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1988 1st Division Season

182 games

Final

Champion

Brondby

40 points · 3rd Title

Last Title: 1987

Relegated

KB Copenhagen

8 pts

Randers · 8 pts

Biggest Overachiever

Herfolge

7.90 points above expected

29 points · 21.10 expected points

Biggest Disappointment

KB Copenhagen

8.81 points below expected

8 points · 16.81 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 26 17 6 3 40 57 22 +35 37.32 +2.68
2 Naestved 26 13 9 4 35 41 26 +15 30.77 +4.23
3 Lyngby 26 15 5 6 35 41 27 +14 30.71 +4.29
4 B 1903 26 12 8 6 32 44 27 +17 27.49 +4.51
5 Vejle BK 26 10 10 6 30 36 24 +12 29.34 +0.66
6 Odense 26 12 5 9 29 47 36 +11 29.17 -0.17
7 Herfolge 26 11 7 8 29 30 30 0 21.10 +7.90
8 Aarhus GF 26 11 6 9 28 37 29 +8 28.99 -0.99
9 Silkeborg 26 11 4 11 26 39 35 +4 27.11 -1.11
10 Ikast 26 8 6 12 22 35 39 -4 28.27 -6.27
11 Aalborg 26 8 6 12 22 33 50 -17 20.29 +1.71
12 Bronshoj 26 8 4 14 20 38 48 -10 23.02 -3.02
13 KB Copenhagen Relegated 26 3 2 21 8 27 66 -39 16.81 -8.81
14 Randers Relegated 26 2 4 20 8 28 74 -46 13.62 -5.62

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 1700 40 37.32 +2.68 79.3% 23 31 35 37 40 43 50
B 1903 1566 32 27.49 +4.51 88.0% 12 21 25 27 30 35 43
Naestved 1562 35 30.77 +4.23 87.0% 16 24 28 31 34 38 45
Aarhus GF 1541 28 28.99 -0.99 45.8% 11 22 26 29 32 36 42
Vejle BK 1522 30 29.34 +0.66 60.4% 14 23 27 29 32 36 45
Lyngby 1521 35 30.71 +4.29 87.6% 16 24 28 31 34 38 46
Odense 1474 29 29.17 -0.17 53.2% 14 22 26 29 32 36 43
Silkeborg 1473 26 27.11 -1.11 44.5% 11 20 24 27 30 34 43
Ikast 1465 22 28.27 -6.27 8.4% 12 21 25 28 31 35 43
Bronshoj 1438 20 23.02 -3.02 27.7% 9 16 20 23 26 30 39
Herfolge 1397 29 21.10 +7.90 97.6% 6 14 18 21 24 28 38
Aalborg 1350 22 20.29 +1.71 70.5% 6 14 17 20 23 27 37
KB Copenhagen 1211 8 16.81 -8.81 1.3% 4 11 14 17 19 23 33
Randers 1156 8 13.62 -5.62 7.4% 3 8 11 13 16 20 31

Head-to-Head

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

Beat expectations Fell short Within expectations
Team AAL AG B1 BRO BRO HER IKA KC LYN NAE ODE RAN SIL VB
Aalborg —
0-1-1
1.87
0-1-1
1.78
0-0-2
1.10
1-0-1
2.50
1-0-1
2.61
1-0-1
1.85
1-1-0
3.25
1-0-1
1.66
0-1-1
1.69
0-1-1
1.79
1-0-1
3.78
1-1-0
1.96
1-0-1
1.58
Aarhus GF
1-1-0
3.66
 —
0-2-0
2.90
1-0-1
1.75
2-0-0
3.34
1-0-1
3.94
1-1-0
2.97
2-0-0
4.03
0-0-2
2.60
0-1-1
2.58
0-0-2
2.71
2-0-0
4.41
1-0-1
2.93
0-1-1
2.67
B 1903
1-1-0
3.76
0-2-0
2.62
 —
0-2-0
1.64
1-1-0
3.32
2-0-0
3.37
1-0-1
2.77
2-0-0
4.02
1-0-1
2.26
1-0-1
2.25
0-1-1
2.43
2-0-0
4.19
1-0-1
2.81
0-1-1
2.75
Brondby
2-0-0
4.46
1-0-1
3.78
0-2-0
3.89
 —
2-0-0
4.29
1-1-0
4.31
2-0-0
3.90
2-0-0
4.62
2-0-0
3.38
0-1-1
3.85
2-0-0
3.96
2-0-0
4.79
1-0-1
4.01
0-2-0
3.82
Bronshoj
1-0-1
3.03
0-0-2
2.19
0-1-1
2.21
0-0-2
1.26
 —
0-1-1
3.06
2-0-0
2.09
1-0-1
3.75
1-0-1
2.09
0-0-2
1.90
1-0-1
1.93
0-2-0
4.05
2-0-0
2.06
0-0-2
1.85
Herfolge
1-0-1
2.92
1-0-1
1.60
0-0-2
2.16
0-1-1
1.24
1-1-0
2.47
 —
1-1-0
1.78
2-0-0
3.32
0-1-1
1.75
1-1-0
1.60
1-1-0
1.97
2-0-0
3.88
0-0-2
2.16
1-1-0
1.72
Ikast
1-0-1
3.68
0-1-1
2.55
1-0-1
2.75
0-0-2
1.64
0-0-2
3.44
0-1-1
3.75
 —
2-0-0
4.08
0-2-0
2.52
1-1-0
2.28
2-0-0
2.46
1-1-0
4.43
0-0-2
3.11
0-0-2
2.63
KB Copenhagen
0-1-1
2.27
0-0-2
1.51
0-0-2
1.52
0-0-2
0.95
1-0-1
1.78
0-0-2
2.21
0-0-2
1.46
 —
0-0-2
1.22
0-1-1
1.22
0-0-2
1.41
2-0-0
3.06
0-0-2
1.69
0-0-2
1.85
Lyngby
1-0-1
3.88
2-0-0
2.93
1-0-1
3.26
0-0-2
2.15
1-0-1
3.44
1-1-0
3.78
0-2-0
3.00
2-0-0
4.33
 —
0-1-1
2.74
1-1-0
2.92
2-0-0
4.55
2-0-0
3.22
2-0-0
2.73
Naestved
1-1-0
3.85
1-1-0
2.95
1-0-1
3.27
1-1-0
1.68
2-0-0
3.63
0-1-1
3.94
0-1-1
3.25
1-1-0
4.33
1-1-0
2.79
 —
1-0-1
3.02
2-0-0
4.45
2-0-0
3.05
0-2-0
2.95
Odense
1-1-0
3.74
2-0-0
2.82
1-1-0
3.09
0-0-2
1.58
1-0-1
3.60
0-1-1
3.56
0-0-2
3.07
2-0-0
4.13
0-1-1
2.61
1-0-1
2.50
 —
2-0-0
4.39
1-0-1
2.82
1-1-0
2.70
Randers
1-0-1
1.75
0-0-2
1.14
0-0-2
1.36
0-0-2
0.80
0-2-0
1.50
0-0-2
1.66
0-1-1
1.12
0-0-2
2.46
0-0-2
1.01
0-0-2
1.11
0-0-2
1.17
 —
0-1-1
1.29
1-0-1
1.22
Silkeborg
0-1-1
3.57
1-0-1
2.60
1-0-1
2.72
1-0-1
1.53
0-0-2
3.46
2-0-0
3.36
2-0-0
2.41
2-0-0
3.84
0-0-2
2.30
0-0-2
2.47
1-0-1
2.70
1-1-0
4.26
 —
0-2-0
2.42
Vejle BK
1-0-1
3.95
1-1-0
2.85
1-1-0
2.77
0-2-0
1.71
2-0-0
3.68
0-1-1
3.82
2-0-0
2.90
2-0-0
3.68
0-0-2
2.79
0-2-0
2.58
0-1-1
2.83
1-0-1
4.33
0-2-0
3.10
 —

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

R² Slope
Scored 0.61 +9.2
Allowed 0.91 -5.6
Differential 0.95 +4.2

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
08.79%7.69%5.22%4.40%1.65%0.55%28.30%
17.69%8.79%8.24%3.30%1.37%1.92%31.32%
25.22%8.24%4.40%1.10%1.10%0.82%20.88%
34.40%3.30%1.10%0.55%0.55%0.55%10.44%
41.65%1.37%1.10%0.55%—0.27%4.95%
5+0.55%1.92%0.82%0.55%0.27%—4.12%
Total28.30%31.32%20.88%10.44%4.95%4.12%100%

Summary Statistics

Scored Allowed Difference
Mean 1.46 1.46 +0.00
SD 1.40 1.40 2.02
CV 0.96 0.96 —
Max 7 7 +6
Min 0 0 -6

Games Played: 182

↓ Scored | Allowed →012345+Total
07.69%11.54%7.69%11.54%——38.46%
13.85%11.54%———7.69%23.08%
2—11.54%3.85%3.85%—3.85%23.08%
33.85%3.85%————7.69%
4——3.85%———3.85%
5+————3.85%—3.85%
Total15.38%38.46%15.38%15.38%3.85%11.54%100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.92 -0.65
SD 1.37 1.65 2.00
CV 1.08 0.86 —
Max 5 6 +3
Min 0 0 -5

Games Played: 26

↓ Scored | Allowed →012345+Total
011.54%15.38%3.85%—3.85%—34.62%
17.69%3.85%7.69%———19.23%
211.54%3.85%7.69%3.85%——26.92%
33.85%3.85%3.85%———11.54%
4——3.85%———3.85%
5+—3.85%————3.85%
Total34.62%30.77%26.92%3.85%3.85%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.42 1.12 +0.31
SD 1.39 1.07 1.72
CV 0.98 0.96 —
Max 5 4 +4
Min 0 0 -4

Games Played: 26

↓ Scored | Allowed →012345+Total
03.85%3.85%15.38%———23.08%
111.54%15.38%3.85%———30.77%
211.54%3.85%11.54%———26.92%
3—3.85%————3.85%
43.85%——3.85%——7.69%
5+3.85%3.85%————7.69%
Total34.62%30.77%30.77%3.85%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.69 1.04 +0.65
SD 1.59 0.92 1.94
CV 0.94 0.88 —
Max 6 3 +5
Min 0 0 -2

Games Played: 26

↓ Scored | Allowed →012345+Total
015.38%3.85%————19.23%
111.54%7.69%————19.23%
23.85%11.54%—3.85%——19.23%
37.69%7.69%———3.85%19.23%
47.69%3.85%3.85%———15.38%
5+—3.85%3.85%———7.69%
Total46.15%38.46%7.69%3.85%—3.85%100%

Summary Statistics

Scored Allowed Difference
Mean 2.19 0.85 +1.35
SD 1.67 1.16 1.70
CV 0.76 1.37 —
Max 6 5 +4
Min 0 0 -2

Games Played: 26

↓ Scored | Allowed →012345+Total
07.69%7.69%3.85%7.69%——26.92%
1—3.85%15.38%3.85%3.85%3.85%30.77%
2—11.54%3.85%—7.69%—23.08%
37.69%3.85%————11.54%
4—3.85%————3.85%
5+——3.85%———3.85%
Total15.38%30.77%26.92%11.54%11.54%3.85%100%

Summary Statistics

Scored Allowed Difference
Mean 1.46 1.85 -0.38
SD 1.33 1.38 2.04
CV 0.91 0.75 —
Max 5 5 +3
Min 0 0 -4

Games Played: 26

↓ Scored | Allowed →012345+Total
07.69%7.69%7.69%——3.85%26.92%
111.54%19.23%7.69%———38.46%
27.69%15.38%——3.85%—26.92%
33.85%—3.85%———7.69%
4———————
5+———————
Total30.77%42.31%19.23%—3.85%3.85%100%

Summary Statistics

Scored Allowed Difference
Mean 1.15 1.15 +0.00
SD 0.92 1.22 1.62
CV 0.80 1.06 —
Max 3 5 +3
Min 0 0 -5

Games Played: 26

↓ Scored | Allowed →012345+Total
019.23%7.69%3.85%11.54%3.85%—46.15%
1—3.85%7.69%3.85%3.85%—19.23%
27.69%3.85%————11.54%
33.85%—————3.85%
47.69%3.85%———3.85%15.38%
5+———3.85%——3.85%
Total38.46%19.23%11.54%19.23%7.69%3.85%100%

Summary Statistics

Scored Allowed Difference
Mean 1.35 1.50 -0.15
SD 1.65 1.56 2.26
CV 1.22 1.04 —
Max 5 5 +4
Min 0 0 -4

Games Played: 26

↓ Scored | Allowed →012345+Total
0—7.69%11.54%11.54%——30.77%
1—3.85%15.38%15.38%3.85%7.69%46.15%
2—3.85%3.85%3.85%——11.54%
3—7.69%———3.85%11.54%
4———————
5+———————
Total—23.08%30.77%30.77%3.85%11.54%100%

Summary Statistics

Scored Allowed Difference
Mean 1.04 2.54 -1.50
SD 0.96 1.33 1.63
CV 0.92 0.53 —
Max 3 6 +2
Min 0 1 -5

Games Played: 26

↓ Scored | Allowed →012345+Total
07.69%3.85%—3.85%—3.85%19.23%
126.92%7.69%7.69%———42.31%
211.54%7.69%3.85%——3.85%26.92%
33.85%—————3.85%
4———————
5+—7.69%————7.69%
Total50.00%26.92%11.54%3.85%—7.69%100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.04 +0.54
SD 1.65 1.56 2.34
CV 1.05 1.50 —
Max 7 6 +6
Min 0 0 -5

Games Played: 26

↓ Scored | Allowed →012345+Total
015.38%3.85%3.85%—3.85%—26.92%
111.54%11.54%3.85%———26.92%
27.69%7.69%7.69%———23.08%
37.69%3.85%3.85%———15.38%
4———————
5+——3.85%3.85%——7.69%
Total42.31%26.92%23.08%3.85%3.85%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.00 +0.58
SD 1.45 1.10 1.58
CV 0.92 1.10 —
Max 5 4 +3
Min 0 0 -4

Games Played: 26

↓ Scored | Allowed →012345+Total
03.85%—7.69%—3.85%—15.38%
17.69%3.85%15.38%7.69%——34.62%
23.85%15.38%11.54%———30.77%
33.85%—————3.85%
43.85%3.85%————7.69%
5+—7.69%————7.69%
Total23.08%30.77%34.62%7.69%3.85%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.81 1.38 +0.42
SD 1.52 1.06 2.16
CV 0.84 0.77 —
Max 6 4 +5
Min 0 0 -4

Games Played: 26

↓ Scored | Allowed →012345+Total
07.69%3.85%7.69%7.69%7.69%—34.62%
1—3.85%7.69%15.38%3.85%7.69%38.46%
2—3.85%——3.85%3.85%11.54%
33.85%——3.85%7.69%—15.38%
4———————
5+———————
Total11.54%11.54%15.38%26.92%23.08%11.54%100%

Summary Statistics

Scored Allowed Difference
Mean 1.08 2.85 -1.77
SD 1.06 1.76 1.90
CV 0.98 0.62 —
Max 3 7 +3
Min 0 0 -6

Games Played: 26

↓ Scored | Allowed →012345+Total
0—19.23%—3.85%——23.08%
111.54%11.54%15.38%—3.85%—42.31%
2—11.54%————11.54%
3—7.69%—3.85%——11.54%
4—3.85%—3.85%——7.69%
5+3.85%—————3.85%
Total15.38%53.85%15.38%11.54%3.85%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.50 1.35 +0.15
SD 1.39 1.02 1.74
CV 0.93 0.76 —
Max 5 4 +5
Min 0 0 -3

Games Played: 26

↓ Scored | Allowed →012345+Total
015.38%11.54%—3.85%——30.77%
13.85%15.38%7.69%———26.92%
27.69%3.85%7.69%———19.23%
311.54%3.85%3.85%———19.23%
4——3.85%———3.85%
5+———————
Total38.46%34.62%23.08%3.85%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.38 0.92 +0.46
SD 1.24 0.89 1.48
CV 0.89 0.97 —
Max 4 3 +3
Min 0 0 -3

Games Played: 26

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 29 21.10 +7.90
2 B 1903 32 27.49 +4.51
3 Lyngby 35 30.71 +4.29
4 Naestved 35 30.77 +4.23
5 Brondby 40 37.32 +2.68

Biggest Disappointments

# Team Actual Sim vsSim
1 KB Copenhagen 8 16.81 -8.81
2 Ikast 22 28.27 -6.27
3 Randers 8 13.62 -5.62
4 Bronshoj 20 23.02 -3.02
5 Silkeborg 26 27.11 -1.11

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 Lyngby 6 Apr 10 – May 15 1 in 125
2 Ikast 2 Oct 2 – Oct 9 1 in 28
3 Aarhus GF 4 Sep 4 – Oct 9 1 in 26
4 B 1903 4 Aug 28 – Oct 2 1 in 23
5 Bronshoj 3 Sep 11 – Oct 9 1 in 23

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Ikast 6 Aug 7 – Sep 25 1 in 585
2 KB Copenhagen 8 Aug 14 – Oct 16 1 in 46
3 Randers 8 Aug 7 – Oct 9 1 in 43
4 Herfolge 5 Sep 4 – Oct 16 1 in 41
5 Odense 3 Sep 11 – Oct 9 1 in 31

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 B 1903 10 Aug 28 – Nov 13 1 in 57
2 Naestved 11 May 29 – Oct 2 1 in 48
3 Herfolge 5 May 23 – Jul 24 1 in 44
4 Aalborg 4 May 26 – Jul 24 1 in 18
5 Lyngby 7 Apr 3 – May 15 1 in 16

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 B 1903 7 May 9 – Jul 27 1 in 36
2 Vejle BK 5 May 29 – Aug 7 1 in 27
3 Lyngby 5 Jul 17 – Aug 14 1 in 24
4 Ikast 6 Aug 7 – Sep 25 1 in 24
5 Randers 19 May 23 – Nov 13 1 in 20

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).

Team1234567891011121314
Brondby68.63%17.00%7.15%3.41%1.69%1.12%0.54%0.25%0.14%0.04%0.03%———
Naestved7.43%17.52%16.07%14.03%12.06%10.12%7.70%6.16%4.55%2.50%1.32%0.39%0.13%0.02%
Lyngby7.09%17.11%15.79%14.01%11.97%10.02%8.27%6.62%4.53%2.59%1.25%0.60%0.13%0.02%
B 19031.78%6.81%7.97%9.75%10.46%11.97%12.19%12.08%10.43%7.99%5.14%2.51%0.82%0.10%
Vejle BK3.93%11.02%12.64%13.12%11.96%11.85%11.04%9.41%7.09%4.38%2.47%0.81%0.22%0.06%
Odense4.10%9.64%11.67%12.79%12.54%12.24%10.92%9.33%7.54%5.15%2.76%1.07%0.22%0.03%
Herfolge0.01%0.11%0.51%0.86%1.55%2.33%3.29%6.29%10.42%16.89%21.81%19.92%12.12%3.89%
Aarhus GF3.54%9.18%11.70%11.62%12.43%11.38%11.19%10.62%8.49%5.49%2.87%1.15%0.28%0.06%
Silkeborg1.26%4.43%6.62%7.68%10.09%11.09%12.76%12.53%12.65%10.36%6.21%3.18%0.95%0.19%
Ikast2.09%6.49%8.54%10.25%11.35%11.77%12.43%11.93%10.73%7.60%4.05%2.04%0.57%0.16%
Aalborg—0.09%0.14%0.56%0.79%1.65%2.87%4.06%7.52%13.07%20.64%26.23%16.53%5.85%
Bronshoj0.14%0.59%1.17%1.86%3.00%4.26%6.33%9.46%13.43%18.40%19.25%13.76%6.72%1.63%
KB Copenhagen—0.01%0.02%0.06%0.10%0.18%0.43%1.15%2.17%4.51%9.50%20.13%37.87%23.87%
Randers——0.01%—0.01%0.02%0.04%0.11%0.31%1.03%2.70%8.21%23.44%64.12%

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
+6.04%
Slight Edge
41.76%22.53%35.71%
Elo Value
Home Edge: 21.02 Elo pts.
168 Elo
0.006 goals per Elo point
0500
Scoring Tilt
Expected
+0.15 goals
Neutral
-2+0.12+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 to 3rd * Middle of the Pack: 4th to 7th * Longshot: 8th or lower.
Title Margin
Points-per-game gap between the champion and the runner-up. Shown per game so it reads the same across long and short seasons. The gold line is the winning margin the model expected, so a dot to the right means a more one-sided race than projected. A title won on goal difference shows 0.00.
Photo Finish: under 0.15 * Tight Race: 0.15 to 0.4 * Comfortable: 0.4 to 0.75 * Runaway: 0.75 and up.
Title-Race Openness
2.1
Top-Heavy
124610
Champion Preseason Odds
69%
Brondby, 1st of 14
LongshotFavorite
Title Margin
Expected
0.19/gm
Tight Race
00.140.5/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 3.29 * Some Luck: 3.29 to 4.94 * Lucky: 4.94 to 6.58 * Wild Swing: 6.58 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 1.54 * Close: 1.54 to 2.31 * Off: 2.31 to 3.08 * Way Off: 3.08 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 14 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 14 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 14 * As Expected: 14 to 22.4 * Several Outliers: 22.4 to 30.8 * Many Outliers: 30.8 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 0.51 * A Surprise: 0.51 to 0.81 * Several Surprises: 0.81 to 1.12 * Many Surprises: 1.12 and up.
Luck Spread
Expected
4.55 points
Some Luck
04.1210
Average Finish Error
Expected
1.29
Pinpoint
01.924
Biggest Overachiever
Expected 96.43%
97.64%
Herfolge
50100
Biggest Underachiever
Expected 3.57%
1.30%
KB Copenhagen
050
Season Outliers
Expected
2 of 14
Minimal Outliers
01.47
Unexpected Relegations
Expected
0 of 2
As Expected
00.52

Parity

How these are measured

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

Gini Index
How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.
Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully
How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge
Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst
Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts
Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.19
Top-Heavy
00.120.180.260.5
Noll-Scully
Coin-flip
1.84
Strong Separation
01.003
Interquartile Edge
68%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline 95%
96%
Dominant
50%100%
Close Games
Expected
58%
Very Frequent
0%54%100%
Blowouts
Expected
21%
Frequent
0%22%100%

Predictability

How these are measured

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

Brier Score
How close the pregame probabilities landed to the actual result, averaged over the season. Confident, correct calls are rewarded most; confident misses are punished most. Lower is better; since draws are possible, a score under 0.66 beats guessing the base rate.
Highly Predictable: under 0.56 * Predictable: 0.56 to 0.62 * Hard to Predict: 0.62 to 0.66 * Coin-Flip: 0.66 and up.
Matchup Imbalance
How lopsided the matchups were on paper, averaging the gap between the two win probabilities over their sum. 0 means every match was a toss-up; 1 means every match was a heavy favorite against a big underdog.
Very Even: under 0.1 * Slight Separation: 0.1 to 0.18 * Notable Separation: 0.18 to 0.28 * Lopsided: 0.28 and up.
Strangeness
How wild the final table was versus what the model expected. A value of 1 means teams landed about one standard deviation from their projections on average. Above 1 is a stranger season; below 1 hugged the projections.
Very Predictable: under 0.8 * As Expected: 0.8 to 1.1 * Wilder Than Modeled: 1.1 to 1.4 * Chaotic: 1.4 and up.
Repeatability
How closely the final table order matched the preseason Elo order, by Spearman rank correlation. Higher means last season's ratings strongly predicted this season's finish. Shows N/A for an inaugural season.
Weak Carryover: under 0.3 * Some Carryover: 0.3 to 0.6 * Strong Carryover: 0.6 to 0.85 * Near-Lock: 0.85 and up.
Upset Rate
Share of matches the underdog won. The gold line is how often the model expected underdogs to win; a dot to the right means upsets ran hotter than expected.
Chalky: under 25% * As Expected: 25% to 33% * Upset-Prone: 33% to 42% * Very Upset-Prone: 42% and up.
Clear Favorite Upset Rate
Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 15% * As Expected: 15% to 25% * Shaky Favorites: 25% to 35% * Very Shaky: 35% and up.
Brier Score
Expected
0.58
Predictable
00.592
Matchup Imbalance
0.38
Lopsided
00.10.180.280.5
Strangeness
Expected
1.26
Wilder Than Modeled
01.002
Repeatability
0.60
Strong Carryover
00.30.60.851
Upset Rate
Expected
26%
As Expected
0%24%50%
Clear Favorite Upset Rate
Expected
22%
As Expected
0%20%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 0.26 * Well Above Noise: 0.26 and up.
Probability calibration
0.61
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.04
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.076
Well Within Noise
00.1290.3

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% —
Lyngby 99.85% 0.15%
Naestved 99.85% 0.15%
Odense 99.75% 0.25%
Vejle BK 99.72% 0.28%
Aarhus GF 99.66% 0.34%
Ikast 99.27% 0.73%
B 1903 99.08% 0.92%
Silkeborg 98.86% 1.14%
Bronshoj 91.65% 8.35%
Herfolge 83.99% 16.01%
Aalborg 77.62% 22.38%
KB Copenhagen 38.26% 61.74%
Randers 12.44% 87.56%

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
1988-04-03 Herfolge L 1-2 1544 1325 65.33% 22.52% 12.15% -17.8 0
1988-04-03 @ Aarhus GF W 2-1 1325 1544 12.15% 22.52% 65.33% +17.8 2
1988-04-03 KB Copenhagen L 1-2 1453 1384 51.24% 23.69% 25.07% -14.1 0
1988-04-03 @ Bronshoj W 2-1 1384 1453 25.07% 23.69% 51.24% +14.1 2
1988-04-03 Brondby D 0-0 1454 1603 23.15% 23.49% 53.37% +2.2 1
1988-04-03 @ B 1903 D 0-0 1603 1454 53.37% 23.49% 23.15% -2.2 1
1988-04-03 Ikast D 0-0 1502 1533 38.14% 23.89% 37.97% -0.0 1
1988-04-03 @ Naestved D 0-0 1533 1502 37.97% 23.89% 38.14% +0.0 1
1988-04-03 Lyngby D 2-2 1472 1494 39.39% 23.89% 36.72% -0.1 1
1988-04-03 @ Odense D 2-2 1494 1472 36.72% 23.89% 39.39% +0.1 1
1988-04-03 Aalborg D 1-1 1461 1399 50.51% 23.72% 25.77% -1.6 1
1988-04-03 @ Silkeborg D 1-1 1399 1461 25.77% 23.72% 50.51% +1.6 1
1988-04-03 Randers L 1-2 1465 1287 62.13% 22.94% 14.93% -16.9 0
1988-04-03 @ Vejle BK W 2-1 1287 1465 14.93% 22.94% 62.13% +16.9 2
1988-04-10 Naestved D 1-1 1400 1502 28.62% 23.73% 47.65% +1.2 2
1988-04-10 @ Aalborg D 1-1 1502 1400 47.65% 23.73% 28.62% -1.2 2
1988-04-10 Aarhus GF W 1-0 1601 1527 51.93% 23.67% 24.40% +8.2 3
1988-04-10 @ Brondby L 0-1 1527 1601 24.40% 23.67% 51.93% -8.2 0
1988-04-10 Silkeborg L 1-2 1343 1460 26.85% 23.67% 49.49% -8.4 2
1988-04-10 @ Herfolge W 2-1 1460 1343 49.49% 23.67% 26.85% +8.4 3
1988-04-10 Odense W 2-0 1533 1472 50.42% 23.72% 25.86% +16.2 3
1988-04-10 @ Ikast L 0-2 1472 1533 25.86% 23.72% 50.42% -16.2 1
1988-04-10 Vejle BK L 0-3 1398 1448 35.51% 23.87% 40.62% -30.3 2
1988-04-10 @ KB Copenhagen W 3-0 1448 1398 40.62% 23.87% 35.51% +30.3 2
1988-04-10 Bronshoj W 1-0 1494 1439 49.66% 23.75% 26.60% +8.8 3
1988-04-10 @ Lyngby L 0-1 1439 1494 26.60% 23.75% 49.66% -8.8 0
1988-04-10 B 1903 L 0-4 1304 1456 22.94% 23.47% 53.59% -27.9 2
1988-04-10 @ Randers W 4-0 1456 1304 53.59% 23.47% 22.94% +27.9 3
1988-04-17 Randers W 2-1 1518 1276 66.91% 22.26% 10.83% +3.8 2
1988-04-17 @ Aarhus GF L 1-2 1276 1518 10.83% 22.26% 66.91% -3.8 2
1988-04-17 Ikast W 2-1 1430 1550 26.50% 23.65% 49.85% +13.7 2
1988-04-17 @ Bronshoj L 1-2 1550 1430 49.85% 23.65% 26.50% -13.7 3
1988-04-17 KB Copenhagen W 2-0 1484 1368 56.40% 23.43% 20.17% +13.2 5
1988-04-17 @ B 1903 L 0-2 1368 1484 20.17% 23.43% 56.40% -13.2 2
1988-04-17 Aalborg W 1-0 1335 1402 33.12% 23.84% 43.04% +12.9 4
1988-04-17 @ Herfolge L 0-1 1402 1335 43.04% 23.84% 33.12% -12.9 2
1988-04-17 Naestved W 2-1 1455 1501 36.05% 23.87% 40.08% +11.5 3
1988-04-17 @ Odense L 1-2 1501 1455 40.08% 23.87% 36.05% -11.5 2
1988-04-17 Brondby W 1-0 1468 1609 24.05% 23.54% 52.41% +15.2 5
1988-04-17 @ Silkeborg L 0-1 1609 1468 52.41% 23.54% 24.05% -15.2 3
1988-04-17 Lyngby L 0-1 1478 1503 39.05% 23.89% 37.06% -11.9 2
1988-04-17 @ Vejle BK W 1-0 1503 1478 37.06% 23.89% 39.05% +11.9 5
1988-04-24 Odense L 0-2 1389 1467 31.64% 23.81% 44.55% -19.1 2
1988-04-24 @ Aalborg W 2-0 1467 1389 44.55% 23.81% 31.64% +19.1 5
1988-04-24 Herfolge D 1-1 1594 1348 67.20% 22.21% 10.59% -4.0 4
1988-04-24 @ Brondby D 1-1 1348 1594 10.59% 22.21% 67.20% +4.0 5
1988-04-24 Vejle BK L 0-3 1536 1466 51.34% 23.69% 24.97% -41.0 3
1988-04-24 @ Ikast W 3-0 1466 1536 24.97% 23.69% 51.34% +41.0 4
1988-04-24 Aarhus GF L 0-1 1355 1522 21.35% 23.37% 55.28% -7.3 2
1988-04-24 @ KB Copenhagen W 1-0 1522 1355 55.28% 23.37% 21.35% +7.3 4
1988-04-24 B 1903 W 2-0 1515 1497 44.90% 23.85% 31.24% +18.9 7
1988-04-24 @ Lyngby L 0-2 1497 1515 31.24% 23.85% 44.90% -18.9 5
1988-04-24 Bronshoj W 3-0 1490 1444 48.50% 23.78% 27.72% +25.0 4
1988-04-24 @ Naestved L 0-3 1444 1490 27.72% 23.78% 48.50% -25.0 2
1988-04-24 Silkeborg D 3-3 1273 1483 17.36% 23.02% 59.62% +1.8 3
1988-04-24 @ Randers D 3-3 1483 1273 59.62% 23.02% 17.36% -1.8 6
1988-05-01 Lyngby L 0-1 1529 1534 41.89% 23.88% 34.23% -12.6 4
1988-05-01 @ Aarhus GF W 1-0 1534 1529 34.23% 23.88% 41.89% +12.6 9
1988-05-01 Aalborg W 2-0 1590 1370 65.41% 22.51% 12.08% +8.4 6
1988-05-01 @ Brondby L 0-2 1370 1590 12.08% 22.51% 65.41% -8.4 2
1988-05-01 Odense W 3-1 1419 1486 33.09% 23.84% 43.07% +21.0 4
1988-05-01 @ Bronshoj L 1-3 1486 1419 43.07% 23.84% 33.09% -21.0 5
1988-05-01 Randers W 1-0 1352 1274 52.25% 23.65% 24.10% +8.1 7
1988-05-01 @ Herfolge L 0-1 1274 1352 24.10% 23.65% 52.25% -8.1 3
1988-05-01 KB Copenhagen W 3-1 1481 1348 58.22% 23.31% 18.48% +10.6 8
1988-05-01 @ Silkeborg L 1-3 1348 1481 18.48% 23.31% 58.22% -10.6 2
1988-05-01 Naestved D 2-2 1507 1515 41.50% 23.88% 34.62% -0.3 5
1988-05-01 @ Vejle BK D 2-2 1515 1507 34.62% 23.88% 41.50% +0.3 5
1988-05-08 Bronshoj W 3-0 1361 1440 31.60% 23.81% 44.60% +36.3 4
1988-05-08 @ Aalborg L 0-3 1440 1361 44.60% 23.81% 31.60% -36.3 4
1988-05-08 Aarhus GF D 0-0 1495 1517 39.41% 23.89% 36.70% -0.2 4
1988-05-08 @ Ikast D 0-0 1517 1495 36.70% 23.89% 39.41% +0.2 5
1988-05-08 Herfolge L 2-3 1337 1360 39.31% 23.89% 36.80% -10.7 2
1988-05-08 @ KB Copenhagen W 3-2 1360 1337 36.80% 23.89% 39.31% +10.7 9
1988-05-08 Silkeborg W 1-0 1546 1492 49.53% 23.75% 26.72% +8.9 11
1988-05-08 @ Lyngby L 0-1 1492 1546 26.72% 23.75% 49.53% -8.8 8
1988-05-08 B 1903 L 0-1 1515 1478 47.37% 23.81% 28.82% -14.0 5
1988-05-08 @ Naestved W 1-0 1478 1515 28.82% 23.81% 47.37% +14.0 7
1988-05-08 Vejle BK W 1-0 1465 1507 36.54% 23.88% 39.58% +12.0 7
1988-05-08 @ Odense L 0-1 1507 1465 39.58% 23.88% 36.54% -12.0 5
1988-05-08 Brondby L 0-4 1266 1598 9.51% 21.65% 68.83% -12.6 3
1988-05-08 @ Randers W 4-0 1598 1266 68.83% 21.65% 9.51% +12.6 8
1988-05-09 Ikast L 0-2 1492 1495 42.12% 23.88% 33.99% -23.8 7
1988-05-09 @ B 1903 W 2-0 1495 1492 33.99% 23.88% 42.12% +23.9 6
1988-05-15 Naestved L 2-3 1517 1501 44.65% 23.86% 31.49% -11.9 5
1988-05-15 @ Aarhus GF W 3-2 1501 1517 31.49% 23.86% 44.65% +11.9 7
1988-05-15 KB Copenhagen W 3-1 1611 1326 69.55% 21.73% 8.73% +5.3 10
1988-05-15 @ Brondby L 1-3 1326 1611 8.73% 21.73% 69.55% -5.3 2
1988-05-15 Odense D 2-2 1468 1477 41.26% 23.89% 34.85% -0.3 8
1988-05-15 @ B 1903 D 2-2 1477 1468 34.85% 23.89% 41.26% +0.3 8
1988-05-15 Lyngby L 0-1 1370 1555 19.65% 23.24% 57.11% -6.8 9
1988-05-15 @ Herfolge W 1-0 1555 1370 57.11% 23.24% 19.65% +6.8 13
1988-05-15 Aalborg W 3-0 1254 1398 23.75% 23.52% 52.73% +42.0 5
1988-05-15 @ Randers L 0-3 1398 1254 52.73% 23.52% 23.75% -42.0 4
1988-05-15 Ikast W 1-0 1483 1518 37.53% 23.88% 38.59% +11.8 10
1988-05-15 @ Silkeborg L 0-1 1518 1483 38.59% 23.88% 37.53% -11.8 6
1988-05-15 Bronshoj W 4-2 1495 1404 53.86% 23.58% 22.57% +11.3 7
1988-05-15 @ Vejle BK L 2-4 1404 1495 22.57% 23.58% 53.86% -11.2 4
1988-05-23 Vejle BK L 2-3 1356 1506 23.03% 23.48% 53.49% -7.0 4
1988-05-23 @ Aalborg W 3-2 1506 1356 53.49% 23.48% 23.03% +7.0 9
1988-05-23 B 1903 D 2-2 1392 1468 31.98% 23.82% 44.20% +0.6 5
1988-05-23 @ Bronshoj D 2-2 1468 1392 44.20% 23.82% 31.98% -0.6 9
1988-05-23 Herfolge D 1-1 1507 1364 59.09% 23.24% 17.68% -2.8 7
1988-05-23 @ Ikast D 1-1 1364 1507 17.68% 23.24% 59.09% +2.8 10
1988-05-23 Randers W 3-1 1321 1296 45.88% 23.84% 30.28% +16.0 4
1988-05-23 @ KB Copenhagen L 1-3 1296 1321 30.28% 23.84% 45.88% -16.0 5
1988-05-23 Brondby L 0-1 1562 1616 34.86% 23.86% 41.28% -10.9 13
1988-05-23 @ Lyngby W 1-0 1616 1562 41.28% 23.86% 34.86% +10.9 12
1988-05-23 Silkeborg W 1-0 1513 1495 44.89% 23.85% 31.26% +10.0 9
1988-05-23 @ Naestved L 0-1 1495 1513 31.26% 23.85% 44.89% -10.0 10
1988-05-23 Aarhus GF W 4-0 1477 1505 38.58% 23.89% 37.53% +41.3 10
1988-05-23 @ Odense L 0-4 1505 1477 37.53% 23.89% 38.58% -41.3 5
1988-05-26 Bronshoj W 3-1 1464 1393 51.52% 23.68% 24.80% +13.6 7
1988-05-26 @ Aarhus GF L 1-3 1393 1464 24.80% 23.68% 51.52% -13.6 5
1988-05-26 Ikast W 2-1 1627 1504 57.18% 23.38% 19.44% +6.4 14
1988-05-26 @ Brondby L 1-2 1504 1627 19.44% 23.38% 57.18% -6.4 7
1988-05-26 Vejle BK L 0-2 1467 1513 35.99% 23.87% 40.14% -21.1 9
1988-05-26 @ B 1903 W 2-0 1513 1467 40.14% 23.87% 35.99% +21.1 11
1988-05-26 Naestved W 2-0 1366 1523 22.42% 23.44% 54.13% +29.6 12
1988-05-26 @ Herfolge L 0-2 1523 1366 54.13% 23.44% 22.42% -29.6 9
1988-05-26 Aalborg D 2-2 1337 1349 40.87% 23.89% 35.25% -0.2 5
1988-05-26 @ KB Copenhagen D 2-2 1349 1337 35.25% 23.89% 40.87% +0.2 5
1988-05-26 Lyngby L 0-2 1280 1551 12.89% 22.41% 64.71% -8.8 5
1988-05-26 @ Randers W 2-0 1551 1280 64.71% 22.41% 12.89% +8.8 15
1988-05-26 Odense W 2-1 1485 1519 37.76% 23.88% 38.36% +11.1 12
1988-05-26 @ Silkeborg L 1-2 1519 1485 38.36% 23.88% 37.76% -11.1 10
1988-05-29 B 1903 D 1-1 1349 1446 29.19% 23.75% 47.06% +1.1 6
1988-05-29 @ Aalborg D 1-1 1446 1349 47.06% 23.75% 29.19% -1.1 10
1988-05-29 Silkeborg W 4-1 1379 1496 26.81% 23.66% 49.52% +33.5 7
1988-05-29 @ Bronshoj L 1-4 1496 1379 49.52% 23.66% 26.81% -33.5 12
1988-05-29 Randers D 0-0 1497 1271 65.87% 22.44% 11.70% -4.2 8
1988-05-29 @ Ikast D 0-0 1271 1497 11.70% 22.44% 65.87% +4.3 6
1988-05-29 KB Copenhagen W 2-1 1560 1337 65.63% 22.48% 11.90% +4.1 17
1988-05-29 @ Lyngby L 1-2 1337 1560 11.90% 22.48% 65.63% -4.1 5
1988-05-29 Brondby D 0-0 1493 1634 24.15% 23.54% 52.31% +2.0 10
1988-05-29 @ Naestved D 0-0 1634 1493 52.31% 23.54% 24.15% -2.0 15
1988-05-29 Herfolge D 1-1 1508 1396 55.99% 23.46% 20.55% -2.3 11
1988-05-29 @ Odense D 1-1 1396 1508 20.55% 23.46% 55.99% +2.3 13
1988-05-29 Aarhus GF D 0-0 1534 1477 49.87% 23.74% 26.39% -1.7 12
1988-05-29 @ Vejle BK D 0-0 1477 1534 26.39% 23.74% 49.87% +1.7 8
1988-07-17 Bronshoj W 1-0 1398 1413 40.50% 23.89% 35.62% +11.1 15
1988-07-17 @ Herfolge L 0-1 1413 1398 35.62% 23.89% 40.50% -11.1 7
1988-07-17 Aalborg L 1-2 1564 1350 64.96% 22.58% 12.46% -17.7 17
1988-07-17 @ Lyngby W 2-1 1350 1564 12.46% 22.58% 64.96% +17.7 8
1988-07-17 Naestved L 2-5 1275 1495 16.57% 22.94% 60.49% -11.8 6
1988-07-17 @ Randers W 5-2 1495 1275 60.49% 22.94% 16.57% +11.8 12
1988-07-19 Vejle BK D 1-1 1463 1533 32.70% 23.83% 43.47% +0.7 13
1988-07-19 @ Silkeborg D 1-1 1533 1463 43.47% 23.83% 32.70% -0.7 13
1988-07-20 Odense W 2-1 1632 1505 57.48% 23.36% 19.16% +6.3 17
1988-07-20 @ Brondby L 1-2 1505 1632 19.16% 23.36% 57.48% -6.3 11
1988-07-20 Ikast L 1-2 1333 1493 22.00% 23.41% 54.59% -7.1 5
1988-07-20 @ KB Copenhagen W 2-1 1493 1333 54.59% 23.41% 22.00% +7.1 10
1988-07-24 Aarhus GF D 0-0 1368 1479 27.47% 23.69% 48.84% +1.5 9
1988-07-24 @ Aalborg D 0-0 1479 1368 48.84% 23.69% 27.47% -1.5 9
1988-07-24 Brondby L 1-5 1402 1638 15.33% 22.78% 61.88% -16.4 7
1988-07-24 @ Bronshoj W 5-1 1638 1402 61.88% 22.78% 15.33% +16.4 19
1988-07-24 Silkeborg L 1-2 1445 1463 39.95% 23.89% 36.17% -11.4 10
1988-07-24 @ B 1903 W 2-1 1463 1445 36.17% 23.89% 39.95% +11.4 15
1988-07-24 Lyngby D 0-0 1500 1546 35.99% 23.87% 40.13% +0.3 11
1988-07-24 @ Ikast D 0-0 1546 1500 40.13% 23.87% 35.99% -0.3 18
1988-07-24 KB Copenhagen W 1-0 1507 1325 62.46% 22.90% 14.64% +5.3 14
1988-07-24 @ Naestved L 0-1 1325 1507 14.64% 22.90% 62.46% -5.3 5
1988-07-24 Randers W 3-0 1499 1263 66.48% 22.34% 11.18% +11.3 13
1988-07-24 @ Odense L 0-3 1263 1499 11.18% 22.34% 66.48% -11.3 6
1988-07-24 Herfolge D 1-1 1532 1409 57.11% 23.39% 19.50% -2.5 14
1988-07-24 @ Vejle BK D 1-1 1409 1532 19.50% 23.39% 57.11% +2.5 16
1988-07-27 B 1903 D 2-2 1478 1434 48.26% 23.78% 27.96% -1.0 10
1988-07-27 @ Aarhus GF D 2-2 1434 1478 27.96% 23.78% 48.26% +1.0 11
1988-07-31 Ikast L 0-3 1369 1501 25.15% 23.59% 51.26% -23.0 9
1988-07-31 @ Aalborg W 3-0 1501 1369 51.26% 23.59% 25.15% +23.0 13
1988-07-31 Vejle BK D 0-0 1654 1530 57.31% 23.37% 19.31% -2.8 20
1988-07-31 @ Brondby D 0-0 1530 1654 19.31% 23.37% 57.31% +2.8 15
1988-07-31 B 1903 L 0-1 1412 1435 39.33% 23.89% 36.78% -12.0 16
1988-07-31 @ Herfolge W 1-0 1435 1412 36.78% 23.89% 39.33% +12.0 13
1988-07-31 Odense L 1-5 1320 1510 19.17% 23.20% 57.64% -20.0 5
1988-07-31 @ KB Copenhagen W 5-1 1510 1320 57.64% 23.20% 19.17% +20.0 15
1988-07-31 Naestved D 1-1 1546 1512 46.96% 23.82% 29.23% -1.1 19
1988-07-31 @ Lyngby D 1-1 1512 1546 29.23% 23.82% 46.96% +1.1 15
1988-07-31 Bronshoj D 1-1 1252 1385 24.93% 23.58% 51.49% +1.7 7
1988-07-31 @ Randers D 1-1 1385 1252 51.49% 23.58% 24.93% -1.7 8
1988-07-31 Aarhus GF L 0-1 1475 1477 42.23% 23.88% 33.89% -12.7 15
1988-07-31 @ Silkeborg W 1-0 1477 1475 33.89% 23.88% 42.23% +12.7 12
1988-08-07 Odense L 1-2 1489 1530 36.73% 23.88% 39.39% -10.7 12
1988-08-07 @ Aarhus GF W 2-1 1530 1489 39.39% 23.88% 36.73% +10.7 17
1988-08-07 Lyngby W 6-2 1651 1545 55.45% 23.49% 21.06% +18.4 22
1988-08-07 @ Brondby L 2-6 1545 1651 21.06% 23.49% 55.45% -18.4 19
1988-08-07 Bronshoj W 2-0 1447 1383 50.59% 23.72% 25.69% +16.2 15
1988-08-07 @ B 1903 L 0-2 1383 1447 25.69% 23.72% 50.59% -16.2 8
1988-08-07 Ikast W 3-0 1400 1524 26.02% 23.63% 50.34% +40.3 18
1988-08-07 @ Herfolge L 0-3 1524 1400 50.34% 23.63% 26.02% -40.3 13
1988-08-07 KB Copenhagen L 1-3 1254 1300 35.93% 23.87% 40.20% -18.2 7
1988-08-07 @ Randers W 3-1 1300 1254 40.20% 23.87% 35.93% +18.2 7
1988-08-07 Naestved L 0-3 1462 1514 35.24% 23.87% 40.89% -30.1 15
1988-08-07 @ Silkeborg W 3-0 1514 1462 40.89% 23.87% 35.24% +30.1 17
1988-08-07 Aalborg L 0-1 1532 1346 62.83% 22.86% 14.31% -18.2 15
1988-08-07 @ Vejle BK W 1-0 1346 1532 14.31% 22.86% 62.83% +18.2 11
1988-08-14 Randers W 3-1 1364 1235 57.74% 23.34% 18.92% +10.8 13
1988-08-14 @ Aalborg L 1-3 1235 1364 18.92% 23.34% 57.74% -10.8 7
1988-08-14 Vejle BK L 1-2 1367 1514 23.43% 23.50% 53.06% -7.5 8
1988-08-14 @ Bronshoj W 2-1 1514 1367 53.06% 23.50% 23.43% +7.5 17
1988-08-14 Silkeborg L 1-4 1483 1432 49.19% 23.76% 27.05% -33.3 13
1988-08-14 @ Ikast W 4-1 1432 1483 27.05% 23.76% 49.19% +33.3 17
1988-08-14 Brondby L 0-3 1318 1670 8.64% 21.39% 69.97% -8.8 7
1988-08-14 @ KB Copenhagen W 3-0 1670 1318 69.97% 21.39% 8.64% +8.8 24
1988-08-14 Herfolge D 1-1 1527 1440 53.28% 23.61% 23.12% -2.0 20
1988-08-14 @ Lyngby D 1-1 1440 1527 23.12% 23.61% 53.28% +2.0 19
1988-08-14 Aarhus GF D 2-2 1544 1479 50.83% 23.71% 25.46% -1.2 18
1988-08-14 @ Naestved D 2-2 1479 1544 25.46% 23.71% 50.83% +1.2 13
1988-08-14 B 1903 W 1-0 1541 1463 52.35% 23.65% 24.00% +8.1 19
1988-08-14 @ Odense L 0-1 1463 1541 24.00% 23.65% 52.35% -8.1 15
1988-08-21 Ikast W 2-0 1480 1450 46.45% 23.83% 29.73% +18.2 15
1988-08-21 @ Aarhus GF L 0-2 1450 1480 29.73% 23.83% 46.45% -18.2 13
1988-08-21 Randers W 4-2 1679 1225 77.22% 19.09% 3.69% +2.0 26
1988-08-21 @ Brondby L 2-4 1225 1679 3.69% 19.09% 77.22% -2.0 7
1988-08-21 Aalborg W 5-2 1360 1375 40.35% 23.89% 35.76% +22.3 10
1988-08-21 @ Bronshoj L 2-5 1375 1360 35.76% 23.89% 40.35% -22.3 13
1988-08-21 Naestved L 0-2 1455 1542 30.38% 23.78% 45.84% -18.5 15
1988-08-21 @ B 1903 W 2-0 1542 1455 45.84% 23.78% 30.38% +18.5 20
1988-08-21 KB Copenhagen W 2-0 1442 1310 58.08% 23.32% 18.60% +12.3 21
1988-08-21 @ Herfolge L 0-2 1310 1442 18.60% 23.32% 58.08% -12.3 7
1988-08-21 Lyngby L 0-1 1465 1525 34.15% 23.85% 42.00% -10.7 17
1988-08-21 @ Silkeborg W 1-0 1525 1465 42.00% 23.85% 34.15% +10.8 22
1988-08-21 Odense D 2-2 1522 1549 38.67% 23.89% 37.44% -0.0 18
1988-08-21 @ Vejle BK D 2-2 1549 1522 37.44% 23.89% 38.67% +0.0 20
1988-08-28 Brondby L 0-3 1353 1680 9.74% 21.71% 68.55% -9.8 13
1988-08-28 @ Aalborg W 3-0 1680 1353 68.55% 21.71% 9.74% +9.8 28
1988-08-28 B 1903 L 0-1 1432 1436 41.91% 23.88% 34.21% -12.6 13
1988-08-28 @ Ikast W 1-0 1436 1432 34.21% 23.88% 41.91% +12.6 17
1988-08-28 Silkeborg L 1-3 1297 1454 22.36% 23.44% 54.20% -12.5 7
1988-08-28 @ KB Copenhagen W 3-1 1454 1297 54.20% 23.44% 22.36% +12.5 19
1988-08-28 Aarhus GF W 2-0 1535 1498 47.43% 23.80% 28.76% +17.7 24
1988-08-28 @ Lyngby L 0-2 1498 1535 28.76% 23.80% 47.43% -17.7 15
1988-08-28 Vejle BK D 0-0 1561 1522 47.67% 23.80% 28.53% -1.4 21
1988-08-28 @ Naestved D 0-0 1522 1561 28.53% 23.80% 47.67% +1.3 19
1988-08-28 Bronshoj W 2-1 1549 1382 61.22% 23.04% 15.74% +5.3 22
1988-08-28 @ Odense L 1-2 1382 1549 15.74% 23.04% 61.22% -5.3 10
1988-08-28 Herfolge L 1-2 1223 1455 15.66% 22.82% 61.52% -5.3 7
1988-08-28 @ Randers W 2-1 1455 1223 61.52% 22.82% 15.66% +5.3 23
1988-09-04 KB Copenhagen W 3-0 1480 1285 63.55% 22.77% 13.68% +13.6 17
1988-09-04 @ Aarhus GF L 0-3 1285 1480 13.68% 22.77% 63.55% -13.6 7
1988-09-04 Naestved L 1-2 1377 1560 19.84% 23.26% 56.91% -6.5 10
1988-09-04 @ Bronshoj W 2-1 1560 1377 56.91% 23.26% 19.84% +6.5 23
1988-09-04 Lyngby W 5-0 1449 1553 28.32% 23.72% 47.96% +62.1 19
1988-09-04 @ B 1903 L 0-5 1553 1449 47.96% 23.72% 28.32% -62.1 24
1988-09-04 Brondby L 1-2 1460 1690 15.77% 22.84% 61.39% -5.3 23
1988-09-04 @ Herfolge W 2-1 1690 1460 61.39% 22.84% 15.77% +5.3 30
1988-09-04 Aalborg D 0-0 1554 1343 64.76% 22.61% 12.64% -4.1 23
1988-09-04 @ Odense D 0-0 1343 1554 12.64% 22.61% 64.76% +4.1 14
1988-09-04 Randers W 4-3 1467 1217 67.41% 22.17% 10.42% +3.4 21
1988-09-04 @ Silkeborg L 3-4 1217 1467 10.42% 22.17% 67.41% -3.4 7
1988-09-11 Herfolge W 4-2 1347 1455 27.95% 23.71% 48.34% +20.7 16
1988-09-11 @ Aalborg L 2-4 1455 1347 48.34% 23.71% 27.95% -20.7 23
1988-09-11 Silkeborg W 1-0 1696 1470 65.77% 22.45% 11.77% +4.3 32
1988-09-11 @ Brondby L 0-1 1470 1696 11.77% 22.45% 65.77% -4.3 21
1988-09-11 Bronshoj L 0-3 1419 1370 48.89% 23.77% 27.35% -39.3 13
1988-09-11 @ Ikast W 3-0 1370 1419 27.35% 23.77% 48.89% +39.3 12
1988-09-11 B 1903 L 1-3 1271 1511 15.08% 22.75% 62.17% -8.8 7
1988-09-11 @ KB Copenhagen W 3-1 1511 1271 62.17% 22.75% 15.08% +8.9 21
1988-09-11 Vejle BK W 3-0 1491 1523 37.97% 23.89% 38.14% +32.0 26
1988-09-11 @ Lyngby L 0-3 1523 1491 38.14% 23.89% 37.97% -32.0 19
1988-09-11 Odense W 2-0 1566 1550 44.62% 23.86% 31.52% +19.0 25
1988-09-11 @ Naestved L 0-2 1550 1566 31.52% 23.86% 44.62% -19.0 23
1988-09-11 Aarhus GF L 0-2 1214 1494 12.36% 22.31% 65.33% -8.5 7
1988-09-11 @ Randers W 2-0 1494 1214 65.33% 22.31% 12.36% +8.5 19
1988-09-25 Ikast W 3-1 1491 1380 55.93% 23.46% 20.61% +11.7 21
1988-09-25 @ Vejle BK L 1-3 1380 1491 20.61% 23.46% 55.93% -11.7 13
1988-10-02 Brondby W 3-2 1502 1700 18.49% 23.14% 58.38% +15.1 21
1988-10-02 @ Aarhus GF L 2-3 1700 1502 58.38% 23.14% 18.49% -15.1 32
1988-10-02 Lyngby W 3-0 1410 1523 27.22% 23.68% 49.10% +39.4 14
1988-10-02 @ Bronshoj L 0-3 1523 1410 49.10% 23.68% 27.22% -39.4 26
1988-10-02 Randers W 4-3 1520 1205 71.17% 21.32% 7.51% +2.5 23
1988-10-02 @ B 1903 L 3-4 1205 1520 7.51% 21.32% 71.17% -2.5 7
1988-10-02 Aalborg W 1-0 1585 1368 65.19% 22.54% 12.26% +4.5 27
1988-10-02 @ Naestved L 0-1 1368 1585 12.26% 22.54% 65.19% -4.5 16
1988-10-02 Ikast L 0-4 1531 1368 60.87% 23.07% 16.05% -63.0 23
1988-10-02 @ Odense W 4-0 1368 1531 16.05% 23.07% 60.87% +63.0 15
1988-10-02 Herfolge W 5-0 1466 1434 46.76% 23.82% 29.42% +42.2 23
1988-10-02 @ Silkeborg L 0-5 1434 1466 29.42% 23.82% 46.76% -42.2 23
1988-10-02 KB Copenhagen W 2-0 1503 1262 66.79% 22.28% 10.92% +7.6 23
1988-10-02 @ Vejle BK L 0-2 1262 1503 10.92% 22.28% 66.79% -7.6 7
1988-10-09 Silkeborg W 2-1 1363 1508 23.67% 23.52% 52.82% +14.5 18
1988-10-09 @ Aalborg L 1-2 1508 1363 52.82% 23.52% 23.67% -14.5 23
1988-10-09 B 1903 D 1-1 1685 1522 60.86% 23.08% 16.06% -3.1 33
1988-10-09 @ Brondby D 1-1 1522 1685 16.06% 23.08% 60.86% +3.1 24
1988-10-09 Aarhus GF L 0-2 1392 1517 25.77% 23.62% 50.61% -16.2 23
1988-10-09 @ Herfolge W 2-0 1517 1392 50.61% 23.62% 25.77% +16.2 23
1988-10-09 Naestved W 4-0 1431 1590 22.24% 23.43% 54.32% +56.4 17
1988-10-09 @ Ikast L 0-4 1590 1431 54.32% 23.43% 22.24% -56.4 27
1988-10-09 Bronshoj L 1-2 1255 1449 18.79% 23.17% 58.04% -6.2 7
1988-10-09 @ KB Copenhagen W 2-1 1449 1255 58.04% 23.17% 18.79% +6.2 16
1988-10-09 Odense W 2-1 1484 1468 44.56% 23.86% 31.58% +9.5 28
1988-10-09 @ Lyngby L 1-2 1468 1484 31.58% 23.86% 44.56% -9.5 23
1988-10-09 Vejle BK L 0-3 1203 1510 10.78% 21.98% 67.24% -10.9 7
1988-10-09 @ Randers W 3-0 1510 1203 67.24% 21.98% 10.78% +10.9 25
1988-10-16 Silkeborg L 0-1 1534 1494 47.76% 23.80% 28.44% -14.1 23
1988-10-16 @ Aarhus GF W 1-0 1494 1534 28.44% 23.80% 47.76% +14.0 25
1988-10-16 Randers D 0-0 1455 1192 68.25% 22.01% 9.74% -4.7 17
1988-10-16 @ Bronshoj D 0-0 1192 1455 9.74% 22.01% 68.25% +4.6 8
1988-10-16 Herfolge W 2-0 1525 1375 59.70% 23.18% 17.12% +11.5 26
1988-10-16 @ B 1903 L 0-2 1375 1525 17.12% 23.18% 59.70% -11.5 23
1988-10-16 Aalborg L 4-5 1488 1378 55.81% 23.47% 20.72% -13.9 17
1988-10-16 @ Ikast W 5-4 1378 1488 20.72% 23.47% 55.81% +13.9 20
1988-10-16 Lyngby W 2-1 1533 1493 47.78% 23.80% 28.43% +8.8 29
1988-10-16 @ Naestved L 1-2 1493 1533 28.43% 23.80% 47.78% -8.8 28
1988-10-16 KB Copenhagen W 4-1 1459 1249 64.67% 22.62% 12.71% +10.7 25
1988-10-16 @ Odense L 1-4 1249 1459 12.71% 22.62% 64.67% -10.8 7
1988-10-16 Brondby D 0-0 1521 1682 21.99% 23.41% 54.59% +2.4 26
1988-10-16 @ Vejle BK D 0-0 1682 1521 54.59% 23.41% 21.99% -2.4 34
1988-10-22 Aalborg W 5-1 1520 1392 57.63% 23.35% 19.02% +19.9 25
1988-10-22 @ Aarhus GF L 1-5 1392 1520 19.02% 23.35% 57.63% -19.9 20
1988-10-23 Bronshoj W 4-1 1679 1450 66.03% 22.41% 11.56% +9.8 36
1988-10-23 @ Brondby L 1-4 1450 1679 11.56% 22.41% 66.03% -9.8 17
1988-10-23 Vejle BK W 2-1 1364 1524 22.11% 23.42% 54.47% +14.9 25
1988-10-23 @ Herfolge L 1-2 1524 1364 54.47% 23.42% 22.11% -14.9 26
1988-10-23 Naestved D 1-1 1238 1542 10.95% 22.02% 67.03% +4.0 8
1988-10-23 @ KB Copenhagen D 1-1 1542 1238 67.03% 22.02% 10.95% -4.0 30
1988-10-23 Ikast D 0-0 1484 1474 43.92% 23.86% 32.22% -0.8 29
1988-10-23 @ Lyngby D 0-0 1474 1484 32.22% 23.86% 43.92% +0.8 18
1988-10-23 Odense L 1-6 1197 1469 12.81% 22.39% 64.79% -17.0 8
1988-10-23 @ Randers W 6-1 1469 1197 64.79% 22.39% 12.81% +17.0 27
1988-10-23 B 1903 L 1-2 1508 1537 38.42% 23.89% 37.69% -11.1 25
1988-10-23 @ Silkeborg W 2-1 1537 1508 37.69% 23.89% 38.42% +11.1 28
1988-10-30 Lyngby L 0-1 1372 1484 27.44% 23.69% 48.87% -9.0 20
1988-10-30 @ Aalborg W 1-0 1484 1372 48.87% 23.69% 27.44% +9.0 31
1988-10-30 Herfolge D 0-0 1441 1379 50.44% 23.72% 25.84% -1.8 18
1988-10-30 @ Bronshoj D 0-0 1379 1441 25.84% 23.72% 50.44% +1.8 26
1988-10-30 Aarhus GF D 1-1 1548 1539 43.61% 23.87% 32.52% -0.7 29
1988-10-30 @ B 1903 D 1-1 1539 1548 32.52% 23.87% 43.61% +0.7 26
1988-10-30 KB Copenhagen W 5-3 1475 1242 66.29% 22.37% 11.34% +5.8 20
1988-10-30 @ Ikast L 3-5 1242 1475 11.34% 22.37% 66.29% -5.8 8
1988-10-30 Randers W 3-1 1538 1180 73.33% 20.67% 6.00% +3.7 32
1988-10-30 @ Naestved L 1-3 1180 1538 6.00% 20.67% 73.33% -3.7 8
1988-10-30 Brondby L 1-3 1486 1689 18.03% 23.09% 58.88% -10.4 27
1988-10-30 @ Odense W 3-1 1689 1486 58.88% 23.09% 18.03% +10.4 38
1988-10-30 Silkeborg D 1-1 1509 1497 44.12% 23.86% 32.02% -0.8 27
1988-10-30 @ Vejle BK D 1-1 1497 1509 32.02% 23.86% 44.12% +0.8 26
1988-11-06 Vejle BK L 0-1 1540 1508 46.78% 23.82% 29.40% -13.8 26
1988-11-06 @ Aarhus GF W 1-0 1508 1540 29.40% 23.82% 46.78% +13.8 29
1988-11-06 Naestved L 3-5 1700 1542 60.44% 23.12% 16.45% -24.1 38
1988-11-06 @ Brondby W 5-3 1542 1700 16.45% 23.12% 60.44% +24.1 34
1988-11-06 Aalborg W 6-1 1547 1363 62.67% 22.88% 14.45% +19.1 31
1988-11-06 @ B 1903 L 1-6 1363 1547 14.45% 22.88% 62.67% -19.1 20
1988-11-06 Odense W 2-1 1381 1476 29.42% 23.75% 46.83% +13.0 28
1988-11-06 @ Herfolge L 1-2 1476 1381 46.83% 23.75% 29.42% -13.0 27
1988-11-06 Lyngby L 1-6 1236 1493 13.88% 22.57% 63.55% -18.3 8
1988-11-06 @ KB Copenhagen W 6-1 1493 1236 63.55% 22.57% 13.88% +18.3 33
1988-11-06 Ikast L 1-4 1176 1480 10.94% 22.02% 67.04% -9.3 8
1988-11-06 @ Randers W 4-1 1480 1176 67.04% 22.02% 10.94% +9.3 22
1988-11-06 Bronshoj L 1-2 1497 1439 50.04% 23.73% 26.22% -13.8 26
1988-11-06 @ Silkeborg W 2-1 1439 1497 26.22% 23.73% 50.04% +13.8 20
1988-11-13 KB Copenhagen W 2-1 1344 1218 57.45% 23.36% 19.18% +6.3 22
1988-11-13 @ Aalborg L 1-2 1218 1344 19.18% 23.36% 57.45% -6.3 8
1988-11-13 Aarhus GF L 2-4 1453 1526 32.22% 23.82% 43.96% -15.0 20
1988-11-13 @ Bronshoj W 4-2 1526 1453 43.96% 23.82% 32.22% +15.0 28
1988-11-13 Brondby L 0-4 1490 1676 19.55% 23.23% 57.22% -24.4 22
1988-11-13 @ Ikast W 4-0 1676 1490 57.22% 23.23% 19.55% +24.4 40
1988-11-13 Randers W 7-1 1511 1167 72.66% 20.88% 6.45% +10.4 35
1988-11-13 @ Lyngby L 1-7 1167 1511 6.45% 20.88% 72.66% -10.4 8
1988-11-13 Herfolge D 0-0 1566 1394 61.67% 22.99% 15.34% -3.6 35
1988-11-13 @ Naestved D 0-0 1394 1566 15.34% 22.99% 61.67% +3.6 29
1988-11-13 Silkeborg W 2-1 1463 1484 39.64% 23.89% 36.47% +10.7 29
1988-11-13 @ Odense L 1-2 1484 1463 36.47% 23.89% 39.64% -10.7 26
1988-11-13 B 1903 D 1-1 1522 1566 36.21% 23.88% 39.91% +0.2 30
1988-11-13 @ Vejle BK D 1-1 1566 1522 39.91% 23.88% 36.21% -0.2 32

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 1988-04-03 12.15% Herfolge 1325 2 @ Aarhus GF 1544 1
2 1988-07-17 12.46% Aalborg 1350 2 @ Lyngby 1564 1
3 1988-08-07 14.31% Aalborg 1346 1 @ Vejle BK 1532 0
4 1988-04-03 14.93% Randers 1287 2 @ Vejle BK 1465 1
5 1988-10-02 16.05% Ikast 1368 4 @ Odense 1531 0
6 1988-11-06 16.45% Naestved 1542 5 @ Brondby 1700 3
7 1988-10-02 18.49% @ Aarhus GF 1502 3 Brondby 1700 2
8 1988-10-16 20.72% Aalborg 1378 5 @ Ikast 1488 4
9 1988-10-23 22.11% @ Herfolge 1364 2 Vejle BK 1524 1
10 1988-10-09 22.24% @ Ikast 1431 4 Naestved 1590 0
11 1988-05-26 22.42% @ Herfolge 1366 2 Naestved 1523 0
12 1988-10-09 23.67% @ Aalborg 1363 2 Silkeborg 1508 1
13 1988-05-15 23.75% @ Randers 1254 3 Aalborg 1398 0
14 1988-04-17 24.05% @ Silkeborg 1468 1 Brondby 1609 0
15 1988-04-24 24.97% Vejle BK 1466 3 @ Ikast 1536 0
16 1988-04-03 25.07% KB Copenhagen 1384 2 @ Bronshoj 1453 1
17 1988-08-07 26.02% @ Herfolge 1400 3 Ikast 1524 0
18 1988-11-06 26.22% Bronshoj 1439 2 @ Silkeborg 1497 1
19 1988-04-17 26.50% @ Bronshoj 1430 2 Ikast 1550 1
20 1988-05-29 26.81% @ Bronshoj 1379 4 Silkeborg 1496 1
21 1988-08-14 27.05% Silkeborg 1432 4 @ Ikast 1483 1
22 1988-10-02 27.22% @ Bronshoj 1410 3 Lyngby 1523 0
23 1988-09-11 27.35% Bronshoj 1370 3 @ Ikast 1419 0
24 1988-09-11 27.95% @ Aalborg 1347 4 Herfolge 1455 2
25 1988-09-04 28.32% @ B 1903 1449 5 Lyngby 1553 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 1988-10-02 62.99 Ikast 4 1368 16.05% @ Odense 0 1531 60.87% 23.07%
2 1988-09-04 62.13 @ B 1903 5 1449 28.32% Lyngby 0 1553 47.96% 23.72%
3 1988-10-09 56.38 @ Ikast 4 1431 22.24% Naestved 0 1590 54.32% 23.43%
4 1988-10-02 42.16 @ Silkeborg 5 1466 46.76% Herfolge 0 1434 29.42% 23.82%
5 1988-05-15 41.99 @ Randers 3 1254 23.75% Aalborg 0 1398 52.73% 23.52%
6 1988-05-23 41.34 @ Odense 4 1477 38.58% Aarhus GF 0 1505 37.53% 23.89%
7 1988-04-24 41.02 Vejle BK 3 1466 24.97% @ Ikast 0 1536 51.34% 23.69%
8 1988-08-07 40.26 @ Herfolge 3 1400 26.02% Ikast 0 1524 50.34% 23.63%
9 1988-10-02 39.38 @ Bronshoj 3 1410 27.22% Lyngby 0 1523 49.10% 23.68%
10 1988-09-11 39.27 Bronshoj 3 1370 27.35% @ Ikast 0 1419 48.89% 23.77%
11 1988-05-08 36.28 @ Aalborg 3 1361 31.60% Bronshoj 0 1440 44.60% 23.81%
12 1988-05-29 33.47 @ Bronshoj 4 1379 26.81% Silkeborg 1 1496 49.52% 23.66%
13 1988-08-14 33.29 Silkeborg 4 1432 27.05% @ Ikast 1 1483 49.19% 23.76%
14 1988-09-11 32.04 @ Lyngby 3 1491 37.97% Vejle BK 0 1523 38.14% 23.89%
15 1988-04-10 30.33 Vejle BK 3 1448 40.62% @ KB Copenhagen 0 1398 35.51% 23.87%
16 1988-08-07 30.15 Naestved 3 1514 40.89% @ Silkeborg 0 1462 35.24% 23.87%
17 1988-05-26 29.62 @ Herfolge 2 1366 22.42% Naestved 0 1523 54.13% 23.44%
18 1988-04-10 27.89 B 1903 4 1456 53.59% @ Randers 0 1304 22.94% 23.47%
19 1988-04-24 24.97 @ Naestved 3 1490 48.50% Bronshoj 0 1444 27.72% 23.78%
20 1988-11-13 24.36 Brondby 4 1676 57.22% @ Ikast 0 1490 19.55% 23.23%
21 1988-11-06 24.13 Naestved 5 1542 16.45% @ Brondby 3 1700 60.44% 23.12%
22 1988-05-09 23.85 Ikast 2 1495 33.99% @ B 1903 0 1492 42.12% 23.88%
23 1988-07-31 23.04 Ikast 3 1501 51.26% @ Aalborg 0 1369 25.15% 23.59%
24 1988-08-21 22.27 @ Bronshoj 5 1360 40.35% Aalborg 2 1375 35.76% 23.89%
25 1988-05-26 21.10 Vejle BK 2 1513 40.14% @ B 1903 0 1467 35.99% 23.87%