Home / Leagues / Denmark / Superliga / 1999-00
‹ ›

1999-00 Superliga Season

198 games

Final

Champion

Herfolge

56 points · 1st Title

Relegated

Esbjerg

28 pts

Vejle BK · 32 pts

Biggest Overachiever

Herfolge

8.27 points above expected

56 points · 47.73 expected points

Biggest Disappointment

Vejle BK

9.76 points below expected

32 points · 41.76 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 Herfolge Champion 33 16 8 9 56 52 49 +3 47.73 +8.27
2 Brondby 33 15 9 9 54 56 37 +19 59.08 -5.08
3 AB Copenhagen 33 14 10 9 52 52 35 +17 49.96 +2.04
4 Viborg 33 15 7 11 52 56 50 +6 45.11 +6.89
5 Aalborg 33 12 13 8 49 57 40 +17 55.22 -6.22
6 Silkeborg 33 13 10 10 49 49 33 +16 50.63 -1.63
7 Lyngby 33 14 5 14 47 51 55 -4 44.68 +2.32
8 FC Copenhagen 33 12 8 13 44 44 37 +7 45.89 -1.89
9 Odense 33 11 10 12 43 42 44 -2 38.68 +4.32
10 Aarhus GF 33 9 9 15 36 36 55 -19 41.11 -5.11
11 Vejle BK Relegated 33 7 11 15 32 38 68 -30 41.76 -9.76
12 Esbjerg Relegated 33 8 4 21 28 40 70 -30 23.84 +4.16

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 1692 54 59.08 -5.08 26.5% 31 47 54 59 64 71 85
Aalborg 1663 49 55.22 -6.22 21.5% 25 43 50 55 60 67 83
AB Copenhagen 1649 52 49.96 +2.04 63.3% 24 38 45 50 55 62 74
Silkeborg 1641 49 50.63 -1.63 43.7% 23 39 46 51 56 62 78
Viborg 1614 52 45.11 +6.89 84.1% 20 33 40 45 50 57 71
FC Copenhagen 1610 44 45.89 -1.89 43.0% 20 34 41 46 51 58 72
Herfolge 1607 56 47.73 +8.27 88.6% 22 36 43 48 53 60 75
Lyngby 1571 47 44.68 +2.32 65.8% 19 33 40 45 49 57 72
Odense 1565 43 38.68 +4.32 75.0% 16 27 34 39 44 50 69
Aarhus GF 1540 36 41.11 -5.11 26.0% 16 30 36 41 46 53 66
Vejle BK 1540 32 41.76 -9.76 9.6% 16 30 37 42 46 54 69
Esbjerg 1411 28 23.84 +4.16 77.6% 5 14 19 24 28 34 48

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 HER LYN ODE SIL VB VIB
AB Copenhagen —
1-2-0
3.36
1-1-1
5.04
2-0-1
3.57
1-1-1
6.32
1-0-2
4.64
2-1-0
4.51
2-1-0
4.82
1-1-1
4.76
1-1-1
4.18
0-2-1
4.51
2-0-1
4.17
Aalborg
0-2-1
4.85
 —
1-2-0
5.51
2-0-1
3.96
1-2-0
6.50
1-2-0
4.57
2-0-1
4.39
0-1-2
5.15
1-1-1
5.31
2-1-0
4.67
1-2-0
5.05
1-0-2
5.24
Aarhus GF
1-1-1
3.17
0-2-1
2.75
 —
0-0-3
2.52
3-0-0
5.89
2-0-1
3.94
0-2-1
3.86
1-0-2
3.51
0-1-2
4.61
1-0-2
3.04
1-1-1
4.28
0-2-1
3.52
Brondby
1-0-2
4.63
1-0-2
4.22
3-0-0
5.79
 —
1-0-2
7.15
1-2-0
5.39
2-1-0
5.30
1-1-1
5.60
1-1-1
5.58
1-2-0
5.06
2-1-0
5.39
1-1-1
5.08
Esbjerg
1-1-1
2.07
0-2-1
1.92
0-0-3
2.43
2-0-1
1.41
 —
1-0-2
2.06
0-0-3
2.03
1-0-2
2.21
1-0-2
2.82
0-0-3
1.85
1-1-1
2.69
1-0-2
2.32
FC Copenhagen
2-0-1
3.56
0-2-1
3.63
1-0-2
4.25
0-2-1
2.86
2-0-1
6.33
 —
1-1-1
4.13
1-0-2
3.99
1-1-1
5.01
1-1-1
3.47
2-0-1
4.82
1-1-1
3.97
Herfolge
0-1-2
3.68
1-0-2
3.80
1-2-0
4.33
0-1-2
2.95
3-0-0
6.38
1-1-1
4.05
 —
2-0-1
4.10
2-1-0
5.07
2-1-0
4.02
2-1-0
4.83
2-0-1
4.50
Lyngby
0-1-2
3.38
2-1-0
3.08
2-0-1
4.68
1-1-1
2.67
2-0-1
6.14
2-0-1
4.21
1-0-2
4.08
 —
2-1-0
4.24
0-1-2
3.79
1-0-2
4.69
1-0-2
3.84
Odense
1-1-1
3.45
1-1-1
2.94
2-1-0
3.60
1-1-1
2.69
2-0-1
5.43
1-1-1
3.20
0-1-2
3.15
0-1-2
3.95
 —
1-0-2
2.85
1-2-0
3.66
1-1-1
3.69
Silkeborg
1-1-1
4.00
0-1-2
3.54
2-0-1
5.19
0-2-1
3.16
3-0-0
6.59
1-1-1
4.73
0-1-2
4.16
2-1-0
4.40
2-0-1
5.41
 —
1-1-1
4.55
1-2-0
4.83
Vejle BK
1-2-0
3.67
0-2-1
3.18
1-1-1
3.91
0-1-2
2.87
1-1-1
5.58
1-0-2
3.39
0-1-2
3.38
2-0-1
3.50
0-2-1
4.53
1-1-1
3.66
 —
0-0-3
4.07
Viborg
1-0-2
4.01
2-0-1
2.99
1-2-0
4.67
1-1-1
3.15
2-0-1
6.01
1-1-1
4.21
1-0-2
3.70
2-0-1
4.35
1-1-1
4.50
0-2-1
3.37
3-0-0
4.12
 —

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 0.75 +10.4
Allowed 0.57 -5.4
Differential 0.79 +4.5

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
05.05%6.82%7.58%3.03%2.53%0.51%25.51%
16.82%15.15%6.06%3.54%2.02%1.01%34.60%
27.58%6.06%5.05%2.53%0.25%0.51%21.97%
33.03%3.54%2.53%1.01%0.25%—10.35%
42.53%2.02%0.25%0.25%—0.25%5.30%
5+0.51%1.01%0.51%—0.25%—2.27%
Total25.51%34.60%21.97%10.35%5.30%2.27%100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.45 +0.00
SD 1.33 1.33 2.01
CV 0.92 0.92 —
Max 7 7 +6
Min 0 0 -6

Games Played: 198

↓ Scored | Allowed →012345+Total
06.06%3.03%6.06%3.03%——18.18%
16.06%12.12%9.09%3.03%——30.30%
215.15%6.06%12.12%3.03%——36.36%
39.09%3.03%————12.12%
4———————
5+3.03%—————3.03%
Total39.39%24.24%27.27%9.09%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.06 +0.52
SD 1.23 1.03 1.84
CV 0.78 0.97 —
Max 6 3 +6
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%3.03%6.06%———21.21%
16.06%18.18%6.06%3.03%——33.33%
29.09%3.03%9.09%3.03%—3.03%27.27%
3—6.06%————6.06%
43.03%3.03%————6.06%
5+—6.06%————6.06%
Total30.30%39.39%21.21%6.06%—3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.73 1.21 +0.52
SD 1.74 1.36 2.18
CV 1.01 1.13 —
Max 7 7 +6
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
0—9.09%9.09%6.06%6.06%—30.30%
112.12%21.21%6.06%3.03%3.03%—45.45%
23.03%3.03%3.03%3.03%——12.12%
33.03%—3.03%3.03%——9.09%
4———3.03%——3.03%
5+———————
Total18.18%33.33%21.21%18.18%9.09%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.09 1.67 -0.58
SD 1.04 1.24 1.68
CV 0.95 0.74 —
Max 4 4 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%—12.12%3.03%——18.18%
19.09%15.15%3.03%6.06%——33.33%
29.09%3.03%9.09%3.03%——24.24%
36.06%6.06%————12.12%
46.06%3.03%————9.09%
5+3.03%—————3.03%
Total36.36%27.27%24.24%12.12%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.70 1.12 +0.58
SD 1.33 1.05 2.03
CV 0.79 0.94 —
Max 5 3 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%9.09%6.06%3.03%—36.36%
1—3.03%12.12%6.06%3.03%6.06%30.30%
29.09%3.03%—6.06%——18.18%
3—3.03%6.06%—3.03%—12.12%
4———————
5+————3.03%—3.03%
Total18.18%18.18%27.27%18.18%12.12%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.21 2.12 -0.91
SD 1.34 1.63 1.94
CV 1.11 0.77 —
Max 6 7 +2
Min 0 0 -6

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%12.12%9.09%———30.30%
16.06%15.15%12.12%3.03%3.03%—39.39%
26.06%9.09%————15.15%
33.03%3.03%————6.06%
43.03%3.03%————6.06%
5+——3.03%———3.03%
Total27.27%42.42%24.24%3.03%3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.33 1.12 +0.21
SD 1.51 0.96 1.83
CV 1.14 0.86 —
Max 7 4 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
0—6.06%9.09%3.03%3.03%3.03%24.24%
19.09%15.15%3.03%———27.27%
26.06%9.09%6.06%———21.21%
3—6.06%12.12%3.03%——21.21%
4—6.06%————6.06%
5+———————
Total15.15%42.42%30.30%6.06%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.48 +0.09
SD 1.25 1.12 1.84
CV 0.79 0.76 —
Max 4 5 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%6.06%9.09%6.06%—33.33%
16.06%3.03%3.03%6.06%3.03%—21.21%
29.09%3.03%6.06%———18.18%
36.06%6.06%6.06%———18.18%
4—————3.03%3.03%
5+—6.06%————6.06%
Total27.27%24.24%21.21%15.15%9.09%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.55 1.67 -0.12
SD 1.50 1.51 2.27
CV 0.97 0.91 —
Max 5 6 +4
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%15.15%6.06%3.03%3.03%—30.30%
19.09%18.18%3.03%3.03%3.03%—36.36%
29.09%6.06%3.03%———18.18%
3———6.06%——6.06%
43.03%3.03%3.03%———9.09%
5+———————
Total24.24%42.42%15.15%12.12%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.33 -0.06
SD 1.23 1.16 1.75
CV 0.97 0.87 —
Max 4 4 +4
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%3.03%———21.21%
19.09%18.18%9.09%—6.06%—42.42%
26.06%3.03%3.03%3.03%——15.15%
36.06%3.03%————9.09%
49.09%3.03%————12.12%
5+———————
Total39.39%36.36%15.15%3.03%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.48 1.00 +0.48
SD 1.28 1.12 1.87
CV 0.86 1.12 —
Max 4 4 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%6.06%9.09%3.03%9.09%—30.30%
13.03%24.24%—6.06%—6.06%39.39%
2—9.09%6.06%3.03%—3.03%21.21%
3—3.03%————3.03%
43.03%3.03%————6.06%
5+———————
Total9.09%45.45%15.15%12.12%9.09%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.15 2.06 -0.91
SD 1.09 1.78 2.26
CV 0.95 0.87 —
Max 4 7 +4
Min 0 0 -6

Games Played: 33

↓ Scored | Allowed →012345+Total
0—3.03%6.06%——3.03%12.12%
16.06%18.18%6.06%3.03%3.03%—36.36%
29.09%15.15%3.03%6.06%3.03%—36.36%
33.03%3.03%3.03%———9.09%
43.03%—————3.03%
5+——3.03%———3.03%
Total21.21%39.39%21.21%9.09%6.06%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.70 1.52 +0.18
SD 1.33 1.37 2.08
CV 0.79 0.91 —
Max 7 6 +5
Min 0 0 -6

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 Herfolge 56 47.73 +8.27
2 Viborg 52 45.11 +6.89
3 Odense 43 38.68 +4.32
4 Esbjerg 28 23.84 +4.16
5 Lyngby 47 44.68 +2.32

Biggest Disappointments

# Team Actual Sim vsSim
1 Vejle BK 32 41.76 -9.76
2 Aalborg 49 55.22 -6.22
3 Aarhus GF 36 41.11 -5.11
4 Brondby 54 59.08 -5.08
5 FC Copenhagen 44 45.89 -1.89

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 Viborg 4 Aug 22 – Sep 19 1 in 44
2 Esbjerg 2 Oct 13 – Oct 17 1 in 42
3 Lyngby 3 Aug 30 – Sep 19 1 in 25
4 Aalborg 4 Aug 2 – Aug 21 1 in 20
5 Herfolge 4 Oct 31 – Nov 28 1 in 18

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Aarhus GF 4 Sep 19 – Oct 13 1 in 27
2 AB Copenhagen 3 Oct 31 – Nov 21 1 in 22
3 Odense 3 Jul 26 – Aug 8 1 in 21
4 Herfolge 3 Oct 13 – Oct 24 1 in 17
5 Lyngby 3 Aug 8 – Aug 22 1 in 15

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Herfolge 11 Jul 25 – Oct 6 1 in 121
2 Odense 7 Aug 29 – Oct 13 1 in 105
3 AB Copenhagen 9 Jul 25 – Sep 26 1 in 28
4 Esbjerg 3 Oct 13 – Oct 20 1 in 22
5 Aarhus GF 5 Oct 17 – Nov 22 1 in 22

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Aalborg 9 Nov 1 – Apr 9 1 in 459
2 Vejle BK 9 Oct 3 – Nov 28 1 in 59
3 Aarhus GF 10 Aug 21 – Nov 1 1 in 34
4 Brondby 4 Nov 7 – Mar 12 1 in 34
5 AB Copenhagen 6 Oct 24 – Mar 12 1 in 21

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
Herfolge4.15%8.43%10.58%12.18%12.78%11.96%11.10%9.86%7.93%6.80%3.92%0.31%
Brondby46.27%22.49%12.66%7.71%4.29%2.85%1.76%1.07%0.56%0.21%0.13%—
AB Copenhagen8.17%12.50%14.64%14.00%12.68%10.40%9.19%7.11%5.17%3.92%2.04%0.18%
Viborg2.31%4.50%7.62%9.10%10.41%11.63%12.22%12.63%11.33%9.75%7.65%0.85%
Aalborg23.84%23.94%16.61%11.99%7.97%6.12%3.83%2.51%1.60%0.99%0.57%0.03%
Silkeborg9.29%13.92%15.39%14.40%12.74%10.02%8.22%6.13%4.89%3.21%1.67%0.12%
Lyngby1.87%3.82%6.67%8.19%10.24%11.87%12.15%12.56%12.59%10.81%8.36%0.87%
FC Copenhagen2.52%5.88%8.42%10.60%11.66%12.09%11.61%11.74%10.28%8.25%6.24%0.71%
Odense0.24%0.91%1.46%2.63%4.27%6.55%8.27%10.70%14.51%20.11%25.59%4.76%
Aarhus GF0.52%1.69%2.75%4.41%6.23%8.11%10.63%12.61%14.93%16.84%18.86%2.42%
Vejle BK0.82%1.92%3.20%4.79%6.71%8.31%10.91%12.67%15.40%16.70%15.98%2.59%
Esbjerg————0.02%0.09%0.11%0.41%0.81%2.41%8.99%87.16%

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
+17.17%
Clear Edge
45.45%26.26%28.28%
Elo Value
Home Edge
186 Elo
0.005 goals per Elo point
060.26500
Scoring Tilt
Expected
+0.46 goals
Neutral
-2+0.32+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
3.5
Top-Heavy
124610
Champion Preseason Odds
4%
Herfolge, 5th of 12
LongshotFavorite
Title Margin
Expected
0.06/gm
Photo Finish
00.160.5/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 5.71 * Some Luck: 5.71 to 8.56 * Lucky: 8.56 to 11.41 * Wild Swing: 11.41 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 1.56 * Close: 1.56 to 2.35 * Off: 2.35 to 3.13 * Way Off: 3.13 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 0.73 * A Surprise: 0.73 to 1.18 * Several Surprises: 1.18 to 1.62 * Many Surprises: 1.62 and up.
Luck Spread
Expected
5.43 points
As Expected
07.1318
Average Finish Error
Expected
1.83
Close
01.964
Biggest Overachiever
Expected 95.83%
88.61%
Herfolge
50100
Biggest Underachiever
Expected 4.17%
9.64%
Vejle BK
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
0.10
Balanced
00.120.180.260.5
Noll-Scully
Coin-flip
1.04
Moderate Separation
01.003
Interquartile Edge
62%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline
83%
Strong Edge
50%82%100%
Close Games
Expected
58%
Very Frequent
0%54%100%
Blowouts
Expected
19%
Frequent
0%21%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
0.63
Hard to Predict
00.622
Matchup Imbalance
0.31
Lopsided
00.10.180.280.5
Strangeness
Expected
0.58
Very Predictable
01.002
Repeatability
0.54
Some Carryover
00.30.60.851
Upset Rate
Expected
28%
As Expected
0%26%50%
Clear Favorite Upset Rate
Expected
22%
As Expected
0%22%50%

Calibration

How these are measured

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

Probability calibration
An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope
Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE)
The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.12 * Near Noise Ceiling: 0.12 to 0.18 * Above Noise: 0.18 to 0.24 * Well Above Noise: 0.24 and up.
Probability calibration
0.35
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
0.62
Overconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.110
Well Within Noise
00.1220.3

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 99.87% 0.13%
Aalborg 99.40% 0.60%
Silkeborg 98.21% 1.79%
AB Copenhagen 97.78% 2.22%
Herfolge 95.77% 4.23%
FC Copenhagen 93.05% 6.95%
Viborg 91.50% 8.50%
Lyngby 90.77% 9.23%
Vejle BK 81.43% 18.57%
Aarhus GF 78.72% 21.28%
Odense 69.65% 30.35%
Esbjerg 3.85% 96.15%

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
1999-07-24 Lyngby W 1-0 1689 1590 57.70% 23.26% 19.04% +2.1 3
1999-07-24 @ Brondby L 0-1 1590 1689 19.04% 23.26% 57.70% -2.1 0
1999-07-25 Aarhus GF W 1-0 1607 1581 48.15% 26.41% 25.44% +2.8 3
1999-07-25 @ AB Copenhagen L 0-1 1581 1607 25.44% 26.41% 48.15% -2.8 0
1999-07-25 Aalborg W 3-1 1601 1655 37.00% 27.85% 35.15% +5.9 3
1999-07-25 @ Herfolge L 1-3 1655 1601 35.15% 27.85% 37.00% -5.9 0
1999-07-25 Silkeborg L 0-4 1607 1614 43.55% 27.30% 29.15% -15.2 0
1999-07-25 @ Vejle BK W 4-0 1614 1607 29.15% 27.30% 43.55% +15.2 3
1999-07-25 FC Copenhagen W 2-1 1589 1602 42.83% 27.41% 29.77% +3.0 3
1999-07-25 @ Viborg L 1-2 1602 1589 29.77% 27.41% 42.83% -3.0 0
1999-07-26 Odense W 2-0 1408 1560 24.84% 26.21% 48.96% +8.8 3
1999-07-26 @ Esbjerg L 0-2 1560 1408 48.96% 26.21% 24.84% -8.8 0
1999-08-01 Herfolge D 1-1 1579 1607 40.64% 27.65% 31.71% -0.2 1
1999-08-01 @ Aarhus GF D 1-1 1607 1579 31.71% 27.65% 40.64% +0.2 4
1999-08-01 Esbjerg W 5-1 1588 1416 66.24% 19.27% 14.50% +4.6 3
1999-08-01 @ Lyngby L 1-5 1416 1588 14.50% 19.27% 66.24% -4.6 3
1999-08-01 AB Copenhagen L 0-3 1551 1610 36.27% 27.86% 35.87% -10.1 0
1999-08-01 @ Odense W 3-0 1610 1551 35.87% 27.86% 36.27% +10.2 6
1999-08-01 FC Copenhagen D 0-0 1629 1599 48.79% 26.25% 24.96% -0.5 4
1999-08-01 @ Silkeborg D 0-0 1599 1629 24.96% 26.25% 48.79% +0.5 1
1999-08-01 Brondby L 0-4 1591 1691 30.72% 27.54% 41.74% -11.7 0
1999-08-01 @ Vejle BK W 4-0 1691 1591 41.74% 27.54% 30.72% +11.7 6
1999-08-02 Viborg W 2-0 1649 1592 52.29% 25.24% 22.47% +4.7 3
1999-08-02 @ Aalborg L 0-2 1592 1649 22.47% 25.24% 52.29% -4.7 3
1999-08-06 Aalborg L 0-2 1599 1654 36.95% 27.85% 35.20% -7.1 1
1999-08-06 @ FC Copenhagen W 2-0 1654 1599 35.20% 27.85% 36.95% +7.1 6
1999-08-08 Lyngby W 3-0 1620 1592 48.42% 26.34% 25.24% +7.6 9
1999-08-08 @ AB Copenhagen L 0-3 1592 1620 25.24% 26.34% 48.42% -7.6 3
1999-08-08 Silkeborg W 1-0 1703 1629 54.53% 24.48% 20.99% +2.3 9
1999-08-08 @ Brondby L 0-1 1629 1703 20.99% 24.48% 54.53% -2.3 4
1999-08-08 Odense W 1-0 1607 1541 53.50% 24.84% 21.66% +2.4 7
1999-08-08 @ Herfolge L 0-1 1541 1607 21.66% 24.84% 53.50% -2.4 0
1999-08-08 Aarhus GF D 1-1 1587 1578 45.85% 26.91% 27.24% -0.4 4
1999-08-08 @ Viborg D 1-1 1578 1587 27.24% 26.91% 45.85% +0.4 2
1999-08-09 Vejle BK D 1-1 1412 1580 23.33% 25.63% 51.04% +0.6 4
1999-08-09 @ Esbjerg D 1-1 1580 1412 51.04% 25.63% 23.33% -0.6 1
1999-08-15 Silkeborg W 2-1 1661 1627 49.28% 26.12% 24.59% +2.6 9
1999-08-15 @ Aalborg L 1-2 1627 1661 24.59% 26.12% 49.28% -2.6 4
1999-08-15 Esbjerg W 3-1 1705 1412 78.46% 12.53% 9.01% +1.4 12
1999-08-15 @ Brondby L 1-3 1412 1705 9.01% 12.53% 78.46% -1.4 4
1999-08-15 Herfolge L 1-2 1585 1610 41.15% 27.60% 31.25% -3.8 3
1999-08-15 @ Lyngby W 2-1 1610 1585 31.25% 27.60% 41.15% +3.8 10
1999-08-15 Viborg D 1-1 1539 1587 37.77% 27.83% 34.40% -0.1 1
1999-08-15 @ Odense D 1-1 1587 1539 34.40% 27.83% 37.77% +0.1 5
1999-08-15 AB Copenhagen D 0-0 1579 1628 37.73% 27.83% 34.43% -0.1 2
1999-08-15 @ Vejle BK D 0-0 1628 1579 34.43% 27.83% 37.73% +0.1 10
1999-08-16 FC Copenhagen W 1-0 1579 1592 42.73% 27.42% 29.85% +3.2 5
1999-08-16 @ Aarhus GF L 0-1 1592 1579 29.85% 27.42% 42.73% -3.2 1
1999-08-21 Aarhus GF W 1-0 1663 1582 55.43% 24.15% 20.42% +2.3 12
1999-08-21 @ Aalborg L 0-1 1582 1663 20.42% 24.15% 55.43% -2.3 5
1999-08-21 Brondby W 2-0 1628 1707 33.46% 27.79% 38.75% +7.3 13
1999-08-21 @ AB Copenhagen L 0-2 1707 1628 38.75% 27.79% 33.46% -7.3 12
1999-08-22 Vejle BK D 1-1 1613 1579 49.31% 26.11% 24.57% -0.5 11
1999-08-22 @ Herfolge D 1-1 1579 1613 24.57% 26.11% 49.31% +0.5 3
1999-08-22 Esbjerg W 4-0 1624 1411 70.76% 16.86% 12.38% +4.5 7
1999-08-22 @ Silkeborg L 0-4 1411 1624 12.38% 16.86% 70.76% -4.5 4
1999-08-22 Lyngby W 2-0 1587 1581 45.47% 26.98% 27.55% +5.7 8
1999-08-22 @ Viborg L 0-2 1581 1587 27.55% 26.98% 45.47% -5.7 3
1999-08-23 Odense W 1-0 1589 1538 51.48% 25.50% 23.02% +2.5 4
1999-08-23 @ FC Copenhagen L 0-1 1538 1589 23.02% 25.50% 51.48% -2.5 1
1999-08-29 Herfolge D 2-2 1699 1613 56.10% 23.90% 20.00% -0.6 13
1999-08-29 @ Brondby D 2-2 1613 1699 20.00% 23.90% 56.10% +0.6 12
1999-08-29 AB Copenhagen L 0-1 1406 1635 18.40% 22.80% 58.80% -2.0 4
1999-08-29 @ Esbjerg W 1-0 1635 1406 58.80% 22.80% 18.40% +2.0 16
1999-08-29 Aalborg D 2-2 1536 1666 27.22% 26.90% 45.87% +0.3 2
1999-08-29 @ Odense D 2-2 1666 1536 45.87% 26.90% 27.22% -0.3 13
1999-08-29 Aarhus GF W 2-0 1629 1580 51.22% 25.57% 23.20% +4.8 10
1999-08-29 @ Silkeborg L 0-2 1580 1629 23.20% 25.57% 51.22% -4.8 5
1999-08-29 Viborg L 2-3 1579 1593 42.77% 27.41% 29.81% -3.8 3
1999-08-29 @ Vejle BK W 3-2 1593 1579 29.81% 27.41% 42.77% +3.8 11
1999-08-30 FC Copenhagen W 1-0 1575 1592 42.32% 27.47% 30.20% +3.2 6
1999-08-30 @ Lyngby L 0-1 1592 1575 30.20% 27.47% 42.32% -3.2 4
1999-09-10 Lyngby L 0-2 1665 1579 56.13% 23.89% 19.99% -9.8 13
1999-09-10 @ Aalborg W 2-0 1579 1665 19.99% 23.89% 56.13% +9.8 9
1999-09-12 Odense D 3-3 1575 1536 49.89% 25.96% 24.15% -0.3 6
1999-09-12 @ Aarhus GF D 3-3 1536 1575 24.15% 25.96% 49.89% +0.3 3
1999-09-12 Silkeborg D 1-1 1637 1633 45.15% 27.04% 27.81% -0.3 17
1999-09-12 @ AB Copenhagen D 1-1 1633 1637 27.81% 27.04% 45.15% +0.4 11
1999-09-12 Vejle BK W 1-0 1588 1576 46.38% 26.80% 26.82% +2.9 7
1999-09-12 @ FC Copenhagen L 0-1 1576 1588 26.82% 26.80% 46.38% -2.9 3
1999-09-12 Brondby W 2-0 1596 1699 30.42% 27.50% 42.08% +7.8 14
1999-09-12 @ Viborg L 0-2 1699 1596 42.08% 27.50% 30.42% -7.8 13
1999-09-13 Esbjerg W 2-0 1613 1404 70.34% 17.09% 12.57% +2.4 15
1999-09-13 @ Herfolge L 0-2 1404 1613 12.57% 17.09% 70.34% -2.4 4
1999-09-19 Herfolge D 2-2 1637 1616 47.50% 26.56% 25.94% -0.3 18
1999-09-19 @ AB Copenhagen D 2-2 1616 1637 25.94% 26.56% 47.50% +0.3 16
1999-09-19 Viborg L 1-2 1402 1604 20.37% 24.13% 55.50% -2.1 4
1999-09-19 @ Esbjerg W 2-1 1604 1402 55.50% 24.13% 20.37% +2.1 17
1999-09-19 Aarhus GF W 3-1 1588 1575 46.51% 26.78% 26.72% +4.8 12
1999-09-19 @ Lyngby L 1-3 1575 1588 26.72% 26.78% 46.51% -4.8 6
1999-09-19 Odense L 0-1 1634 1537 57.43% 23.37% 19.20% -5.3 11
1999-09-19 @ Silkeborg W 1-0 1537 1634 19.20% 23.37% 57.43% +5.3 6
1999-09-19 Aalborg D 2-2 1573 1655 32.96% 27.76% 39.29% +0.1 4
1999-09-19 @ Vejle BK D 2-2 1655 1573 39.29% 27.76% 32.96% -0.1 14
1999-09-20 FC Copenhagen W 3-1 1691 1591 57.74% 23.24% 19.02% +3.4 16
1999-09-20 @ Brondby L 1-3 1591 1691 19.02% 23.24% 57.74% -3.4 7
1999-09-26 Brondby W 3-1 1655 1694 39.11% 27.77% 33.12% +5.7 17
1999-09-26 @ Aalborg L 1-3 1694 1655 33.12% 27.77% 39.11% -5.7 16
1999-09-26 Vejle BK L 1-2 1570 1573 44.19% 27.20% 28.60% -4.0 6
1999-09-26 @ Aarhus GF W 2-1 1573 1570 28.60% 27.20% 44.19% +4.0 7
1999-09-26 Esbjerg W 3-0 1588 1400 68.09% 18.30% 13.61% +3.9 10
1999-09-26 @ FC Copenhagen L 0-3 1400 1588 13.61% 18.30% 68.09% -3.9 4
1999-09-26 Lyngby D 0-0 1542 1593 37.37% 27.84% 34.79% -0.0 7
1999-09-26 @ Odense D 0-0 1593 1542 34.79% 27.84% 37.37% +0.1 13
1999-09-26 AB Copenhagen L 1-3 1606 1636 40.39% 27.67% 31.94% -6.6 17
1999-09-26 @ Viborg W 3-1 1636 1606 31.94% 27.67% 40.39% +6.5 21
1999-09-27 Silkeborg W 3-2 1616 1628 42.91% 27.40% 29.70% +2.8 19
1999-09-27 @ Herfolge L 2-3 1628 1616 29.70% 27.40% 42.91% -2.9 11
1999-10-03 FC Copenhagen L 1-2 1643 1592 51.55% 25.48% 22.98% -4.6 21
1999-10-03 @ AB Copenhagen W 2-1 1592 1643 22.98% 25.48% 51.55% +4.6 13
1999-10-03 Aarhus GF W 3-0 1689 1566 60.60% 22.00% 17.40% +5.2 19
1999-10-03 @ Brondby L 0-3 1566 1689 17.40% 22.00% 60.60% -5.2 6
1999-10-03 Viborg W 2-1 1619 1600 47.26% 26.61% 26.13% +2.7 22
1999-10-03 @ Herfolge L 1-2 1600 1619 26.13% 26.61% 47.26% -2.7 17
1999-10-03 Silkeborg L 1-3 1593 1626 40.05% 27.70% 32.25% -6.5 13
1999-10-03 @ Lyngby W 3-1 1626 1593 32.25% 27.70% 40.05% +6.5 14
1999-10-03 Odense D 1-1 1577 1542 49.43% 26.08% 24.49% -0.5 8
1999-10-03 @ Vejle BK D 1-1 1542 1577 24.49% 26.08% 49.43% +0.5 8
1999-10-06 AB Copenhagen D 2-2 1661 1638 47.72% 26.51% 25.77% -0.3 18
1999-10-06 @ Aalborg D 2-2 1638 1661 25.77% 26.51% 47.72% +0.3 22
1999-10-06 Herfolge L 0-1 1596 1622 41.07% 27.61% 31.32% -4.1 13
1999-10-06 @ FC Copenhagen W 1-0 1622 1596 31.32% 27.61% 41.07% +4.1 25
1999-10-06 Vejle BK W 5-1 1587 1576 46.02% 26.87% 27.11% +8.8 16
1999-10-06 @ Lyngby L 1-5 1576 1587 27.11% 26.87% 46.02% -8.8 8
1999-10-06 Brondby W 2-1 1542 1694 24.89% 26.22% 48.89% +4.4 11
1999-10-06 @ Odense L 1-2 1694 1542 48.89% 26.22% 24.89% -4.4 19
1999-10-06 Viborg D 1-1 1632 1597 49.39% 26.09% 24.52% -0.5 15
1999-10-06 @ Silkeborg D 1-1 1597 1632 24.52% 26.09% 49.39% +0.5 18
1999-10-13 Herfolge W 4-0 1661 1626 49.39% 26.09% 24.52% +9.7 21
1999-10-13 @ Aalborg L 0-4 1626 1661 24.52% 26.09% 49.39% -9.7 25
1999-10-13 Brondby L 0-2 1561 1690 27.28% 26.92% 45.80% -5.6 6
1999-10-13 @ Aarhus GF W 2-0 1690 1561 45.80% 26.92% 27.28% +5.6 22
1999-10-13 Esbjerg L 1-2 1639 1396 73.80% 15.18% 11.02% -5.9 22
1999-10-13 @ AB Copenhagen W 2-1 1396 1639 11.02% 15.18% 73.80% +5.9 7
1999-10-13 Odense D 1-1 1592 1547 50.83% 25.69% 23.48% -0.6 14
1999-10-13 @ FC Copenhagen D 1-1 1547 1592 23.48% 25.69% 50.83% +0.6 12
1999-10-13 Vejle BK D 2-2 1632 1568 53.21% 24.94% 21.85% -0.5 16
1999-10-13 @ Silkeborg D 2-2 1568 1632 21.85% 24.94% 53.21% +0.5 9
1999-10-13 Lyngby L 0-2 1598 1595 44.93% 27.08% 27.99% -8.2 18
1999-10-13 @ Viborg W 2-0 1595 1598 27.99% 27.08% 44.93% +8.2 19
1999-10-17 Viborg W 4-1 1695 1589 58.50% 22.92% 18.57% +4.7 25
1999-10-17 @ Brondby L 1-4 1589 1695 18.57% 22.92% 58.50% -4.7 18
1999-10-17 FC Copenhagen W 2-0 1402 1592 21.38% 24.70% 53.92% +9.5 10
1999-10-17 @ Esbjerg L 0-2 1592 1402 53.92% 24.70% 21.38% -9.5 14
1999-10-17 Aalborg W 3-2 1604 1670 35.13% 27.85% 37.02% +3.4 22
1999-10-17 @ Lyngby L 2-3 1670 1604 37.02% 27.85% 35.13% -3.4 21
1999-10-17 Silkeborg L 0-4 1547 1631 32.79% 27.75% 39.46% -12.3 12
1999-10-17 @ Odense W 4-0 1631 1547 39.46% 27.75% 32.79% +12.3 19
1999-10-17 Aarhus GF D 1-1 1568 1555 46.44% 26.79% 26.77% -0.4 10
1999-10-17 @ Vejle BK D 1-1 1555 1568 26.77% 26.79% 46.44% +0.4 7
1999-10-18 AB Copenhagen L 1-2 1616 1633 42.27% 27.48% 30.25% -3.9 25
1999-10-18 @ Herfolge W 2-1 1633 1616 30.25% 27.48% 42.27% +3.9 25
1999-10-20 Aalborg D 0-0 1411 1667 16.61% 21.33% 62.06% +1.1 11
1999-10-20 @ Esbjerg D 0-0 1667 1411 62.06% 21.33% 16.61% -1.1 22
1999-10-24 Brondby W 3-1 1666 1700 39.83% 27.72% 32.45% +5.6 25
1999-10-24 @ Aalborg L 1-3 1700 1666 32.45% 27.72% 39.83% -5.6 25
1999-10-24 Lyngby D 2-2 1637 1607 48.71% 26.27% 25.02% -0.4 26
1999-10-24 @ AB Copenhagen D 2-2 1607 1637 25.02% 26.27% 48.71% +0.4 23
1999-10-24 Herfolge W 2-0 1582 1612 40.42% 27.67% 31.90% +6.4 17
1999-10-24 @ FC Copenhagen L 0-2 1612 1582 31.90% 27.67% 40.42% -6.4 25
1999-10-24 Vejle BK D 1-1 1535 1568 40.00% 27.71% 32.30% -0.2 13
1999-10-24 @ Odense D 1-1 1568 1535 32.30% 27.71% 40.00% +0.1 11
1999-10-24 Aarhus GF D 1-1 1585 1555 48.64% 26.29% 25.08% -0.5 19
1999-10-24 @ Viborg D 1-1 1555 1585 25.08% 26.29% 48.64% +0.5 8
1999-10-25 Esbjerg W 2-0 1643 1412 72.61% 15.84% 11.55% +2.2 22
1999-10-25 @ Silkeborg L 0-2 1412 1643 11.55% 15.84% 72.61% -2.2 11
1999-10-31 AB Copenhagen W 3-0 1694 1636 52.43% 25.20% 22.37% +6.8 28
1999-10-31 @ Brondby L 0-3 1636 1694 22.37% 25.20% 52.43% -6.8 26
1999-10-31 Odense L 0-2 1410 1535 27.79% 27.03% 45.18% -5.7 11
1999-10-31 @ Esbjerg W 2-0 1535 1410 45.18% 27.03% 27.79% +5.7 16
1999-10-31 Silkeborg W 4-1 1606 1646 39.01% 27.77% 33.22% +8.0 28
1999-10-31 @ Herfolge L 1-4 1646 1606 33.22% 27.77% 39.01% -8.0 22
1999-10-31 FC Copenhagen L 0-4 1607 1589 47.18% 26.63% 26.19% -16.2 23
1999-10-31 @ Lyngby W 4-0 1589 1607 26.19% 26.63% 47.18% +16.2 20
1999-10-31 Viborg L 0-2 1568 1584 42.33% 27.47% 30.20% -7.8 11
1999-10-31 @ Vejle BK W 2-0 1584 1568 30.20% 27.47% 42.33% +7.8 22
1999-11-01 Aalborg D 1-1 1556 1672 28.81% 27.24% 43.95% +0.3 9
1999-11-01 @ Aarhus GF D 1-1 1672 1556 43.95% 27.24% 28.81% -0.3 26
1999-11-07 Aarhus GF L 2-3 1630 1556 54.45% 24.51% 21.04% -4.5 26
1999-11-07 @ AB Copenhagen W 3-2 1556 1630 21.04% 24.51% 54.45% +4.5 12
1999-11-07 Vejle BK W 3-1 1404 1560 24.51% 26.09% 49.40% +7.6 14
1999-11-07 @ Esbjerg L 1-3 1560 1404 49.40% 26.09% 24.51% -7.6 11
1999-11-07 Brondby D 1-1 1605 1701 31.18% 27.60% 41.23% +0.2 21
1999-11-07 @ FC Copenhagen D 1-1 1701 1605 41.23% 27.60% 31.18% -0.2 29
1999-11-07 Herfolge L 0-1 1540 1614 34.21% 27.82% 37.97% -3.6 16
1999-11-07 @ Odense W 1-0 1614 1540 37.97% 27.82% 34.21% +3.6 31
1999-11-07 Lyngby W 3-0 1638 1591 50.92% 25.66% 23.42% +7.1 25
1999-11-07 @ Silkeborg L 0-3 1591 1638 23.42% 25.66% 50.92% -7.1 23
1999-11-08 Viborg L 1-2 1671 1592 55.17% 24.25% 20.58% -4.8 26
1999-11-08 @ Aalborg W 2-1 1592 1671 20.58% 24.25% 55.17% +4.8 25
1999-11-21 Silkeborg D 0-0 1701 1645 52.22% 25.27% 22.52% -0.7 30
1999-11-21 @ Brondby D 0-0 1645 1701 22.52% 25.27% 52.22% +0.7 26
1999-11-21 Esbjerg W 3-2 1617 1412 69.94% 17.31% 12.75% +1.2 34
1999-11-21 @ Herfolge L 2-3 1412 1617 12.75% 17.31% 69.94% -1.2 14
1999-11-21 Odense W 2-0 1584 1537 51.02% 25.64% 23.35% +4.9 26
1999-11-21 @ Lyngby L 0-2 1537 1584 23.35% 25.64% 51.02% -4.9 16
1999-11-21 Aalborg D 1-1 1552 1666 29.01% 27.28% 43.72% +0.3 12
1999-11-21 @ Vejle BK D 1-1 1666 1552 43.72% 27.28% 29.01% -0.3 27
1999-11-21 AB Copenhagen W 2-1 1597 1625 40.65% 27.65% 31.70% +3.2 28
1999-11-21 @ Viborg L 1-2 1625 1597 31.70% 27.65% 40.65% -3.2 26
1999-11-22 FC Copenhagen W 1-0 1561 1605 38.35% 27.81% 33.85% +3.5 15
1999-11-22 @ Aarhus GF L 0-1 1605 1561 33.85% 27.81% 38.35% -3.5 21
1999-11-27 Brondby D 1-1 1532 1700 23.29% 25.61% 51.10% +0.6 17
1999-11-27 @ Odense D 1-1 1700 1532 51.10% 25.61% 23.29% -0.6 31
1999-11-28 Aalborg D 1-1 1622 1666 38.38% 27.81% 33.81% -0.1 27
1999-11-28 @ AB Copenhagen D 1-1 1666 1622 33.81% 27.81% 38.38% +0.1 28
1999-11-28 Lyngby L 2-3 1411 1589 22.41% 25.22% 52.37% -2.2 14
1999-11-28 @ Esbjerg W 3-2 1589 1411 52.37% 25.22% 22.41% +2.2 29
1999-11-28 Viborg W 2-1 1602 1600 44.83% 27.10% 28.07% +2.9 24
1999-11-28 @ FC Copenhagen L 1-2 1600 1602 28.07% 27.10% 44.83% -2.9 28
1999-11-28 Vejle BK W 3-1 1619 1553 53.47% 24.85% 21.68% +3.9 37
1999-11-28 @ Herfolge L 1-3 1553 1619 21.68% 24.85% 53.47% -3.9 12
1999-11-28 Aarhus GF W 4-1 1645 1564 55.43% 24.15% 20.42% +5.2 29
1999-11-28 @ Silkeborg L 1-4 1564 1645 20.42% 24.15% 55.43% -5.2 15
2000-03-12 FC Copenhagen D 0-0 1666 1604 52.94% 25.03% 22.03% -0.7 29
2000-03-12 @ Aalborg D 0-0 1604 1666 22.03% 25.03% 52.94% +0.7 25
2000-03-12 Odense L 0-1 1559 1533 48.23% 26.39% 25.38% -4.6 15
2000-03-12 @ Aarhus GF W 1-0 1533 1559 25.38% 26.39% 48.23% +4.6 20
2000-03-12 Esbjerg L 2-3 1700 1409 78.29% 12.62% 9.08% -5.8 31
2000-03-12 @ Brondby W 3-2 1409 1700 9.08% 12.62% 78.29% +5.8 17
2000-03-12 AB Copenhagen W 3-1 1549 1622 34.25% 27.83% 37.92% +6.3 15
2000-03-12 @ Vejle BK L 1-3 1622 1549 37.92% 27.83% 34.25% -6.3 27
2000-03-12 Silkeborg D 1-1 1597 1651 37.05% 27.85% 35.10% -0.0 29
2000-03-12 @ Viborg D 1-1 1651 1597 35.10% 27.85% 37.05% +0.0 30
2000-03-13 Herfolge W 1-0 1591 1623 40.21% 27.69% 32.10% +3.4 32
2000-03-13 @ Lyngby L 0-1 1623 1591 32.10% 27.69% 40.21% -3.4 37
2000-03-19 Aarhus GF L 0-1 1415 1554 26.12% 26.61% 47.27% -2.9 17
2000-03-19 @ Esbjerg W 1-0 1554 1415 47.27% 26.61% 26.12% +2.9 18
2000-03-19 AB Copenhagen L 1-2 1605 1616 43.15% 27.36% 29.48% -4.0 25
2000-03-19 @ FC Copenhagen W 2-1 1616 1605 29.48% 27.36% 43.15% +4.0 30
2000-03-19 Brondby L 0-2 1619 1694 34.03% 27.82% 38.15% -6.7 37
2000-03-19 @ Herfolge W 2-0 1694 1619 38.15% 27.82% 34.03% +6.7 34
2000-03-19 Vejle BK L 0-1 1595 1555 50.00% 25.93% 24.07% -4.7 32
2000-03-19 @ Lyngby W 1-0 1555 1595 24.07% 25.93% 50.00% +4.7 18
2000-03-19 Viborg L 0-1 1537 1597 36.11% 27.86% 36.03% -3.7 20
2000-03-19 @ Odense W 1-0 1597 1537 36.03% 27.86% 36.11% +3.7 32
2000-03-20 Aalborg D 1-1 1651 1666 42.54% 27.44% 30.01% -0.2 31
2000-03-20 @ Silkeborg D 1-1 1666 1651 30.01% 27.44% 42.54% +0.2 30
2000-03-26 Odense L 1-2 1666 1533 61.71% 21.49% 16.80% -5.2 30
2000-03-26 @ Aalborg W 2-1 1533 1666 16.80% 21.49% 61.71% +5.2 23
2000-03-26 Herfolge L 2-3 1557 1612 36.79% 27.85% 35.36% -3.4 18
2000-03-26 @ Aarhus GF W 3-2 1612 1557 35.36% 27.85% 36.79% +3.3 40
2000-03-26 Silkeborg W 2-0 1620 1650 40.29% 27.68% 32.03% +6.4 33
2000-03-26 @ AB Copenhagen L 0-2 1650 1620 32.03% 27.68% 40.29% -6.4 31
2000-03-26 Lyngby D 2-2 1701 1590 59.11% 22.66% 18.23% -0.6 35
2000-03-26 @ Brondby D 2-2 1590 1701 18.23% 22.66% 59.11% +0.7 33
2000-03-26 FC Copenhagen L 2-7 1560 1601 38.77% 27.79% 33.44% -11.9 18
2000-03-26 @ Vejle BK W 7-2 1601 1560 33.44% 27.79% 38.77% +11.9 28
2000-03-26 Esbjerg L 2-3 1601 1412 68.20% 18.24% 13.56% -5.3 32
2000-03-26 @ Viborg W 3-2 1412 1601 13.56% 18.24% 68.20% +5.3 20
2000-03-30 Esbjerg W 1-0 1554 1417 62.25% 21.24% 16.51% +1.8 21
2000-03-30 @ Aarhus GF L 0-1 1417 1554 16.51% 21.24% 62.25% -1.8 20
2000-04-02 Aalborg D 0-0 1415 1661 17.28% 21.91% 60.81% +1.0 21
2000-04-02 @ Esbjerg D 0-0 1661 1415 60.81% 21.91% 17.28% -1.0 31
2000-04-02 Aarhus GF W 3-0 1590 1556 49.37% 26.10% 24.53% +7.4 36
2000-04-02 @ Lyngby L 0-3 1556 1590 24.53% 26.10% 49.37% -7.4 21
2000-04-02 AB Copenhagen D 1-1 1539 1626 32.35% 27.71% 39.94% +0.1 24
2000-04-02 @ Odense D 1-1 1626 1539 39.94% 27.71% 32.35% -0.1 34
2000-04-02 FC Copenhagen W 2-1 1644 1613 48.86% 26.23% 24.91% +2.6 34
2000-04-02 @ Silkeborg L 1-2 1613 1644 24.91% 26.23% 48.86% -2.6 28
2000-04-02 Brondby D 1-1 1548 1700 24.85% 26.21% 48.94% +0.5 19
2000-04-02 @ Vejle BK D 1-1 1700 1548 48.94% 26.21% 24.85% -0.5 36
2000-04-03 Viborg W 3-2 1616 1595 47.42% 26.58% 26.01% +2.6 43
2000-04-03 @ Herfolge L 2-3 1595 1616 26.01% 26.58% 47.42% -2.5 32
2000-04-09 Lyngby D 1-1 1659 1598 52.91% 25.04% 22.05% -0.6 32
2000-04-09 @ Aalborg D 1-1 1598 1659 22.05% 25.04% 52.91% +0.6 37
2000-04-09 Herfolge W 3-0 1626 1618 45.65% 26.95% 27.40% +8.2 37
2000-04-09 @ AB Copenhagen L 0-3 1618 1626 27.40% 26.95% 45.65% -8.2 43
2000-04-09 Esbjerg W 3-1 1610 1416 68.75% 17.95% 13.30% +2.3 31
2000-04-09 @ FC Copenhagen L 1-3 1416 1610 13.30% 17.95% 68.75% -2.3 21
2000-04-09 Odense W 1-0 1647 1539 58.75% 22.82% 18.43% +2.0 37
2000-04-09 @ Silkeborg L 0-1 1539 1647 18.43% 22.82% 58.75% -2.0 24
2000-04-09 Brondby D 2-2 1593 1699 29.91% 27.43% 42.66% +0.2 33
2000-04-09 @ Viborg D 2-2 1699 1593 42.66% 27.43% 29.91% -0.2 37
2000-04-10 Vejle BK W 2-0 1548 1548 44.61% 27.14% 28.26% +5.8 24
2000-04-10 @ Aarhus GF L 0-2 1548 1548 28.26% 27.14% 44.61% -5.8 19
2000-04-16 Aarhus GF W 2-0 1699 1554 63.24% 20.77% 16.00% +3.3 40
2000-04-16 @ Brondby L 0-2 1554 1699 16.00% 20.77% 63.24% -3.3 24
2000-04-16 AB Copenhagen D 0-0 1414 1634 19.03% 23.25% 57.72% +0.9 22
2000-04-16 @ Esbjerg D 0-0 1634 1414 57.72% 23.25% 19.03% -0.9 38
2000-04-16 Aalborg L 0-2 1610 1659 37.74% 27.83% 34.43% -7.2 43
2000-04-16 @ Herfolge W 2-0 1659 1610 34.43% 27.83% 37.74% +7.2 35
2000-04-16 Viborg L 1-3 1599 1593 45.37% 27.00% 27.63% -7.2 37
2000-04-16 @ Lyngby W 3-1 1593 1599 27.63% 27.00% 45.37% +7.2 36
2000-04-16 Silkeborg W 2-1 1543 1649 29.96% 27.44% 42.60% +3.9 22
2000-04-16 @ Vejle BK L 1-2 1649 1543 42.60% 27.44% 29.96% -3.9 37
2000-04-17 FC Copenhagen W 2-0 1537 1613 33.87% 27.81% 38.32% +7.3 27
2000-04-17 @ Odense L 0-2 1613 1537 38.32% 27.81% 33.87% -7.3 31
2000-04-20 Esbjerg W 7-1 1666 1415 74.60% 14.73% 10.67% +4.5 38
2000-04-20 @ Aalborg L 1-7 1415 1666 10.67% 14.73% 74.60% -4.6 22
2000-04-20 Lyngby W 3-0 1551 1591 38.89% 27.78% 33.33% +9.5 27
2000-04-20 @ Aarhus GF L 0-3 1591 1551 33.33% 27.78% 38.89% -9.5 37
2000-04-20 Odense L 0-2 1633 1544 56.41% 23.78% 19.81% -9.8 38
2000-04-20 @ AB Copenhagen W 2-0 1544 1633 19.81% 23.78% 56.41% +9.8 30
2000-04-20 Vejle BK W 4-0 1703 1546 64.49% 20.15% 15.36% +5.9 43
2000-04-20 @ Brondby L 0-4 1546 1703 15.36% 20.15% 64.49% -5.9 22
2000-04-20 Silkeborg W 4-1 1605 1645 39.08% 27.77% 33.15% +8.0 34
2000-04-20 @ FC Copenhagen L 1-4 1645 1605 33.15% 27.77% 39.08% -8.0 37
2000-04-20 Herfolge W 1-0 1600 1603 44.24% 27.20% 28.56% +3.1 39
2000-04-20 @ Viborg L 0-1 1603 1600 28.56% 27.20% 44.24% -3.1 43
2000-04-23 Viborg L 1-2 1410 1603 21.13% 24.56% 54.31% -2.2 22
2000-04-23 @ Esbjerg W 2-1 1603 1410 54.31% 24.56% 21.13% +2.2 42
2000-04-23 Vejle BK L 1-4 1613 1541 54.36% 24.54% 21.10% -11.7 34
2000-04-23 @ FC Copenhagen W 4-1 1541 1613 21.10% 24.54% 54.36% +11.7 25
2000-04-23 Aarhus GF D 1-1 1600 1560 50.02% 25.92% 24.06% -0.5 44
2000-04-23 @ Herfolge D 1-1 1560 1600 24.06% 25.92% 50.02% +0.5 28
2000-04-23 Brondby W 3-0 1582 1708 27.56% 26.98% 45.46% +12.0 40
2000-04-23 @ Lyngby L 0-3 1708 1582 45.46% 26.98% 27.56% -12.0 43
2000-04-23 Aalborg L 1-4 1554 1671 28.69% 27.22% 44.09% -7.1 30
2000-04-23 @ Odense W 4-1 1671 1554 44.09% 27.22% 28.69% +7.2 41
2000-04-23 AB Copenhagen W 1-0 1637 1623 46.47% 26.78% 26.75% +2.9 40
2000-04-23 @ Silkeborg L 0-1 1623 1637 26.75% 26.78% 46.47% -2.9 38
2000-04-30 Esbjerg W 4-3 1561 1408 64.10% 20.35% 15.56% +1.5 31
2000-04-30 @ Aarhus GF L 3-4 1408 1561 15.56% 20.35% 64.10% -1.5 22
2000-04-30 FC Copenhagen L 0-2 1620 1602 47.17% 26.63% 26.19% -8.5 38
2000-04-30 @ AB Copenhagen W 2-0 1602 1620 26.19% 26.63% 47.17% +8.5 37
2000-04-30 Herfolge W 5-0 1696 1599 57.41% 23.38% 19.21% +9.4 46
2000-04-30 @ Brondby L 0-5 1599 1696 19.21% 23.38% 57.41% -9.4 44
2000-04-30 Lyngby W 4-0 1552 1594 38.75% 27.79% 33.46% +12.5 28
2000-04-30 @ Vejle BK L 0-4 1594 1552 33.46% 27.79% 38.75% -12.5 40
2000-04-30 Odense L 2-4 1606 1547 52.55% 25.16% 22.29% -7.2 42
2000-04-30 @ Viborg W 4-2 1547 1606 22.29% 25.16% 52.55% +7.2 33
2000-05-01 Silkeborg W 1-0 1678 1640 49.81% 25.98% 24.21% +2.7 44
2000-05-01 @ Aalborg L 0-1 1640 1678 24.21% 25.98% 49.81% -2.7 40
2000-05-03 Aarhus GF W 2-1 1610 1562 51.13% 25.60% 23.27% +2.4 40
2000-05-03 @ FC Copenhagen L 1-2 1562 1610 23.27% 25.60% 51.13% -2.4 31
2000-05-07 Vejle BK D 1-1 1612 1565 51.01% 25.64% 23.35% -0.6 39
2000-05-07 @ AB Copenhagen D 1-1 1565 1612 23.35% 25.64% 51.01% +0.6 29
2000-05-07 Brondby W 2-0 1407 1706 14.11% 18.85% 67.04% +11.1 25
2000-05-07 @ Esbjerg L 0-2 1706 1407 67.04% 18.85% 14.11% -11.1 46
2000-05-07 Aalborg D 0-0 1613 1680 35.02% 27.85% 37.13% +0.0 41
2000-05-07 @ FC Copenhagen D 0-0 1680 1613 37.13% 27.85% 35.02% -0.1 45
2000-05-07 Lyngby W 4-1 1590 1581 45.82% 26.91% 27.27% +6.9 47
2000-05-07 @ Herfolge L 1-4 1581 1590 27.27% 26.91% 45.82% -6.9 40
2000-05-07 Aarhus GF W 4-0 1554 1560 43.79% 27.27% 28.94% +11.2 36
2000-05-07 @ Odense L 0-4 1560 1554 28.94% 27.27% 43.79% -11.2 31
2000-05-07 Viborg W 1-0 1637 1598 49.87% 25.96% 24.17% +2.7 43
2000-05-07 @ Silkeborg L 0-1 1598 1637 24.17% 25.96% 49.87% -2.7 42
2000-05-10 AB Copenhagen L 0-2 1680 1611 53.87% 24.71% 21.41% -9.4 45
2000-05-10 @ Aalborg W 2-0 1611 1680 21.41% 24.71% 53.87% +9.4 42
2000-05-10 Silkeborg W 2-1 1549 1640 31.87% 27.67% 40.46% +3.8 34
2000-05-10 @ Aarhus GF L 1-2 1640 1549 40.46% 27.67% 31.87% -3.8 43
2000-05-10 Odense W 2-1 1695 1565 61.39% 21.64% 16.97% +1.8 49
2000-05-10 @ Brondby L 1-2 1565 1695 16.97% 21.64% 61.39% -1.8 36
2000-05-10 Herfolge L 0-2 1565 1597 40.18% 27.69% 32.13% -7.5 29
2000-05-10 @ Vejle BK W 2-0 1597 1565 32.13% 27.69% 40.18% +7.5 50
2000-05-10 FC Copenhagen D 1-1 1596 1613 42.23% 27.48% 30.28% -0.2 43
2000-05-10 @ Viborg D 1-1 1613 1596 30.28% 27.48% 42.23% +0.2 42
2000-05-11 Esbjerg L 4-6 1574 1418 64.56% 20.12% 15.32% -7.7 40
2000-05-11 @ Lyngby W 6-4 1418 1574 15.32% 20.12% 64.56% +7.7 28
2000-05-14 Vejle BK W 7-1 1671 1558 59.40% 22.54% 18.06% +8.6 48
2000-05-14 @ Aalborg L 1-7 1558 1671 18.06% 22.54% 59.40% -8.6 29
2000-05-14 Viborg W 6-0 1621 1596 48.08% 26.42% 25.50% +14.7 45
2000-05-14 @ AB Copenhagen L 0-6 1596 1621 25.50% 26.42% 48.08% -14.7 43
2000-05-14 Herfolge L 1-2 1425 1604 22.33% 25.18% 52.49% -2.3 28
2000-05-14 @ Esbjerg W 2-1 1604 1425 52.49% 25.18% 22.33% +2.3 53
2000-05-14 Lyngby L 1-3 1563 1567 44.13% 27.21% 28.66% -7.0 36
2000-05-14 @ Odense W 3-1 1567 1563 28.66% 27.21% 44.13% +7.0 43
2000-05-15 Brondby D 1-1 1636 1696 36.02% 27.86% 36.12% +0.0 44
2000-05-15 @ Silkeborg D 1-1 1696 1636 36.12% 27.86% 36.02% -0.0 50
2000-05-21 AB Copenhagen D 2-2 1552 1635 32.92% 27.75% 39.32% +0.1 35
2000-05-21 @ Aarhus GF D 2-2 1635 1552 39.32% 27.75% 32.92% -0.1 46
2000-05-21 FC Copenhagen D 1-1 1696 1613 55.70% 24.05% 20.25% -0.7 51
2000-05-21 @ Brondby D 1-1 1613 1696 20.25% 24.05% 55.70% +0.8 43
2000-05-21 Odense D 3-3 1607 1556 51.45% 25.51% 23.04% -0.4 54
2000-05-21 @ Herfolge D 3-3 1556 1607 23.04% 25.51% 51.45% +0.4 37
2000-05-21 Silkeborg D 0-0 1574 1636 35.82% 27.86% 36.32% +0.0 44
2000-05-21 @ Lyngby D 0-0 1636 1574 36.32% 27.86% 35.82% -0.0 45
2000-05-21 Aalborg W 7-2 1581 1680 30.88% 27.56% 41.56% +12.5 46
2000-05-21 @ Viborg L 2-7 1680 1581 41.56% 27.56% 30.88% -12.5 48
2000-05-22 Esbjerg W 2-1 1549 1423 60.97% 21.84% 17.20% +1.8 32
2000-05-22 @ Vejle BK L 1-2 1423 1549 17.20% 21.84% 60.97% -1.8 28
2000-05-25 Aarhus GF D 1-1 1667 1553 59.56% 22.47% 17.97% -0.9 49
2000-05-25 @ Aalborg D 1-1 1553 1667 17.97% 22.47% 59.56% +0.9 36
2000-05-25 Brondby W 2-0 1635 1696 36.06% 27.86% 36.08% +7.0 49
2000-05-25 @ AB Copenhagen L 0-2 1696 1635 36.08% 27.86% 36.06% -7.0 51
2000-05-25 Lyngby L 1-2 1614 1574 50.06% 25.91% 24.03% -4.5 43
2000-05-25 @ FC Copenhagen W 2-1 1574 1614 24.03% 25.91% 50.06% +4.5 47
2000-05-25 Herfolge D 1-1 1636 1606 48.65% 26.28% 25.07% -0.5 46
2000-05-25 @ Silkeborg D 1-1 1606 1636 25.07% 26.28% 48.65% +0.5 55
2000-05-25 Vejle BK W 3-0 1593 1551 50.38% 25.82% 23.80% +7.2 49
2000-05-25 @ Viborg L 0-3 1551 1593 23.80% 25.82% 50.38% -7.2 32
2000-05-26 Esbjerg W 4-1 1557 1421 62.07% 21.33% 16.61% +4.2 40
2000-05-26 @ Odense L 1-4 1421 1557 16.61% 21.33% 62.07% -4.2 28
2000-05-28 Viborg L 0-4 1553 1601 37.96% 27.82% 34.22% -13.7 36
2000-05-28 @ Aarhus GF W 4-0 1601 1553 34.22% 27.82% 37.96% +13.7 52
2000-05-28 Aalborg W 1-0 1689 1666 47.72% 26.51% 25.77% +2.8 54
2000-05-28 @ Brondby L 0-1 1666 1689 25.77% 26.51% 47.72% -2.8 49
2000-05-28 Silkeborg L 0-3 1417 1635 19.16% 23.34% 57.49% -5.8 28
2000-05-28 @ Esbjerg W 3-0 1635 1417 57.49% 23.34% 19.16% +5.8 49
2000-05-28 FC Copenhagen D 1-1 1607 1609 44.28% 27.19% 28.53% -0.3 56
2000-05-28 @ Herfolge D 1-1 1609 1607 28.53% 27.19% 44.28% +0.3 44
2000-05-28 AB Copenhagen L 0-2 1578 1642 35.54% 27.86% 36.61% -6.9 47
2000-05-28 @ Lyngby W 2-0 1642 1578 36.61% 27.86% 35.54% +6.9 52
2000-05-28 Odense L 0-1 1544 1561 42.23% 27.48% 30.29% -4.2 32
2000-05-28 @ Vejle BK W 1-0 1561 1544 30.29% 27.48% 42.23% +4.2 43

Biggest Upsets

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

# Date Underdog Win % Winning Team Losing Team
Team Elo Score Team Elo Score
1 2000-03-12 9.08% Esbjerg 1409 3 @ Brondby 1700 2
2 1999-10-13 11.02% Esbjerg 1396 2 @ AB Copenhagen 1639 1
3 2000-03-26 13.56% Esbjerg 1412 3 @ Viborg 1601 2
4 2000-05-07 14.11% @ Esbjerg 1407 2 Brondby 1706 0
5 2000-05-11 15.32% Esbjerg 1418 6 @ Lyngby 1574 4
6 2000-03-26 16.80% Odense 1533 2 @ Aalborg 1666 1
7 1999-09-19 19.20% Odense 1537 1 @ Silkeborg 1634 0
8 2000-04-20 19.81% Odense 1544 2 @ AB Copenhagen 1633 0
9 1999-09-10 19.99% Lyngby 1579 2 @ Aalborg 1665 0
10 1999-11-08 20.58% Viborg 1592 2 @ Aalborg 1671 1
11 1999-11-07 21.04% Aarhus GF 1556 3 @ AB Copenhagen 1630 2
12 2000-04-23 21.10% Vejle BK 1541 4 @ FC Copenhagen 1613 1
13 1999-10-17 21.38% @ Esbjerg 1402 2 FC Copenhagen 1592 0
14 2000-05-10 21.41% AB Copenhagen 1611 2 @ Aalborg 1680 0
15 2000-04-30 22.29% Odense 1547 4 @ Viborg 1606 2
16 1999-10-03 22.98% FC Copenhagen 1592 2 @ AB Copenhagen 1643 1
17 2000-05-25 24.03% Lyngby 1574 2 @ FC Copenhagen 1614 1
18 2000-03-19 24.07% Vejle BK 1555 1 @ Lyngby 1595 0
19 1999-11-07 24.51% @ Esbjerg 1404 3 Vejle BK 1560 1
20 1999-07-26 24.84% @ Esbjerg 1408 2 Odense 1560 0
21 1999-10-06 24.89% @ Odense 1542 2 Brondby 1694 1
22 2000-03-12 25.38% Odense 1533 1 @ Aarhus GF 1559 0
23 1999-10-31 26.19% FC Copenhagen 1589 4 @ Lyngby 1607 0
24 2000-04-30 26.19% FC Copenhagen 1602 2 @ AB Copenhagen 1620 0
25 2000-04-23 27.56% @ Lyngby 1582 3 Brondby 1708 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 1999-10-31 16.16 FC Copenhagen 4 1589 26.19% @ Lyngby 0 1607 47.18% 26.63%
2 1999-07-25 15.20 Silkeborg 4 1614 29.15% @ Vejle BK 0 1607 43.55% 27.30%
3 2000-05-14 14.68 @ AB Copenhagen 6 1621 48.08% Viborg 0 1596 25.50% 26.42%
4 2000-05-28 13.71 Viborg 4 1601 34.22% @ Aarhus GF 0 1553 37.96% 27.82%
5 2000-05-21 12.53 @ Viborg 7 1581 30.88% Aalborg 2 1680 41.56% 27.56%
6 2000-04-30 12.50 @ Vejle BK 4 1552 38.75% Lyngby 0 1594 33.46% 27.79%
7 1999-10-17 12.31 Silkeborg 4 1631 39.46% @ Odense 0 1547 32.79% 27.75%
8 2000-04-23 12.02 @ Lyngby 3 1582 27.56% Brondby 0 1708 45.46% 26.98%
9 2000-03-26 11.89 FC Copenhagen 7 1601 33.44% @ Vejle BK 2 1560 38.77% 27.79%
10 1999-08-01 11.71 Brondby 4 1691 41.74% @ Vejle BK 0 1591 30.72% 27.54%
11 2000-04-23 11.65 Vejle BK 4 1541 21.10% @ FC Copenhagen 1 1613 54.36% 24.54%
12 2000-05-07 11.17 @ Odense 4 1554 43.79% Aarhus GF 0 1560 28.94% 27.27%
13 2000-05-07 11.11 @ Esbjerg 2 1407 14.11% Brondby 0 1706 67.04% 18.85%
14 1999-08-01 10.15 AB Copenhagen 3 1610 35.87% @ Odense 0 1551 36.27% 27.86%
15 2000-04-20 9.78 Odense 2 1544 19.81% @ AB Copenhagen 0 1633 56.41% 23.78%
16 1999-09-10 9.75 Lyngby 2 1579 19.99% @ Aalborg 0 1665 56.13% 23.89%
17 1999-10-13 9.68 @ Aalborg 4 1661 49.39% Herfolge 0 1626 24.52% 26.09%
18 2000-04-20 9.54 @ Aarhus GF 3 1551 38.89% Lyngby 0 1591 33.33% 27.78%
19 1999-10-17 9.45 @ Esbjerg 2 1402 21.38% FC Copenhagen 0 1592 53.92% 24.70%
20 2000-05-10 9.44 AB Copenhagen 2 1611 21.41% @ Aalborg 0 1680 53.87% 24.71%
21 2000-04-30 9.38 @ Brondby 5 1696 57.41% Herfolge 0 1599 19.21% 23.38%
22 1999-10-06 8.81 @ Lyngby 5 1587 46.02% Vejle BK 1 1576 27.11% 26.87%
23 1999-07-26 8.77 @ Esbjerg 2 1408 24.84% Odense 0 1560 48.96% 26.21%
24 2000-05-14 8.60 @ Aalborg 7 1671 59.40% Vejle BK 1 1558 18.06% 22.54%
25 2000-04-30 8.52 FC Copenhagen 2 1602 26.19% @ AB Copenhagen 0 1620 47.17% 26.63%