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1952-53 1st Division Season

90 games

Final

Champion

KB Copenhagen

30 points · 4th Title

Last Title: 1949-50

Relegated

B 1909

9 pts

Biggest Overachiever

KB Copenhagen

7.46 points above expected

30 points · 22.54 expected points

Biggest Disappointment

B 1909

5.12 points below expected

9 points · 14.12 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 KB Copenhagen Champion 18 14 2 2 30 43 25 +18 22.54 +7.46
2 Skovshoved 18 9 5 4 23 38 24 +14 19.69 +3.31
3 Odense 18 7 7 4 21 40 29 +11 19.25 +1.75
4 AB Gladsaxe 18 8 4 6 20 38 38 0 19.42 +0.58
5 Koge BK 18 7 4 7 18 51 43 +8 18.33 -0.33
6 B.93 18 7 3 8 17 30 32 -2 16.95 +0.05
7 Esbjerg 18 6 3 9 15 32 37 -5 17.01 -2.01
8 Frem 18 6 3 9 15 25 36 -11 16.51 -1.51
9 B 1903 18 6 0 12 12 26 41 -15 16.18 -4.18
10 B 1909 Relegated 18 2 5 11 9 27 45 -18 14.12 -5.12

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
KB Copenhagen 1524 30 22.54 +7.46 99.2% 10 17 20 23 25 28 34
Skovshoved 1486 23 19.69 +3.31 85.6% 7 14 17 20 22 26 31
Koge BK 1465 18 18.33 -0.33 51.5% 6 12 16 18 21 24 33
Odense 1463 21 19.25 +1.75 72.9% 7 13 17 19 22 25 32
AB Gladsaxe 1453 20 19.42 +0.58 61.6% 5 14 17 19 22 25 32
B.93 1417 17 16.95 +0.05 56.1% 4 11 15 17 19 23 30
Frem 1398 15 16.51 -1.51 39.1% 4 11 14 17 19 22 29
Esbjerg 1387 15 17.01 -2.01 33.9% 5 11 15 17 19 23 30
B 1903 1342 12 16.18 -4.18 14.8% 5 11 14 16 19 22 30
B 1909 1324 9 14.12 -5.12 8.7% 3 9 12 14 16 20 29

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 B1 B1 B.9 ESB FRE KC KB ODE SKO
AB Gladsaxe —
2-0-0
3.10
0-1-1
3.83
0-1-1
3.15
0-1-1
3.26
2-0-0
3.23
0-0-2
2.33
1-0-1
2.84
1-1-0
2.85
2-0-0
2.65
B 1903
0-0-2
2.48
 —
1-0-1
2.95
1-0-1
2.62
1-0-1
2.68
2-0-0
2.56
0-0-2
2.05
1-0-1
2.23
0-0-2
2.48
0-0-2
2.36
B 1909
1-1-0
1.76
1-0-1
2.64
 —
0-0-2
2.43
0-0-2
2.34
0-1-1
2.46
0-0-2
1.37
0-1-1
1.89
0-1-1
2.30
0-1-1
2.06
B.93
1-1-0
2.43
1-0-1
2.96
2-0-0
3.15
 —
1-0-1
2.70
0-0-2
2.94
0-0-2
2.02
1-1-0
2.58
1-0-1
2.30
0-1-1
2.40
Esbjerg
1-1-0
2.32
1-0-1
2.90
2-0-0
3.24
1-0-1
2.88
 —
0-0-2
2.88
0-0-2
2.03
1-0-1
2.63
0-1-1
2.49
0-1-1
2.36
Frem
0-0-2
2.35
0-0-2
3.02
1-1-0
3.11
2-0-0
2.64
2-0-0
2.70
 —
0-0-2
1.87
0-1-1
2.64
0-1-1
2.36
1-0-1
2.13
KB Copenhagen
2-0-0
3.25
2-0-0
3.54
2-0-0
4.23
2-0-0
3.56
2-0-0
3.56
2-0-0
3.72
 —
1-0-1
3.67
0-2-0
3.20
1-0-1
3.17
Koge BK
1-0-1
2.74
1-0-1
3.35
1-1-0
3.69
0-1-1
3.00
1-0-1
2.95
1-1-0
2.94
1-0-1
1.91
 —
1-0-1
2.50
0-1-1
2.59
Odense
0-1-1
2.72
2-0-0
3.10
1-1-0
3.29
1-0-1
3.27
1-1-0
3.09
1-1-0
3.22
0-2-0
2.38
1-0-1
3.08
 —
0-1-1
2.86
Skovshoved
0-0-2
2.93
2-0-0
3.22
1-1-0
3.52
1-1-0
3.18
1-1-0
3.22
1-0-1
3.45
1-0-1
2.41
1-1-0
2.98
1-1-0
2.72
 —

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 0.45 +4.7
Allowed 0.67 -6.6
Differential 0.86 +4.4

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
0—3.89%3.33%3.89%2.22%0.56%13.89%
13.89%8.89%10.00%3.89%2.22%0.56%29.44%
23.33%10.00%6.67%3.89%1.67%1.67%27.22%
33.89%3.89%3.89%2.22%0.56%1.67%16.11%
42.22%2.22%1.67%0.56%2.22%—8.89%
5+0.56%0.56%1.67%1.67%——4.44%
Total13.89%29.44%27.22%16.11%8.89%4.44%100%

Summary Statistics

Scored Allowed Difference
Mean 1.94 1.94 +0.00
SD 1.46 1.46 2.15
CV 0.75 0.75 —
Max 8 8 +7
Min 0 0 -7

Games Played: 90

↓ Scored | Allowed →012345+Total
0———————
1—5.56%11.11%11.11%5.56%—33.33%
2—22.22%5.56%—5.56%—33.33%
35.56%5.56%5.56%5.56%——22.22%
4———5.56%5.56%—11.11%
5+———————
Total5.56%33.33%22.22%22.22%16.67%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.11 2.11 +0.00
SD 1.02 1.23 1.57
CV 0.48 0.58 —
Max 4 4 +3
Min 1 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%11.11%11.11%——27.78%
15.56%—16.67%—5.56%—27.78%
25.56%5.56%—11.11%——22.22%
3——11.11%——5.56%16.67%
4——5.56%———5.56%
5+———————
Total11.11%11.11%44.44%22.22%5.56%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.44 2.28 -0.83
SD 1.25 1.56 1.82
CV 0.86 0.69 —
Max 4 7 +2
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0—11.11%—5.56%5.56%—22.22%
1—5.56%11.11%—5.56%—22.22%
25.56%5.56%16.67%11.11%—5.56%44.44%
3—————5.56%5.56%
4————5.56%—5.56%
5+———————
Total5.56%22.22%27.78%16.67%16.67%11.11%100%

Summary Statistics

Scored Allowed Difference
Mean 1.50 2.50 -1.00
SD 1.10 1.47 1.53
CV 0.73 0.59 —
Max 4 5 +2
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%11.11%5.56%5.56%—27.78%
1—5.56%11.11%———16.67%
2—5.56%11.11%——5.56%22.22%
311.11%11.11%5.56%———27.78%
4—5.56%————5.56%
5+———————
Total11.11%33.33%38.89%5.56%5.56%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.67 1.78 -0.11
SD 1.33 1.26 2.19
CV 0.80 0.71 —
Max 4 5 +3
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0———11.11%——11.11%
1—11.11%22.22%———33.33%
2—22.22%—5.56%5.56%—33.33%
3———5.56%—5.56%11.11%
45.56%—5.56%———11.11%
5+———————
Total5.56%33.33%27.78%22.22%5.56%5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 1.78 2.06 -0.28
SD 1.17 1.26 1.78
CV 0.66 0.61 —
Max 4 5 +4
Min 0 0 -3

Games Played: 18

↓ Scored | Allowed →012345+Total
0—11.11%5.56%5.56%——22.22%
111.11%5.56%11.11%——5.56%33.33%
2—11.11%11.11%5.56%—5.56%33.33%
35.56%—————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 1.39 2.00 -0.61
SD 1.09 2.06 2.35
CV 0.79 1.03 —
Max 4 8 +3
Min 0 0 -6

Games Played: 18

↓ Scored | Allowed →012345+Total
0—5.56%———5.56%11.11%
111.11%5.56%————16.67%
222.22%5.56%————27.78%
3—11.11%5.56%5.56%——22.22%
4—5.56%5.56%———11.11%
5+——5.56%5.56%——11.11%
Total33.33%33.33%16.67%11.11%—5.56%100%

Summary Statistics

Scored Allowed Difference
Mean 2.39 1.39 +1.00
SD 1.50 1.72 2.25
CV 0.63 1.24 —
Max 5 7 +3
Min 0 0 -7

Games Played: 18

↓ Scored | Allowed →012345+Total
0——5.56%—5.56%—11.11%
1——5.56%11.11%——16.67%
2——16.67%—5.56%—22.22%
35.56%5.56%5.56%—5.56%—22.22%
4————5.56%—5.56%
5+5.56%—5.56%11.11%——22.22%
Total11.11%5.56%38.89%22.22%22.22%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.83 2.39 +0.44
SD 2.09 1.24 2.68
CV 0.74 0.52 —
Max 7 4 +7
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0————5.56%—5.56%
1—27.78%5.56%5.56%——38.89%
2—5.56%5.56%5.56%——16.67%
311.11%5.56%5.56%5.56%——27.78%
4—5.56%————5.56%
5+——5.56%———5.56%
Total11.11%44.44%22.22%16.67%5.56%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.22 1.61 +0.61
SD 1.80 1.09 2.23
CV 0.81 0.68 —
Max 8 4 +6
Min 0 0 -4

Games Played: 18

↓ Scored | Allowed →012345+Total
0———————
111.11%22.22%5.56%11.11%5.56%—55.56%
2—16.67%————16.67%
3———————
416.67%———5.56%—22.22%
5+—5.56%————5.56%
Total27.78%44.44%5.56%11.11%11.11%—100%

Summary Statistics

Scored Allowed Difference
Mean 2.11 1.33 +0.78
SD 1.57 1.33 2.24
CV 0.74 1.00 —
Max 6 4 +5
Min 1 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 KB Copenhagen 30 22.54 +7.46
2 Skovshoved 23 19.69 +3.31
3 Odense 21 19.25 +1.75
4 AB Gladsaxe 20 19.42 +0.58
5 B.93 17 16.95 +0.05

Biggest Disappointments

# Team Actual Sim vsSim
1 B 1909 9 14.12 -5.12
2 B 1903 12 16.18 -4.18
3 Esbjerg 15 17.01 -2.01
4 Frem 15 16.51 -1.51
5 Koge BK 18 18.33 -0.33

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 KB Copenhagen 12 Aug 28 – Apr 25 1 in 1,483
2 Odense 5 Sep 14 – Nov 2 1 in 64
3 Skovshoved 5 Oct 25 – Apr 3 1 in 32
4 AB Gladsaxe 3 Aug 24 – Sep 13 1 in 21
5 Frem 3 Apr 15 – Apr 26 1 in 16

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 B 1909 5 Aug 24 – Oct 12 1 in 161
2 B 1903 6 Mar 22 – Apr 25 1 in 123
3 Frem 4 Sep 28 – Nov 2 1 in 45
4 Esbjerg 4 Sep 7 – Oct 25 1 in 16
5 B.93 3 Aug 24 – Sep 14 1 in 15

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 KB Copenhagen 14 Aug 16 – Apr 25 1 in 68
2 Skovshoved 9 Sep 27 – Apr 11 1 in 23
3 Esbjerg 5 Mar 29 – Apr 19 1 in 12
4 B 1909 3 May 3 – May 17 1 in 9
5 Odense 5 Sep 14 – Nov 2 1 in 8

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 B 1909 15 Aug 17 – Apr 26 1 in 252
2 AB Gladsaxe 3 Oct 26 – Nov 23 1 in 12
3 B 1903 6 Mar 22 – Apr 25 1 in 11
4 Odense 4 Nov 23 – Apr 6 1 in 10
5 B.93 4 Aug 24 – Sep 27 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
KB Copenhagen44.15%20.94%12.55%8.04%5.44%3.81%2.32%1.69%0.72%0.34%
Skovshoved14.85%17.36%15.04%12.85%11.61%8.84%7.26%5.85%4.25%2.09%
Odense11.60%15.35%14.63%13.66%12.18%9.85%8.47%6.91%4.53%2.82%
AB Gladsaxe10.70%14.20%14.66%13.43%12.03%11.10%9.03%6.99%5.14%2.72%
Koge BK7.31%11.26%13.10%12.47%12.01%11.37%10.62%9.28%7.44%5.14%
B.933.11%5.87%7.78%10.31%11.29%13.18%12.73%13.25%12.64%9.84%
Esbjerg3.29%5.75%8.32%10.24%11.28%12.02%12.93%13.71%12.45%10.01%
Frem2.58%4.37%6.35%8.69%10.37%11.64%13.34%13.92%14.59%14.15%
B 19031.96%3.65%5.54%7.07%9.01%11.46%13.14%14.72%17.69%15.76%
B 19090.45%1.25%2.03%3.24%4.78%6.73%10.16%13.68%20.55%37.13%

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
+20.00%
Clear Edge
50.00%20.00%30.00%
Elo Value
Home Edge
143 Elo
0.007 goals per Elo point
070.44400
Scoring Tilt
Expected
+0.71 goals
Home-Tilted
-2+0.49+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
4.0
Top-Heavy
124610
Champion Preseason Odds
44%
KB Copenhagen, 1st of 10
LongshotFavorite
Title Margin
Expected
0.39/gm
Tight Race
00.130.6/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 2.84 * Some Luck: 2.84 to 4.26 * Lucky: 4.26 to 5.68 * Wild Swing: 5.68 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 1.74 * Close: 1.74 to 2.62 * Off: 2.62 to 3.49 * Way Off: 3.49 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 0.63 * A Surprise: 0.63 to 1.01 * Several Surprises: 1.01 to 1.38 * Many Surprises: 1.38 and up.
Luck Spread
Expected
3.47 points
Some Luck
03.559
Average Finish Error
Expected
0.40
Pinpoint
02.185
Biggest Overachiever
Expected 95.00%
99.20%
KB Copenhagen
50100
Biggest Underachiever
Expected 5.00%
8.74%
B 1909
050
Season Outliers
Expected
1 of 10
Minimal Outliers
01.010
Unexpected Relegations
Expected
0 of 1
As Expected
00.61

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
0.17
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.40
Moderate Separation
01.003
Interquartile Edge
61%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline
76%
Clear Edge
50%77%100%
Close Games
Expected
57%
Very Frequent
0%51%100%
Blowouts
Expected
23%
Very Frequent
0%24%100%

Predictability

How these are measured

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

Brier Score
How close the pregame probabilities landed to the actual result, averaged over the season. Confident, correct calls are rewarded most; confident misses are punished most. Lower is better; since draws are possible, a score under 0.66 beats guessing the base rate.
Highly Predictable: under 0.56 * Predictable: 0.56 to 0.62 * Hard to Predict: 0.62 to 0.66 * Coin-Flip: 0.66 and up.
Matchup Imbalance
How lopsided the matchups were on paper, averaging the gap between the two win probabilities over their sum. 0 means every match was a toss-up; 1 means every match was a heavy favorite against a big underdog.
Very Even: under 0.1 * Slight Separation: 0.1 to 0.18 * Notable Separation: 0.18 to 0.28 * Lopsided: 0.28 and up.
Strangeness
How wild the final table was versus what the model expected. A value of 1 means teams landed about one standard deviation from their projections on average. Above 1 is a stranger season; below 1 hugged the projections.
Very Predictable: under 0.8 * As Expected: 0.8 to 1.1 * Wilder Than Modeled: 1.1 to 1.4 * Chaotic: 1.4 and up.
Repeatability
How closely the final table order matched the preseason Elo order, by Spearman rank correlation. Higher means last season's ratings strongly predicted this season's finish. Shows N/A for an inaugural season.
Weak Carryover: under 0.3 * Some Carryover: 0.3 to 0.6 * Strong Carryover: 0.6 to 0.85 * Near-Lock: 0.85 and up.
Upset Rate
Share of matches the underdog won. The gold line is how often the model expected underdogs to win; a dot to the right means upsets ran hotter than expected.
Chalky: under 25% * As Expected: 25% to 33% * Upset-Prone: 33% to 42% * Very Upset-Prone: 42% and up.
Clear Favorite Upset Rate
Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 15% * As Expected: 15% to 25% * Shaky Favorites: 25% to 35% * Very Shaky: 35% and up.
Brier Score
Expected
0.59
Predictable
00.602
Matchup Imbalance
0.34
Lopsided
00.10.180.280.5
Strangeness
Expected
0.99
As Expected
01.002
Repeatability
0.69
Strong Carryover
00.30.60.851
Upset Rate
Expected
30%
As Expected
0%26%50%
Clear Favorite Upset Rate
Expected
26%
Shaky Favorites
0%24%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 0.26 * Above Noise: 0.26 to 0.35 * Well Above Noise: 0.35 and up.
Probability calibration
0.72
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.30
Underconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.123
Well Within Noise
00.1740.4

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
KB Copenhagen 99.66% 0.34%
Skovshoved 97.91% 2.09%
AB Gladsaxe 97.28% 2.72%
Odense 97.18% 2.82%
Koge BK 94.86% 5.14%
B.93 90.16% 9.84%
Esbjerg 89.99% 10.01%
Frem 85.85% 14.15%
B 1903 84.24% 15.76%
B 1909 62.87% 37.13%

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
1952-08-16 KB Copenhagen L 2-3 1413 1469 46.24% 21.20% 32.56% -9.1 0
1952-08-16 @ B 1903 W 3-2 1469 1413 32.56% 21.20% 46.24% +9.1 2
1952-08-17 Esbjerg L 2-4 1460 1403 59.44% 20.85% 19.71% -18.8 0
1952-08-17 @ AB Gladsaxe W 4-2 1403 1460 19.71% 20.85% 59.44% +18.8 2
1952-08-17 B 1909 D 2-2 1416 1418 53.01% 21.11% 25.89% -1.0 1
1952-08-17 @ Frem D 2-2 1418 1416 25.89% 21.11% 53.01% +1.0 1
1952-08-17 Skovshoved D 1-1 1421 1419 53.60% 21.09% 25.31% -1.4 1
1952-08-17 @ Odense D 1-1 1419 1421 25.31% 21.09% 53.60% +1.4 1
1952-08-17 B.93 L 1-3 1428 1412 55.21% 21.04% 23.75% -19.6 0
1952-08-17 @ Koge BK W 3-1 1412 1428 23.75% 21.04% 55.21% +19.6 2
1952-08-23 Koge BK D 2-2 1415 1409 54.01% 21.08% 24.92% -1.1 2
1952-08-23 @ Frem D 2-2 1409 1415 24.92% 21.08% 54.01% +1.1 1
1952-08-24 B 1903 L 2-3 1419 1404 55.11% 21.04% 23.85% -10.7 1
1952-08-24 @ B 1909 W 3-2 1404 1419 23.85% 21.04% 55.11% +10.7 2
1952-08-24 B.93 W 2-1 1422 1431 52.17% 21.13% 26.70% +6.2 4
1952-08-24 @ Esbjerg L 1-2 1431 1422 26.70% 21.13% 52.17% -6.1 2
1952-08-24 Odense D 3-3 1478 1420 59.55% 20.84% 19.61% -1.3 3
1952-08-24 @ KB Copenhagen D 3-3 1420 1478 19.61% 20.84% 59.55% +1.3 2
1952-08-24 AB Gladsaxe L 1-2 1420 1441 50.72% 21.15% 28.13% -10.4 1
1952-08-24 @ Skovshoved W 2-1 1441 1420 28.13% 21.15% 50.72% +10.4 2
1952-08-28 Koge BK W 2-0 1477 1410 60.38% 20.79% 18.83% +9.1 5
1952-08-28 @ KB Copenhagen L 0-2 1410 1477 18.83% 20.79% 60.38% -9.1 1
1952-09-06 Frem W 1-0 1486 1414 60.86% 20.76% 18.38% +4.7 7
1952-09-06 @ KB Copenhagen L 0-1 1414 1486 18.38% 20.76% 60.86% -4.7 2
1952-09-07 B.93 W 2-0 1414 1425 52.01% 21.13% 26.86% +12.4 4
1952-09-07 @ B 1903 L 0-2 1425 1414 26.86% 21.13% 52.01% -12.4 2
1952-09-07 B 1909 W 4-0 1409 1409 53.37% 21.10% 25.54% +22.5 3
1952-09-07 @ Skovshoved L 0-4 1409 1409 25.54% 21.10% 53.37% -22.5 1
1952-09-07 Esbjerg W 5-3 1401 1428 50.02% 21.17% 28.81% +9.6 3
1952-09-07 @ Koge BK L 3-5 1428 1401 28.81% 21.17% 50.02% -9.6 4
1952-09-07 AB Gladsaxe L 1-2 1421 1452 49.57% 21.17% 29.26% -10.2 2
1952-09-07 @ Odense W 2-1 1452 1421 29.26% 21.17% 49.57% +10.2 4
1952-09-13 B 1903 W 3-0 1462 1427 57.22% 20.96% 21.82% +15.1 6
1952-09-13 @ AB Gladsaxe L 0-3 1427 1462 21.82% 20.96% 57.22% -15.1 4
1952-09-14 Odense L 1-4 1386 1411 50.32% 21.16% 28.52% -25.4 1
1952-09-14 @ B 1909 W 4-1 1411 1386 28.52% 21.16% 50.32% +25.4 4
1952-09-14 Frem L 0-3 1413 1409 53.67% 21.09% 25.25% -31.9 2
1952-09-14 @ B.93 W 3-0 1409 1413 25.25% 21.09% 53.67% +32.0 4
1952-09-14 Skovshoved W 3-1 1491 1432 59.59% 20.84% 19.57% +8.2 9
1952-09-14 @ KB Copenhagen L 1-3 1432 1491 19.57% 20.84% 59.59% -8.2 3
1952-09-27 Skovshoved D 1-1 1381 1424 47.97% 21.19% 30.84% -0.8 3
1952-09-27 @ B.93 D 1-1 1424 1381 30.84% 21.19% 47.97% +0.8 4
1952-09-28 B 1903 L 1-2 1441 1412 56.62% 20.98% 22.40% -11.6 4
1952-09-28 @ Frem W 2-1 1412 1441 22.40% 20.98% 56.62% +11.6 6
1952-09-28 AB Gladsaxe W 3-1 1499 1477 55.76% 21.02% 23.22% +9.5 11
1952-09-28 @ KB Copenhagen L 1-3 1477 1499 23.22% 21.02% 55.76% -9.5 6
1952-09-28 B 1909 W 5-2 1410 1361 58.68% 20.89% 20.43% +10.4 5
1952-09-28 @ Koge BK L 2-5 1361 1410 20.43% 20.89% 58.68% -10.4 1
1952-09-28 Esbjerg W 3-0 1436 1418 55.34% 21.03% 23.62% +16.1 6
1952-09-28 @ Odense L 0-3 1418 1436 23.62% 21.03% 55.34% -16.1 4
1952-10-11 AB Gladsaxe L 1-2 1430 1468 48.65% 21.19% 30.17% -10.1 4
1952-10-11 @ Frem W 2-1 1468 1430 30.17% 21.19% 48.65% +10.1 8
1952-10-12 B.93 L 0-3 1350 1380 49.73% 21.17% 29.10% -29.8 1
1952-10-12 @ B 1909 W 3-0 1380 1350 29.10% 21.17% 49.73% +29.8 5
1952-10-12 KB Copenhagen L 1-2 1402 1508 39.33% 21.18% 39.49% -8.4 4
1952-10-12 @ Esbjerg W 2-1 1508 1402 39.49% 21.18% 39.33% +8.4 13
1952-10-12 Odense L 2-3 1423 1452 49.73% 21.17% 29.10% -9.7 6
1952-10-12 @ B 1903 W 3-2 1452 1423 29.10% 21.17% 49.73% +9.7 8
1952-10-12 Koge BK D 4-4 1425 1421 53.73% 21.09% 25.19% -0.8 5
1952-10-12 @ Skovshoved D 4-4 1421 1425 25.19% 21.09% 53.73% +0.8 6
1952-10-25 KB Copenhagen L 2-5 1410 1517 39.20% 21.18% 39.63% -17.8 5
1952-10-25 @ B.93 W 5-2 1517 1410 39.63% 21.18% 39.20% +17.8 15
1952-10-25 Esbjerg W 2-1 1424 1394 56.67% 20.98% 22.35% +5.3 7
1952-10-25 @ Skovshoved L 1-2 1394 1424 22.35% 20.98% 56.67% -5.3 4
1952-10-26 B 1909 D 4-4 1478 1321 67.79% 20.09% 12.12% -1.6 9
1952-10-26 @ AB Gladsaxe D 4-4 1321 1478 12.12% 20.09% 67.79% +1.6 2
1952-10-26 B 1903 W 7-3 1422 1413 54.24% 21.07% 24.69% +14.1 8
1952-10-26 @ Koge BK L 3-7 1413 1422 24.69% 21.07% 54.24% -14.1 6
1952-10-26 Frem W 8-2 1462 1420 57.96% 20.92% 21.11% +19.1 10
1952-10-26 @ Odense L 2-8 1420 1462 21.11% 20.92% 57.96% -19.1 4
1952-11-02 B.93 L 1-2 1476 1392 61.99% 20.68% 17.33% -12.6 9
1952-11-02 @ AB Gladsaxe W 2-1 1392 1476 17.33% 20.68% 61.99% +12.6 7
1952-11-02 B 1909 W 2-1 1388 1322 60.31% 20.79% 18.90% +4.6 6
1952-11-02 @ Esbjerg L 1-2 1322 1388 18.90% 20.79% 60.31% -4.6 2
1952-11-02 Koge BK W 3-1 1481 1436 58.27% 20.91% 20.82% +8.6 12
1952-11-02 @ Odense L 1-3 1436 1481 20.82% 20.91% 58.27% -8.6 8
1952-11-02 Frem W 6-1 1429 1400 56.50% 20.99% 22.51% +20.6 9
1952-11-02 @ Skovshoved L 1-6 1400 1429 22.51% 20.99% 56.50% -20.6 4
1952-11-16 KB Copenhagen L 0-1 1318 1535 25.15% 20.73% 54.12% -6.2 2
1952-11-16 @ B 1909 W 1-0 1535 1318 54.12% 20.73% 25.15% +6.2 17
1952-11-16 Esbjerg W 2-1 1380 1393 51.73% 21.14% 27.14% +6.2 6
1952-11-16 @ Frem L 1-2 1393 1380 27.14% 21.14% 51.73% -6.2 6
1952-11-23 Odense W 3-1 1404 1490 42.27% 21.20% 36.53% +13.8 9
1952-11-23 @ B.93 L 1-3 1490 1404 36.53% 21.20% 42.27% -13.8 12
1952-11-23 AB Gladsaxe W 3-1 1427 1463 48.85% 21.18% 29.97% +11.7 10
1952-11-23 @ Koge BK L 1-3 1463 1427 29.97% 21.18% 48.85% -11.7 9
1952-11-23 B 1903 L 2-3 1387 1399 51.80% 21.13% 27.06% -10.1 6
1952-11-23 @ Esbjerg W 3-2 1399 1387 27.06% 21.13% 51.80% +10.1 8
1953-03-22 Skovshoved L 1-2 1409 1450 48.31% 21.19% 30.50% -10.0 8
1953-03-22 @ B 1903 W 2-1 1450 1409 30.50% 21.19% 48.31% +10.0 11
1953-03-28 B.93 W 2-0 1541 1418 65.23% 20.39% 14.38% +7.2 19
1953-03-28 @ KB Copenhagen L 0-2 1418 1541 14.38% 20.39% 65.23% -7.2 9
1953-03-29 Esbjerg L 1-2 1312 1377 45.07% 21.21% 33.73% -9.4 2
1953-03-29 @ B 1909 W 2-1 1377 1312 33.73% 21.21% 45.07% +9.4 8
1953-03-29 AB Gladsaxe L 1-2 1399 1452 46.77% 21.20% 32.03% -9.7 8
1953-03-29 @ B 1903 W 2-1 1452 1399 32.03% 21.20% 46.77% +9.7 11
1953-03-29 Frem W 3-0 1439 1386 59.00% 20.87% 20.13% +14.1 12
1953-03-29 @ Koge BK L 0-3 1386 1439 20.13% 20.87% 59.00% -14.0 6
1953-03-29 Odense W 4-0 1460 1476 51.34% 21.14% 27.52% +24.0 13
1953-03-29 @ Skovshoved L 0-4 1476 1460 27.52% 21.14% 51.34% -24.0 12
1953-04-02 Koge BK D 2-2 1411 1453 48.14% 21.19% 30.67% -0.6 10
1953-04-02 @ B.93 D 2-2 1453 1411 30.67% 21.19% 48.14% +0.6 13
1953-04-02 AB Gladsaxe D 3-3 1386 1461 43.67% 21.21% 35.12% -0.2 9
1953-04-02 @ Esbjerg D 3-3 1461 1386 35.12% 21.21% 43.67% +0.2 12
1953-04-02 KB Copenhagen L 0-2 1372 1548 29.97% 20.96% 49.07% -13.5 6
1953-04-02 @ Frem W 2-0 1548 1372 49.07% 20.96% 29.97% +13.5 21
1953-04-02 B 1909 D 2-2 1452 1302 67.30% 20.15% 12.55% -2.2 13
1953-04-02 @ Odense D 2-2 1302 1452 12.55% 20.15% 67.30% +2.2 3
1953-04-03 B 1903 W 1-0 1484 1390 62.87% 20.61% 16.52% +4.3 15
1953-04-03 @ Skovshoved L 0-1 1390 1484 16.52% 20.61% 62.87% -4.3 8
1953-04-06 Skovshoved D 1-1 1304 1488 28.99% 20.92% 50.08% +1.0 4
1953-04-06 @ B 1909 D 1-1 1488 1304 50.08% 20.92% 28.99% -1.0 16
1953-04-06 Odense D 1-1 1386 1450 45.18% 21.21% 33.61% -0.5 10
1953-04-06 @ Esbjerg D 1-1 1450 1386 33.61% 21.21% 45.18% +0.5 14
1953-04-11 B.93 W 4-0 1487 1410 61.30% 20.73% 17.97% +16.6 18
1953-04-11 @ Skovshoved L 0-4 1410 1487 17.97% 20.73% 61.30% -16.6 10
1953-04-12 Frem W 3-2 1462 1359 63.64% 20.55% 15.82% +3.7 14
1953-04-12 @ AB Gladsaxe L 2-3 1359 1462 15.82% 20.55% 63.64% -3.7 6
1953-04-12 Koge BK W 4-0 1385 1454 44.64% 21.21% 34.16% +28.6 12
1953-04-12 @ Esbjerg L 0-4 1454 1385 34.16% 21.21% 44.64% -28.6 13
1953-04-12 B 1903 W 3-0 1451 1385 60.23% 20.80% 18.97% +13.3 16
1953-04-12 @ Odense L 0-3 1385 1451 18.97% 20.80% 60.23% -13.3 8
1953-04-12 B 1909 W 5-3 1561 1305 73.68% 18.98% 7.34% +2.7 23
1953-04-12 @ KB Copenhagen L 3-5 1305 1561 7.34% 18.98% 73.68% -2.7 4
1953-04-15 B.93 W 1-0 1355 1394 48.51% 21.19% 30.31% +7.2 8
1953-04-15 @ Frem L 0-1 1394 1355 30.31% 21.19% 48.51% -7.2 10
1953-04-16 KB Copenhagen L 1-4 1465 1564 40.38% 21.19% 38.43% -21.1 14
1953-04-16 @ AB Gladsaxe W 4-1 1564 1465 38.43% 21.19% 40.38% +21.1 25
1953-04-18 Skovshoved W 4-1 1362 1504 34.42% 21.10% 44.49% +22.8 10
1953-04-18 @ Frem L 1-4 1504 1362 44.49% 21.10% 34.42% -22.8 18
1953-04-18 Odense W 3-2 1425 1464 48.51% 21.19% 30.31% +6.5 15
1953-04-18 @ Koge BK L 2-3 1464 1425 30.31% 21.19% 48.51% -6.5 16
1953-04-19 B 1909 W 3-2 1387 1303 61.97% 20.68% 17.35% +4.0 12
1953-04-19 @ B.93 L 2-3 1303 1387 17.35% 20.68% 61.97% -4.0 4
1953-04-19 Esbjerg L 1-2 1372 1414 48.14% 21.19% 30.67% -10.0 8
1953-04-19 @ B 1903 W 2-1 1414 1372 30.67% 21.19% 48.14% +10.0 14
1953-04-25 B 1903 W 2-0 1585 1362 71.94% 19.38% 8.68% +4.4 27
1953-04-25 @ KB Copenhagen L 0-2 1362 1585 8.68% 19.38% 71.94% -4.4 8
1953-04-26 Odense D 1-1 1444 1457 51.72% 21.14% 27.14% -1.2 15
1953-04-26 @ AB Gladsaxe D 1-1 1457 1444 27.14% 21.14% 51.72% +1.2 17
1953-04-26 Frem L 0-1 1299 1385 42.14% 21.20% 36.65% -9.4 4
1953-04-26 @ B 1909 W 1-0 1385 1299 36.65% 21.20% 42.14% +9.4 12
1953-04-26 Esbjerg W 3-0 1391 1424 49.24% 21.18% 29.58% +19.5 14
1953-04-26 @ B.93 L 0-3 1424 1391 29.58% 21.18% 49.24% -19.5 14
1953-04-26 Skovshoved L 1-2 1431 1481 47.15% 21.20% 31.65% -9.8 15
1953-04-26 @ Koge BK W 2-1 1481 1431 31.65% 21.20% 47.15% +9.8 20
1953-04-30 Frem W 1-0 1358 1394 48.79% 21.18% 30.02% +7.2 10
1953-04-30 @ B 1903 L 0-1 1394 1358 30.02% 21.18% 48.79% -7.2 12
1953-05-01 B.93 W 2-1 1459 1410 58.58% 20.89% 20.53% +4.9 19
1953-05-01 @ Odense L 1-2 1410 1459 20.53% 20.89% 58.58% -4.9 14
1953-05-03 AB Gladsaxe W 2-1 1289 1443 32.77% 21.05% 46.18% +9.6 6
1953-05-03 @ B 1909 L 1-2 1443 1289 46.18% 21.05% 32.77% -9.6 15
1953-05-03 Skovshoved D 1-1 1404 1491 42.15% 21.20% 36.65% -0.3 15
1953-05-03 @ Esbjerg D 1-1 1491 1404 36.65% 21.20% 42.15% +0.3 21
1953-05-03 KB Copenhagen W 7-0 1422 1590 30.95% 21.00% 48.05% +63.9 17
1953-05-03 @ Koge BK L 0-7 1590 1422 48.05% 21.00% 30.95% -63.9 27
1953-05-08 B 1903 W 4-1 1405 1365 57.74% 20.94% 21.33% +12.4 16
1953-05-08 @ B.93 L 1-4 1365 1405 21.33% 20.94% 57.74% -12.5 10
1953-05-09 Skovshoved W 3-1 1433 1491 46.09% 21.21% 32.70% +12.6 17
1953-05-09 @ AB Gladsaxe L 1-3 1491 1433 32.70% 21.21% 46.09% -12.6 21
1953-05-10 Koge BK D 2-2 1299 1485 28.63% 20.91% 50.46% +0.8 7
1953-05-10 @ B 1909 D 2-2 1485 1299 50.46% 20.91% 28.63% -0.8 18
1953-05-10 Odense D 1-1 1387 1464 43.52% 21.21% 35.27% -0.4 13
1953-05-10 @ Frem D 1-1 1464 1387 35.27% 21.21% 43.52% +0.4 20
1953-05-10 Esbjerg W 4-2 1526 1404 65.16% 20.40% 14.44% +5.5 29
1953-05-10 @ KB Copenhagen L 2-4 1404 1526 14.44% 20.40% 65.16% -5.6 15
1953-05-13 AB Gladsaxe D 2-2 1418 1446 49.84% 21.17% 28.99% -0.8 17
1953-05-13 @ B.93 D 2-2 1446 1418 28.99% 21.17% 49.84% +0.8 18
1953-05-14 Koge BK W 4-2 1352 1485 35.66% 21.12% 43.21% +14.1 12
1953-05-14 @ B 1903 L 2-4 1485 1352 43.21% 21.12% 35.66% -14.1 18
1953-05-14 KB Copenhagen W 1-0 1478 1531 46.68% 21.20% 32.12% +7.6 23
1953-05-14 @ Skovshoved L 0-1 1531 1478 32.12% 21.20% 46.68% -7.6 29
1953-05-17 Koge BK W 4-3 1447 1471 50.42% 21.16% 28.42% +6.0 20
1953-05-17 @ AB Gladsaxe L 3-4 1471 1447 28.42% 21.16% 50.42% -6.0 18
1953-05-17 Frem L 1-2 1399 1387 54.64% 21.06% 24.30% -11.2 15
1953-05-17 @ Esbjerg W 2-1 1387 1399 24.30% 21.06% 54.64% +11.2 15
1953-05-17 B 1909 L 0-2 1366 1300 60.38% 20.79% 18.83% -24.6 12
1953-05-17 @ B 1903 W 2-0 1300 1366 18.83% 20.79% 60.38% +24.6 9
1953-05-17 KB Copenhagen D 1-1 1464 1524 45.78% 21.21% 33.02% -0.6 21
1953-05-17 @ Odense D 1-1 1524 1464 33.02% 21.21% 45.78% +0.6 30

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 1952-11-02 17.33% B.93 1392 2 @ AB Gladsaxe 1476 1
2 1953-05-17 18.83% B 1909 1300 2 @ B 1903 1366 0
3 1952-08-17 19.71% Esbjerg 1403 4 @ AB Gladsaxe 1460 2
4 1952-09-28 22.40% B 1903 1412 2 @ Frem 1441 1
5 1952-08-17 23.75% B.93 1412 3 @ Koge BK 1428 1
6 1952-08-24 23.85% B 1903 1404 3 @ B 1909 1419 2
7 1953-05-17 24.30% Frem 1387 2 @ Esbjerg 1399 1
8 1952-09-14 25.25% Frem 1409 3 @ B.93 1413 0
9 1952-11-23 27.06% B 1903 1399 3 @ Esbjerg 1387 2
10 1952-08-24 28.13% AB Gladsaxe 1441 2 @ Skovshoved 1420 1
11 1952-09-14 28.52% Odense 1411 4 @ B 1909 1386 1
12 1952-10-12 29.10% B.93 1380 3 @ B 1909 1350 0
13 1952-10-12 29.10% Odense 1452 3 @ B 1903 1423 2
14 1952-09-07 29.26% AB Gladsaxe 1452 2 @ Odense 1421 1
15 1952-10-11 30.17% AB Gladsaxe 1468 2 @ Frem 1430 1
16 1953-03-22 30.50% Skovshoved 1450 2 @ B 1903 1409 1
17 1953-04-19 30.67% Esbjerg 1414 2 @ B 1903 1372 1
18 1953-05-03 30.95% @ Koge BK 1422 7 KB Copenhagen 1590 0
19 1953-04-26 31.65% Skovshoved 1481 2 @ Koge BK 1431 1
20 1953-03-29 32.03% AB Gladsaxe 1452 2 @ B 1903 1399 1
21 1952-08-16 32.56% KB Copenhagen 1469 3 @ B 1903 1413 2
22 1953-05-03 32.77% @ B 1909 1289 2 AB Gladsaxe 1443 1
23 1953-03-29 33.73% Esbjerg 1377 2 @ B 1909 1312 1
24 1953-04-18 34.42% @ Frem 1362 4 Skovshoved 1504 1
25 1953-05-14 35.66% @ B 1903 1352 4 Koge BK 1485 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 1953-05-03 63.87 @ Koge BK 7 1422 30.95% KB Copenhagen 0 1590 48.05% 21.00%
2 1952-09-14 31.95 Frem 3 1409 25.25% @ B.93 0 1413 53.67% 21.09%
3 1952-10-12 29.80 B.93 3 1380 29.10% @ B 1909 0 1350 49.73% 21.17%
4 1953-04-12 28.58 @ Esbjerg 4 1385 44.64% Koge BK 0 1454 34.16% 21.21%
5 1952-09-14 25.40 Odense 4 1411 28.52% @ B 1909 1 1386 50.32% 21.16%
6 1953-05-17 24.63 B 1909 2 1300 18.83% @ B 1903 0 1366 60.38% 20.79%
7 1953-03-29 23.96 @ Skovshoved 4 1460 51.34% Odense 0 1476 27.52% 21.14%
8 1953-04-18 22.79 @ Frem 4 1362 34.42% Skovshoved 1 1504 44.49% 21.10%
9 1952-09-07 22.51 @ Skovshoved 4 1409 53.37% B 1909 0 1409 25.54% 21.10%
10 1953-04-16 21.07 KB Copenhagen 4 1564 38.43% @ AB Gladsaxe 1 1465 40.38% 21.19%
11 1952-11-02 20.63 @ Skovshoved 6 1429 56.50% Frem 1 1400 22.51% 20.99%
12 1952-08-17 19.56 B.93 3 1412 23.75% @ Koge BK 1 1428 55.21% 21.04%
13 1953-04-26 19.47 @ B.93 3 1391 49.24% Esbjerg 0 1424 29.58% 21.18%
14 1952-10-26 19.13 @ Odense 8 1462 57.96% Frem 2 1420 21.11% 20.92%
15 1952-08-17 18.78 Esbjerg 4 1403 19.71% @ AB Gladsaxe 2 1460 59.44% 20.85%
16 1952-10-25 17.82 KB Copenhagen 5 1517 39.63% @ B.93 2 1410 39.20% 21.18%
17 1953-04-11 16.61 @ Skovshoved 4 1487 61.30% B.93 0 1410 17.97% 20.73%
18 1952-09-28 16.13 @ Odense 3 1436 55.34% Esbjerg 0 1418 23.62% 21.03%
19 1952-09-13 15.07 @ AB Gladsaxe 3 1462 57.22% B 1903 0 1427 21.82% 20.96%
20 1952-10-26 14.12 @ Koge BK 7 1422 54.24% B 1903 3 1413 24.69% 21.07%
21 1953-05-14 14.07 @ B 1903 4 1352 35.66% Koge BK 2 1485 43.21% 21.12%
22 1953-03-29 14.05 @ Koge BK 3 1439 59.00% Frem 0 1386 20.13% 20.87%
23 1952-11-23 13.76 @ B.93 3 1404 42.27% Odense 1 1490 36.53% 21.20%
24 1953-04-02 13.50 KB Copenhagen 2 1548 49.07% @ Frem 0 1372 29.97% 20.96%
25 1953-04-12 13.34 @ Odense 3 1451 60.23% B 1903 0 1385 18.97% 20.80%