Home / Leagues / Denmark / Superliga / 2001-02

2001-02 Superliga Season

198 games

Final

Champion

Brondby

69 points · 9th Title

Last Title: 1997-98

Relegated

Lyngby

15 pts

Vejle BK · 28 pts

Biggest Overachiever

Midtjylland

8.02 points above expected

57 points · 48.98 expected points

Biggest Disappointment

Lyngby

12.66 points below expected

15 points · 27.66 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 Brondby Champion 33 20 9 4 69 74 28 +46 67.24 +1.76
2 FC Copenhagen 33 20 9 4 69 62 25 +37 61.32 +7.68
3 Midtjylland 33 16 9 8 57 47 27 +20 48.98 +8.02
4 Aalborg 33 16 6 11 54 52 45 +7 47.69 +6.31
5 AB Copenhagen 33 13 11 9 50 48 38 +10 52.65 -2.65
6 Odense 33 13 10 10 49 56 51 +5 43.59 +5.41
7 Esbjerg 33 13 6 14 45 42 44 -2 39.53 +5.47
8 Viborg 33 10 11 12 41 46 45 +1 43.26 -2.26
9 Silkeborg 33 8 8 17 32 41 50 -9 40.61 -8.61
10 Aarhus GF 33 7 10 16 31 42 56 -14 37.05 -6.05
11 Vejle BK Relegated 33 6 10 17 28 38 72 -34 31.11 -3.11
12 Lyngby Relegated 33 2 9 22 15 25 92 -67 27.66 -12.66

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
Brondby 1861 69 67.24 +1.76 62.0% 40 56 63 67 72 78 92
FC Copenhagen 1857 69 61.32 +7.68 88.1% 30 50 57 61 66 73 87
Midtjylland 1737 57 48.98 +8.02 88.6% 24 37 44 49 54 61 74
AB Copenhagen 1652 50 52.65 -2.65 37.7% 27 41 48 53 57 64 84
Odense 1632 49 43.59 +5.41 80.1% 20 32 39 43 48 56 70
Aalborg 1625 54 47.69 +6.31 83.2% 24 36 43 48 52 59 75
Viborg 1598 41 43.26 -2.26 40.3% 15 32 38 43 48 55 68
Aarhus GF 1562 31 37.05 -6.05 21.2% 13 26 32 37 42 49 67
Silkeborg 1553 32 40.61 -8.61 11.9% 16 30 36 40 45 52 66
Esbjerg 1546 45 39.53 +5.47 81.0% 13 28 35 39 44 51 66
Vejle BK 1447 28 31.11 -3.11 35.0% 9 21 27 31 35 42 57
Lyngby 1246 15 27.66 -12.66 1.9% 5 18 23 27 32 38 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 AC AAL AG BRO ESB FC LYN MID ODE SIL VB VIB
AB Copenhagen
2-0-1
4.46
1-2-0
5.73
0-0-3
2.83
2-1-0
5.17
1-2-0
3.29
3-0-0
6.16
0-1-2
4.33
1-2-0
5.01
1-2-0
4.86
2-1-0
5.82
0-0-3
4.99
Aalborg
1-0-2
3.68
1-1-1
5.20
0-1-2
2.59
2-1-0
4.85
0-1-2
2.96
3-0-0
5.85
2-0-1
3.75
2-1-0
3.93
1-0-2
5.28
1-1-1
5.40
3-0-0
4.22
Aarhus GF
0-2-1
2.46
1-1-1
2.97
0-1-2
2.16
0-0-3
3.96
0-1-2
2.05
2-1-0
5.08
0-0-3
3.24
0-0-3
3.55
1-1-1
3.86
2-1-0
4.51
1-2-0
3.33
Brondby
3-0-0
5.33
2-1-0
5.59
2-1-0
6.09
3-0-0
6.44
2-1-0
4.91
1-1-1
7.08
1-1-1
5.94
2-0-1
6.00
2-0-1
6.39
2-1-0
7.03
0-3-0
6.41
Esbjerg
0-1-2
2.99
0-1-2
3.31
3-0-0
4.17
0-0-3
1.83
1-0-2
2.13
2-0-1
5.51
1-1-1
2.73
2-0-1
3.71
1-2-0
4.40
0-1-2
5.10
3-0-0
3.56
FC Copenhagen
0-2-1
4.86
2-1-0
5.22
2-1-0
6.21
0-1-2
3.25
2-0-1
6.11
3-0-0
6.50
1-2-0
5.43
1-2-0
5.69
3-0-0
5.88
3-0-0
6.61
3-0-0
5.59
Lyngby
0-0-3
2.12
0-0-3
2.37
0-1-2
3.10
1-1-1
1.36
1-0-2
2.75
0-0-3
1.84
0-1-2
2.73
0-1-2
3.14
0-1-2
2.16
0-2-1
3.21
0-2-1
2.88
Midtjylland
2-1-0
3.81
1-0-2
4.39
3-0-0
4.91
1-1-1
2.27
1-1-1
5.45
0-2-1
2.74
2-1-0
5.51
1-0-2
4.59
3-0-0
4.92
1-2-0
5.61
1-1-1
4.91
Odense
0-2-1
3.15
0-1-2
4.20
3-0-0
4.60
1-0-2
2.22
1-0-2
4.42
0-2-1
2.50
2-1-0
5.08
2-0-1
3.55
2-1-0
4.18
2-1-0
5.46
0-2-1
4.24
Silkeborg
0-2-1
3.32
2-0-1
2.88
1-1-1
4.28
1-0-2
1.89
0-2-1
3.74
0-0-3
2.33
2-1-0
6.11
0-0-3
3.23
0-1-2
3.96
2-0-1
5.25
0-1-2
3.49
Vejle BK
0-1-2
2.39
1-1-1
2.78
0-1-2
3.63
0-1-2
1.35
2-1-0
3.10
0-0-3
1.71
1-2-0
4.95
0-2-1
2.59
0-1-2
2.74
1-0-2
2.92
1-0-2
3.06
Viborg
3-0-0
3.16
0-0-3
3.92
0-2-1
4.81
0-3-0
1.86
0-0-3
4.58
0-0-3
2.59
1-2-0
5.32
1-1-1
3.24
1-2-0
3.90
2-1-0
4.66
2-0-1
5.10

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

Slope
Scored 0.83 +12.1
Allowed 0.84 -7.8
Differential 0.93 +5.3

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
07.58%7.32%6.31%1.77%2.53%2.53%28.03%
17.32%11.62%7.32%2.78%1.52%1.01%31.57%
26.31%7.32%8.08%1.26%0.51%0.51%23.99%
31.77%2.78%1.26%1.01%6.82%
42.53%1.52%0.51%1.01%5.56%
5+2.53%1.01%0.51%4.04%
Total28.03%31.57%23.99%6.82%5.56%4.04%100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.45 +0.00
SD 1.40 1.40 2.17
CV 0.97 0.97
Max 7 7 +7
Min 0 0 -7

Games Played: 198

↓ Scored | Allowed →012345+Total
09.09%3.03%3.03%3.03%18.18%
112.12%12.12%15.15%3.03%42.42%
29.09%3.03%12.12%24.24%
33.03%3.03%6.06%
46.06%3.03%9.09%
5+
Total39.39%21.21%30.30%6.06%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.15 +0.30
SD 1.15 1.20 1.76
CV 0.79 1.04
Max 4 5 +4
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%9.09%3.03%24.24%
19.09%6.06%3.03%3.03%3.03%24.24%
23.03%21.21%6.06%6.06%36.36%
36.06%3.03%9.09%
43.03%3.03%
5+3.03%3.03%
Total24.24%39.39%21.21%6.06%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.36 +0.21
SD 1.44 1.19 2.03
CV 0.91 0.88
Max 7 4 +7
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
015.15%12.12%6.06%3.03%6.06%42.42%
13.03%6.06%6.06%6.06%3.03%3.03%27.27%
29.09%3.03%12.12%
36.06%6.06%
43.03%3.03%3.03%9.09%
5+3.03%3.03%
Total30.30%21.21%21.21%15.15%3.03%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.70 -0.42
SD 1.64 1.65 2.53
CV 1.29 0.97
Max 7 6 +7
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%12.12%
16.06%12.12%3.03%21.21%
212.12%15.15%9.09%36.36%
39.09%3.03%12.12%
43.03%3.03%6.06%
5+9.09%3.03%12.12%
Total36.36%48.48%12.12%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 2.24 0.85 +1.39
SD 1.70 0.87 1.97
CV 0.76 1.03
Max 7 4 +7
Min 0 0 -1

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%15.15%6.06%39.39%
16.06%9.09%9.09%3.03%27.27%
218.18%3.03%21.21%
3
43.03%3.03%6.06%
5+3.03%3.03%6.06%
Total36.36%27.27%24.24%6.06%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.33 -0.06
SD 1.55 1.63 2.51
CV 1.22 1.22
Max 6 7 +5
Min 0 0 -7

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%3.03%6.06%18.18%
19.09%15.15%3.03%27.27%
26.06%15.15%3.03%24.24%
39.09%6.06%15.15%
43.03%6.06%3.03%12.12%
5+3.03%3.03%
Total39.39%45.45%15.15%100%

Summary Statistics

Scored Allowed Difference
Mean 1.88 0.76 +1.12
SD 1.47 0.71 1.71
CV 0.78 0.94
Max 6 2 +6
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%9.09%6.06%6.06%12.12%12.12%51.52%
13.03%6.06%3.03%3.03%3.03%3.03%21.21%
23.03%15.15%3.03%6.06%27.27%
3
4
5+
Total12.12%15.15%24.24%12.12%15.15%21.21%100%

Summary Statistics

Scored Allowed Difference
Mean 0.76 2.79 -2.03
SD 0.87 1.93 2.23
CV 1.14 0.69
Max 2 7 +2
Min 0 0 -7

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%3.03%21.21%
118.18%15.15%9.09%3.03%45.45%
29.09%3.03%3.03%15.15%
33.03%6.06%9.09%
46.06%6.06%
5+3.03%3.03%
Total45.45%30.30%21.21%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.42 0.82 +0.61
SD 1.28 0.88 1.62
CV 0.90 1.08
Max 5 3 +5
Min 0 0 -2

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%15.15%3.03%21.21%
19.09%15.15%3.03%3.03%30.30%
29.09%15.15%24.24%
36.06%3.03%3.03%12.12%
43.03%3.03%6.06%
5+3.03%3.03%6.06%
Total15.15%36.36%36.36%3.03%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.70 1.55 +0.15
SD 1.42 1.09 1.94
CV 0.84 0.71
Max 5 4 +5
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%12.12%6.06%3.03%6.06%33.33%
19.09%12.12%12.12%3.03%36.36%
26.06%6.06%6.06%18.18%
33.03%3.03%
43.03%3.03%
5+3.03%3.03%6.06%
Total27.27%24.24%27.27%12.12%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.24 1.52 -0.27
SD 1.37 1.28 1.96
CV 1.10 0.84
Max 5 4 +5
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%6.06%9.09%3.03%30.30%
115.15%9.09%6.06%6.06%6.06%42.42%
26.06%3.03%9.09%18.18%
33.03%3.03%
43.03%3.03%
5+3.03%3.03%
Total15.15%24.24%24.24%12.12%15.15%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.15 2.18 -1.03
SD 1.18 1.63 2.23
CV 1.02 0.75
Max 5 6 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%6.06%24.24%
13.03%15.15%12.12%3.03%33.33%
23.03%15.15%9.09%3.03%30.30%
33.03%3.03%6.06%
43.03%3.03%
5+3.03%3.03%
Total15.15%45.45%30.30%6.06%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.36 +0.03
SD 1.20 0.93 1.33
CV 0.86 0.68
Max 5 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 Midtjylland 57 48.98 +8.02
2 FC Copenhagen 69 61.32 +7.68
3 Aalborg 54 47.69 +6.31
4 Esbjerg 45 39.53 +5.47
5 Odense 49 43.59 +5.41

Biggest Disappointments

# Team Actual Sim vsSim
1 Lyngby 15 27.66 -12.66
2 Silkeborg 32 40.61 -8.61
3 Aarhus GF 31 37.05 -6.05
4 Vejle BK 28 31.11 -3.11
5 AB Copenhagen 50 52.65 -2.65

Top Streaks

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

Most Unlikely Winning Streaks

# Team Games Dates Probability
1 Midtjylland 7 Apr 14 – May 16 1 in 481
2 Silkeborg 4 Nov 18 – Dec 9 1 in 383
3 Esbjerg 4 Sep 9 – Sep 24 1 in 320
4 Aalborg 4 Mar 4 – Mar 24 1 in 73
5 Odense 3 Mar 3 – Mar 17 1 in 34

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Lyngby 12 Dec 9 – May 1 1 in 191
2 AB Copenhagen 4 Dec 9 – Mar 17 1 in 140
3 Silkeborg 6 Aug 12 – Sep 23 1 in 131
4 FC Copenhagen 2 Aug 12 – Aug 17 1 in 33
5 Odense 3 May 5 – May 16 1 in 16

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Odense 10 Oct 21 – Mar 17 1 in 167
2 AB Copenhagen 14 Aug 17 – Dec 2 1 in 48
3 Vejle BK 4 Mar 24 – Apr 10 1 in 48
4 Lyngby 6 Jul 22 – Aug 26 1 in 25
5 Silkeborg 4 Nov 18 – Dec 9 1 in 15

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Lyngby 29 Aug 19 – May 16 1 in 456
2 Silkeborg 15 Jul 22 – Nov 4 1 in 174
3 AB Copenhagen 7 Nov 25 – Mar 24 1 in 36
4 Brondby 3 Apr 7 – Apr 14 1 in 30
5 Viborg 7 Sep 16 – Nov 4 1 in 29

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
Brondby68.43%23.43%6.02%1.49%0.41%0.16%0.03%0.03%
FC Copenhagen25.42%46.21%16.85%6.50%2.85%1.31%0.56%0.22%0.05%0.02%0.01%
Midtjylland1.29%7.09%17.79%20.27%17.36%13.34%9.67%5.97%4.12%2.18%0.82%0.10%
Aalborg0.86%5.14%13.22%18.14%18.10%14.37%12.03%7.84%5.64%3.22%1.15%0.29%
AB Copenhagen3.41%13.67%28.78%20.49%12.99%9.44%5.32%3.28%1.59%0.70%0.30%0.03%
Odense0.34%1.58%6.09%10.65%13.42%15.53%15.11%14.33%11.09%6.81%3.89%1.16%
Esbjerg0.07%0.46%2.13%4.43%7.27%10.34%13.73%16.34%16.82%15.58%9.07%3.76%
Viborg0.12%1.54%5.45%9.57%13.85%15.00%15.07%13.76%11.65%8.35%4.28%1.36%
Silkeborg0.04%0.63%2.69%5.86%8.23%11.61%14.53%16.56%15.75%13.86%7.52%2.72%
Aarhus GF0.02%0.24%0.90%2.21%4.58%6.86%9.75%13.82%17.84%21.10%15.22%7.46%
Vejle BK0.07%0.35%0.73%1.52%2.98%5.60%10.39%17.47%33.66%27.23%
Lyngby0.01%0.01%0.04%0.21%0.52%1.22%2.25%5.06%10.71%24.08%55.89%

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
+4.04%
No Edge
38.38%27.27%34.34%
Elo Value
Home Edge: 14.05 Elo pts.
160 Elo
0.006 goals per Elo point
0400
Scoring Tilt
Expected
+0.23 goals
Neutral
-2+0.09+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
1.9
One-Team Race
124610
Champion Preseason Odds
68%
Brondby, 1st of 12
LongshotFavorite
Title Margin
Expected
0.00/gm
Photo Finish
00.230.5/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 5.5 * Some Luck: 5.5 to 8.25 * Lucky: 8.25 to 11.01 * Wild Swing: 11.01 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 1.15 * Close: 1.15 to 1.73 * Off: 1.73 to 2.31 * Way Off: 2.31 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 0.59 * A Surprise: 0.59 to 0.95 * Several Surprises: 0.95 to 1.3 * Many Surprises: 1.3 and up.
Luck Spread
Expected
6.57 points
Some Luck
06.8817
Average Finish Error
Expected
0.67
Pinpoint
01.443
Biggest Overachiever
Expected 95.83%
88.64%
Midtjylland
50100
Biggest Underachiever
Expected 4.17%
1.93%
Lyngby
050
Season Outliers
Expected
1 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
0 of 2
As Expected
00.62

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
0.20
Top-Heavy
00.120.180.260.5
Noll-Scully
Coin-flip
1.91
Strong Separation
01.003
Interquartile Edge
67%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline 97%
97%
Dominant
50%100%
Close Games
Expected
61%
Very Frequent
0%51%100%
Blowouts
Expected
20%
Frequent
0%25%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
0.59
Predictable
00.602
Matchup Imbalance
0.38
Lopsided
00.10.180.280.5
Strangeness
Expected
0.96
As Expected
01.002
Repeatability
0.55
Some Carryover
00.30.60.851
Upset Rate
Expected
19%
Chalky
0%23%50%
Clear Favorite Upset Rate
Expected
17%
As Expected
0%18%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 0.13 * Near Noise Ceiling: 0.13 to 0.19 * Above Noise: 0.19 to 0.25 * Well Above Noise: 0.25 and up.
Probability calibration
0.25
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
1.09
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.080
Well Within Noise
00.1270.3

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
Brondby 100%
FC Copenhagen 99.99% 0.01%
AB Copenhagen 99.67% 0.33%
Midtjylland 99.08% 0.92%
Aalborg 98.56% 1.44%
Odense 94.95% 5.05%
Viborg 94.36% 5.64%
Silkeborg 89.76% 10.24%
Esbjerg 87.17% 12.83%
Aarhus GF 77.32% 22.68%
Vejle BK 39.11% 60.89%
Lyngby 20.03% 79.97%

Overall Game Log

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

Date Opponent Score Pre Elo Opp Elo Win % Tie % Loss % Elo Δ Points
2001-07-21 Viborg W 2-1 1697 1613 48.67% 28.07% 23.27% +8.6 3
2001-07-21 @ FC Copenhagen L 1-2 1613 1697 23.27% 28.07% 48.67% -8.6 0
2001-07-22 Aarhus GF W 5-0 1678 1618 45.65% 28.44% 25.92% +44.0 3
2001-07-22 @ Brondby L 0-5 1618 1678 25.92% 28.44% 45.65% -44.0 0
2001-07-22 AB Copenhagen D 1-1 1653 1627 41.22% 28.78% 30.00% -0.8 1
2001-07-22 @ Silkeborg D 1-1 1627 1653 30.00% 28.78% 41.22% +0.8 1
2001-07-22 Lyngby D 2-2 1571 1549 40.55% 28.81% 30.64% -0.5 1
2001-07-22 @ Vejle BK D 2-2 1549 1571 30.64% 28.81% 40.55% +0.5 1
2001-07-23 Midtjylland W 2-1 1617 1609 38.56% 28.89% 32.55% +11.2 3
2001-07-23 @ Aalborg L 1-2 1609 1617 32.55% 28.89% 38.56% -11.2 0
2001-07-29 Aalborg L 1-3 1574 1628 30.14% 28.79% 41.07% -18.3 0
2001-07-29 @ Aarhus GF W 3-1 1628 1574 41.07% 28.79% 30.14% +18.3 6
2001-07-29 Brondby L 1-3 1628 1722 25.20% 28.35% 46.45% -15.9 1
2001-07-29 @ AB Copenhagen W 3-1 1722 1628 46.45% 28.35% 25.20% +15.9 6
2001-07-29 Esbjerg W 2-0 1550 1491 45.43% 28.46% 26.11% +18.9 4
2001-07-29 @ Lyngby L 0-2 1491 1550 26.11% 28.46% 45.43% -18.9 0
2001-07-29 Vejle BK W 4-1 1706 1570 54.62% 26.97% 18.41% +17.3 6
2001-07-29 @ FC Copenhagen L 1-4 1570 1706 18.41% 26.97% 54.62% -17.3 1
2001-07-29 Viborg D 1-1 1598 1605 36.60% 28.92% 34.48% -0.1 1
2001-07-29 @ Midtjylland D 1-1 1605 1598 34.48% 28.92% 36.60% +0.1 1
2001-07-30 Silkeborg W 3-1 1592 1653 29.19% 28.73% 42.08% +23.4 3
2001-07-30 @ Odense L 1-3 1653 1592 42.08% 28.73% 29.19% -23.4 1
2001-08-05 Aarhus GF D 0-0 1605 1556 44.22% 28.57% 27.21% -1.3 2
2001-08-05 @ Viborg D 0-0 1556 1605 27.21% 28.57% 44.22% +1.3 1
2001-08-05 AB Copenhagen L 0-2 1646 1612 42.26% 28.72% 29.02% -27.1 6
2001-08-05 @ Aalborg W 2-0 1612 1646 29.02% 28.72% 42.26% +27.1 4
2001-08-05 FC Copenhagen D 0-0 1598 1723 21.92% 27.83% 50.25% +2.3 2
2001-08-05 @ Midtjylland D 0-0 1723 1598 50.25% 27.83% 21.92% -2.2 7
2001-08-05 Odense W 2-0 1738 1615 53.18% 27.29% 19.53% +14.9 9
2001-08-05 @ Brondby L 0-2 1615 1738 19.53% 27.29% 53.18% -14.9 3
2001-08-05 Vejle BK D 1-1 1472 1553 26.80% 28.53% 44.67% +1.2 1
2001-08-05 @ Esbjerg D 1-1 1553 1472 44.67% 28.53% 26.80% -1.2 2
2001-08-06 Lyngby D 0-0 1629 1569 45.75% 28.43% 25.82% -1.5 2
2001-08-06 @ Silkeborg D 0-0 1569 1629 25.82% 28.43% 45.75% +1.5 5
2001-08-12 Aalborg L 0-2 1600 1619 34.88% 28.93% 36.19% -23.5 3
2001-08-12 @ Odense W 2-0 1619 1600 36.19% 28.93% 34.88% +23.5 9
2001-08-12 Brondby W 1-0 1570 1753 16.91% 26.48% 56.61% +18.3 8
2001-08-12 @ Lyngby L 0-1 1753 1570 56.61% 26.48% 16.91% -18.3 9
2001-08-12 FC Copenhagen W 2-1 1474 1721 12.66% 24.48% 62.86% +18.9 4
2001-08-12 @ Esbjerg L 1-2 1721 1474 62.86% 24.48% 12.66% -18.9 7
2001-08-12 Midtjylland L 0-1 1557 1600 31.52% 28.85% 39.62% -11.6 1
2001-08-12 @ Aarhus GF W 1-0 1600 1557 39.62% 28.85% 31.52% +11.6 5
2001-08-12 Silkeborg W 3-0 1552 1628 27.32% 28.58% 44.10% +40.7 5
2001-08-12 @ Vejle BK L 0-3 1628 1552 44.10% 28.58% 27.32% -40.7 2
2001-08-12 Viborg L 1-2 1639 1604 42.41% 28.71% 28.88% -13.6 4
2001-08-12 @ AB Copenhagen W 2-1 1604 1639 28.88% 28.71% 42.41% +13.6 5
2001-08-17 AB Copenhagen L 0-2 1702 1625 47.79% 28.19% 24.02% -29.9 7
2001-08-17 @ FC Copenhagen W 2-0 1625 1702 24.02% 28.19% 47.79% +29.9 7
2001-08-19 Lyngby D 0-0 1612 1588 40.80% 28.80% 30.39% -0.8 6
2001-08-19 @ Midtjylland D 0-0 1588 1612 30.39% 28.80% 40.80% +0.8 9
2001-08-19 Odense L 0-1 1546 1577 33.13% 28.90% 37.97% -12.0 1
2001-08-19 @ Aarhus GF W 1-0 1577 1546 37.97% 28.90% 33.13% +12.0 6
2001-08-19 Silkeborg W 4-0 1735 1587 55.85% 26.68% 17.47% +25.5 12
2001-08-19 @ Brondby L 0-4 1587 1735 17.47% 26.68% 55.85% -25.5 2
2001-08-19 Vejle BK L 1-2 1617 1592 41.00% 28.79% 30.21% -13.2 5
2001-08-19 @ Viborg W 2-1 1592 1617 30.21% 28.79% 41.00% +13.2 8
2001-08-20 Esbjerg W 2-1 1642 1493 56.10% 26.61% 17.29% +6.7 12
2001-08-20 @ Aalborg L 1-2 1493 1642 17.29% 26.61% 56.10% -6.7 4
2001-08-26 Aalborg L 1-3 1606 1649 31.45% 28.85% 39.70% -18.9 8
2001-08-26 @ Vejle BK W 3-1 1649 1606 39.70% 28.85% 31.45% +18.9 15
2001-08-26 Aarhus GF D 0-0 1655 1534 53.03% 27.32% 19.65% -2.7 8
2001-08-26 @ AB Copenhagen D 0-0 1534 1655 19.65% 27.32% 53.03% +2.7 2
2001-08-26 Brondby L 0-7 1486 1760 11.24% 23.54% 65.22% -27.9 4
2001-08-26 @ Esbjerg W 7-0 1760 1486 65.22% 23.54% 11.24% +28.0 15
2001-08-26 FC Copenhagen L 0-2 1562 1672 23.41% 28.09% 48.50% -17.3 2
2001-08-26 @ Silkeborg W 2-0 1672 1562 48.50% 28.09% 23.41% +17.3 10
2001-08-26 Midtjylland L 0-2 1589 1611 34.37% 28.92% 36.70% -23.2 6
2001-08-26 @ Odense W 2-0 1611 1589 36.70% 28.92% 34.37% +23.2 9
2001-08-26 Viborg D 2-2 1589 1604 35.43% 28.93% 35.64% +0.0 10
2001-08-26 @ Lyngby D 2-2 1604 1589 35.64% 28.93% 35.43% -0.0 6
2001-09-09 Brondby L 1-3 1668 1788 22.45% 27.93% 49.62% -14.5 15
2001-09-09 @ Aalborg W 3-1 1788 1668 49.62% 27.93% 22.45% +14.5 18
2001-09-09 Esbjerg L 0-2 1634 1458 58.80% 25.86% 15.34% -35.7 9
2001-09-09 @ Midtjylland W 2-0 1458 1634 15.34% 25.86% 58.80% +35.7 7
2001-09-09 Lyngby W 3-1 1652 1589 46.07% 28.39% 25.53% +16.1 11
2001-09-09 @ AB Copenhagen L 1-3 1589 1652 25.53% 28.39% 46.07% -16.1 10
2001-09-09 Odense D 1-1 1690 1566 53.33% 27.26% 19.42% -2.5 11
2001-09-09 @ FC Copenhagen D 1-1 1566 1690 19.42% 27.26% 53.33% +2.5 7
2001-09-09 Silkeborg W 2-0 1604 1544 45.61% 28.44% 25.95% +18.8 9
2001-09-09 @ Viborg L 0-2 1544 1604 25.95% 28.44% 45.61% -18.8 2
2001-09-10 Vejle BK W 3-0 1536 1587 30.56% 28.81% 40.63% +38.1 5
2001-09-10 @ Aarhus GF L 0-3 1587 1536 40.63% 28.81% 30.56% -38.1 8
2001-09-12 Odense W 2-0 1494 1568 27.52% 28.60% 43.88% +27.9 10
2001-09-12 @ Esbjerg L 0-2 1568 1494 43.88% 28.60% 27.52% -27.9 7
2001-09-16 Aalborg L 1-2 1525 1653 21.67% 27.78% 50.55% -8.1 2
2001-09-16 @ Silkeborg W 2-1 1653 1525 50.55% 27.78% 21.67% +8.1 18
2001-09-16 AB Copenhagen D 2-2 1540 1669 21.63% 27.77% 50.60% +1.5 8
2001-09-16 @ Odense D 2-2 1669 1540 50.60% 27.77% 21.63% -1.5 12
2001-09-16 Esbjerg L 0-2 1623 1521 50.71% 27.75% 21.53% -31.4 9
2001-09-16 @ Viborg W 2-0 1521 1623 21.53% 27.75% 50.71% +31.4 13
2001-09-16 FC Copenhagen W 2-0 1803 1687 52.33% 27.46% 20.21% +15.3 21
2001-09-16 @ Brondby L 0-2 1687 1803 20.21% 27.46% 52.33% -15.3 11
2001-09-16 Midtjylland D 1-1 1549 1599 30.59% 28.81% 40.60% +0.7 9
2001-09-16 @ Vejle BK D 1-1 1599 1549 40.60% 28.81% 30.59% -0.7 10
2001-09-17 Aarhus GF D 1-1 1573 1575 37.33% 28.92% 33.75% -0.2 11
2001-09-17 @ Lyngby D 1-1 1575 1573 33.75% 28.92% 37.33% +0.2 6
2001-09-23 AB Copenhagen D 1-1 1549 1667 22.69% 27.97% 49.34% +1.9 10
2001-09-23 @ Vejle BK D 1-1 1667 1549 49.34% 27.97% 22.69% -1.9 13
2001-09-23 FC Copenhagen D 1-1 1662 1672 36.06% 28.93% 35.01% -0.1 19
2001-09-23 @ Aalborg D 1-1 1672 1662 35.01% 28.93% 36.06% +0.1 12
2001-09-23 Midtjylland L 0-1 1517 1598 26.78% 28.53% 44.69% -10.2 2
2001-09-23 @ Silkeborg W 1-0 1598 1517 44.69% 28.53% 26.78% +10.2 13
2001-09-23 Odense D 2-2 1573 1542 41.86% 28.74% 29.40% -0.6 12
2001-09-23 @ Lyngby D 2-2 1542 1573 29.40% 28.74% 41.86% +0.6 9
2001-09-23 Viborg D 0-0 1818 1591 63.51% 24.23% 12.26% -4.4 22
2001-09-23 @ Brondby D 0-0 1591 1818 12.26% 24.23% 63.51% +4.4 10
2001-09-24 Aarhus GF W 4-1 1553 1575 34.41% 28.92% 36.66% +29.8 16
2001-09-24 @ Esbjerg L 1-4 1575 1553 36.66% 28.92% 34.41% -29.8 6
2001-09-30 Aalborg L 2-3 1596 1661 28.58% 28.69% 42.73% -9.6 10
2001-09-30 @ Viborg W 3-2 1661 1596 42.73% 28.69% 28.58% +9.6 22
2001-09-30 Brondby D 1-1 1608 1813 15.27% 25.83% 58.89% +3.3 14
2001-09-30 @ Midtjylland D 1-1 1813 1608 58.89% 25.83% 15.27% -3.3 23
2001-09-30 Esbjerg W 2-0 1665 1583 48.46% 28.10% 23.44% +17.3 16
2001-09-30 @ AB Copenhagen L 0-2 1583 1665 23.44% 28.10% 48.46% -17.4 16
2001-09-30 Lyngby W 1-0 1672 1572 50.54% 27.78% 21.68% +8.6 15
2001-09-30 @ FC Copenhagen L 0-1 1572 1672 21.68% 27.78% 50.54% -8.6 12
2001-09-30 Silkeborg D 2-2 1545 1507 42.76% 28.69% 28.55% -0.7 7
2001-09-30 @ Aarhus GF D 2-2 1507 1545 28.55% 28.69% 42.76% +0.7 3
2001-09-30 Vejle BK W 5-1 1542 1551 36.29% 28.93% 34.78% +37.0 12
2001-09-30 @ Odense L 1-5 1551 1542 34.78% 28.93% 36.29% -37.0 10
2001-10-10 Aarhus GF W 3-0 1681 1544 54.67% 26.96% 18.37% +20.5 18
2001-10-10 @ FC Copenhagen L 0-3 1544 1681 18.37% 26.96% 54.67% -20.5 7
2001-10-10 AB Copenhagen D 2-2 1611 1682 27.93% 28.64% 43.44% +0.8 15
2001-10-10 @ Midtjylland D 2-2 1682 1611 43.44% 28.64% 27.93% -0.8 17
2001-10-10 Esbjerg L 3-4 1508 1565 29.62% 28.76% 41.62% -9.6 3
2001-10-10 @ Silkeborg W 4-3 1565 1508 41.62% 28.76% 29.62% +9.6 19
2001-10-10 Lyngby W 2-1 1671 1564 51.44% 27.62% 20.94% +7.9 25
2001-10-10 @ Aalborg L 1-2 1564 1671 20.94% 27.62% 51.44% -7.9 12
2001-10-10 Odense D 2-2 1586 1579 38.49% 28.89% 32.62% -0.3 11
2001-10-10 @ Viborg D 2-2 1579 1586 32.62% 28.89% 38.49% +0.3 13
2001-10-10 Vejle BK W 2-1 1810 1514 69.30% 21.67% 9.03% +3.4 26
2001-10-10 @ Brondby L 1-2 1514 1810 9.03% 21.67% 69.30% -3.4 10
2001-10-14 Aalborg D 0-0 1814 1679 54.49% 27.00% 18.51% -2.9 27
2001-10-14 @ Brondby D 0-0 1679 1814 18.51% 27.00% 54.49% +2.9 26
2001-10-14 AB Copenhagen D 1-1 1524 1682 18.93% 27.12% 53.95% +2.6 8
2001-10-14 @ Aarhus GF D 1-1 1682 1524 53.95% 27.12% 18.93% -2.6 18
2001-10-14 FC Copenhagen L 0-1 1498 1701 15.44% 25.91% 58.65% -6.4 3
2001-10-14 @ Silkeborg W 1-0 1701 1498 58.65% 25.91% 15.44% +6.4 21
2001-10-14 Midtjylland L 0-4 1556 1612 29.75% 28.77% 41.48% -39.7 12
2001-10-14 @ Lyngby W 4-0 1612 1556 41.48% 28.77% 29.75% +39.6 18
2001-10-14 Odense W 2-0 1575 1580 36.87% 28.92% 34.20% +23.1 22
2001-10-14 @ Esbjerg L 0-2 1580 1575 34.20% 28.92% 36.87% -23.2 13
2001-10-21 Brondby L 1-3 1652 1811 18.84% 27.10% 54.06% -12.5 18
2001-10-21 @ Midtjylland W 3-1 1811 1652 54.06% 27.10% 18.84% +12.5 30
2001-10-21 Esbjerg L 0-1 1586 1598 35.79% 28.93% 35.28% -12.7 11
2001-10-21 @ Viborg W 1-0 1598 1586 35.28% 28.93% 35.79% +12.7 25
2001-10-21 Lyngby W 4-1 1707 1516 60.26% 25.40% 14.34% +13.7 24
2001-10-21 @ FC Copenhagen L 1-4 1516 1707 14.34% 25.40% 60.26% -13.7 12
2001-10-21 Silkeborg W 2-1 1556 1492 46.25% 28.37% 25.37% +9.2 16
2001-10-21 @ Odense L 1-2 1492 1556 25.37% 28.37% 46.25% -9.2 3
2001-10-21 Vejle BK W 4-0 1679 1511 58.02% 26.09% 15.89% +23.4 21
2001-10-21 @ AB Copenhagen L 0-4 1511 1679 15.89% 26.09% 58.02% -23.4 10
2001-10-22 Aarhus GF L 1-4 1682 1526 56.70% 26.46% 16.84% -42.3 26
2001-10-22 @ Aalborg W 4-1 1526 1682 16.84% 26.46% 56.70% +42.3 11
2001-10-28 Aalborg W 4-2 1487 1640 19.41% 27.25% 53.33% +25.4 13
2001-10-28 @ Vejle BK L 2-4 1640 1487 53.33% 27.25% 19.41% -25.4 26
2001-10-28 Brondby L 1-2 1569 1823 12.27% 24.24% 63.50% -4.8 11
2001-10-28 @ Aarhus GF W 2-1 1823 1569 63.50% 24.24% 12.27% +4.8 33
2001-10-28 Midtjylland D 1-1 1721 1639 48.38% 28.11% 23.51% -1.8 25
2001-10-28 @ FC Copenhagen D 1-1 1639 1721 23.51% 28.11% 48.38% +1.8 19
2001-10-28 Odense L 2-3 1502 1566 28.88% 28.71% 42.41% -9.7 12
2001-10-28 @ Lyngby W 3-2 1566 1502 42.41% 28.71% 28.88% +9.7 19
2001-10-28 Viborg D 1-1 1483 1573 25.63% 28.40% 45.97% +1.4 4
2001-10-28 @ Silkeborg D 1-1 1573 1483 45.97% 28.40% 25.63% -1.4 12
2001-10-29 AB Copenhagen L 1-2 1611 1702 25.50% 28.39% 46.12% -9.3 25
2001-10-29 @ Esbjerg W 2-1 1702 1611 46.12% 28.39% 25.50% +9.3 24
2001-11-04 Aarhus GF W 2-0 1641 1564 47.82% 28.18% 24.00% +17.7 22
2001-11-04 @ Midtjylland L 0-2 1564 1641 24.00% 28.18% 47.82% -17.7 11
2001-11-04 FC Copenhagen D 1-1 1575 1719 20.16% 27.44% 52.39% +2.3 20
2001-11-04 @ Odense D 1-1 1719 1575 52.39% 27.44% 20.16% -2.3 26
2001-11-04 Lyngby D 1-1 1572 1493 48.04% 28.15% 23.81% -1.7 13
2001-11-04 @ Viborg D 1-1 1493 1572 23.81% 28.15% 48.04% +1.7 13
2001-11-04 Silkeborg W 1-0 1712 1484 63.62% 24.19% 12.19% +5.0 27
2001-11-04 @ AB Copenhagen L 0-1 1484 1712 12.19% 24.19% 63.62% -5.0 4
2001-11-04 Vejle BK W 6-1 1828 1513 70.77% 20.92% 8.31% +12.0 36
2001-11-04 @ Brondby L 1-6 1513 1828 8.31% 20.92% 70.77% -12.0 13
2001-11-05 Esbjerg D 0-0 1614 1601 39.32% 28.86% 31.81% -0.6 27
2001-11-05 @ Aalborg D 0-0 1601 1614 31.81% 28.86% 39.32% +0.6 26
2001-11-12 Viborg L 1-2 1501 1570 28.14% 28.65% 43.21% -10.0 13
2001-11-12 @ Vejle BK W 2-1 1570 1501 43.21% 28.65% 28.14% +10.0 16
2001-11-18 Aalborg W 2-0 1479 1614 21.02% 27.64% 51.33% +31.7 7
2001-11-18 @ Silkeborg L 0-2 1614 1479 51.33% 27.64% 21.02% -31.7 27
2001-11-18 Aarhus GF L 0-3 1491 1546 29.86% 28.77% 41.36% -30.4 13
2001-11-18 @ Vejle BK W 3-0 1546 1491 41.36% 28.77% 29.86% +30.4 14
2001-11-18 AB Copenhagen L 0-1 1494 1717 14.15% 25.31% 60.54% -5.9 13
2001-11-18 @ Lyngby W 1-0 1717 1494 60.54% 25.31% 14.15% +5.8 30
2001-11-18 Brondby L 0-2 1602 1840 13.20% 24.80% 61.99% -10.3 26
2001-11-18 @ Esbjerg W 2-0 1840 1602 61.99% 24.80% 13.20% +10.3 39
2001-11-18 Viborg W 2-1 1717 1580 54.74% 26.94% 18.32% +7.0 29
2001-11-18 @ FC Copenhagen L 1-2 1580 1717 18.32% 26.94% 54.74% -7.0 16
2001-11-19 Midtjylland W 2-1 1578 1659 26.73% 28.52% 44.74% +14.2 23
2001-11-19 @ Odense L 1-2 1659 1578 44.74% 28.52% 26.73% -14.2 22
2001-11-25 FC Copenhagen D 2-2 1723 1724 37.34% 28.92% 33.74% -0.2 31
2001-11-25 @ AB Copenhagen D 2-2 1724 1723 33.74% 28.92% 37.34% +0.2 30
2001-11-25 Lyngby W 4-0 1582 1489 49.78% 27.90% 22.32% +31.6 30
2001-11-25 @ Aalborg L 0-4 1489 1582 22.32% 27.90% 49.78% -31.6 13
2001-11-25 Odense D 1-1 1573 1592 34.84% 28.93% 36.24% +0.1 17
2001-11-25 @ Viborg D 1-1 1592 1573 36.24% 28.93% 34.84% -0.1 24
2001-11-25 Silkeborg L 0-1 1850 1511 72.56% 19.97% 7.47% -22.3 39
2001-11-25 @ Brondby W 1-0 1511 1850 7.47% 19.97% 72.56% +22.3 10
2001-11-25 Vejle BK W 5-0 1645 1460 59.59% 25.62% 14.79% +26.9 25
2001-11-25 @ Midtjylland L 0-5 1460 1645 14.79% 25.62% 59.59% -26.9 13
2001-11-26 Esbjerg L 1-6 1577 1592 35.38% 28.93% 35.69% -45.9 14
2001-11-26 @ Aarhus GF W 6-1 1592 1577 35.69% 28.93% 35.38% +45.9 29
2001-12-01 Aalborg W 3-0 1724 1613 51.81% 27.56% 20.63% +22.6 33
2001-12-01 @ FC Copenhagen L 0-3 1613 1724 20.63% 27.56% 51.81% -22.6 30
2001-12-02 AB Copenhagen D 2-2 1592 1722 21.41% 27.72% 50.86% +1.6 25
2001-12-02 @ Odense D 2-2 1722 1592 50.86% 27.72% 21.41% -1.6 32
2001-12-02 Brondby D 2-2 1457 1828 7.36% 19.84% 72.80% +3.8 14
2001-12-02 @ Lyngby D 2-2 1828 1457 72.80% 19.84% 7.36% -3.8 40
2001-12-02 Midtjylland W 2-1 1573 1672 24.74% 28.29% 46.97% +14.7 20
2001-12-02 @ Viborg L 1-2 1672 1573 46.97% 28.29% 24.74% -14.7 25
2001-12-02 Vejle BK L 0-2 1638 1433 61.49% 24.98% 13.53% -37.0 29
2001-12-02 @ Esbjerg W 2-0 1433 1638 13.53% 24.98% 61.49% +37.0 16
2001-12-03 Aarhus GF W 1-0 1533 1531 37.86% 28.91% 33.24% +12.0 13
2001-12-03 @ Silkeborg L 0-1 1531 1533 33.24% 28.91% 37.86% -12.0 14
2001-12-09 Esbjerg D 1-1 1657 1601 45.16% 28.49% 26.36% -1.3 26
2001-12-09 @ Midtjylland D 1-1 1601 1657 26.36% 28.49% 45.16% +1.3 30
2001-12-09 FC Copenhagen W 1-0 1824 1747 47.83% 28.18% 23.99% +9.4 43
2001-12-09 @ Brondby L 0-1 1747 1824 23.99% 28.18% 47.83% -9.4 33
2001-12-09 Lyngby W 7-0 1519 1461 45.40% 28.46% 26.14% +60.8 17
2001-12-09 @ Aarhus GF L 0-7 1461 1519 26.14% 28.46% 45.40% -60.8 14
2001-12-09 Silkeborg L 0-4 1470 1545 27.49% 28.60% 43.91% -37.3 16
2001-12-09 @ Vejle BK W 4-0 1545 1470 43.91% 28.60% 27.49% +37.3 16
2001-12-09 Viborg L 1-2 1721 1588 54.31% 27.04% 18.65% -16.7 32
2001-12-09 @ AB Copenhagen W 2-1 1588 1721 18.65% 27.04% 54.31% +16.7 23
2001-12-10 Odense D 1-1 1591 1593 37.18% 28.92% 33.90% -0.2 31
2001-12-10 @ Aalborg D 1-1 1593 1591 33.90% 28.92% 37.18% +0.2 26
2002-03-03 Aarhus GF D 0-0 1737 1580 56.95% 26.39% 16.66% -3.3 34
2002-03-03 @ FC Copenhagen D 0-0 1580 1737 16.66% 26.39% 56.95% +3.3 18
2002-03-03 Brondby W 4-3 1594 1834 13.09% 24.73% 62.18% +17.3 29
2002-03-03 @ Odense L 3-4 1834 1594 62.18% 24.73% 13.09% -17.3 43
2002-03-03 Vejle BK L 2-5 1400 1433 32.85% 28.90% 38.25% -23.8 14
2002-03-03 @ Lyngby W 5-2 1433 1400 38.25% 28.90% 32.85% +23.8 19
2002-03-04 Aalborg L 0-1 1604 1591 39.48% 28.86% 31.66% -13.6 23
2002-03-04 @ Viborg W 1-0 1591 1604 31.66% 28.86% 39.48% +13.6 34
2002-03-10 FC Copenhagen L 1-3 1457 1734 11.09% 23.43% 65.48% -7.4 19
2002-03-10 @ Vejle BK W 3-1 1734 1457 65.48% 23.43% 11.09% +7.4 37
2002-03-10 Lyngby W 5-0 1602 1376 63.45% 24.25% 12.29% +22.3 33
2002-03-10 @ Esbjerg L 0-5 1376 1602 12.29% 24.25% 63.45% -22.3 14
2002-03-10 Odense L 1-3 1583 1611 33.56% 28.91% 37.53% -19.8 18
2002-03-10 @ Aarhus GF W 3-1 1611 1583 37.53% 28.91% 33.56% +19.8 32
2002-03-10 Silkeborg W 1-0 1655 1582 47.32% 28.25% 24.44% +9.5 29
2002-03-10 @ Midtjylland L 0-1 1582 1655 24.44% 28.25% 47.32% -9.5 16
2002-03-10 Viborg D 2-2 1816 1591 63.41% 24.27% 12.32% -2.9 44
2002-03-10 @ Brondby D 2-2 1591 1816 12.32% 24.27% 63.41% +2.9 24
2002-03-11 AB Copenhagen W 2-1 1604 1704 24.58% 28.27% 47.16% +14.8 37
2002-03-11 @ Aalborg L 1-2 1704 1604 47.16% 28.27% 24.58% -14.8 32
2002-03-13 Esbjerg D 0-0 1573 1624 30.40% 28.80% 40.80% +0.8 17
2002-03-13 @ Silkeborg D 0-0 1624 1573 40.80% 28.80% 30.40% -0.8 34
2002-03-14 Midtjylland L 0-1 1689 1665 40.95% 28.80% 30.26% -14.0 32
2002-03-14 @ AB Copenhagen W 1-0 1665 1689 30.26% 28.80% 40.95% +14.0 32
2002-03-17 Aarhus GF D 0-0 1594 1563 41.78% 28.75% 29.47% -0.9 25
2002-03-17 @ Viborg D 0-0 1563 1594 29.47% 28.75% 41.78% +0.9 19
2002-03-17 Brondby L 1-2 1675 1813 20.72% 27.58% 51.70% -7.8 32
2002-03-17 @ AB Copenhagen W 2-1 1813 1675 51.70% 27.58% 20.72% +7.8 47
2002-03-17 Esbjerg W 6-0 1742 1623 52.65% 27.39% 19.96% +42.1 40
2002-03-17 @ FC Copenhagen L 0-6 1623 1742 19.96% 27.39% 52.65% -42.1 34
2002-03-17 Silkeborg L 0-5 1354 1574 14.31% 25.39% 60.31% -26.1 14
2002-03-17 @ Lyngby W 5-0 1574 1354 60.31% 25.39% 14.31% +26.1 20
2002-03-17 Vejle BK W 1-0 1631 1449 59.29% 25.71% 15.00% +6.2 35
2002-03-17 @ Odense L 0-1 1449 1631 15.00% 25.71% 59.29% -6.2 19
2002-03-18 Aalborg L 0-1 1679 1619 45.65% 28.44% 25.91% -15.3 32
2002-03-18 @ Midtjylland W 1-0 1619 1679 25.91% 28.44% 45.65% +15.3 40
2002-03-24 Aalborg L 0-7 1328 1634 9.75% 22.34% 67.91% -23.9 14
2002-03-24 @ Lyngby W 7-0 1634 1328 67.91% 22.34% 9.75% +23.9 43
2002-03-24 Aarhus GF W 2-0 1581 1564 39.97% 28.84% 31.19% +21.6 37
2002-03-24 @ Esbjerg L 0-2 1564 1581 31.19% 28.84% 39.97% -21.6 19
2002-03-24 AB Copenhagen D 0-0 1784 1668 52.42% 27.44% 20.14% -2.6 41
2002-03-24 @ FC Copenhagen D 0-0 1668 1784 20.14% 27.44% 52.42% +2.6 33
2002-03-24 Brondby L 1-2 1600 1821 14.21% 25.33% 60.46% -5.5 20
2002-03-24 @ Silkeborg W 2-1 1821 1600 60.46% 25.33% 14.21% +5.5 50
2002-03-24 Midtjylland D 0-0 1443 1664 14.27% 25.37% 60.36% +3.9 20
2002-03-24 @ Vejle BK D 0-0 1664 1443 60.36% 25.37% 14.27% -3.9 33
2002-03-24 Viborg L 0-1 1637 1593 43.58% 28.62% 27.79% -14.7 35
2002-03-24 @ Odense W 1-0 1593 1637 27.79% 28.62% 43.58% +14.7 28
2002-04-01 Esbjerg W 1-0 1827 1603 63.25% 24.33% 12.42% +5.1 53
2002-04-01 @ Brondby L 0-1 1603 1827 12.42% 24.33% 63.25% -5.1 37
2002-04-01 FC Copenhagen L 0-2 1607 1781 17.63% 26.73% 55.64% -13.6 28
2002-04-01 @ Viborg W 2-0 1781 1607 55.64% 26.73% 17.63% +13.6 44
2002-04-01 Lyngby W 3-0 1670 1304 74.46% 18.90% 6.64% +7.0 36
2002-04-01 @ AB Copenhagen L 0-3 1304 1670 6.64% 18.90% 74.46% -7.0 14
2002-04-01 Odense L 0-1 1660 1622 42.74% 28.69% 28.58% -14.5 33
2002-04-01 @ Midtjylland W 1-0 1622 1660 28.58% 28.69% 42.74% +14.5 38
2002-04-01 Silkeborg L 0-2 1658 1594 46.18% 28.38% 25.44% -29.0 43
2002-04-01 @ Aalborg W 2-0 1594 1658 25.44% 28.38% 46.18% +29.1 23
2002-04-01 Vejle BK D 0-0 1542 1447 50.01% 27.87% 22.12% -2.2 20
2002-04-01 @ Aarhus GF D 0-0 1447 1542 22.12% 27.87% 50.01% +2.2 21
2002-04-07 Aalborg L 0-1 1598 1629 33.11% 28.90% 37.99% -12.0 37
2002-04-07 @ Esbjerg W 1-0 1629 1598 37.99% 28.90% 33.11% +12.0 46
2002-04-07 AB Copenhagen D 1-1 1623 1677 30.07% 28.78% 41.15% +0.7 24
2002-04-07 @ Silkeborg D 1-1 1677 1623 41.15% 28.78% 30.07% -0.7 37
2002-04-07 Brondby D 1-1 1449 1832 7.00% 19.38% 73.62% +5.1 22
2002-04-07 @ Vejle BK D 1-1 1832 1449 73.62% 19.38% 7.00% -5.1 54
2002-04-07 Midtjylland L 2-3 1540 1645 24.01% 28.19% 47.81% -8.4 20
2002-04-07 @ Aarhus GF W 3-2 1645 1540 47.81% 28.19% 24.01% +8.4 36
2002-04-07 Odense W 4-0 1795 1637 56.95% 26.39% 16.66% +24.4 47
2002-04-07 @ FC Copenhagen L 0-4 1637 1795 16.66% 26.39% 56.95% -24.5 38
2002-04-07 Viborg L 1-5 1297 1594 10.17% 22.70% 67.14% -12.3 14
2002-04-07 @ Lyngby W 5-1 1594 1297 67.14% 22.70% 10.17% +12.3 31
2002-04-10 Aarhus GF D 2-2 1827 1532 69.21% 21.71% 9.08% -3.5 55
2002-04-10 @ Brondby D 2-2 1532 1827 9.08% 21.71% 69.21% +3.5 21
2002-04-10 Esbjerg D 0-0 1676 1586 49.44% 27.96% 22.61% -2.1 38
2002-04-10 @ AB Copenhagen D 0-0 1586 1676 22.61% 27.96% 49.44% +2.1 38
2002-04-10 FC Copenhagen L 0-1 1654 1819 18.30% 26.94% 54.76% -7.4 36
2002-04-10 @ Midtjylland W 1-0 1819 1654 54.76% 26.94% 18.30% +7.4 50
2002-04-10 Lyngby W 4-0 1612 1284 71.70% 20.43% 7.87% +11.1 41
2002-04-10 @ Odense L 0-4 1284 1612 7.87% 20.43% 71.70% -11.1 14
2002-04-10 Silkeborg W 3-2 1606 1624 35.02% 28.93% 36.05% +11.4 34
2002-04-10 @ Viborg L 2-3 1624 1606 36.05% 28.93% 35.02% -11.4 24
2002-04-10 Vejle BK D 2-2 1641 1454 59.82% 25.54% 14.64% -2.5 47
2002-04-10 @ Aalborg D 2-2 1454 1641 14.64% 25.54% 59.82% +2.5 23
2002-04-14 Aalborg D 2-2 1535 1639 24.20% 28.21% 47.58% +1.2 22
2002-04-14 @ Aarhus GF D 2-2 1639 1535 47.58% 28.21% 24.20% -1.2 48
2002-04-14 AB Copenhagen L 0-4 1457 1674 14.48% 25.47% 60.06% -21.4 23
2002-04-14 @ Vejle BK W 4-0 1674 1457 60.06% 25.47% 14.48% +21.4 41
2002-04-14 FC Copenhagen L 0-3 1273 1827 3.23% 12.96% 83.81% -3.0 14
2002-04-14 @ Lyngby W 3-0 1827 1273 83.81% 12.96% 3.23% +3.0 53
2002-04-14 Midtjylland L 1-2 1823 1646 58.86% 25.84% 15.30% -17.8 55
2002-04-14 @ Brondby W 2-1 1646 1823 15.30% 25.84% 58.86% +17.8 39
2002-04-14 Odense D 2-2 1612 1623 36.01% 28.93% 35.06% -0.0 25
2002-04-14 @ Silkeborg D 2-2 1623 1612 35.06% 28.93% 36.01% +0.0 42
2002-04-14 Viborg W 1-0 1588 1618 33.34% 28.91% 37.75% +13.2 41
2002-04-14 @ Esbjerg L 0-1 1618 1588 37.75% 28.91% 33.34% -13.2 34
2002-04-21 Brondby L 1-2 1637 1805 18.08% 26.87% 55.05% -7.0 48
2002-04-21 @ Aalborg W 2-1 1805 1637 55.05% 26.87% 18.08% +6.9 58
2002-04-21 Esbjerg W 2-1 1623 1601 40.62% 28.81% 30.57% +10.7 45
2002-04-21 @ Odense L 1-2 1601 1623 30.57% 28.81% 40.62% -10.7 41
2002-04-21 Lyngby W 4-0 1664 1270 76.29% 17.83% 5.88% +7.9 42
2002-04-21 @ Midtjylland L 0-4 1270 1664 5.88% 17.83% 76.29% -7.9 14
2002-04-21 Silkeborg W 2-1 1829 1612 62.65% 24.56% 12.79% +5.0 56
2002-04-21 @ FC Copenhagen L 1-2 1612 1829 12.79% 24.56% 62.65% -5.0 25
2002-04-21 Vejle BK W 4-1 1604 1436 58.06% 26.08% 15.86% +15.1 37
2002-04-21 @ Viborg L 1-4 1436 1604 15.86% 26.08% 58.06% -15.1 23
2002-04-22 Aarhus GF W 1-0 1696 1536 57.08% 26.36% 16.57% +6.8 44
2002-04-22 @ AB Copenhagen L 0-1 1536 1696 16.57% 26.36% 57.08% -6.8 22
2002-04-28 AB Copenhagen W 5-0 1812 1702 51.71% 27.57% 20.71% +36.6 61
2002-04-28 @ Brondby L 0-5 1702 1812 20.71% 27.57% 51.71% -36.6 44
2002-04-28 FC Copenhagen L 1-3 1591 1834 12.86% 24.60% 62.54% -8.7 41
2002-04-28 @ Esbjerg W 3-1 1834 1591 62.54% 24.60% 12.86% +8.7 59
2002-04-28 Lyngby W 5-2 1607 1262 72.95% 19.76% 7.30% +5.7 28
2002-04-28 @ Silkeborg L 2-5 1262 1607 7.30% 19.76% 72.95% -5.7 14
2002-04-28 Midtjylland L 0-1 1630 1672 31.71% 28.86% 39.43% -11.6 48
2002-04-28 @ Aalborg W 1-0 1672 1630 39.43% 28.86% 31.71% +11.6 45
2002-04-28 Odense D 1-1 1421 1634 14.73% 25.59% 59.68% +3.4 24
2002-04-28 @ Vejle BK D 1-1 1634 1421 59.68% 25.59% 14.73% -3.4 46
2002-04-28 Viborg W 4-3 1530 1620 25.71% 28.41% 45.88% +13.4 25
2002-04-28 @ Aarhus GF L 3-4 1620 1530 45.88% 28.41% 25.71% -13.4 37
2002-05-01 Aalborg W 1-0 1666 1619 43.97% 28.59% 27.44% +10.4 47
2002-05-01 @ AB Copenhagen L 0-1 1619 1666 27.44% 28.59% 43.97% -10.4 48
2002-05-01 Aarhus GF W 5-0 1631 1543 49.08% 28.01% 22.91% +39.8 49
2002-05-01 @ Odense L 0-5 1543 1631 22.91% 28.01% 49.08% -39.8 25
2002-05-01 Brondby D 1-1 1606 1849 12.92% 24.64% 62.44% +3.8 38
2002-05-01 @ Viborg D 1-1 1849 1606 62.44% 24.64% 12.92% -3.8 62
2002-05-01 Esbjerg L 0-2 1257 1582 9.00% 21.63% 69.37% -6.8 14
2002-05-01 @ Lyngby W 2-0 1582 1257 69.37% 21.63% 9.00% +6.8 44
2002-05-01 Midtjylland L 2-3 1613 1684 28.00% 28.64% 43.36% -9.5 28
2002-05-01 @ Silkeborg W 3-2 1684 1613 43.36% 28.64% 28.00% +9.5 48
2002-05-01 Vejle BK W 2-1 1843 1424 77.91% 16.84% 5.25% +1.8 62
2002-05-01 @ FC Copenhagen L 1-2 1424 1843 5.25% 16.84% 77.91% -1.8 24
2002-05-05 AB Copenhagen W 2-0 1693 1676 39.90% 28.84% 31.26% +21.7 51
2002-05-05 @ Midtjylland L 0-2 1676 1693 31.26% 28.84% 39.90% -21.7 47
2002-05-05 FC Copenhagen L 1-2 1503 1845 8.37% 20.99% 70.64% -3.1 25
2002-05-05 @ Aarhus GF W 2-1 1845 1503 70.64% 20.99% 8.37% +3.1 65
2002-05-05 Lyngby D 2-2 1422 1250 58.37% 25.99% 15.64% -2.4 25
2002-05-05 @ Vejle BK D 2-2 1250 1422 15.64% 25.99% 58.37% +2.4 15
2002-05-05 Odense W 4-1 1845 1670 58.65% 25.91% 15.45% +14.7 65
2002-05-05 @ Brondby L 1-4 1670 1845 15.45% 25.91% 58.65% -14.7 49
2002-05-05 Viborg W 2-1 1608 1610 37.33% 28.92% 33.75% +11.5 51
2002-05-05 @ Aalborg L 1-2 1610 1608 33.75% 28.92% 37.33% -11.5 38
2002-05-06 Silkeborg D 1-1 1589 1604 35.40% 28.93% 35.67% +0.0 45
2002-05-06 @ Esbjerg D 1-1 1604 1589 35.67% 28.93% 35.40% -0.0 29
2002-05-12 Aalborg L 1-2 1656 1620 42.48% 28.70% 28.81% -13.6 49
2002-05-12 @ Odense W 2-1 1620 1656 28.81% 28.70% 42.48% +13.6 54
2002-05-12 Aarhus GF L 0-1 1252 1500 12.64% 24.47% 62.88% -5.2 15
2002-05-12 @ Lyngby W 1-0 1500 1252 62.88% 24.47% 12.64% +5.2 28
2002-05-12 AB Copenhagen W 2-1 1598 1655 29.79% 28.77% 41.44% +13.3 41
2002-05-12 @ Viborg L 1-2 1655 1598 41.44% 28.77% 29.79% -13.3 47
2002-05-12 Brondby D 1-1 1848 1860 35.86% 28.93% 35.21% -0.0 66
2002-05-12 @ FC Copenhagen D 1-1 1860 1848 35.21% 28.93% 35.86% +0.0 66
2002-05-12 Midtjylland L 0-1 1589 1715 21.86% 27.82% 50.33% -8.7 45
2002-05-12 @ Esbjerg W 1-0 1715 1589 50.33% 27.82% 21.86% +8.7 54
2002-05-12 Vejle BK W 1-0 1604 1420 59.55% 25.63% 14.82% +6.1 32
2002-05-12 @ Silkeborg L 0-1 1420 1604 14.82% 25.63% 59.55% -6.1 25
2002-05-16 Esbjerg W 2-0 1414 1580 18.21% 26.91% 54.88% +33.6 28
2002-05-16 @ Vejle BK L 0-2 1580 1414 54.88% 26.91% 18.21% -33.6 45
2002-05-16 FC Copenhagen L 2-4 1633 1848 14.66% 25.55% 59.79% -8.8 54
2002-05-16 @ Aalborg W 4-2 1848 1633 59.79% 25.55% 14.66% +8.8 69
2002-05-16 Lyngby W 2-0 1860 1247 87.70% 10.18% 2.12% +1.3 69
2002-05-16 @ Brondby L 0-2 1247 1860 2.12% 10.18% 87.70% -1.2 15
2002-05-16 Odense W 4-3 1641 1642 37.43% 28.91% 33.66% +10.6 50
2002-05-16 @ AB Copenhagen L 3-4 1642 1641 33.66% 28.91% 37.43% -10.6 49
2002-05-16 Silkeborg W 4-0 1505 1610 24.09% 28.20% 47.71% +56.6 31
2002-05-16 @ Aarhus GF L 0-4 1610 1505 47.71% 28.20% 24.09% -56.6 32
2002-05-16 Viborg W 3-1 1723 1612 51.92% 27.53% 20.54% +13.5 57
2002-05-16 @ Midtjylland L 1-3 1612 1723 20.54% 27.53% 51.92% -13.5 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 2001-11-25 7.47% Silkeborg 1511 1 @ Brondby 1850 0
2 2001-08-12 12.66% @ Esbjerg 1474 2 FC Copenhagen 1721 1
3 2002-03-03 13.09% @ Odense 1594 4 Brondby 1834 3
4 2001-12-02 13.53% Vejle BK 1433 2 @ Esbjerg 1638 0
5 2002-04-14 15.30% Midtjylland 1646 2 @ Brondby 1823 1
6 2001-09-09 15.34% Esbjerg 1458 2 @ Midtjylland 1634 0
7 2001-10-22 16.84% Aarhus GF 1526 4 @ Aalborg 1682 1
8 2001-08-12 16.91% @ Lyngby 1570 1 Brondby 1753 0
9 2002-05-16 18.21% @ Vejle BK 1414 2 Esbjerg 1580 0
10 2001-12-09 18.65% Viborg 1588 2 @ AB Copenhagen 1721 1
11 2001-10-28 19.41% @ Vejle BK 1487 4 Aalborg 1640 2
12 2001-11-18 21.02% @ Silkeborg 1479 2 Aalborg 1614 0
13 2001-09-16 21.53% Esbjerg 1521 2 @ Viborg 1623 0
14 2001-08-17 24.02% AB Copenhagen 1625 2 @ FC Copenhagen 1702 0
15 2002-05-16 24.09% @ Aarhus GF 1505 4 Silkeborg 1610 0
16 2002-03-11 24.58% @ Aalborg 1604 2 AB Copenhagen 1704 1
17 2001-12-02 24.74% @ Viborg 1573 2 Midtjylland 1672 1
18 2002-04-01 25.44% Silkeborg 1594 2 @ Aalborg 1658 0
19 2002-04-28 25.71% @ Aarhus GF 1530 4 Viborg 1620 3
20 2002-03-18 25.91% Aalborg 1619 1 @ Midtjylland 1679 0
21 2001-11-19 26.73% @ Odense 1578 2 Midtjylland 1659 1
22 2001-08-12 27.32% @ Vejle BK 1552 3 Silkeborg 1628 0
23 2001-09-12 27.52% @ Esbjerg 1494 2 Odense 1568 0
24 2002-03-24 27.79% Viborg 1593 1 @ Odense 1637 0
25 2002-04-01 28.58% Odense 1622 1 @ Midtjylland 1660 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 2001-12-09 60.84 @ Aarhus GF 7 1519 45.40% Lyngby 0 1461 26.14% 28.46%
2 2002-05-16 56.62 @ Aarhus GF 4 1505 24.09% Silkeborg 0 1610 47.71% 28.20%
3 2001-11-26 45.93 Esbjerg 6 1592 35.69% @ Aarhus GF 1 1577 35.38% 28.93%
4 2001-07-22 43.96 @ Brondby 5 1678 45.65% Aarhus GF 0 1618 25.92% 28.44%
5 2001-10-22 42.32 Aarhus GF 4 1526 16.84% @ Aalborg 1 1682 56.70% 26.46%
6 2002-03-17 42.08 @ FC Copenhagen 6 1742 52.65% Esbjerg 0 1623 19.96% 27.39%
7 2001-08-12 40.66 @ Vejle BK 3 1552 27.32% Silkeborg 0 1628 44.10% 28.58%
8 2002-05-01 39.81 @ Odense 5 1631 49.08% Aarhus GF 0 1543 22.91% 28.01%
9 2001-10-14 39.65 Midtjylland 4 1612 41.48% @ Lyngby 0 1556 29.75% 28.77%
10 2001-09-10 38.14 @ Aarhus GF 3 1536 30.56% Vejle BK 0 1587 40.63% 28.81%
11 2001-12-09 37.34 Silkeborg 4 1545 43.91% @ Vejle BK 0 1470 27.49% 28.60%
12 2001-12-02 37.05 Vejle BK 2 1433 13.53% @ Esbjerg 0 1638 61.49% 24.98%
13 2001-09-30 37.04 @ Odense 5 1542 36.29% Vejle BK 1 1551 34.78% 28.93%
14 2002-04-28 36.59 @ Brondby 5 1812 51.71% AB Copenhagen 0 1702 20.71% 27.57%
15 2001-09-09 35.66 Esbjerg 2 1458 15.34% @ Midtjylland 0 1634 58.80% 25.86%
16 2002-05-16 33.61 @ Vejle BK 2 1414 18.21% Esbjerg 0 1580 54.88% 26.91%
17 2001-11-18 31.73 @ Silkeborg 2 1479 21.02% Aalborg 0 1614 51.33% 27.64%
18 2001-11-25 31.61 @ Aalborg 4 1582 49.78% Lyngby 0 1489 22.32% 27.90%
19 2001-09-16 31.40 Esbjerg 2 1521 21.53% @ Viborg 0 1623 50.71% 27.75%
20 2001-11-18 30.44 Aarhus GF 3 1546 41.36% @ Vejle BK 0 1491 29.86% 28.77%
21 2001-08-17 29.88 AB Copenhagen 2 1625 24.02% @ FC Copenhagen 0 1702 47.79% 28.19%
22 2001-09-24 29.80 @ Esbjerg 4 1553 34.41% Aarhus GF 1 1575 36.66% 28.92%
23 2002-04-01 29.05 Silkeborg 2 1594 25.44% @ Aalborg 0 1658 46.18% 28.38%
24 2001-08-26 27.95 Brondby 7 1760 65.22% @ Esbjerg 0 1486 11.24% 23.54%
25 2001-09-12 27.88 @ Esbjerg 2 1494 27.52% Odense 0 1568 43.88% 28.60%