Home / Leagues / Denmark / Superliga / 1991
‹ ›

1991 Superliga Season

90 games

Final

Champion

Brondby

26 points · 5th Title

Last Title: 1990

Relegated

Ikast

10 pts

Biggest Overachiever

Brondby

5.63 points above expected

26 points · 20.37 expected points

Biggest Disappointment

Ikast

6.09 points below expected

10 points · 16.09 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 18 10 6 2 26 26 15 +11 20.37 +5.63
2 Lyngby 18 10 4 4 24 35 18 +17 20.97 +3.03
3 Aarhus GF 18 6 8 4 20 29 26 +3 17.69 +2.31
4 Frem 18 6 7 5 19 25 24 +1 18.61 +0.39
5 Odense 18 3 11 4 17 21 20 +1 17.92 -0.92
6 Aalborg 18 6 5 7 17 29 33 -4 16.88 +0.12
7 B 1903 18 6 4 8 16 19 18 +1 17.29 -1.29
8 Vejle BK 18 5 6 7 16 20 22 -2 16.95 -0.95
9 Silkeborg 18 4 7 7 15 23 33 -10 17.25 -2.25
10 Ikast Relegated 18 3 4 11 10 9 27 -18 16.09 -6.09

Notes

  • Silkeborg won the promotion/relegation playoff over B 1909 by an aggregate score of 5-4 to retain their place in the Superliga.

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 1682 26 20.37 +5.63 98.2% 7 15 18 20 22 25 31
Lyngby 1678 24 20.97 +3.03 88.3% 9 16 19 21 23 26 32
B 1903 1588 16 17.29 -1.29 39.6% 6 12 15 17 19 22 28
Aarhus GF 1570 20 17.69 +2.31 83.0% 7 13 16 18 20 23 30
Frem 1568 19 18.61 +0.39 61.5% 7 14 17 19 21 24 31
Odense 1560 17 17.92 -0.92 44.8% 7 13 16 18 20 23 29
Vejle BK 1535 16 16.95 -0.95 44.5% 4 12 15 17 19 22 28
Aalborg 1516 17 16.88 +0.12 58.0% 5 12 15 17 19 22 28
Silkeborg 1510 15 17.25 -2.25 28.4% 4 12 15 17 19 22 30
Ikast 1454 10 16.09 -6.09 3.1% 5 11 14 16 18 21 28

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 FRE IKA LYN ODE SIL VB
Aalborg —
1-0-1
2.47
1-0-1
2.53
0-1-1
2.11
1-0-1
2.53
1-1-0
2.82
0-0-2
2.17
1-1-0
2.34
1-1-0
2.54
0-1-1
2.70
Aarhus GF
1-0-1
2.82
 —
1-0-1
2.72
0-1-1
2.35
1-1-0
2.45
1-1-0
2.85
0-1-1
1.90
1-1-0
2.66
1-1-0
2.79
0-2-0
2.89
B 1903
1-0-1
2.78
1-0-1
2.57
 —
0-0-2
2.27
1-0-1
2.44
0-1-1
3.03
1-0-1
2.00
0-2-0
2.59
1-1-0
2.58
1-0-1
2.48
Brondby
1-1-0
3.21
1-1-0
2.95
2-0-0
3.02
 —
1-1-0
2.97
2-0-0
3.22
0-1-1
2.63
0-2-0
2.92
1-0-1
3.32
2-0-0
3.18
Frem
1-0-1
2.77
0-1-1
2.84
1-0-1
2.84
0-1-1
2.33
 —
1-0-1
3.18
1-1-0
2.30
1-1-0
2.74
0-2-0
2.86
1-1-0
2.84
Ikast
0-1-1
2.49
0-1-1
2.47
1-1-0
2.25
0-0-2
2.08
1-0-1
2.11
 —
1-0-1
2.19
0-1-1
2.34
0-0-2
2.38
0-0-2
2.61
Lyngby
2-0-0
3.15
1-1-0
3.42
1-0-1
3.29
1-1-0
2.66
0-1-1
2.99
1-0-1
3.17
 —
1-1-0
3.11
1-0-1
3.34
2-0-0
3.19
Odense
0-1-1
2.94
0-1-1
2.63
0-2-0
2.71
0-2-0
2.38
0-1-1
2.54
1-1-0
2.94
0-1-1
2.19
 —
1-1-0
2.69
1-1-0
2.66
Silkeborg
0-1-1
2.76
0-1-1
2.49
0-1-1
2.72
1-0-1
2.01
0-2-0
2.43
2-0-0
2.92
1-0-1
1.96
0-1-1
2.60
 —
0-1-1
2.81
Vejle BK
1-1-0
2.58
0-2-0
2.41
1-0-1
2.81
0-0-2
2.14
0-1-1
2.46
2-0-0
2.70
0-0-2
2.14
0-1-1
2.63
1-1-0
2.48
 —

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 0.64 +5.2
Allowed 0.32 -4.2
Differential 0.87 +4.3

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
012.22%7.78%3.33%3.33%—1.11%27.78%
17.78%16.67%8.89%1.67%2.78%1.67%39.44%
23.33%8.89%4.44%0.56%0.56%0.56%18.33%
33.33%1.67%0.56%1.11%0.56%—7.22%
4—2.78%0.56%0.56%——3.89%
5+1.11%1.67%0.56%———3.33%
Total27.78%39.44%18.33%7.22%3.89%3.33%100%

Summary Statistics

Scored Allowed Difference
Mean 1.31 1.31 +0.00
SD 1.28 1.28 1.82
CV 0.98 0.98 —
Max 6 6 +6
Min 0 0 -6

Games Played: 90

↓ Scored | Allowed →012345+Total
05.56%—11.11%———16.67%
1—16.67%11.11%—5.56%11.11%44.44%
25.56%11.11%5.56%———22.22%
3———————
4—11.11%————11.11%
5+—5.56%————5.56%
Total11.11%44.44%27.78%—5.56%11.11%100%

Summary Statistics

Scored Allowed Difference
Mean 1.61 1.83 -0.22
SD 1.42 1.62 2.41
CV 0.88 0.88 —
Max 5 6 +4
Min 0 0 -5

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%——5.56%——22.22%
1—16.67%11.11%—5.56%—33.33%
2—16.67%5.56%———22.22%
3—5.56%5.56%5.56%——16.67%
4———————
5+—5.56%————5.56%
Total16.67%44.44%22.22%11.11%5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.61 1.44 +0.17
SD 1.50 1.10 1.76
CV 0.93 0.76 —
Max 6 4 +5
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%27.78%————44.44%
15.56%5.56%5.56%—11.11%—27.78%
25.56%5.56%————11.11%
311.11%—————11.11%
4—5.56%————5.56%
5+———————
Total38.89%44.44%5.56%—11.11%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.00 +0.06
SD 1.26 1.24 1.83
CV 1.19 1.24 —
Max 4 4 +3
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
011.11%5.56%—5.56%——22.22%
116.67%16.67%————33.33%
25.56%16.67%5.56%———27.78%
3—11.11%————11.11%
4—5.56%————5.56%
5+———————
Total33.33%55.56%5.56%5.56%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.44 0.83 +0.61
SD 1.15 0.79 1.33
CV 0.80 0.94 —
Max 4 3 +3
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
0———————
111.11%27.78%22.22%—5.56%—66.67%
2—16.67%11.11%———27.78%
35.56%—————5.56%
4———————
5+———————
Total16.67%44.44%33.33%—5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 1.33 +0.06
SD 0.61 0.97 1.26
CV 0.44 0.73 —
Max 3 4 +3
Min 1 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%16.67%11.11%11.11%—5.56%61.11%
111.11%5.56%11.11%———27.78%
2—5.56%—5.56%——11.11%
3———————
4———————
5+———————
Total27.78%27.78%22.22%16.67%—5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 0.50 1.50 -1.00
SD 0.71 1.38 1.57
CV 1.41 0.92 —
Max 2 5 +1
Min 0 0 -5

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%5.56%———11.11%
111.11%22.22%5.56%———38.89%
211.11%11.11%————22.22%
35.56%———5.56%—11.11%
4—5.56%————5.56%
5+5.56%—5.56%———11.11%
Total33.33%44.44%16.67%—5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.94 1.00 +0.94
SD 1.51 1.03 1.80
CV 0.78 1.03 —
Max 5 4 +5
Min 0 0 -2

Games Played: 18

↓ Scored | Allowed →012345+Total
033.33%5.56%—5.56%——44.44%
1—22.22%—5.56%—5.56%33.33%
2——5.56%———5.56%
35.56%—————5.56%
4——5.56%———5.56%
5+5.56%—————5.56%
Total44.44%27.78%11.11%11.11%—5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.17 1.11 +0.06
SD 1.65 1.41 2.15
CV 1.42 1.27 —
Max 6 5 +6
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
05.56%11.11%———5.56%22.22%
111.11%16.67%16.67%———44.44%
2—5.56%11.11%——5.56%22.22%
3———5.56%——5.56%
4———5.56%——5.56%
5+———————
Total16.67%33.33%27.78%11.11%—11.11%100%

Summary Statistics

Scored Allowed Difference
Mean 1.28 1.83 -0.56
SD 1.07 1.62 1.69
CV 0.84 0.88 —
Max 4 6 +1
Min 0 0 -6

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%5.56%5.56%5.56%——33.33%
111.11%16.67%5.56%11.11%——44.44%
25.56%———5.56%—11.11%
35.56%—————5.56%
4———————
5+—5.56%————5.56%
Total38.89%27.78%11.11%16.67%5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.11 1.22 -0.11
SD 1.28 1.31 1.84
CV 1.15 1.07 —
Max 5 4 +4
Min 0 0 -3

Games Played: 18

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 Brondby 26 20.37 +5.63
2 Lyngby 24 20.97 +3.03
3 Aarhus GF 20 17.69 +2.31
4 Frem 19 18.61 +0.39
5 Aalborg 17 16.88 +0.12

Biggest Disappointments

# Team Actual Sim vsSim
1 Ikast 10 16.09 -6.09
2 Silkeborg 15 17.25 -2.25
3 B 1903 16 17.29 -1.29
4 Vejle BK 16 16.95 -0.95
5 Odense 17 17.92 -0.92

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 Brondby 6 May 23 – Jun 19 1 in 383
2 Lyngby 5 Apr 14 – May 12 1 in 162
3 B 1903 3 May 16 – May 23 1 in 63
4 Vejle BK 2 May 5 – May 12 1 in 16
5 Frem 2 Mar 17 – Mar 24 1 in 13

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Ikast 8 Apr 28 – May 30 1 in 2,452
2 Frem 3 Jun 9 – Jun 23 1 in 38
3 Brondby 2 Apr 28 – May 5 1 in 18
4 B 1903 3 Mar 24 – Apr 7 1 in 17
5 Aalborg 3 Jun 2 – Jun 19 1 in 15

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Aalborg 6 Apr 6 – May 12 1 in 33
2 Brondby 10 May 12 – Jun 23 1 in 28
3 Lyngby 10 Mar 24 – May 20 1 in 16
4 Frem 6 May 16 – Jun 2 1 in 11
5 Aarhus GF 5 May 16 – May 30 1 in 9

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Ikast 14 Mar 24 – Jun 2 1 in 102
2 B 1903 9 Mar 17 – May 12 1 in 25
3 Odense 8 Apr 14 – May 23 1 in 25
4 Vejle BK 7 Mar 17 – Apr 28 1 in 18
5 Brondby 5 Apr 28 – May 20 1 in 16

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).

Team12345678910
Brondby25.84%20.62%15.58%11.14%8.22%6.45%4.81%3.51%2.43%1.40%
Lyngby35.73%20.71%13.24%9.48%7.06%5.10%3.72%2.40%1.61%0.95%
Aarhus GF5.61%8.79%10.61%11.64%11.56%11.85%10.76%11.15%9.65%8.38%
Frem9.53%11.75%13.33%12.68%11.81%10.89%9.43%8.31%7.23%5.04%
Odense6.66%9.79%10.85%11.30%11.43%11.10%11.21%10.49%9.26%7.91%
Aalborg2.96%5.67%7.43%8.96%10.14%11.34%12.45%13.38%13.76%13.91%
B 19034.54%7.18%8.92%10.57%11.59%11.19%11.86%12.18%11.42%10.55%
Vejle BK3.55%5.93%7.38%9.36%10.38%11.01%12.33%12.90%13.15%14.01%
Silkeborg3.87%6.22%7.96%9.37%10.26%11.61%11.93%12.11%13.86%12.81%
Ikast1.71%3.34%4.70%5.50%7.55%9.46%11.50%13.57%17.63%25.04%

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
+30.00%
Strong Edge
47.78%34.44%17.78%
Elo Value
Home Edge
152 Elo
0.007 goals per Elo point
0107.54400
Scoring Tilt
Expected
+0.76 goals
Home-Tilted
-2+0.71+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 5th * Longshot: 6th 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
4.6
Open
124610
Champion Preseason Odds
26%
Brondby, 2nd of 10
LongshotFavorite
Title Margin
Expected
0.11/gm
Photo Finish
00.110.5/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 2.42 * Some Luck: 2.42 to 3.63 * Lucky: 3.63 to 4.84 * Wild Swing: 4.84 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 1.95 * Close: 1.95 to 2.93 * Off: 2.93 to 3.91 * Way Off: 3.91 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 10 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 10 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 10 * As Expected: 10 to 16 * Several Outliers: 16 to 22 * Many Outliers: 22 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 1 * A Surprise: 1 to 1.6 * Several Surprises: 1.6 to 2.2 * Many Surprises: 2.2 and up.
Luck Spread
Expected
3.03 points
Some Luck
03.038
Average Finish Error
Expected
1.20
Pinpoint
02.445
Biggest Overachiever
Expected 95.00%
98.21%
Brondby
50100
Biggest Underachiever
Expected 5.00%
3.07%
Ikast
050
Season Outliers
Expected
2 of 10
Minimal Outliers
01.010
Unexpected Relegations
Expected 1.0
1 of 1
A Surprise
01

Parity

How these are measured

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

Gini Index
How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.
Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully
How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge
Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst
Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts
Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.13
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.08
Moderate Separation
01.003
Interquartile Edge
59%
Even
50%60%70%80%100%
Best vs. Worst
Baseline
79%
Clear Edge
50%79%100%
Close Games
Expected
70%
Very Frequent
0%59%100%
Blowouts
Expected
19%
Frequent
0%17%100%

Predictability

How these are measured

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

Brier Score
How close the pregame probabilities landed to the actual result, averaged over the season. Confident, correct calls are rewarded most; confident misses are punished most. Lower is better; since draws are possible, a score under 0.66 beats guessing the base rate.
Highly Predictable: under 0.56 * Predictable: 0.56 to 0.62 * Hard to Predict: 0.62 to 0.66 * Coin-Flip: 0.66 and up.
Matchup Imbalance
How lopsided the matchups were on paper, averaging the gap between the two win probabilities over their sum. 0 means every match was a toss-up; 1 means every match was a heavy favorite against a big underdog.
Very Even: under 0.1 * Slight Separation: 0.1 to 0.18 * Notable Separation: 0.18 to 0.28 * Lopsided: 0.28 and up.
Strangeness
How wild the final table was versus what the model expected. A value of 1 means teams landed about one standard deviation from their projections on average. Above 1 is a stranger season; below 1 hugged the projections.
Very Predictable: under 0.8 * As Expected: 0.8 to 1.1 * Wilder Than Modeled: 1.1 to 1.4 * Chaotic: 1.4 and up.
Repeatability
How closely the final table order matched the preseason Elo order, by Spearman rank correlation. Higher means last season's ratings strongly predicted this season's finish. Shows N/A for an inaugural season.
Weak Carryover: under 0.3 * Some Carryover: 0.3 to 0.6 * Strong Carryover: 0.6 to 0.85 * Near-Lock: 0.85 and up.
Upset Rate
Share of matches the underdog won. The gold line is how often the model expected underdogs to win; a dot to the right means upsets ran hotter than expected.
Chalky: under 25% * As Expected: 25% to 33% * Upset-Prone: 33% to 42% * Very Upset-Prone: 42% and up.
Clear Favorite Upset Rate
Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 15% * As Expected: 15% to 25% * Shaky Favorites: 25% to 35% * Very Shaky: 35% and up.
Brier Score
Expected
0.61
Predictable
00.602
Matchup Imbalance
0.53
Lopsided
00.10.180.280.5
Strangeness
Expected
1.00
As Expected
01.002
Repeatability
0.49
Some Carryover
00.30.60.851
Upset Rate
Expected
19%
Chalky
0%15%50%
Clear Favorite Upset Rate
Expected
18%
As Expected
0%14%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 0.15 * Near Noise Ceiling: 0.15 to 0.23 * Above Noise: 0.23 to 0.31 * Well Above Noise: 0.31 and up.
Probability calibration
0.37
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
1.16
Underconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.093
Well Within Noise
00.1530.4

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 Qualified for relegation playoff
Aalborg 72.33% 27.67%
Aarhus GF 81.97% 18.03%
B 1903 78.03% 21.97%
Brondby 96.17% 3.83%
Frem 87.73% 12.27%
Ikast 57.33% 42.67%
Lyngby 97.44% 2.56%
Odense 82.83% 17.17%
Silkeborg 73.33% 26.67%
Vejle BK 72.84% 27.16%

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
1991-03-16 Brondby L 1-2 1559 1624 44.01% 36.37% 19.62% -13.3 0
1991-03-16 @ Aarhus GF W 2-1 1624 1559 19.62% 36.37% 44.01% +13.3 2
1991-03-17 Vejle BK D 1-1 1531 1547 49.03% 35.78% 15.19% -2.2 1
1991-03-17 @ Aalborg D 1-1 1547 1531 15.19% 35.78% 49.03% +2.3 1
1991-03-17 Silkeborg D 1-1 1571 1557 51.86% 35.20% 12.94% -2.7 1
1991-03-17 @ B 1903 D 1-1 1557 1571 12.94% 35.20% 51.86% +2.7 1
1991-03-17 Odense W 3-0 1555 1562 49.98% 35.60% 14.41% +17.7 2
1991-03-17 @ Frem L 0-3 1562 1555 14.41% 35.60% 49.98% -17.7 0
1991-03-17 Lyngby W 1-0 1556 1598 46.43% 36.14% 17.43% +7.4 2
1991-03-17 @ Ikast L 0-1 1598 1556 17.43% 36.14% 46.43% -7.4 0
1991-03-24 Ikast W 2-1 1638 1563 56.84% 33.63% 9.53% +4.3 4
1991-03-24 @ Brondby L 1-2 1563 1638 9.53% 33.63% 56.84% -4.3 2
1991-03-24 B 1903 W 4-1 1591 1568 52.63% 35.00% 12.37% +13.2 2
1991-03-24 @ Lyngby L 1-4 1568 1591 12.37% 35.00% 52.63% -13.2 1
1991-03-24 Aarhus GF D 0-0 1544 1546 50.40% 35.52% 14.08% -2.8 1
1991-03-24 @ Odense D 0-0 1546 1544 14.08% 35.52% 50.40% +2.7 1
1991-03-24 Aalborg D 1-1 1560 1528 53.39% 34.79% 11.81% -2.9 2
1991-03-24 @ Silkeborg D 1-1 1528 1560 11.81% 34.79% 53.39% +2.9 2
1991-03-24 Frem L 1-2 1550 1573 48.40% 35.88% 15.72% -14.4 1
1991-03-24 @ Vejle BK W 2-1 1573 1550 15.72% 35.88% 48.40% +14.4 4
1991-04-01 Lyngby L 1-2 1531 1604 43.11% 36.42% 20.47% -13.0 2
1991-04-01 @ Aalborg W 2-1 1604 1531 20.47% 36.42% 43.11% +13.0 4
1991-04-01 Brondby L 0-1 1555 1642 41.52% 36.49% 21.99% -13.4 1
1991-04-01 @ B 1903 W 1-0 1642 1555 21.99% 36.49% 41.52% +13.4 6
1991-04-01 Silkeborg D 2-2 1587 1557 53.27% 34.83% 11.90% -2.1 5
1991-04-01 @ Frem D 2-2 1557 1587 11.90% 34.83% 53.27% +2.1 3
1991-04-01 Aarhus GF D 1-1 1559 1549 51.53% 35.27% 13.19% -2.6 3
1991-04-01 @ Ikast D 1-1 1549 1559 13.19% 35.27% 51.53% +2.6 2
1991-04-01 Odense D 0-0 1535 1541 50.03% 35.59% 14.37% -2.7 2
1991-04-01 @ Vejle BK D 0-0 1541 1535 14.37% 35.59% 50.03% +2.7 2
1991-04-06 Aalborg D 2-2 1655 1518 61.42% 31.49% 7.09% -3.0 7
1991-04-06 @ Brondby D 2-2 1518 1655 7.09% 31.49% 61.42% +3.0 3
1991-04-07 B 1903 W 2-1 1552 1542 51.49% 35.29% 13.23% +5.7 4
1991-04-07 @ Aarhus GF L 1-2 1542 1552 13.23% 35.29% 51.49% -5.7 1
1991-04-07 Frem D 1-1 1617 1585 53.47% 34.77% 11.76% -2.9 5
1991-04-07 @ Lyngby D 1-1 1585 1617 11.76% 34.77% 53.47% +2.9 6
1991-04-07 Ikast W 3-0 1544 1556 49.42% 35.71% 14.87% +18.1 4
1991-04-07 @ Odense L 0-3 1556 1544 14.87% 35.71% 49.42% -18.1 3
1991-04-07 Vejle BK D 0-0 1559 1532 52.98% 34.91% 12.11% -3.2 4
1991-04-07 @ Silkeborg D 0-0 1532 1559 12.11% 34.91% 52.98% +3.2 3
1991-04-14 Aarhus GF W 4-1 1521 1557 47.10% 36.06% 16.84% +16.8 5
1991-04-14 @ Aalborg L 1-4 1557 1521 16.84% 36.06% 47.10% -16.8 4
1991-04-14 Ikast D 0-0 1536 1538 50.40% 35.52% 14.08% -2.8 2
1991-04-14 @ B 1903 D 0-0 1538 1536 14.08% 35.52% 50.40% +2.7 4
1991-04-14 Brondby D 1-1 1588 1652 44.05% 36.36% 19.59% -1.5 7
1991-04-14 @ Frem D 1-1 1652 1588 19.59% 36.36% 44.05% +1.5 8
1991-04-14 Odense D 2-2 1556 1562 50.04% 35.59% 14.37% -1.8 5
1991-04-14 @ Silkeborg D 2-2 1562 1556 14.37% 35.59% 50.04% +1.8 5
1991-04-14 Lyngby L 0-2 1536 1614 42.44% 36.46% 21.11% -25.8 3
1991-04-14 @ Vejle BK W 2-0 1614 1536 21.11% 36.46% 42.44% +25.8 7
1991-04-20 Vejle BK W 3-1 1654 1510 61.90% 31.23% 6.87% +5.3 10
1991-04-20 @ Brondby L 1-3 1510 1654 6.87% 31.23% 61.90% -5.3 3
1991-04-21 Frem W 2-1 1540 1586 46.09% 36.18% 17.73% +7.1 6
1991-04-21 @ Aarhus GF L 1-2 1586 1540 17.73% 36.18% 46.09% -7.1 7
1991-04-21 Aalborg D 0-0 1541 1538 50.90% 35.42% 13.68% -2.8 5
1991-04-21 @ Ikast D 0-0 1538 1541 13.68% 35.42% 50.90% +2.8 6
1991-04-21 Silkeborg W 5-2 1640 1554 57.73% 33.26% 9.00% +8.6 9
1991-04-21 @ Lyngby L 2-5 1554 1640 9.00% 33.26% 57.73% -8.6 5
1991-04-21 B 1903 D 0-0 1564 1533 53.30% 34.82% 11.88% -3.2 6
1991-04-21 @ Odense D 0-0 1533 1564 11.88% 34.82% 53.30% +3.2 3
1991-04-28 B 1903 W 4-1 1541 1537 50.98% 35.40% 13.62% +14.2 8
1991-04-28 @ Aalborg L 1-4 1537 1541 13.62% 35.40% 50.98% -14.3 3
1991-04-28 Ikast W 1-0 1579 1538 54.17% 34.56% 11.26% +5.3 9
1991-04-28 @ Frem L 0-1 1538 1579 11.26% 34.56% 54.17% -5.3 5
1991-04-28 Odense W 1-0 1649 1561 57.90% 33.19% 8.91% +4.3 11
1991-04-28 @ Lyngby L 0-1 1561 1649 8.91% 33.19% 57.90% -4.3 6
1991-04-28 Brondby W 1-0 1546 1659 38.21% 36.53% 25.26% +9.6 7
1991-04-28 @ Silkeborg L 0-1 1659 1546 25.26% 36.53% 38.21% -9.6 10
1991-04-28 Aarhus GF D 1-1 1504 1548 46.37% 36.15% 17.48% -1.9 4
1991-04-28 @ Vejle BK D 1-1 1548 1504 17.48% 36.15% 46.37% +1.9 7
1991-05-05 Silkeborg W 2-1 1549 1555 50.07% 35.59% 14.34% +6.1 9
1991-05-05 @ Aarhus GF L 1-2 1555 1549 14.34% 35.59% 50.07% -6.1 7
1991-05-05 Lyngby L 0-3 1650 1653 50.29% 35.54% 14.16% -43.3 10
1991-05-05 @ Brondby W 3-0 1653 1650 14.16% 35.54% 50.29% +43.3 13
1991-05-05 Frem L 0-1 1522 1584 44.33% 36.34% 19.33% -14.2 3
1991-05-05 @ B 1903 W 1-0 1584 1522 19.33% 36.34% 44.33% +14.2 11
1991-05-05 Vejle BK L 0-2 1533 1503 53.30% 34.82% 11.88% -31.4 5
1991-05-05 @ Ikast W 2-0 1503 1533 11.88% 34.82% 53.30% +31.4 6
1991-05-05 Aalborg D 1-1 1556 1555 50.73% 35.45% 13.82% -2.5 7
1991-05-05 @ Odense D 1-1 1555 1556 13.82% 35.45% 50.73% +2.5 9
1991-05-12 Aalborg L 1-2 1599 1558 54.19% 34.56% 11.25% -15.9 11
1991-05-12 @ Frem W 2-1 1558 1599 11.25% 34.56% 54.19% +15.9 11
1991-05-12 Aarhus GF W 2-1 1696 1555 61.67% 31.35% 6.97% +3.1 15
1991-05-12 @ Lyngby L 1-2 1555 1696 6.97% 31.35% 61.67% -3.1 9
1991-05-12 Brondby D 1-1 1554 1606 45.36% 36.25% 18.38% -1.7 8
1991-05-12 @ Odense D 1-1 1606 1554 18.38% 36.25% 45.36% +1.7 11
1991-05-12 Ikast W 1-0 1549 1502 54.72% 34.39% 10.89% +5.1 9
1991-05-12 @ Silkeborg L 0-1 1502 1549 10.89% 34.39% 54.72% -5.1 5
1991-05-12 B 1903 W 1-0 1534 1508 52.90% 34.93% 12.17% +5.6 8
1991-05-12 @ Vejle BK L 0-1 1508 1534 12.17% 34.93% 52.90% -5.6 3
1991-05-16 Frem L 1-2 1573 1583 49.74% 35.65% 14.61% -14.8 11
1991-05-16 @ Aalborg W 2-1 1583 1573 14.61% 35.65% 49.74% +14.8 13
1991-05-16 Lyngby D 1-1 1552 1699 33.82% 36.39% 29.79% -0.2 10
1991-05-16 @ Aarhus GF D 1-1 1699 1552 29.79% 36.39% 33.82% +0.2 16
1991-05-16 Odense D 0-0 1608 1552 55.41% 34.16% 10.43% -3.6 12
1991-05-16 @ Brondby D 0-0 1552 1608 10.43% 34.16% 55.41% +3.6 9
1991-05-16 Vejle BK W 3-0 1503 1540 46.99% 36.08% 16.93% +19.9 5
1991-05-16 @ B 1903 L 0-3 1540 1503 16.93% 36.08% 46.99% -19.9 8
1991-05-16 Silkeborg L 1-2 1497 1554 44.81% 36.30% 18.89% -13.5 5
1991-05-16 @ Ikast W 2-1 1554 1497 18.89% 36.30% 44.81% +13.5 11
1991-05-20 Aarhus GF D 0-0 1605 1552 55.12% 34.26% 10.62% -3.5 13
1991-05-20 @ Brondby D 0-0 1552 1605 10.62% 34.26% 55.12% +3.5 11
1991-05-20 Ikast W 5-0 1700 1483 66.70% 28.28% 5.02% +10.0 18
1991-05-20 @ Lyngby L 0-5 1483 1700 5.02% 28.28% 66.70% -10.0 5
1991-05-20 Frem D 1-1 1556 1597 46.51% 36.13% 17.36% -1.9 10
1991-05-20 @ Odense D 1-1 1597 1556 17.36% 36.13% 46.51% +1.9 14
1991-05-20 B 1903 L 0-1 1568 1523 54.53% 34.45% 11.02% -17.0 11
1991-05-20 @ Silkeborg W 1-0 1523 1568 11.02% 34.45% 54.53% +17.0 7
1991-05-20 Aalborg W 5-1 1520 1559 46.80% 36.10% 17.10% +21.9 10
1991-05-20 @ Vejle BK L 1-5 1559 1520 17.10% 36.10% 46.80% -21.9 11
1991-05-23 Silkeborg W 2-1 1537 1551 49.30% 35.73% 14.97% +6.3 13
1991-05-23 @ Aalborg L 1-2 1551 1537 14.97% 35.73% 49.30% -6.3 11
1991-05-23 Odense W 3-1 1556 1554 50.78% 35.44% 13.78% +10.2 13
1991-05-23 @ Aarhus GF L 1-3 1554 1556 13.78% 35.44% 50.78% -10.2 10
1991-05-23 Lyngby W 2-0 1540 1710 30.66% 36.17% 33.17% +21.4 9
1991-05-23 @ B 1903 L 0-2 1710 1540 33.17% 36.17% 30.66% -21.4 18
1991-05-23 Vejle BK D 1-1 1599 1542 55.55% 34.11% 10.34% -3.2 15
1991-05-23 @ Frem D 1-1 1542 1599 10.34% 34.11% 55.55% +3.2 11
1991-05-23 Brondby L 0-1 1473 1601 36.36% 36.49% 27.14% -12.1 5
1991-05-23 @ Ikast W 1-0 1601 1473 27.14% 36.49% 36.36% +12.1 15
1991-05-26 Ikast W 3-2 1566 1461 59.13% 32.64% 8.23% +3.5 15
1991-05-26 @ Aarhus GF L 2-3 1461 1566 8.23% 32.64% 59.13% -3.5 5
1991-05-26 B 1903 W 1-0 1613 1561 55.11% 34.26% 10.63% +5.0 17
1991-05-26 @ Brondby L 0-1 1561 1613 10.63% 34.26% 55.11% -5.0 9
1991-05-26 Aalborg W 2-0 1688 1543 61.97% 31.19% 6.84% +6.1 20
1991-05-26 @ Lyngby L 0-2 1543 1688 6.84% 31.19% 61.97% -6.1 13
1991-05-26 Vejle BK W 4-2 1544 1545 50.49% 35.50% 14.00% +9.2 12
1991-05-26 @ Odense L 2-4 1545 1544 14.00% 35.50% 50.49% -9.2 11
1991-05-26 Frem D 1-1 1544 1596 45.46% 36.24% 18.30% -1.8 12
1991-05-26 @ Silkeborg D 1-1 1596 1544 18.30% 36.24% 45.46% +1.7 16
1991-05-30 Ikast W 2-0 1537 1457 57.24% 33.47% 9.29% +8.4 15
1991-05-30 @ Aalborg L 0-2 1457 1537 9.29% 33.47% 57.24% -8.4 5
1991-05-30 Odense D 0-0 1556 1553 50.89% 35.42% 13.69% -2.8 10
1991-05-30 @ B 1903 D 0-0 1553 1556 13.69% 35.42% 50.89% +2.8 13
1991-05-30 Aarhus GF D 2-2 1598 1569 53.14% 34.87% 12.00% -2.1 17
1991-05-30 @ Frem D 2-2 1569 1598 12.00% 34.87% 53.14% +2.1 16
1991-05-30 Lyngby W 4-3 1543 1694 33.20% 36.35% 30.45% +9.4 14
1991-05-30 @ Silkeborg L 3-4 1694 1543 30.45% 36.35% 33.20% -9.4 20
1991-05-30 Brondby L 1-3 1536 1618 41.98% 36.48% 21.54% -22.1 11
1991-05-30 @ Vejle BK W 3-1 1618 1536 21.54% 36.48% 41.98% +22.1 19
1991-06-02 Brondby L 0-2 1545 1640 40.51% 36.52% 22.97% -24.8 15
1991-06-02 @ Aalborg W 2-0 1640 1545 22.97% 36.52% 40.51% +24.8 21
1991-06-02 Aarhus GF W 3-0 1553 1571 48.86% 35.80% 15.33% +18.5 12
1991-06-02 @ B 1903 L 0-3 1571 1553 15.33% 35.80% 48.86% -18.5 16
1991-06-02 Lyngby W 2-1 1596 1685 41.22% 36.50% 22.28% +8.3 19
1991-06-02 @ Frem L 1-2 1685 1596 22.28% 36.50% 41.22% -8.3 20
1991-06-02 Odense D 0-0 1449 1556 39.10% 36.53% 24.37% -1.0 6
1991-06-02 @ Ikast D 0-0 1556 1449 24.37% 36.53% 39.10% +1.0 14
1991-06-02 Silkeborg W 1-0 1513 1552 46.83% 36.10% 17.07% +7.3 13
1991-06-02 @ Vejle BK L 0-1 1552 1513 17.07% 36.10% 46.83% -7.3 14
1991-06-09 Aalborg W 6-1 1553 1520 53.47% 34.77% 11.76% +20.0 18
1991-06-09 @ Aarhus GF L 1-6 1520 1553 11.76% 34.77% 53.47% -20.0 15
1991-06-09 Frem W 4-1 1665 1604 55.82% 34.01% 10.17% +11.1 23
1991-06-09 @ Brondby L 1-4 1604 1665 10.17% 34.01% 55.82% -11.1 19
1991-06-09 B 1903 W 1-0 1448 1572 36.94% 36.51% 26.55% +9.9 8
1991-06-09 @ Ikast L 0-1 1572 1448 26.55% 36.51% 36.94% -9.9 12
1991-06-09 Vejle BK W 1-0 1677 1521 62.70% 30.78% 6.52% +3.1 22
1991-06-09 @ Lyngby L 0-1 1521 1677 6.52% 30.78% 62.70% -3.1 13
1991-06-09 Silkeborg W 6-0 1557 1545 51.68% 35.24% 13.08% +31.3 16
1991-06-09 @ Odense L 0-6 1545 1557 13.08% 35.24% 51.68% -31.3 14
1991-06-19 Vejle BK D 0-0 1573 1518 55.35% 34.18% 10.47% -3.5 19
1991-06-19 @ Aarhus GF D 0-0 1518 1573 10.47% 34.18% 55.35% +3.5 14
1991-06-19 Silkeborg W 2-1 1676 1513 63.18% 30.50% 6.32% +2.8 25
1991-06-19 @ Brondby L 1-2 1513 1676 6.32% 30.50% 63.18% -2.8 14
1991-06-19 Aalborg W 4-1 1562 1500 55.83% 34.01% 10.16% +11.1 14
1991-06-19 @ B 1903 L 1-4 1500 1562 10.16% 34.01% 55.83% -11.1 15
1991-06-19 Frem W 2-1 1458 1593 35.45% 36.46% 28.09% +9.7 10
1991-06-19 @ Ikast L 1-2 1593 1458 28.09% 36.46% 35.45% -9.7 19
1991-06-19 Lyngby D 1-1 1588 1680 40.91% 36.51% 22.58% -1.1 17
1991-06-19 @ Odense D 1-1 1680 1588 22.58% 36.51% 40.91% +1.1 23
1991-06-23 Odense W 5-1 1489 1587 40.23% 36.52% 23.25% +27.0 17
1991-06-23 @ Aalborg L 1-5 1587 1489 23.25% 36.52% 40.23% -27.0 17
1991-06-23 B 1903 L 1-2 1583 1573 51.55% 35.27% 13.18% -15.2 19
1991-06-23 @ Frem W 2-1 1573 1583 13.18% 35.27% 51.55% +15.2 16
1991-06-23 Brondby D 1-1 1681 1679 50.76% 35.45% 13.80% -2.5 24
1991-06-23 @ Lyngby D 1-1 1679 1681 13.80% 35.45% 50.76% +2.5 26
1991-06-23 Aarhus GF D 3-3 1511 1569 44.70% 36.31% 18.99% -1.0 15
1991-06-23 @ Silkeborg D 3-3 1569 1511 18.99% 36.31% 44.70% +1.0 20
1991-06-23 Ikast W 3-0 1521 1468 55.22% 34.22% 10.56% +13.6 16
1991-06-23 @ Vejle BK L 0-3 1468 1521 10.56% 34.22% 55.22% -13.6 10

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 1991-05-20 11.02% B 1903 1523 1 @ Silkeborg 1568 0
2 1991-05-12 11.25% Aalborg 1558 2 @ Frem 1599 1
3 1991-05-05 11.88% Vejle BK 1503 2 @ Ikast 1533 0
4 1991-06-23 13.18% B 1903 1573 2 @ Frem 1583 1
5 1991-05-05 14.16% Lyngby 1653 3 @ Brondby 1650 0
6 1991-05-16 14.61% Frem 1583 2 @ Aalborg 1573 1
7 1991-03-24 15.72% Frem 1573 2 @ Vejle BK 1550 1
8 1991-05-16 18.89% Silkeborg 1554 2 @ Ikast 1497 1
9 1991-05-05 19.33% Frem 1584 1 @ B 1903 1522 0
10 1991-03-16 19.62% Brondby 1624 2 @ Aarhus GF 1559 1
11 1991-04-01 20.47% Lyngby 1604 2 @ Aalborg 1531 1
12 1991-04-14 21.11% Lyngby 1614 2 @ Vejle BK 1536 0
13 1991-05-30 21.54% Brondby 1618 3 @ Vejle BK 1536 1
14 1991-04-01 21.99% Brondby 1642 1 @ B 1903 1555 0
15 1991-06-02 22.97% Brondby 1640 2 @ Aalborg 1545 0
16 1991-05-23 27.14% Brondby 1601 1 @ Ikast 1473 0
17 1991-05-23 30.66% @ B 1903 1540 2 Lyngby 1710 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 1991-05-05 43.28 Lyngby 3 1653 14.16% @ Brondby 0 1650 50.29% 35.54%
2 1991-05-05 31.39 Vejle BK 2 1503 11.88% @ Ikast 0 1533 53.30% 34.82%
3 1991-06-09 31.29 @ Odense 6 1557 51.68% Silkeborg 0 1545 13.08% 35.24%
4 1991-06-23 27.04 @ Aalborg 5 1489 40.23% Odense 1 1587 23.25% 36.52%
5 1991-04-14 25.78 Lyngby 2 1614 21.11% @ Vejle BK 0 1536 42.44% 36.46%
6 1991-06-02 24.84 Brondby 2 1640 22.97% @ Aalborg 0 1545 40.51% 36.52%
7 1991-05-30 22.13 Brondby 3 1618 21.54% @ Vejle BK 1 1536 41.98% 36.48%
8 1991-05-20 21.87 @ Vejle BK 5 1520 46.80% Aalborg 1 1559 17.10% 36.10%
9 1991-05-23 21.43 @ B 1903 2 1540 30.66% Lyngby 0 1710 33.17% 36.17%
10 1991-06-09 19.98 @ Aarhus GF 6 1553 53.47% Aalborg 1 1520 11.76% 34.77%
11 1991-05-16 19.94 @ B 1903 3 1503 46.99% Vejle BK 0 1540 16.93% 36.08%
12 1991-06-02 18.53 @ B 1903 3 1553 48.86% Aarhus GF 0 1571 15.33% 35.80%
13 1991-04-07 18.10 @ Odense 3 1544 49.42% Ikast 0 1556 14.87% 35.71%
14 1991-03-17 17.68 @ Frem 3 1555 49.98% Odense 0 1562 14.41% 35.60%
15 1991-05-20 17.00 B 1903 1 1523 11.02% @ Silkeborg 0 1568 54.53% 34.45%
16 1991-04-14 16.75 @ Aalborg 4 1521 47.10% Aarhus GF 1 1557 16.84% 36.06%
17 1991-05-12 15.94 Aalborg 2 1558 11.25% @ Frem 1 1599 54.19% 34.56%
18 1991-06-23 15.23 B 1903 2 1573 13.18% @ Frem 1 1583 51.55% 35.27%
19 1991-05-16 14.76 Frem 2 1583 14.61% @ Aalborg 1 1573 49.74% 35.65%
20 1991-03-24 14.40 Frem 2 1573 15.72% @ Vejle BK 1 1550 48.40% 35.88%
21 1991-04-28 14.26 @ Aalborg 4 1541 50.98% B 1903 1 1537 13.62% 35.40%
22 1991-05-05 14.17 Frem 1 1584 19.33% @ B 1903 0 1522 44.33% 36.34%
23 1991-06-23 13.65 @ Vejle BK 3 1521 55.22% Ikast 0 1468 10.56% 34.22%
24 1991-05-16 13.48 Silkeborg 2 1554 18.89% @ Ikast 1 1497 44.81% 36.30%
25 1991-04-01 13.43 Brondby 1 1642 21.99% @ B 1903 0 1555 41.52% 36.49%