeborg 4 1677 36.80% Midtjylland 0 1713 38.57% 24.64%
7 2009-08-02 16.21 Aalborg 5 1665 46.61% @ HB Koge 0 1571 29.37% 24.02%
8 2010-05-06 14.51 @ Esbjerg 4 1665 42.44% Silkeborg 0 1662 33.09% 24.47%
9 2010-03-24 13.35 Nordsjaelland 2 1660 15.10% @ FC Copenhagen 0 1860 67.05% 17.85%
10 2009-12-06 12.69 @ Nordsjaelland 3 1646 36.02% Midtjylland 0 1688 39.36% 24.62%
11 2010-05-09 12.58 @ Silkeborg 2 1647 18.01% FC Copenhagen 0 1863 62.09% 19.90%
12 2010-05-01 12.43 Aarhus GF 4 1633 28.48% @ Silkeborg 1 1674 47.66% 23.86%
13 2009-11-21 12.39 @ Midtjylland 3 1680 37.20% Esbjerg 0 1713 38.16% 24.64%
14 2009-08-08 12.25 @ Nordsjaelland 3 1665 37.76% Silkeborg 0 1694 37.60% 24.64%
15 2009-12-06 12.14 @ Silkeborg 3 1705 38.22% Brondby 0 1732 37.14% 24.64%
16 2009-09-14 11.98 Aalborg 3 1694 38.89% @ Randers 0 1655 36.48% 24.63%
17 2010-04-18 11.90 Nordsjaelland 4 1666 30.66% @ Silkeborg 1 1689 45.13% 24.21%
18 2010-05-03 11.89 @ Sonderjyske 2 1612 20.72% Odense 0 1792 57.90% 21.38%
19 2010-03-25 11.53 HB Koge 3 1516 15.24% @ Brondby 1 1713 66.80% 17.96%
20 2009-07-18 11.53 @ Nordsjaelland 2 1653 22.24% FC Copenhagen 0 1816 55.70% 22.06%
21 2009-09-27 11.26 Sonderjyske 2 1592 23.35% @ Midtjylland 0 1682 54.17% 22.48%
22 2009-09-27 11.22 @ Silkeborg 4 1691 33.67% Brondby 1 1750 41.83% 24.51%
23 2009-08-09 10.52 Aalborg 2 1681 26.71% @ Brondby 0 1738 49.81% 23.48%
24 2010-05-16 10.24 @ Midtjylland 3 1688 45.90% Silkeborg 0 1660 29.99% 24.11%
25 2010-03-20 10.22 Midtjylland 2 1684 28.15% @ Silkeborg 0 1727 48.06% 23.80%