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1955-56 1st Division Season

90 games

Final

Champion

Aarhus GF

26 points · 2nd Title

Last Title: 1954-55

Relegated

Koge BK

9 pts

Biggest Overachiever

Aarhus GF

5.04 points above expected

26 points · 20.96 expected points

Biggest Disappointment

Koge BK

6.60 points below expected

9 points · 15.60 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 Aarhus GF Champion 18 12 2 4 26 48 25 +23 20.96 +5.04
2 Esbjerg 18 9 4 5 22 42 30 +12 19.63 +2.37
3 AB Gladsaxe 18 9 4 5 22 39 31 +8 20.69 +1.31
4 B 1909 18 7 6 5 20 34 29 +5 17.43 +2.57
5 Skovshoved 18 6 6 6 18 23 24 -1 17.54 +0.46
6 B 1903 18 8 2 8 18 34 36 -2 16.68 +1.32
7 Frem 18 7 4 7 18 27 29 -2 17.38 +0.62
8 AIA Tranbjerg 18 4 6 8 14 38 40 -2 18.27 -4.27
9 KB Copenhagen 18 3 7 8 13 22 37 -15 15.83 -2.83
10 Koge BK Relegated 18 3 3 12 9 25 51 -26 15.60 -6.60

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
Aarhus GF 1577 26 20.96 +5.04 94.3% 8 15 19 21 23 27 32
Esbjerg 1494 22 19.63 +2.37 78.5% 8 14 17 20 22 25 33
AB Gladsaxe 1489 22 20.69 +1.31 69.3% 8 15 18 21 23 26 33
Frem 1465 18 17.38 +0.62 61.8% 5 12 15 17 20 23 31
B 1909 1459 20 17.43 +2.57 80.6% 5 12 15 17 20 23 30
AIA Tranbjerg 1458 14 18.27 -4.27 15.0% 6 12 16 18 21 24 30
Skovshoved 1444 18 17.54 +0.46 60.9% 5 12 15 18 20 24 29
B 1903 1436 18 16.68 +1.32 69.2% 4 11 14 17 19 23 28
KB Copenhagen 1388 13 15.83 -2.83 26.1% 3 10 13 16 18 22 30
Koge BK 1337 9 15.60 -6.60 3.9% 3 10 13 16 18 21 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 AG AT AG B1 B1 ESB FRE KC KB SKO
AB Gladsaxe —
2-0-0
3.04
1-0-1
2.63
1-0-1
3.39
1-0-1
3.40
1-1-0
2.81
1-1-0
2.93
1-1-0
3.61
0-1-1
3.56
1-0-1
3.31
AIA Tranbjerg
0-0-2
2.44
 —
0-1-1
2.34
1-1-0
2.99
0-0-2
2.69
0-1-1
2.49
0-0-2
2.93
1-1-0
3.10
2-0-0
3.17
0-2-0
2.91
Aarhus GF
1-0-1
2.85
1-1-0
3.15
 —
2-0-0
3.45
1-0-1
3.15
1-0-1
2.97
2-0-0
3.31
1-1-0
3.32
2-0-0
3.47
1-0-1
3.45
B 1903
1-0-1
2.11
0-1-1
2.50
0-0-2
2.04
 —
1-0-1
2.52
1-1-0
2.11
0-0-2
2.87
2-0-0
2.80
2-0-0
3.06
1-0-1
2.76
B 1909
1-0-1
2.09
2-0-0
2.79
1-0-1
2.34
1-0-1
2.97
 —
0-1-1
2.46
1-1-0
2.58
0-2-0
2.87
1-1-0
3.02
0-1-1
2.72
Esbjerg
0-1-1
2.67
1-1-0
2.99
1-0-1
2.52
0-1-1
3.38
1-1-0
3.02
 —
1-0-1
3.14
1-0-1
3.31
2-0-0
3.23
2-0-0
2.86
Frem
0-1-1
2.55
2-0-0
2.55
0-0-2
2.17
2-0-0
2.61
0-1-1
2.90
1-0-1
2.34
 —
1-0-1
2.90
1-0-1
2.92
0-2-0
2.77
KB Copenhagen
0-1-1
1.88
0-1-1
2.38
0-1-1
2.17
0-0-2
2.69
0-2-0
2.61
1-0-1
2.18
1-0-1
2.58
 —
1-1-0
2.67
0-1-1
2.30
Koge BK
1-1-0
1.93
0-0-2
2.31
0-0-2
2.03
0-0-2
2.42
0-1-1
2.47
0-0-2
2.26
1-0-1
2.56
0-1-1
2.81
 —
1-0-1
2.22
Skovshoved
1-0-1
2.17
0-2-0
2.57
1-0-1
2.04
1-0-1
2.73
1-1-0
2.77
0-0-2
2.62
0-2-0
2.71
1-1-0
3.19
1-0-1
3.27
 —

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 0.55 +4.2
Allowed 0.70 -5.1
Differential 0.94 +3.5

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
04.44%5.56%2.78%3.89%1.67%1.11%19.44%
15.56%10.00%4.44%5.00%2.22%2.22%29.44%
22.78%4.44%6.67%2.78%1.67%1.67%20.00%
33.89%5.00%2.78%3.33%2.22%0.56%17.78%
41.67%2.22%1.67%2.22%——7.78%
5+1.11%2.22%1.67%0.56%——5.56%
Total19.44%29.44%20.00%17.78%7.78%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.84 1.84 +0.00
SD 1.50 1.50 2.21
CV 0.81 0.81 —
Max 7 7 +7
Min 0 0 -7

Games Played: 90

↓ Scored | Allowed →012345+Total
0————5.56%—5.56%
15.56%11.11%5.56%5.56%11.11%—38.89%
25.56%—11.11%———16.67%
311.11%11.11%5.56%———27.78%
4———————
5+——11.11%———11.11%
Total22.22%22.22%33.33%5.56%16.67%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.17 1.72 +0.44
SD 1.54 1.36 2.33
CV 0.71 0.79 —
Max 6 4 +4
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0—11.11%————11.11%
15.56%11.11%—5.56%5.56%—27.78%
2——11.11%5.56%—5.56%22.22%
3———11.11%11.11%—22.22%
45.56%—5.56%———11.11%
5+—5.56%————5.56%
Total11.11%27.78%16.67%22.22%16.67%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 2.11 2.22 -0.11
SD 1.41 1.48 1.94
CV 0.67 0.66 —
Max 5 5 +4
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%5.56%———11.11%
1—11.11%—5.56%——16.67%
211.11%5.56%———5.56%22.22%
3—11.11%5.56%———16.67%
45.56%5.56%5.56%5.56%——22.22%
5+5.56%5.56%————11.11%
Total22.22%44.44%16.67%11.11%—5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 2.67 1.39 +1.28
SD 1.81 1.29 2.44
CV 0.68 0.93 —
Max 7 5 +7
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%—16.67%5.56%—27.78%
15.56%—11.11%———16.67%
25.56%5.56%5.56%———16.67%
35.56%5.56%—5.56%5.56%—22.22%
4—5.56%—5.56%——11.11%
5+———5.56%——5.56%
Total16.67%22.22%16.67%33.33%11.11%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.89 2.00 -0.11
SD 1.60 1.33 2.17
CV 0.85 0.66 —
Max 5 4 +3
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
011.11%5.56%—5.56%—5.56%27.78%
15.56%16.67%5.56%———27.78%
2—5.56%5.56%5.56%——16.67%
3———————
45.56%5.56%—5.56%——16.67%
5+—5.56%5.56%———11.11%
Total22.22%38.89%16.67%16.67%—5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.89 1.61 +0.28
SD 1.91 1.69 2.67
CV 1.01 1.05 —
Max 6 7 +5
Min 0 0 -7

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%5.56%5.56%——16.67%
15.56%5.56%—5.56%——16.67%
2—5.56%11.11%5.56%——22.22%
35.56%5.56%5.56%5.56%——22.22%
4——5.56%5.56%——11.11%
5+5.56%5.56%————11.11%
Total16.67%27.78%27.78%27.78%——100%

Summary Statistics

Scored Allowed Difference
Mean 2.33 1.67 +0.67
SD 1.71 1.08 2.22
CV 0.73 0.65 —
Max 6 3 +6
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%—5.56%—5.56%—27.78%
111.11%5.56%5.56%——5.56%27.78%
2———11.11%—5.56%16.67%
311.11%11.11%————22.22%
4—5.56%————5.56%
5+———————
Total38.89%22.22%11.11%11.11%5.56%11.11%100%

Summary Statistics

Scored Allowed Difference
Mean 1.50 1.61 -0.11
SD 1.29 1.88 2.32
CV 0.86 1.17 —
Max 4 6 +3
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%5.56%11.11%——22.22%
111.11%22.22%—11.11%—5.56%50.00%
2——11.11%———11.11%
3——5.56%5.56%5.56%—16.67%
4———————
5+———————
Total11.11%27.78%22.22%27.78%5.56%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.22 2.06 -0.83
SD 1.00 1.35 1.50
CV 0.82 0.66 —
Max 3 5 +1
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0—11.11%5.56%——5.56%22.22%
15.56%5.56%11.11%—5.56%11.11%38.89%
2——5.56%—11.11%—16.67%
3—5.56%5.56%5.56%—5.56%22.22%
4———————
5+———————
Total5.56%22.22%27.78%5.56%16.67%22.22%100%

Summary Statistics

Scored Allowed Difference
Mean 1.39 2.83 -1.44
SD 1.09 1.86 2.09
CV 0.79 0.65 —
Max 3 6 +2
Min 0 0 -6

Games Played: 18

↓ Scored | Allowed →012345+Total
016.67%5.56%————22.22%
1—11.11%5.56%16.67%——33.33%
25.56%22.22%5.56%—5.56%—38.89%
35.56%—————5.56%
4———————
5+———————
Total27.78%38.89%11.11%16.67%5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.28 1.33 -0.06
SD 0.89 1.24 1.43
CV 0.70 0.93 —
Max 3 4 +3
Min 0 0 -2

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 Aarhus GF 26 20.96 +5.04
2 B 1909 20 17.43 +2.57
3 Esbjerg 22 19.63 +2.37
4 B 1903 18 16.68 +1.32
5 AB Gladsaxe 22 20.69 +1.31

Biggest Disappointments

# Team Actual Sim vsSim
1 Koge BK 9 15.60 -6.60
2 AIA Tranbjerg 14 18.27 -4.27
3 KB Copenhagen 13 15.83 -2.83
4 Skovshoved 18 17.54 +0.46
5 Frem 18 17.38 +0.62

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 Frem 4 Apr 8 – May 13 1 in 51
2 B 1909 3 Nov 27 – Jan 9 1 in 22
3 Aarhus GF 4 Jan 30 – Apr 8 1 in 21
4 Esbjerg 3 Aug 20 – Sep 18 1 in 16
5 AB Gladsaxe 3 Sep 18 – Nov 13 1 in 15

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Koge BK 6 Sep 24 – Jan 30 1 in 277
2 AIA Tranbjerg 3 Apr 29 – May 27 1 in 16
3 B 1903 3 Aug 28 – Sep 25 1 in 13
4 Esbjerg 2 Jan 9 – Jan 30 1 in 11
5 KB Copenhagen 2 Aug 21 – Aug 28 1 in 7

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 B 1909 7 Aug 28 – Jan 9 1 in 36
2 Frem 6 Apr 8 – May 27 1 in 16
3 Skovshoved 5 Aug 28 – Nov 27 1 in 14
4 KB Copenhagen 3 Apr 22 – May 13 1 in 8
5 Esbjerg 4 Mar 25 – Apr 22 1 in 5

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Koge BK 11 Sep 24 – Apr 29 1 in 65
2 AIA Tranbjerg 8 Aug 24 – Jan 30 1 in 55
3 KB Copenhagen 9 Jan 29 – Jun 3 1 in 24
4 Esbjerg 5 Apr 29 – Jun 10 1 in 19
5 Frem 5 Aug 21 – Nov 13 1 in 8

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
Aarhus GF29.03%19.74%14.70%11.12%8.06%6.16%4.58%3.36%2.04%1.21%
Esbjerg16.42%15.98%14.49%13.24%10.43%8.52%7.52%6.13%4.53%2.74%
AB Gladsaxe23.56%18.89%15.29%11.89%9.27%7.33%5.35%4.15%2.72%1.55%
B 19095.69%7.83%9.77%10.72%11.78%12.24%11.37%11.22%10.67%8.71%
Skovshoved5.59%7.95%8.97%10.67%11.92%11.90%12.20%11.03%10.41%9.36%
B 19033.46%5.61%7.63%8.76%10.12%11.34%12.34%13.17%14.44%13.13%
Frem5.07%7.49%8.93%10.29%11.14%11.79%12.03%11.51%11.73%10.02%
AIA Tranbjerg7.78%10.40%10.78%11.55%11.55%11.40%11.21%9.92%8.91%6.50%
KB Copenhagen1.85%3.31%4.98%6.26%8.39%10.12%11.92%14.37%17.16%21.64%
Koge BK1.55%2.80%4.46%5.50%7.34%9.20%11.48%15.14%17.39%25.14%

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
+6.67%
Slight Edge
41.11%24.44%34.44%
Elo Value
Home Edge: 23.20 Elo pts.
141 Elo
0.007 goals per Elo point
0400
Scoring Tilt
Expected
+0.29 goals
Neutral
-2+0.16+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
5.4
Open
124610
Champion Preseason Odds
29%
Aarhus GF, 1st of 10
LongshotFavorite
Title Margin
Expected
0.22/gm
Tight Race
00.120.5/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 2.86 * Some Luck: 2.86 to 4.28 * Lucky: 4.28 to 5.71 * Wild Swing: 5.71 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 1.9 * Close: 1.9 to 2.86 * Off: 2.86 to 3.81 * Way Off: 3.81 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 0.75 * A Surprise: 0.75 to 1.2 * Several Surprises: 1.2 to 1.65 * Many Surprises: 1.65 and up.
Luck Spread
Expected
3.34 points
Some Luck
03.579
Average Finish Error
Expected
1.00
Pinpoint
02.385
Biggest Overachiever
Expected 95.00%
94.30%
Aarhus GF
50100
Biggest Underachiever
Expected 5.00%
3.94%
Koge BK
050
Season Outliers
Expected
1 of 10
Minimal Outliers
01.010
Unexpected Relegations
Expected
0 of 1
As Expected
00.71

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
0.15
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.17
Moderate Separation
01.003
Interquartile Edge
56%
Even
50%60%70%80%100%
Best vs. Worst
Baseline
80%
Clear Edge
50%77%100%
Close Games
Expected
54%
Very Frequent
0%50%100%
Blowouts
Expected
26%
Very Frequent
0%26%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
0.64
Hard to Predict
00.642
Matchup Imbalance
0.20
Notable Separation
00.10.180.280.5
Strangeness
Expected
0.89
As Expected
01.002
Repeatability
0.23
Weak Carryover
00.30.60.851
Upset Rate
Expected
29%
As Expected
0%30%50%
Clear Favorite Upset Rate
Expected
22%
As Expected
0%25%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 0.17 * Near Noise Ceiling: 0.17 to 0.25 * Above Noise: 0.25 to 0.34 * Well Above Noise: 0.34 and up.
Probability calibration
0.65
Excellent
0.010.050.10.51
Calibration slope
Ideal
0.92
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.125
Well Within Noise
00.1680.4

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 Direct relegation
Aarhus GF 98.79% 1.21%
AB Gladsaxe 98.45% 1.55%
Esbjerg 97.26% 2.74%
AIA Tranbjerg 93.50% 6.50%
B 1909 91.29% 8.71%
Skovshoved 90.64% 9.36%
Frem 89.98% 10.02%
B 1903 86.87% 13.13%
KB Copenhagen 78.36% 21.64%
Koge BK 74.86% 25.14%

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
1955-08-20 Esbjerg L 2-3 1425 1450 38.50% 25.92% 35.58% -6.9 0
1955-08-20 @ B 1909 W 3-2 1450 1425 35.58% 25.92% 38.50% +6.9 2
1955-08-20 Skovshoved W 2-1 1438 1439 41.80% 25.90% 32.30% +6.4 2
1955-08-20 @ B 1903 L 1-2 1439 1438 32.30% 25.90% 41.80% -6.4 0
1955-08-21 Koge BK W 4-2 1472 1449 44.93% 25.82% 29.25% +9.1 2
1955-08-21 @ AIA Tranbjerg L 2-4 1449 1472 29.25% 25.82% 44.93% -9.1 0
1955-08-21 AB Gladsaxe L 2-6 1459 1477 39.40% 25.92% 34.68% -19.8 0
1955-08-21 @ Frem W 6-2 1477 1459 34.68% 25.92% 39.40% +19.8 2
1955-08-21 Aarhus GF L 1-5 1464 1474 40.48% 25.91% 33.60% -23.8 0
1955-08-21 @ KB Copenhagen W 5-1 1474 1464 33.60% 25.91% 40.48% +23.8 2
1955-08-24 Aarhus GF D 1-1 1481 1498 39.51% 25.92% 34.57% -0.2 3
1955-08-24 @ AIA Tranbjerg D 1-1 1498 1481 34.57% 25.92% 39.51% +0.2 3
1955-08-27 Koge BK L 1-3 1497 1440 49.22% 25.61% 25.17% -15.4 2
1955-08-27 @ AB Gladsaxe W 3-1 1440 1497 25.17% 25.61% 49.22% +15.4 2
1955-08-28 B 1903 W 4-3 1498 1444 48.92% 25.63% 25.45% +4.9 5
1955-08-28 @ Aarhus GF L 3-4 1444 1498 25.45% 25.63% 48.92% -4.9 2
1955-08-28 KB Copenhagen W 3-0 1456 1440 44.09% 25.85% 30.06% +17.5 4
1955-08-28 @ Esbjerg L 0-3 1440 1456 30.06% 25.85% 44.09% -17.5 0
1955-08-28 B 1909 D 0-0 1439 1418 44.70% 25.83% 29.47% -0.7 1
1955-08-28 @ Frem D 0-0 1418 1439 29.47% 25.83% 44.70% +0.7 1
1955-08-28 AIA Tranbjerg D 2-2 1432 1481 35.13% 25.89% 38.98% +0.1 1
1955-08-28 @ Skovshoved D 2-2 1481 1432 38.98% 25.89% 35.13% -0.1 4
1955-09-18 Skovshoved L 0-2 1503 1433 50.90% 25.49% 23.61% -18.3 5
1955-09-18 @ Aarhus GF W 2-0 1433 1503 23.61% 25.49% 50.90% +18.3 3
1955-09-18 AIA Tranbjerg W 4-3 1474 1481 41.00% 25.91% 33.10% +6.0 6
1955-09-18 @ Esbjerg L 3-4 1481 1474 33.10% 25.91% 41.00% -6.0 4
1955-09-18 AB Gladsaxe L 0-3 1439 1481 36.02% 25.90% 38.07% -20.1 2
1955-09-18 @ B 1903 W 3-0 1481 1439 38.07% 25.90% 36.02% +20.1 4
1955-09-18 B 1909 D 2-2 1423 1419 42.45% 25.89% 31.66% -0.3 1
1955-09-18 @ KB Copenhagen D 2-2 1419 1423 31.66% 25.89% 42.45% +0.3 2
1955-09-18 Frem W 3-2 1455 1438 44.22% 25.84% 29.94% +5.7 4
1955-09-18 @ Koge BK L 2-3 1438 1455 29.94% 25.84% 44.22% -5.7 1
1955-09-24 Koge BK W 1-0 1422 1461 36.49% 25.91% 37.60% +7.6 3
1955-09-24 @ KB Copenhagen L 0-1 1461 1422 37.60% 25.91% 36.49% -7.6 4
1955-09-25 Esbjerg W 3-0 1501 1480 44.79% 25.82% 29.38% +17.2 6
1955-09-25 @ AB Gladsaxe L 0-3 1480 1501 29.38% 25.82% 44.79% -17.2 6
1955-09-25 B 1903 W 1-0 1419 1419 41.88% 25.90% 32.22% +6.7 4
1955-09-25 @ B 1909 L 0-1 1419 1419 32.22% 25.90% 41.88% -6.7 2
1955-09-25 Frem D 0-0 1451 1433 44.36% 25.84% 29.80% -0.7 4
1955-09-25 @ Skovshoved D 0-0 1433 1451 29.80% 25.84% 44.36% +0.7 2
1955-11-13 AB Gladsaxe L 2-5 1475 1519 35.73% 25.90% 38.37% -14.6 4
1955-11-13 @ AIA Tranbjerg W 5-2 1519 1475 38.37% 25.90% 35.73% +14.6 8
1955-11-13 Frem W 5-1 1463 1433 45.83% 25.79% 28.39% +18.2 8
1955-11-13 @ Esbjerg L 1-5 1433 1463 28.39% 25.79% 45.83% -18.2 2
1955-11-13 B 1903 L 1-3 1430 1413 44.24% 25.84% 29.92% -14.0 3
1955-11-13 @ KB Copenhagen W 3-1 1413 1430 29.92% 25.84% 44.24% +14.0 4
1955-11-13 Aarhus GF L 2-4 1454 1485 37.50% 25.92% 36.58% -11.0 4
1955-11-13 @ Koge BK W 4-2 1485 1454 36.58% 25.92% 37.50% +11.0 7
1955-11-13 B 1909 D 0-0 1450 1426 45.15% 25.81% 29.04% -0.7 5
1955-11-13 @ Skovshoved D 0-0 1426 1450 29.04% 25.81% 45.15% +0.7 5
1955-11-27 Skovshoved L 1-2 1533 1449 52.38% 25.37% 22.25% -9.4 8
1955-11-27 @ AB Gladsaxe W 2-1 1449 1533 22.25% 25.37% 52.38% +9.4 7
1955-11-27 KB Copenhagen D 2-2 1460 1416 47.68% 25.70% 26.62% -0.6 5
1955-11-27 @ AIA Tranbjerg D 2-2 1416 1460 26.62% 25.70% 47.68% +0.6 4
1955-11-27 Aarhus GF W 5-2 1427 1496 32.23% 25.82% 41.96% +16.4 7
1955-11-27 @ B 1909 L 2-5 1496 1427 41.96% 25.82% 32.23% -16.4 7
1955-11-27 B 1903 W 3-0 1415 1427 40.31% 25.92% 33.78% +19.1 4
1955-11-27 @ Frem L 0-3 1427 1415 33.78% 25.92% 40.31% -19.1 4
1955-11-27 Esbjerg L 1-2 1442 1481 36.53% 25.91% 37.56% -7.0 4
1955-11-27 @ Koge BK W 2-1 1481 1442 37.56% 25.91% 36.53% +7.0 10
1955-12-04 Frem W 4-0 1480 1434 47.86% 25.69% 26.45% +20.7 9
1955-12-04 @ Aarhus GF L 0-4 1434 1480 26.45% 25.69% 47.86% -20.7 4
1955-12-04 KB Copenhagen W 2-0 1524 1417 54.94% 25.10% 19.96% +8.6 10
1955-12-04 @ AB Gladsaxe L 0-2 1417 1524 19.96% 25.10% 54.94% -8.6 4
1955-12-04 Koge BK W 6-1 1443 1436 42.93% 25.88% 31.20% +24.0 9
1955-12-04 @ B 1909 L 1-6 1436 1443 31.20% 25.88% 42.93% -24.0 4
1955-12-04 Skovshoved W 3-1 1488 1459 45.78% 25.79% 28.43% +10.0 12
1955-12-04 @ Esbjerg L 1-3 1459 1488 28.43% 25.79% 45.78% -10.0 7
1955-12-04 AIA Tranbjerg D 3-3 1408 1459 34.63% 25.88% 39.48% +0.1 5
1955-12-04 @ B 1903 D 3-3 1459 1408 39.48% 25.88% 34.63% -0.1 6
1956-01-09 Aarhus GF W 3-1 1532 1500 46.15% 25.77% 28.07% +9.9 12
1956-01-09 @ AB Gladsaxe L 1-3 1500 1532 28.07% 25.77% 46.15% -9.9 9
1956-01-09 B 1909 L 3-4 1459 1467 40.86% 25.91% 33.23% -7.0 6
1956-01-09 @ AIA Tranbjerg W 4-3 1467 1459 33.23% 25.91% 40.86% +7.0 11
1956-01-09 B 1903 L 0-2 1498 1408 53.10% 25.30% 21.60% -19.0 12
1956-01-09 @ Esbjerg W 2-0 1408 1498 21.60% 25.30% 53.10% +19.0 7
1956-01-09 KB Copenhagen L 2-3 1413 1408 42.66% 25.88% 31.46% -7.5 4
1956-01-09 @ Frem W 3-2 1408 1413 31.46% 25.88% 42.66% +7.5 6
1956-01-09 Skovshoved L 1-2 1412 1449 36.69% 25.91% 37.39% -7.0 4
1956-01-09 @ Koge BK W 2-1 1449 1412 37.39% 25.91% 36.69% +7.0 9
1956-01-29 KB Copenhagen W 3-0 1456 1415 47.21% 25.72% 27.07% +16.1 11
1956-01-29 @ Skovshoved L 0-3 1415 1456 27.07% 25.72% 47.21% -16.1 6
1956-01-30 Esbjerg W 3-2 1490 1479 43.48% 25.86% 30.66% +5.8 11
1956-01-30 @ Aarhus GF L 2-3 1479 1490 30.66% 25.86% 43.48% -5.8 12
1956-01-30 AB Gladsaxe L 0-1 1474 1542 32.40% 25.82% 41.78% -6.8 11
1956-01-30 @ B 1909 W 1-0 1542 1474 41.78% 25.82% 32.40% +6.8 14
1956-01-30 Koge BK W 5-3 1427 1405 44.86% 25.82% 29.32% +8.6 9
1956-01-30 @ B 1903 L 3-5 1405 1427 29.32% 25.82% 44.86% -8.6 4
1956-01-30 AIA Tranbjerg W 1-0 1406 1452 35.41% 25.90% 38.69% +7.7 6
1956-01-30 @ Frem L 0-1 1452 1406 38.69% 25.90% 35.41% -7.7 6
1956-03-24 Frem L 0-3 1435 1414 44.80% 25.82% 29.38% -23.8 9
1956-03-24 @ B 1903 W 3-0 1414 1435 29.38% 25.82% 44.80% +23.8 8
1956-03-25 B 1909 W 7-0 1496 1467 45.76% 25.79% 28.45% +37.1 13
1956-03-25 @ Aarhus GF L 0-7 1467 1496 28.45% 25.79% 45.76% -37.1 11
1956-03-25 AIA Tranbjerg L 0-1 1399 1445 35.56% 25.90% 38.54% -7.2 6
1956-03-25 @ KB Copenhagen W 1-0 1445 1399 38.54% 25.90% 35.56% +7.2 8
1956-03-25 AB Gladsaxe D 2-2 1396 1549 22.39% 25.11% 52.50% +0.9 5
1956-03-25 @ Koge BK D 2-2 1549 1396 52.50% 25.11% 22.39% -0.9 15
1956-03-25 Esbjerg L 2-4 1472 1473 41.75% 25.90% 32.36% -12.0 11
1956-03-25 @ Skovshoved W 4-2 1473 1472 32.36% 25.90% 41.75% +12.0 14
1956-04-01 Skovshoved D 1-1 1452 1460 40.80% 25.91% 33.29% -0.3 9
1956-04-01 @ AIA Tranbjerg D 1-1 1460 1452 33.29% 25.91% 40.80% +0.3 12
1956-04-02 B 1903 L 1-4 1548 1411 57.92% 24.70% 17.38% -25.2 15
1956-04-02 @ AB Gladsaxe W 4-1 1411 1548 17.38% 24.70% 57.92% +25.2 11
1956-04-02 KB Copenhagen D 1-1 1430 1392 46.93% 25.74% 27.33% -0.8 12
1956-04-02 @ B 1909 D 1-1 1392 1430 27.33% 25.74% 46.93% +0.8 7
1956-04-02 Koge BK W 6-0 1485 1397 52.88% 25.32% 21.80% +25.9 16
1956-04-02 @ Esbjerg L 0-6 1397 1485 21.80% 25.32% 52.88% -25.8 5
1956-04-02 Aarhus GF L 0-2 1437 1533 28.85% 25.66% 45.49% -11.7 8
1956-04-02 @ Frem W 2-0 1533 1437 45.49% 25.66% 28.85% +11.6 15
1956-04-07 AB Gladsaxe L 1-3 1460 1523 33.14% 25.85% 41.01% -11.2 12
1956-04-07 @ Skovshoved W 3-1 1523 1460 41.01% 25.85% 33.14% +11.2 17
1956-04-08 AIA Tranbjerg W 3-1 1545 1451 53.46% 25.26% 21.27% +7.9 17
1956-04-08 @ Aarhus GF L 1-3 1451 1545 21.27% 25.26% 53.46% -7.9 9
1956-04-08 Esbjerg D 2-2 1437 1511 31.61% 25.79% 42.60% +0.3 12
1956-04-08 @ B 1903 D 2-2 1511 1437 42.60% 25.79% 31.61% -0.3 17
1956-04-08 Frem L 1-3 1393 1426 37.30% 25.92% 36.78% -12.3 7
1956-04-08 @ KB Copenhagen W 3-1 1426 1393 36.78% 25.92% 37.30% +12.3 10
1956-04-08 B 1909 D 1-1 1371 1429 33.74% 25.86% 40.40% +0.3 6
1956-04-08 @ Koge BK D 1-1 1429 1371 40.40% 25.86% 33.74% -0.3 13
1956-04-21 Koge BK W 4-1 1438 1371 50.43% 25.53% 24.05% +12.4 12
1956-04-21 @ Frem L 1-4 1371 1438 24.05% 25.53% 50.43% -12.3 6
1956-04-22 B 1909 L 0-4 1534 1429 54.71% 25.13% 20.16% -37.0 17
1956-04-22 @ AB Gladsaxe W 4-0 1429 1534 20.16% 25.13% 54.71% +37.0 15
1956-04-22 B 1903 W 4-0 1444 1437 42.81% 25.88% 31.31% +23.6 11
1956-04-22 @ AIA Tranbjerg L 0-4 1437 1444 31.31% 25.88% 42.81% -23.6 12
1956-04-22 Aarhus GF W 1-0 1511 1553 35.97% 25.90% 38.12% +7.6 19
1956-04-22 @ Esbjerg L 0-1 1553 1511 38.12% 25.90% 35.97% -7.6 17
1956-04-22 Skovshoved D 1-1 1381 1449 32.38% 25.82% 41.79% +0.4 8
1956-04-22 @ KB Copenhagen D 1-1 1449 1381 41.79% 25.82% 32.38% -0.4 13
1956-04-29 KB Copenhagen D 1-1 1545 1381 60.50% 24.27% 15.23% -2.0 18
1956-04-29 @ Aarhus GF D 1-1 1381 1545 15.23% 24.27% 60.50% +2.0 9
1956-04-29 AIA Tranbjerg W 3-2 1497 1467 45.90% 25.78% 28.32% +5.5 19
1956-04-29 @ AB Gladsaxe L 2-3 1467 1497 28.32% 25.78% 45.90% -5.5 11
1956-04-29 Skovshoved L 1-2 1466 1449 44.26% 25.84% 29.90% -8.1 15
1956-04-29 @ B 1909 W 2-1 1449 1466 29.90% 25.84% 44.26% +8.1 15
1956-04-29 Esbjerg W 3-1 1450 1518 32.47% 25.82% 41.71% +13.4 14
1956-04-29 @ Frem L 1-3 1518 1450 41.71% 25.82% 32.47% -13.4 19
1956-04-29 B 1903 L 0-1 1359 1413 34.27% 25.87% 39.85% -7.1 6
1956-04-29 @ Koge BK W 1-0 1413 1359 39.85% 25.87% 34.27% +7.0 14
1956-05-12 Koge BK L 0-1 1457 1352 54.69% 25.13% 20.18% -10.3 15
1956-05-12 @ Skovshoved W 1-0 1352 1457 20.18% 25.13% 54.69% +10.3 8
1956-05-13 Frem L 0-1 1462 1464 41.63% 25.90% 32.47% -8.2 11
1956-05-13 @ AIA Tranbjerg W 1-0 1464 1462 32.47% 25.90% 41.63% +8.2 16
1956-05-13 B 1909 D 1-1 1505 1458 48.02% 25.68% 26.30% -0.9 20
1956-05-13 @ Esbjerg D 1-1 1458 1505 26.30% 25.68% 48.02% +0.9 16
1956-05-13 Aarhus GF L 1-2 1420 1543 25.66% 25.44% 48.90% -5.3 14
1956-05-13 @ B 1903 W 2-1 1543 1420 48.90% 25.44% 25.66% +5.3 20
1956-05-13 AB Gladsaxe D 1-1 1383 1503 26.01% 25.47% 48.52% +0.9 10
1956-05-13 @ KB Copenhagen D 1-1 1503 1383 48.52% 25.47% 26.01% -0.9 20
1956-05-17 Frem D 1-1 1502 1472 45.86% 25.78% 28.35% -0.7 21
1956-05-17 @ AB Gladsaxe D 1-1 1472 1502 28.35% 25.78% 45.86% +0.7 17
1956-05-27 Koge BK W 2-0 1549 1362 62.42% 23.88% 13.71% +6.2 22
1956-05-27 @ Aarhus GF L 0-2 1362 1549 13.71% 23.88% 62.42% -6.2 8
1956-05-27 AIA Tranbjerg W 4-1 1459 1454 42.64% 25.88% 31.48% +15.3 18
1956-05-27 @ B 1909 L 1-4 1454 1459 31.48% 25.88% 42.64% -15.3 11
1956-05-27 AB Gladsaxe D 2-2 1504 1501 42.31% 25.89% 31.80% -0.3 21
1956-05-27 @ Esbjerg D 2-2 1501 1504 31.80% 25.89% 42.31% +0.3 22
1956-05-27 KB Copenhagen W 4-3 1415 1384 46.05% 25.78% 28.17% +5.3 16
1956-05-27 @ B 1903 L 3-4 1384 1415 28.17% 25.78% 46.05% -5.3 10
1956-05-27 Skovshoved D 0-0 1473 1446 45.41% 25.80% 28.78% -0.8 18
1956-05-27 @ Frem D 0-0 1446 1473 28.78% 25.80% 45.41% +0.8 16
1956-06-03 Esbjerg D 3-3 1438 1504 32.79% 25.83% 41.38% +0.2 12
1956-06-03 @ AIA Tranbjerg D 3-3 1504 1438 41.38% 25.83% 32.79% -0.2 22
1956-06-03 B 1909 W 3-0 1420 1474 34.38% 25.88% 39.74% +21.6 18
1956-06-03 @ B 1903 L 0-3 1474 1420 39.74% 25.88% 34.38% -21.6 18
1956-06-03 KB Copenhagen D 3-3 1356 1379 38.79% 25.92% 35.29% -0.1 9
1956-06-03 @ Koge BK D 3-3 1379 1356 35.29% 25.92% 38.79% +0.1 11
1956-06-03 Aarhus GF L 1-3 1447 1555 27.43% 25.57% 47.00% -9.7 16
1956-06-03 @ Skovshoved W 3-1 1555 1447 47.00% 25.57% 27.43% +9.7 24
1956-06-09 B 1903 W 2-1 1437 1442 41.29% 25.91% 32.81% +6.4 18
1956-06-09 @ Skovshoved L 1-2 1442 1437 32.81% 25.91% 41.29% -6.4 18
1956-06-10 AB Gladsaxe W 4-1 1564 1501 49.98% 25.56% 24.46% +12.5 26
1956-06-10 @ Aarhus GF L 1-4 1501 1564 24.46% 25.56% 49.98% -12.5 22
1956-06-10 Frem W 2-1 1453 1472 39.23% 25.92% 34.85% +6.7 20
1956-06-10 @ B 1909 L 1-2 1472 1453 34.85% 25.92% 39.23% -6.7 18
1956-06-10 Esbjerg W 1-0 1379 1503 25.43% 25.42% 49.15% +9.4 13
1956-06-10 @ KB Copenhagen L 0-1 1503 1379 49.15% 25.42% 25.43% -9.4 22
1956-06-10 AIA Tranbjerg L 1-5 1356 1438 30.54% 25.75% 43.71% -19.2 9
1956-06-10 @ Koge BK W 5-1 1438 1356 43.71% 25.75% 30.54% +19.2 14

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 1956-04-02 17.38% B 1903 1411 4 @ AB Gladsaxe 1548 1
2 1956-04-22 20.16% B 1909 1429 4 @ AB Gladsaxe 1534 0
3 1956-05-12 20.18% Koge BK 1352 1 @ Skovshoved 1457 0
4 1956-01-09 21.60% B 1903 1408 2 @ Esbjerg 1498 0
5 1955-11-27 22.25% Skovshoved 1449 2 @ AB Gladsaxe 1533 1
6 1955-09-18 23.61% Skovshoved 1433 2 @ Aarhus GF 1503 0
7 1955-08-27 25.17% Koge BK 1440 3 @ AB Gladsaxe 1497 1
8 1956-06-10 25.43% @ KB Copenhagen 1379 1 Esbjerg 1503 0
9 1956-03-24 29.38% Frem 1414 3 @ B 1903 1435 0
10 1956-04-29 29.90% Skovshoved 1449 2 @ B 1909 1466 1
11 1955-11-13 29.92% B 1903 1413 3 @ KB Copenhagen 1430 1
12 1956-01-09 31.46% KB Copenhagen 1408 3 @ Frem 1413 2
13 1955-11-27 32.23% @ B 1909 1427 5 Aarhus GF 1496 2
14 1956-03-25 32.36% Esbjerg 1473 4 @ Skovshoved 1472 2
15 1956-04-29 32.47% @ Frem 1450 3 Esbjerg 1518 1
16 1956-05-13 32.47% Frem 1464 1 @ AIA Tranbjerg 1462 0
17 1956-01-09 33.23% B 1909 1467 4 @ AIA Tranbjerg 1459 3
18 1955-08-21 33.60% Aarhus GF 1474 5 @ KB Copenhagen 1464 1
19 1956-06-03 34.38% @ B 1903 1420 3 B 1909 1474 0
20 1955-08-21 34.68% AB Gladsaxe 1477 6 @ Frem 1459 2
21 1956-01-30 35.41% @ Frem 1406 1 AIA Tranbjerg 1452 0
22 1955-08-20 35.58% Esbjerg 1450 3 @ B 1909 1425 2
23 1956-04-22 35.97% @ Esbjerg 1511 1 Aarhus GF 1553 0
24 1955-09-24 36.49% @ KB Copenhagen 1422 1 Koge BK 1461 0
25 1955-11-13 36.58% Aarhus GF 1485 4 @ Koge BK 1454 2

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 1956-03-25 37.10 @ Aarhus GF 7 1496 45.76% B 1909 0 1467 28.45% 25.79%
2 1956-04-22 36.98 B 1909 4 1429 20.16% @ AB Gladsaxe 0 1534 54.71% 25.13%
3 1956-04-02 25.85 @ Esbjerg 6 1485 52.88% Koge BK 0 1397 21.80% 25.32%
4 1956-04-02 25.16 B 1903 4 1411 17.38% @ AB Gladsaxe 1 1548 57.92% 24.70%
5 1955-12-04 24.00 @ B 1909 6 1443 42.93% Koge BK 1 1436 31.20% 25.88%
6 1955-08-21 23.85 Aarhus GF 5 1474 33.60% @ KB Copenhagen 1 1464 40.48% 25.91%
7 1956-03-24 23.77 Frem 3 1414 29.38% @ B 1903 0 1435 44.80% 25.82%
8 1956-04-22 23.58 @ AIA Tranbjerg 4 1444 42.81% B 1903 0 1437 31.31% 25.88%
9 1956-06-03 21.59 @ B 1903 3 1420 34.38% B 1909 0 1474 39.74% 25.88%
10 1955-12-04 20.67 @ Aarhus GF 4 1480 47.86% Frem 0 1434 26.45% 25.69%
11 1955-09-18 20.05 AB Gladsaxe 3 1481 38.07% @ B 1903 0 1439 36.02% 25.90%
12 1955-08-21 19.82 AB Gladsaxe 6 1477 34.68% @ Frem 2 1459 39.40% 25.92%
13 1956-06-10 19.25 AIA Tranbjerg 5 1438 43.71% @ Koge BK 1 1356 30.54% 25.75%
14 1955-11-27 19.12 @ Frem 3 1415 40.31% B 1903 0 1427 33.78% 25.92%
15 1956-01-09 18.97 B 1903 2 1408 21.60% @ Esbjerg 0 1498 53.10% 25.30%
16 1955-09-18 18.26 Skovshoved 2 1433 23.61% @ Aarhus GF 0 1503 50.90% 25.49%
17 1955-11-13 18.21 @ Esbjerg 5 1463 45.83% Frem 1 1433 28.39% 25.79%
18 1955-08-28 17.50 @ Esbjerg 3 1456 44.09% KB Copenhagen 0 1440 30.06% 25.85%
19 1955-09-25 17.19 @ AB Gladsaxe 3 1501 44.79% Esbjerg 0 1480 29.38% 25.82%
20 1955-11-27 16.44 @ B 1909 5 1427 32.23% Aarhus GF 2 1496 41.96% 25.82%
21 1956-01-29 16.12 @ Skovshoved 3 1456 47.21% KB Copenhagen 0 1415 27.07% 25.72%
22 1955-08-27 15.35 Koge BK 3 1440 25.17% @ AB Gladsaxe 1 1497 49.22% 25.61%
23 1956-05-27 15.28 @ B 1909 4 1459 42.64% AIA Tranbjerg 1 1454 31.48% 25.88%
24 1955-11-13 14.56 AB Gladsaxe 5 1519 38.37% @ AIA Tranbjerg 2 1475 35.73% 25.90%
25 1955-11-13 14.03 B 1903 3 1413 29.92% @ KB Copenhagen 1 1430 44.24% 25.84%