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2014-15 Superliga Season

198 games

Final

Champion

Midtjylland

71 points · 1st Title

Relegated

Silkeborg

14 pts

FC Vestsjaelland · 33 pts

Biggest Overachiever

FC Copenhagen

11.59 points above expected

67 points · 55.41 expected points

Biggest Disappointment

Silkeborg

16.23 points below expected

14 points · 30.23 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 Midtjylland Champion 33 22 5 6 71 64 34 +30 59.88 +11.12
2 FC Copenhagen 33 20 7 6 67 40 22 +18 55.41 +11.59
3 Brondby 33 16 7 10 55 43 29 +14 50.34 +4.66
4 Randers 33 14 10 9 52 39 28 +11 47.31 +4.69
5 Aalborg 33 13 9 11 48 39 31 +8 52.15 -4.15
6 Nordsjaelland 33 13 5 15 44 39 44 -5 45.31 -1.31
7 Hobro 33 11 10 12 43 40 47 -7 38.05 +4.95
8 Esbjerg 33 10 10 13 40 47 45 +2 47.40 -7.40
9 Odense 33 11 7 15 40 35 43 -8 42.32 -2.32
10 Sonderjyske 33 7 16 10 37 35 44 -9 41.59 -4.59
11 Vestsjaelland 33 9 6 18 33 31 52 -21 33.78 -0.78
12 Silkeborg Relegated 33 2 8 23 14 26 59 -33 30.23 -16.23

Going into Phase 2, the championship group halved its Phase 1 points (rounded up); the relegation group kept its full Phase 1 points. Each group then played its own round-robin to determine final standings.

Form

Each team's 5-game rolling points-per-game across the season. Hot streaks push above the dashed 1.5 PPG reference line; cold spells drop below. Each team gets a distinct color; the legend below the plot lets you read off which line is which. (First 4 games of each team have no rolling window, so the lines start at game 5.)

League Race

Cumulative points across the season for each team. Highlighted teams are drawn in color (top finishers for the Title Race, bottom finishers for the Relegation Race); the rest of the league appears in light gray as context. Switch views with the buttons below.

Season Summary

Every team's regular-season finish compared against 100,000 simulations. Click any column header to sort. Luck is the team's actual points minus the sim's mean — positive means the team beat the model. Percentile is where the actual result fell in the team's sim distribution (e.g. 90% = the team did this well or better in only 10% of sims).

Team Elo Points Avg Luck Percentile Min 5th Q1 Median Q3 95th Max
Midtjylland 1681 71 59.88 +11.12 95.1% 33 48 55 60 65 71 85
FC Copenhagen 1661 67 55.41 +11.59 95.3% 27 43 50 56 60 67 83
Brondby 1612 55 50.34 +4.66 76.0% 19 38 45 50 55 62 79
Randers 1607 52 47.31 +4.69 76.5% 22 36 42 47 52 59 73
Aalborg 1597 48 52.15 -4.15 30.9% 24 40 47 52 57 64 79
Esbjerg 1555 40 47.40 -7.40 17.2% 17 35 43 47 52 59 76
Odense 1521 40 42.32 -2.32 40.7% 14 31 37 42 47 55 70
Nordsjaelland 1519 44 45.31 -1.31 46.2% 22 34 40 45 50 57 74
Sonderjyske 1486 37 41.59 -4.59 29.0% 13 30 37 42 46 53 69
Hobro 1485 43 38.05 +4.95 77.7% 14 26 33 38 43 50 64
Vestsjaelland 1442 33 33.78 -0.78 49.4% 11 23 29 34 38 45 59
Silkeborg 1373 14 30.23 -16.23 0.7% 8 19 26 30 35 41 57

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 BRO ESB FC HOB MID NOR ODE RAN SIL SON VES
Aalborg —
1-1-1
4.09
2-1-0
4.64
1-0-2
4.13
1-1-1
5.36
1-0-2
3.61
2-0-1
4.85
0-2-1
4.82
1-2-0
4.60
2-1-0
5.75
1-1-1
4.78
1-0-2
5.43
Brondby
1-1-1
4.11
 —
0-2-1
4.30
0-1-2
3.32
0-0-3
5.13
1-1-1
3.09
2-0-1
4.39
2-1-0
4.84
1-1-1
4.80
3-0-0
5.85
3-0-0
4.80
3-0-0
5.68
Esbjerg
0-1-2
3.58
1-2-0
3.92
 —
0-0-3
3.12
1-1-1
4.64
0-1-2
2.85
1-1-1
4.10
2-0-1
4.78
0-1-2
4.52
2-1-0
5.74
0-2-1
4.90
3-0-0
5.23
FC Copenhagen
2-0-1
4.09
2-1-0
4.90
3-0-0
5.11
 —
2-0-1
5.73
1-0-2
3.81
2-1-0
5.16
2-0-1
4.94
1-1-1
5.15
2-1-0
5.78
1-2-0
5.05
2-1-0
5.78
Hobro
1-1-1
2.89
3-0-0
3.10
1-1-1
3.57
1-0-2
2.56
 —
0-1-2
2.63
1-1-1
3.84
1-1-1
3.32
1-0-2
2.96
1-2-0
4.73
0-2-1
3.74
1-1-1
4.74
Midtjylland
2-0-1
4.61
1-1-1
5.13
2-1-0
5.39
2-0-1
4.39
2-1-0
5.65
 —
1-0-2
5.28
2-0-1
5.90
3-0-0
5.28
3-0-0
6.66
2-1-0
5.22
2-1-0
6.43
Nordsjaelland
1-0-2
3.37
1-0-2
3.83
1-1-1
4.11
0-1-2
3.08
1-1-1
4.36
2-0-1
2.96
 —
1-0-2
4.82
0-1-2
3.67
2-1-0
5.17
2-0-1
4.50
2-0-1
5.46
Odense
1-2-0
3.40
0-1-2
3.38
1-0-2
3.44
1-0-2
3.29
1-1-1
4.91
1-0-2
2.38
2-0-1
3.40
 —
1-0-2
3.48
2-1-0
5.48
0-2-1
4.26
1-0-2
4.73
Randers
0-2-1
3.62
1-1-1
3.42
2-1-0
3.69
1-1-1
3.08
2-0-1
5.29
0-0-3
2.96
2-1-0
4.54
2-0-1
4.73
 —
2-0-1
6.00
0-3-0
4.51
2-1-0
5.39
Silkeborg
0-1-2
2.53
0-0-3
2.43
0-1-2
2.53
0-1-2
2.51
0-2-1
3.49
0-0-3
1.74
0-1-2
3.06
0-1-2
2.78
1-0-2
2.30
 —
1-1-1
3.43
0-0-3
3.48
Sonderjyske
1-1-1
3.45
0-0-3
3.41
1-2-0
3.32
0-2-1
3.18
1-2-0
4.47
0-1-2
3.04
1-0-2
3.70
1-2-0
3.95
0-3-0
3.70
1-1-1
4.79
 —
1-2-0
4.64
Vestsjaelland
2-0-1
2.82
0-0-3
2.59
0-0-3
3.01
0-1-2
2.51
1-1-1
3.48
0-1-2
1.93
1-0-2
2.79
2-0-1
3.49
0-1-2
2.87
3-0-0
4.74
0-2-1
3.57
 —

Points vs. Goals Scored, Allowed, and Differential

Points plotted against goals scored, allowed, and differential. Use the buttons to switch views; hover a team for exact values. The table gives each fit's R² and slope (the change in points per 10 goals).

Fit Metrics

R² Slope
Scored 0.61 +12.6
Allowed 0.76 -12.0
Differential 0.93 +8.4

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
08.08%10.61%7.58%3.03%0.76%0.51%30.56%
110.61%12.12%7.58%3.54%0.76%0.25%34.85%
27.58%7.58%4.55%1.77%0.51%0.51%22.47%
33.03%3.54%1.77%0.51%——8.84%
40.76%0.76%0.51%———2.02%
5+0.51%0.25%0.51%———1.26%
Total30.56%34.85%22.47%8.84%2.02%1.26%100%

Summary Statistics

Scored Allowed Difference
Mean 1.21 1.21 +0.00
SD 1.11 1.11 1.64
CV 0.92 0.92 —
Max 5 5 +5
Min 0 0 -5

Games Played: 198

↓ Scored | Allowed →012345+Total
06.06%12.12%6.06%———24.24%
115.15%18.18%12.12%—3.03%—48.48%
29.09%6.06%3.03%———18.18%
33.03%3.03%————6.06%
4———————
5+3.03%—————3.03%
Total36.36%39.39%21.21%—3.03%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 0.94 +0.24
SD 1.07 0.93 1.58
CV 0.91 0.99 —
Max 5 4 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%12.12%9.09%3.03%——30.30%
115.15%12.12%—6.06%——33.33%
215.15%3.03%3.03%———21.21%
33.03%3.03%3.03%———9.09%
43.03%—————3.03%
5+3.03%—————3.03%
Total45.45%30.30%15.15%9.09%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.30 0.88 +0.42
SD 1.26 0.99 1.84
CV 0.97 1.13 —
Max 5 3 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
015.15%9.09%6.06%3.03%——33.33%
13.03%9.09%6.06%6.06%——24.24%
26.06%3.03%3.03%9.09%——21.21%
33.03%6.06%—3.03%——12.12%
4—3.03%3.03%———6.06%
5+——3.03%———3.03%
Total27.27%30.30%21.21%21.21%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.42 1.36 +0.06
SD 1.39 1.11 1.60
CV 0.98 0.82 —
Max 5 3 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%6.06%3.03%6.06%——24.24%
130.30%9.09%3.03%———42.42%
29.09%12.12%3.03%———24.24%
33.03%3.03%————6.06%
43.03%—————3.03%
5+———————
Total54.55%30.30%9.09%6.06%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.21 0.67 +0.55
SD 0.99 0.89 1.48
CV 0.82 1.33 —
Max 4 3 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%12.12%3.03%3.03%—3.03%27.27%
115.15%12.12%3.03%3.03%—3.03%36.36%
23.03%3.03%12.12%—6.06%—24.24%
36.06%6.06%————12.12%
4———————
5+———————
Total30.30%33.33%18.18%6.06%6.06%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.21 1.42 -0.21
SD 0.99 1.46 1.82
CV 0.82 1.02 —
Max 3 5 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%3.03%3.03%3.03%——15.15%
16.06%6.06%3.03%3.03%——18.18%
212.12%21.21%—3.03%——36.36%
39.09%9.09%3.03%3.03%——24.24%
4———————
5+—3.03%3.03%———6.06%
Total33.33%42.42%12.12%12.12%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.94 1.03 +0.91
SD 1.27 0.98 1.61
CV 0.66 0.95 —
Max 5 3 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%12.12%9.09%6.06%——39.39%
16.06%—9.09%6.06%——21.21%
26.06%15.15%3.03%3.03%——27.27%
3——6.06%———6.06%
43.03%—3.03%———6.06%
5+———————
Total27.27%27.27%30.30%15.15%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 1.33 -0.15
SD 1.21 1.05 1.60
CV 1.02 0.79 —
Max 4 3 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%6.06%15.15%6.06%——30.30%
19.09%15.15%12.12%3.03%——39.39%
212.12%6.06%3.03%3.03%——24.24%
3—6.06%————6.06%
4———————
5+———————
Total24.24%33.33%30.30%12.12%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.30 -0.24
SD 0.90 0.98 1.54
CV 0.85 0.75 —
Max 3 3 +2
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%9.09%3.03%———24.24%
115.15%18.18%9.09%3.03%——45.45%
212.12%3.03%———3.03%18.18%
39.09%—3.03%———12.12%
4———————
5+———————
Total48.48%30.30%15.15%3.03%—3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 0.85 +0.33
SD 0.95 1.12 1.47
CV 0.80 1.32 —
Max 3 5 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%21.21%21.21%—3.03%—51.52%
1—3.03%15.15%6.06%——24.24%
2—3.03%15.15%——3.03%21.21%
3———————
4—3.03%————3.03%
5+———————
Total6.06%30.30%51.52%6.06%3.03%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 0.79 1.79 -1.00
SD 0.99 0.99 1.25
CV 1.26 0.56 —
Max 4 5 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%6.06%3.03%3.03%3.03%—27.27%
16.06%30.30%9.09%3.03%3.03%—51.52%
23.03%3.03%6.06%———12.12%
3——6.06%———6.06%
4—3.03%————3.03%
5+———————
Total21.21%42.42%24.24%6.06%6.06%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.33 -0.27
SD 0.97 1.08 1.40
CV 0.91 0.81 —
Max 4 4 +3
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%18.18%9.09%3.03%3.03%3.03%39.39%
16.06%12.12%9.09%3.03%3.03%—33.33%
23.03%12.12%3.03%3.03%——21.21%
3—6.06%————6.06%
4———————
5+———————
Total12.12%48.48%21.21%9.09%6.06%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 0.94 1.58 -0.64
SD 0.93 1.20 1.67
CV 0.99 0.76 —
Max 3 5 +2
Min 0 0 -5

Games Played: 33

Home-Field Advantage Edge

The simulation applies the same home-field boost to every game across the league, so the per-game home win probabilities bake in the model's idea of HFA. For each team, we sum expected points at home and compare to actual home points, and the same on the road. The bar shows (home points above expected) minus (away points above expected). A tall positive bar means the team's home/road split exceeded what the model predicted — a real fortress effect. A tall negative bar means the reverse: they played worse at home or better on the road than expected.

Top Overachievers & Disappointments

Teams that most beat — or most fell short of — their simulated point projections. A positive vsSim means the team accumulated more points than the model expected on average; a negative one means fewer.

Biggest Overachievers

# Team Actual Sim vsSim
1 FC Copenhagen 67 55.41 +11.59
2 Midtjylland 71 59.88 +11.12
3 Hobro 43 38.05 +4.95
4 Randers 52 47.31 +4.69
5 Brondby 55 50.34 +4.66

Biggest Disappointments

# Team Actual Sim vsSim
1 Silkeborg 14 30.23 -16.23
2 Esbjerg 40 47.40 -7.40
3 Sonderjyske 37 41.59 -4.59
4 Aalborg 48 52.15 -4.15
5 Odense 40 42.32 -2.32

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 Midtjylland 5 Aug 4 – Sep 12 1 in 53
2 Hobro 3 Feb 28 – Mar 16 1 in 23
3 FC Copenhagen 4 Nov 22 – Feb 22 1 in 21
4 Brondby 3 May 17 – May 25 1 in 16
5 Nordsjaelland 3 Sep 14 – Sep 29 1 in 16

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Silkeborg 9 Oct 4 – Feb 21 1 in 234
2 Nordsjaelland 4 May 3 – May 21 1 in 41
3 Randers 3 Mar 1 – Mar 13 1 in 38
4 Odense 3 Mar 15 – Apr 7 1 in 30
5 Vestsjaelland 5 Feb 22 – Mar 22 1 in 29

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Sonderjyske 9 Aug 30 – Nov 9 1 in 107
2 Hobro 7 Aug 3 – Sep 27 1 in 47
3 FC Copenhagen 11 Sep 21 – Feb 22 1 in 42
4 Brondby 7 Apr 26 – May 31 1 in 15
5 Randers 5 Aug 30 – Oct 5 1 in 14

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Silkeborg 18 Jul 20 – Feb 21 1 in 160
2 Randers 7 Mar 1 – Apr 20 1 in 51
3 Sonderjyske 7 Aug 10 – Oct 5 1 in 22
4 Esbjerg 6 Jul 21 – Aug 31 1 in 21
5 Vestsjaelland 10 Nov 1 – Mar 22 1 in 18

Finish Position Heatmap

Each cell is the probability — across 100,000 simulations — that the team (row) finished at that position (column). Rows are sorted by actual finish (champion at top, bottom of the table at the bottom).

Team123456789101112
Midtjylland49.24%22.58%12.10%7.21%4.03%2.40%1.26%0.68%0.30%0.12%0.05%0.03%
FC Copenhagen22.23%24.48%17.46%12.48%8.85%5.86%3.89%2.51%1.34%0.62%0.22%0.06%
Brondby7.06%13.20%16.13%15.53%13.23%11.06%8.82%6.85%4.34%2.25%1.32%0.21%
Randers3.41%7.44%10.48%12.76%13.77%13.32%12.69%10.54%7.83%4.57%2.31%0.88%
Aalborg10.99%15.76%17.50%15.82%12.63%9.79%7.31%4.66%3.05%1.63%0.71%0.15%
Nordsjaelland2.02%4.79%6.87%9.38%12.21%12.46%13.98%13.24%11.49%7.86%4.31%1.39%
Hobro0.21%0.57%1.46%2.41%4.36%6.69%8.49%11.50%16.14%20.28%17.23%10.66%
Esbjerg3.40%7.15%10.54%12.30%13.62%13.48%12.76%10.10%8.14%4.83%2.75%0.93%
Odense0.79%1.84%4.16%5.90%8.00%11.32%12.92%14.91%15.09%12.91%8.40%3.76%
Sonderjyske0.65%1.98%2.88%5.38%7.50%10.14%12.15%14.68%15.91%14.14%9.92%4.67%
Vestsjaelland—0.17%0.35%0.69%1.25%2.58%4.05%6.97%10.69%18.12%28.36%26.77%
Silkeborg—0.04%0.07%0.14%0.55%0.90%1.68%3.36%5.68%12.67%24.42%50.49%

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
+15.15%
Clear Edge
44.95%25.25%29.80%
Elo Value
Home Edge
195 Elo
0.005 goals per Elo point
053.05500
Scoring Tilt
Expected
+0.30 goals
Neutral
-2+0.27+2

Title Race

How these are measured

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

Title-Race Openness
Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 4 * Open: 4 to 6 * Wide Open: 6 and up.
Champion Preseason Odds
Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd * Middle of the Pack: 3rd to 6th * Longshot: 7th or lower.
Title Margin
Points-per-game gap between the champion and the runner-up. Shown per game so it reads the same across long and short seasons. The gold line is the winning margin the model expected, so a dot to the right means a more one-sided race than projected. A title won on goal difference shows 0.00.
Photo Finish: under 0.15 * Tight Race: 0.15 to 0.4 * Comfortable: 0.4 to 0.75 * Runaway: 0.75 and up.
Title-Race Openness
3.2
Top-Heavy
124610
Champion Preseason Odds
49%
Midtjylland, 1st of 12
LongshotFavorite
Title Margin
Expected
0.12/gm
Photo Finish
00.170.5/gm

Simulation-Based Surprises

How these are measured

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

Luck Spread
Standard deviation of the gap between each team's actual points and their simulated average points. The gold line is the spread the model expected from chance alone.
As Expected: under 5.73 * Some Luck: 5.73 to 8.59 * Lucky: 8.59 to 11.46 * Wild Swing: 11.46 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 1.43 * Close: 1.43 to 2.15 * Off: 2.15 to 2.87 * Way Off: 2.87 and up.
Biggest Overachiever
The team that finished highest inside its own range of simulated outcomes. The gold line is where the top team in a league of 12 typically lands.
Biggest Underachiever
The team that finished lowest inside its own range of simulated outcomes. The gold line is where the bottom team in a league of 12 typically lands.
Season Outliers
Number of teams that finished above the 95th or below the 5th percentile of their own simulated range. Even a well-calibrated model expects about 10% of teams in the extremes.
Minimal Outliers: under 12 * As Expected: 12 to 19.2 * Several Outliers: 19.2 to 26.4 * Many Outliers: 26.4 and up.
Unexpected Relegations
Number of teams that were actually relegated but were not in the model's projected bottom field of the same size. The gold line is how many the model expected to miss on average.
As Expected: under 0.7 * A Surprise: 0.7 to 1.12 * Several Surprises: 1.12 to 1.54 * Many Surprises: 1.54 and up.
Luck Spread
Expected
7.58 points
Some Luck
07.1618
Average Finish Error
Expected
1.17
Pinpoint
01.794
Biggest Overachiever
Expected 95.83%
95.28%
FC Copenhagen
50100
Biggest Underachiever
Expected 4.17%
0.68%
Silkeborg
050
Season Outliers
Expected
3 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
1 of 2
A Surprise
00.72

Parity

How these are measured

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

Gini Index
How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.
Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully
How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge
Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst
Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts
Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.18
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.76
Strong Separation
01.003
Interquartile Edge
67%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline
86%
Strong Edge
50%86%100%
Close Games
Expected
65%
Very Frequent
0%64%100%
Blowouts
Expected
12%
Occasional
0%13%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
0.60
Predictable
00.622
Matchup Imbalance
0.31
Lopsided
00.10.180.280.5
Strangeness
Expected
1.17
Wilder Than Modeled
01.002
Repeatability
0.77
Strong Carryover
00.30.60.851
Upset Rate
Expected
23%
Chalky
0%26%50%
Clear Favorite Upset Rate
Expected
22%
As Expected
0%22%50%

Calibration

How these are measured

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

Probability calibration
An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope
Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE)
The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.12 * Near Noise Ceiling: 0.12 to 0.17 * Above Noise: 0.17 to 0.23 * Well Above Noise: 0.23 and up.
Probability calibration
0.28
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
1.11
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.135
Near Noise Ceiling
00.1160.3

Next-Season Status

Across 100,000 regular-season simulations, the probability of each team's next-season status. Columns appear in best-to-worst outcome order: promotion-positive on the left, relegation-positive on the right. Cells with darker shading indicate higher likelihood.

Team Same level Direct relegation
Midtjylland 99.92% 0.08%
FC Copenhagen 99.72% 0.28%
Aalborg 99.14% 0.86%
Brondby 98.47% 1.53%
Randers 96.81% 3.19%
Esbjerg 96.32% 3.68%
Nordsjaelland 94.30% 5.70%
Odense 87.84% 12.16%
Sonderjyske 85.41% 14.59%
Hobro 72.11% 27.89%
Vestsjaelland 44.87% 55.13%
Silkeborg 25.09% 74.91%

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
2014-07-18 Vestsjaelland W 3-2 1555 1496 51.64% 25.34% 23.02% +4.6 3
2014-07-18 @ Nordsjaelland L 2-3 1496 1555 23.02% 25.34% 51.64% -4.6 0
2014-07-19 Aalborg D 0-0 1529 1595 34.81% 26.77% 38.41% +0.2 1
2014-07-19 @ Sonderjyske D 0-0 1595 1529 38.41% 26.77% 34.81% -0.2 1
2014-07-20 Brondby W 3-1 1596 1573 47.11% 26.10% 26.79% +9.6 3
2014-07-20 @ Midtjylland L 1-3 1573 1596 26.79% 26.10% 47.11% -9.6 0
2014-07-20 FC Copenhagen D 0-0 1492 1609 28.17% 26.30% 45.53% +0.8 1
2014-07-20 @ Silkeborg D 0-0 1609 1492 45.53% 26.30% 28.17% -0.8 1
2014-07-20 Hobro L 1-2 1542 1451 55.60% 24.41% 20.00% -9.9 0
2014-07-20 @ Odense W 2-1 1451 1542 20.00% 24.41% 55.60% +9.9 3
2014-07-21 Randers L 0-1 1571 1531 49.36% 25.76% 24.88% -9.5 0
2014-07-21 @ Esbjerg W 1-0 1531 1571 24.88% 25.76% 49.36% +9.5 3
2014-07-25 Odense W 3-1 1491 1533 38.31% 26.78% 34.92% +11.9 3
2014-07-25 @ Vestsjaelland L 1-3 1533 1491 34.92% 26.78% 38.31% -11.9 0
2014-07-26 Midtjylland W 2-0 1594 1606 42.46% 26.58% 30.95% +12.5 4
2014-07-26 @ Aalborg L 0-2 1606 1594 30.95% 26.58% 42.46% -12.5 3
2014-07-26 Nordsjaelland W 2-1 1608 1559 50.42% 25.57% 24.01% +5.1 4
2014-07-26 @ FC Copenhagen L 1-2 1559 1608 24.01% 25.57% 50.42% -5.1 3
2014-07-27 Hobro W 2-1 1540 1461 54.19% 24.76% 21.04% +4.5 6
2014-07-27 @ Randers L 1-2 1461 1540 21.04% 24.76% 54.19% -4.5 3
2014-07-27 Sonderjyske D 1-1 1562 1529 48.37% 25.92% 25.71% -0.9 1
2014-07-27 @ Esbjerg D 1-1 1529 1562 25.71% 25.92% 48.37% +0.9 2
2014-07-28 Silkeborg W 2-0 1564 1492 53.20% 25.00% 21.80% +9.3 3
2014-07-28 @ Brondby L 0-2 1492 1564 21.80% 25.00% 53.20% -9.3 1
2014-08-01 Sonderjyske L 0-2 1483 1530 37.48% 26.79% 35.73% -14.4 1
2014-08-01 @ Silkeborg W 2-0 1530 1483 35.73% 26.79% 37.48% +14.4 5
2014-08-02 Aalborg D 1-1 1521 1607 32.02% 26.66% 41.32% +0.4 1
2014-08-02 @ Odense D 1-1 1607 1521 41.32% 26.66% 32.02% -0.4 5
2014-08-02 FC Copenhagen D 2-2 1503 1613 29.05% 26.41% 44.54% +0.5 4
2014-08-02 @ Vestsjaelland D 2-2 1613 1503 44.54% 26.41% 29.05% -0.5 5
2014-08-03 Brondby W 2-0 1456 1573 28.20% 26.30% 45.50% +16.8 6
2014-08-03 @ Hobro L 0-2 1573 1456 45.50% 26.30% 28.20% -16.8 3
2014-08-03 Esbjerg W 3-2 1554 1561 43.14% 26.53% 30.33% +5.8 6
2014-08-03 @ Nordsjaelland L 2-3 1561 1554 30.33% 26.53% 43.14% -5.8 1
2014-08-04 Randers W 3-1 1594 1545 50.41% 25.58% 24.02% +8.8 6
2014-08-04 @ Midtjylland L 1-3 1545 1594 24.02% 25.58% 50.41% -8.8 6
2014-08-08 Vestsjaelland W 1-0 1536 1504 48.33% 25.93% 25.74% +5.7 9
2014-08-08 @ Randers L 0-1 1504 1536 25.74% 25.93% 48.33% -5.7 4
2014-08-09 Nordsjaelland L 1-2 1607 1560 50.15% 25.62% 24.22% -9.1 5
2014-08-09 @ Aalborg W 2-1 1560 1607 24.22% 25.62% 50.15% +9.1 9
2014-08-10 Hobro L 0-3 1613 1473 60.93% 22.75% 16.32% -31.0 5
2014-08-10 @ FC Copenhagen W 3-0 1473 1613 16.32% 22.75% 60.93% +31.0 9
2014-08-10 Midtjylland L 1-3 1545 1602 35.92% 26.79% 37.29% -12.1 5
2014-08-10 @ Sonderjyske W 3-1 1602 1545 37.29% 26.79% 35.92% +12.1 9
2014-08-10 Odense D 1-1 1556 1521 48.71% 25.87% 25.42% -1.0 4
2014-08-10 @ Brondby D 1-1 1521 1556 25.42% 25.87% 48.71% +1.0 2
2014-08-11 Silkeborg D 0-0 1555 1469 54.97% 24.57% 20.46% -1.7 2
2014-08-11 @ Esbjerg D 0-0 1469 1555 20.46% 24.57% 54.97% +1.6 2
2014-08-15 Midtjylland L 1-2 1582 1614 39.49% 26.74% 33.77% -7.5 5
2014-08-15 @ FC Copenhagen W 2-1 1614 1582 33.77% 26.74% 39.49% +7.5 12
2014-08-16 Esbjerg D 1-1 1598 1553 49.85% 25.68% 24.47% -1.1 6
2014-08-16 @ Aalborg D 1-1 1553 1598 24.47% 25.68% 49.85% +1.1 3
2014-08-17 Odense L 0-2 1542 1522 46.69% 26.16% 27.15% -17.1 9
2014-08-17 @ Randers W 2-0 1522 1542 27.15% 26.16% 46.69% +17.1 5
2014-08-17 Silkeborg W 2-0 1498 1470 47.73% 26.02% 26.26% +11.0 7
2014-08-17 @ Vestsjaelland L 0-2 1470 1498 26.26% 26.02% 47.73% -10.9 2
2014-08-17 Sonderjyske W 2-0 1555 1532 47.12% 26.10% 26.78% +11.1 7
2014-08-17 @ Brondby L 0-2 1532 1555 26.78% 26.10% 47.12% -11.1 5
2014-08-18 Nordsjaelland D 0-0 1504 1569 34.90% 26.78% 38.32% +0.2 10
2014-08-18 @ Hobro D 0-0 1569 1504 38.32% 26.78% 34.90% -0.1 10
2014-08-30 Randers D 1-1 1521 1525 43.58% 26.50% 29.93% -0.5 6
2014-08-30 @ Sonderjyske D 1-1 1525 1521 29.93% 26.50% 43.58% +0.5 10
2014-08-31 Aalborg D 2-2 1459 1596 25.89% 25.95% 48.16% +0.7 3
2014-08-31 @ Silkeborg D 2-2 1596 1459 48.16% 25.95% 25.89% -0.7 7
2014-08-31 Brondby L 0-3 1569 1567 44.37% 26.42% 29.21% -23.9 10
2014-08-31 @ Nordsjaelland W 3-0 1567 1569 29.21% 26.42% 44.37% +23.9 10
2014-08-31 Esbjerg W 2-0 1622 1554 52.75% 25.10% 22.15% +9.5 15
2014-08-31 @ Midtjylland L 0-2 1554 1622 22.15% 25.10% 52.75% -9.5 3
2014-08-31 FC Copenhagen L 0-1 1539 1574 39.19% 26.75% 34.05% -7.9 5
2014-08-31 @ Odense W 1-0 1574 1539 34.05% 26.75% 39.19% +7.9 8
2014-09-01 Vestsjaelland W 3-1 1504 1509 43.39% 26.51% 30.10% +10.6 13
2014-09-01 @ Hobro L 1-3 1509 1504 30.10% 26.51% 43.39% -10.6 7
2014-09-12 Odense W 3-2 1631 1531 56.58% 24.13% 19.28% +3.9 18
2014-09-12 @ Midtjylland L 2-3 1531 1631 19.28% 24.13% 56.58% -3.9 5
2014-09-13 FC Copenhagen W 1-0 1596 1582 45.90% 26.26% 27.84% +6.1 10
2014-09-13 @ Aalborg L 0-1 1582 1596 27.84% 26.26% 45.90% -6.1 8
2014-09-14 Nordsjaelland L 1-2 1460 1545 32.20% 26.67% 41.13% -6.4 3
2014-09-14 @ Silkeborg W 2-1 1545 1460 41.13% 26.67% 32.20% +6.5 13
2014-09-14 Randers L 0-2 1590 1525 52.45% 25.17% 22.38% -18.8 10
2014-09-14 @ Brondby W 2-0 1525 1590 22.38% 25.17% 52.45% +18.8 13
2014-09-14 Vestsjaelland W 3-0 1545 1498 50.14% 25.62% 24.23% +14.9 6
2014-09-14 @ Esbjerg L 0-3 1498 1545 24.23% 25.62% 50.14% -14.9 7
2014-09-15 Hobro D 1-1 1521 1515 44.85% 26.37% 28.78% -0.7 7
2014-09-15 @ Sonderjyske D 1-1 1515 1521 28.78% 26.37% 44.85% +0.7 14
2014-09-19 Silkeborg W 1-0 1544 1454 55.46% 24.44% 20.10% +4.6 16
2014-09-19 @ Randers L 0-1 1454 1544 20.10% 24.44% 55.46% -4.6 3
2014-09-20 Esbjerg D 1-1 1515 1560 37.85% 26.78% 35.37% -0.1 15
2014-09-20 @ Hobro D 1-1 1560 1515 35.37% 26.78% 37.85% +0.1 7
2014-09-21 Brondby W 1-0 1576 1572 44.63% 26.40% 28.97% +6.3 11
2014-09-21 @ FC Copenhagen L 0-1 1572 1576 28.97% 26.40% 44.63% -6.3 10
2014-09-21 Midtjylland W 2-1 1552 1635 32.34% 26.68% 40.98% +7.7 16
2014-09-21 @ Nordsjaelland L 1-2 1635 1552 40.98% 26.68% 32.34% -7.7 18
2014-09-21 Sonderjyske D 1-1 1527 1520 45.03% 26.36% 28.62% -0.7 6
2014-09-21 @ Odense D 1-1 1520 1527 28.62% 26.36% 45.03% +0.7 8
2014-09-22 Aalborg W 1-0 1484 1602 28.02% 26.28% 45.70% +8.9 10
2014-09-22 @ Vestsjaelland L 0-1 1602 1484 45.70% 26.28% 28.02% -8.9 10
2014-09-26 Randers D 0-0 1593 1549 49.86% 25.67% 24.47% -1.2 11
2014-09-26 @ Aalborg D 0-0 1549 1593 24.47% 25.67% 49.86% +1.2 17
2014-09-27 FC Copenhagen D 1-1 1521 1582 35.40% 26.78% 37.81% +0.1 9
2014-09-27 @ Sonderjyske D 1-1 1582 1521 37.81% 26.78% 35.40% -0.1 12
2014-09-27 Hobro D 2-2 1449 1515 34.73% 26.77% 38.49% +0.1 4
2014-09-27 @ Silkeborg D 2-2 1515 1449 38.49% 26.77% 34.73% -0.1 16
2014-09-28 Brondby D 2-2 1560 1565 43.31% 26.52% 30.17% -0.4 8
2014-09-28 @ Esbjerg D 2-2 1565 1560 30.17% 26.52% 43.31% +0.4 11
2014-09-28 Vestsjaelland W 1-0 1628 1492 60.46% 22.91% 16.63% +3.8 21
2014-09-28 @ Midtjylland L 0-1 1492 1628 16.63% 22.91% 60.46% -3.8 10
2014-09-29 Odense W 2-1 1559 1527 48.36% 25.92% 25.72% +5.4 19
2014-09-29 @ Nordsjaelland L 1-2 1527 1559 25.72% 25.92% 48.36% -5.4 6
2014-10-03 Midtjylland L 1-5 1515 1631 28.27% 26.31% 45.41% -18.4 16
2014-10-03 @ Hobro W 5-1 1631 1515 45.41% 26.31% 28.27% +18.4 24
2014-10-04 Silkeborg W 2-0 1521 1449 53.29% 24.98% 21.73% +9.3 9
2014-10-04 @ Odense L 0-2 1449 1521 21.73% 24.98% 53.29% -9.3 4
2014-10-05 Aalborg W 2-1 1566 1592 40.44% 26.70% 32.86% +6.5 14
2014-10-05 @ Brondby L 1-2 1592 1566 32.86% 26.70% 40.44% -6.5 11
2014-10-05 Esbjerg W 2-1 1582 1559 47.07% 26.11% 26.82% +5.6 15
2014-10-05 @ FC Copenhagen L 1-2 1559 1582 26.82% 26.11% 47.07% -5.6 8
2014-10-05 Nordsjaelland D 0-0 1550 1565 42.02% 26.62% 31.36% -0.5 18
2014-10-05 @ Randers D 0-0 1565 1550 31.36% 26.62% 42.02% +0.5 20
2014-10-05 Sonderjyske D 1-1 1489 1521 39.58% 26.74% 33.68% -0.2 11
2014-10-05 @ Vestsjaelland D 1-1 1521 1489 33.68% 26.74% 39.58% +0.2 10
2014-10-17 Hobro D 1-1 1585 1497 55.23% 24.50% 20.27% -1.5 12
2014-10-17 @ Aalborg D 1-1 1497 1585 20.27% 24.50% 55.23% +1.5 17
2014-10-18 Sonderjyske L 2-3 1565 1521 49.83% 25.68% 24.49% -8.6 20
2014-10-18 @ Nordsjaelland W 3-2 1521 1565 24.49% 25.68% 49.83% +8.6 13
2014-10-19 Randers W 1-0 1588 1549 49.10% 25.80% 25.10% +5.6 18
2014-10-19 @ FC Copenhagen L 0-1 1549 1588 25.10% 25.80% 49.10% -5.6 18
2014-10-19 Silkeborg W 2-1 1650 1440 67.96% 19.88% 12.16% +2.6 27
2014-10-19 @ Midtjylland L 1-2 1440 1650 12.16% 19.88% 67.96% -2.6 4
2014-10-19 Vestsjaelland W 5-0 1572 1488 54.69% 24.64% 20.67% +20.8 17
2014-10-19 @ Brondby L 0-5 1488 1572 20.67% 24.64% 54.69% -20.8 11
2014-10-20 Odense W 2-0 1554 1531 47.16% 26.10% 26.74% +11.1 11
2014-10-20 @ Esbjerg L 0-2 1531 1554 26.74% 26.10% 47.16% -11.1 9
2014-10-24 Vestsjaelland L 1-2 1437 1468 39.84% 26.73% 33.43% -7.6 4
2014-10-24 @ Silkeborg W 2-1 1468 1437 33.43% 26.73% 39.84% +7.6 14
2014-10-25 Midtjylland D 1-1 1530 1652 27.50% 26.21% 46.29% +0.8 14
2014-10-25 @ Sonderjyske D 1-1 1652 1530 46.29% 26.21% 27.50% -0.8 28
2014-10-26 Brondby D 0-0 1565 1593 40.18% 26.72% 33.10% -0.3 12
2014-10-26 @ Esbjerg D 0-0 1593 1565 33.10% 26.72% 40.18% +0.3 18
2014-10-26 FC Copenhagen L 0-2 1498 1593 30.90% 26.58% 42.52% -12.5 17
2014-10-26 @ Hobro W 2-0 1593 1498 42.52% 26.58% 30.90% +12.5 21
2014-10-26 Odense W 3-0 1544 1519 47.29% 26.08% 26.63% +16.1 21
2014-10-26 @ Randers L 0-3 1519 1544 26.63% 26.08% 47.29% -16.1 9
2014-10-27 Aalborg L 0-1 1557 1584 40.28% 26.71% 33.01% -8.1 20
2014-10-27 @ Nordsjaelland W 1-0 1584 1557 33.01% 26.71% 40.28% +8.1 15
2014-10-31 Nordsjaelland W 2-0 1652 1548 56.93% 24.03% 19.04% +8.2 31
2014-10-31 @ Midtjylland L 0-2 1548 1652 19.04% 24.03% 56.93% -8.2 20
2014-11-01 Esbjerg L 1-4 1475 1565 31.60% 26.63% 41.76% -15.6 14
2014-11-01 @ Vestsjaelland W 4-1 1565 1475 41.76% 26.63% 31.60% +15.6 15
2014-11-02 Hobro W 3-1 1503 1486 46.39% 26.20% 27.41% +9.8 12
2014-11-02 @ Odense L 1-3 1486 1503 27.41% 26.20% 46.39% -9.8 17
2014-11-02 Randers W 1-0 1593 1560 48.47% 25.91% 25.63% +5.7 21
2014-11-02 @ Brondby L 0-1 1560 1593 25.63% 25.91% 48.47% -5.7 21
2014-11-02 Sonderjyske D 1-1 1606 1530 53.69% 24.89% 21.43% -1.4 22
2014-11-02 @ FC Copenhagen D 1-1 1530 1606 21.43% 24.89% 53.69% +1.4 15
2014-11-03 Silkeborg W 2-0 1592 1430 63.27% 21.88% 14.85% +6.4 18
2014-11-03 @ Aalborg L 0-2 1430 1592 14.85% 21.88% 63.27% -6.4 4
2014-11-07 Midtjylland L 1-2 1423 1660 16.97% 23.09% 59.94% -3.7 4
2014-11-07 @ Silkeborg W 2-1 1660 1423 59.94% 23.09% 16.97% +3.7 34
2014-11-08 Esbjerg W 3-2 1554 1580 40.44% 26.70% 32.86% +6.2 24
2014-11-08 @ Randers L 2-3 1580 1554 32.86% 26.70% 40.44% -6.2 15
2014-11-09 Brondby W 3-0 1476 1599 27.48% 26.21% 46.31% +24.7 20
2014-11-09 @ Hobro L 0-3 1599 1476 46.31% 26.21% 27.48% -24.7 21
2014-11-09 FC Copenhagen D 0-0 1540 1604 35.03% 26.78% 38.20% +0.1 21
2014-11-09 @ Nordsjaelland D 0-0 1604 1540 38.20% 26.78% 35.03% -0.1 23
2014-11-09 Odense W 2-1 1532 1513 46.54% 26.18% 27.29% +5.7 18
2014-11-09 @ Sonderjyske L 1-2 1513 1532 27.29% 26.18% 46.54% -5.7 12
2014-11-09 Vestsjaelland W 2-0 1598 1460 60.82% 22.79% 16.39% +7.1 21
2014-11-09 @ Aalborg L 0-2 1460 1598 16.39% 22.79% 60.82% -7.1 14
2014-11-21 Randers L 0-1 1453 1560 29.29% 26.43% 44.28% -6.3 14
2014-11-21 @ Vestsjaelland W 1-0 1560 1453 44.28% 26.43% 29.29% +6.3 27
2014-11-22 Hobro W 4-2 1574 1501 53.44% 24.94% 21.61% +7.2 18
2014-11-22 @ Esbjerg L 2-4 1501 1574 21.61% 24.94% 53.44% -7.2 20
2014-11-22 Silkeborg W 1-0 1604 1420 65.52% 20.96% 13.52% +3.1 26
2014-11-22 @ FC Copenhagen L 0-1 1420 1604 13.52% 20.96% 65.52% -3.1 4
2014-11-23 Aalborg W 2-0 1664 1605 51.60% 25.34% 23.06% +9.8 37
2014-11-23 @ Midtjylland L 0-2 1605 1664 23.06% 25.34% 51.60% -9.8 21
2014-11-23 Nordsjaelland W 1-0 1508 1540 39.49% 26.74% 33.77% +7.1 15
2014-11-23 @ Odense L 0-1 1540 1508 33.77% 26.74% 39.49% -7.1 21
2014-11-23 Sonderjyske W 1-0 1574 1537 48.91% 25.83% 25.25% +5.6 24
2014-11-23 @ Brondby L 0-1 1537 1574 25.25% 25.83% 48.91% -5.6 18
2014-11-28 Esbjerg D 0-0 1532 1581 37.12% 26.79% 36.09% -0.0 19
2014-11-28 @ Sonderjyske D 0-0 1581 1532 36.09% 26.79% 37.12% +0.0 19
2014-11-29 Odense L 0-1 1417 1515 30.52% 26.55% 42.93% -6.6 4
2014-11-29 @ Silkeborg W 1-0 1515 1417 42.93% 26.55% 30.52% +6.6 18
2014-11-30 Brondby W 2-0 1533 1580 37.53% 26.79% 35.68% +13.9 24
2014-11-30 @ Nordsjaelland L 0-2 1580 1533 35.68% 26.79% 37.53% -13.9 24
2014-11-30 FC Copenhagen L 0-1 1595 1607 42.43% 26.59% 30.99% -8.4 21
2014-11-30 @ Aalborg W 1-0 1607 1595 30.99% 26.59% 42.43% +8.4 29
2014-11-30 Randers L 0-1 1494 1567 33.77% 26.74% 39.48% -7.1 20
2014-11-30 @ Hobro W 1-0 1567 1494 39.48% 26.74% 33.77% +7.1 30
2014-12-01 Vestsjaelland W 2-1 1673 1446 69.54% 19.14% 11.32% +2.4 40
2014-12-01 @ Midtjylland L 1-2 1446 1673 11.32% 19.14% 69.54% -2.4 14
2014-12-05 Sonderjyske D 0-0 1574 1532 49.58% 25.72% 24.70% -1.2 31
2014-12-05 @ Randers D 0-0 1532 1574 24.70% 25.72% 49.58% +1.2 20
2014-12-06 Aalborg D 1-1 1521 1587 34.78% 26.77% 38.45% +0.1 19
2014-12-06 @ Odense D 1-1 1587 1521 38.45% 26.77% 34.78% -0.1 22
2014-12-07 Hobro D 1-1 1444 1486 38.11% 26.78% 35.11% -0.1 15
2014-12-07 @ Vestsjaelland D 1-1 1486 1444 35.11% 26.78% 38.11% +0.1 21
2014-12-07 Midtjylland W 3-0 1616 1676 35.62% 26.79% 37.59% +21.0 32
2014-12-07 @ FC Copenhagen L 0-3 1676 1616 37.59% 26.79% 35.62% -21.0 40
2014-12-07 Silkeborg W 1-0 1566 1410 62.64% 22.12% 15.24% +3.5 27
2014-12-07 @ Brondby L 0-1 1410 1566 15.24% 22.12% 62.64% -3.5 4
2014-12-08 Nordsjaelland D 0-0 1581 1547 48.55% 25.89% 25.55% -1.1 20
2014-12-08 @ Esbjerg D 0-0 1547 1581 25.55% 25.89% 48.55% +1.1 25
2015-02-20 Randers L 0-3 1548 1573 40.68% 26.69% 32.63% -22.3 25
2015-02-20 @ Nordsjaelland W 3-0 1573 1548 32.63% 26.69% 40.68% +22.3 34
2015-02-21 Esbjerg L 1-3 1407 1580 22.16% 25.10% 52.73% -8.2 4
2015-02-21 @ Silkeborg W 3-1 1580 1407 52.73% 25.10% 22.16% +8.2 23
2015-02-22 Brondby W 1-0 1587 1569 46.39% 26.20% 27.41% +6.0 25
2015-02-22 @ Aalborg L 0-1 1569 1587 27.41% 26.20% 46.39% -6.0 27
2015-02-22 Hobro W 1-0 1533 1487 50.12% 25.63% 24.25% +5.4 23
2015-02-22 @ Sonderjyske L 0-1 1487 1533 24.25% 25.63% 50.12% -5.4 21
2015-02-22 Vestsjaelland W 2-0 1637 1444 66.35% 20.61% 13.05% +5.5 35
2015-02-22 @ FC Copenhagen L 0-2 1444 1637 13.05% 20.61% 66.35% -5.5 15
2015-02-23 Odense W 3-0 1655 1521 60.26% 22.98% 16.76% +10.5 43
2015-02-23 @ Midtjylland L 0-3 1521 1655 16.76% 22.98% 60.26% -10.5 19
2015-02-27 Sonderjyske L 0-1 1438 1538 30.25% 26.53% 43.23% -6.5 15
2015-02-27 @ Vestsjaelland W 1-0 1538 1438 43.23% 26.53% 30.25% +6.5 26
2015-02-28 Nordsjaelland W 1-0 1481 1526 37.78% 26.78% 35.43% +7.3 24
2015-02-28 @ Hobro L 0-1 1526 1481 35.43% 26.78% 37.78% -7.4 25
2015-03-01 FC Copenhagen W 1-0 1511 1642 26.51% 26.06% 47.43% +9.2 22
2015-03-01 @ Odense L 0-1 1642 1511 47.43% 26.06% 26.51% -9.2 35
2015-03-01 Midtjylland D 1-1 1563 1665 30.04% 26.51% 43.45% +0.5 28
2015-03-01 @ Brondby D 1-1 1665 1563 43.45% 26.51% 30.04% -0.5 44
2015-03-01 Silkeborg L 1-2 1595 1398 66.69% 20.46% 12.86% -11.5 34
2015-03-01 @ Randers W 2-1 1398 1595 12.86% 20.46% 66.69% +11.5 7
2015-03-02 Aalborg L 1-3 1588 1593 43.43% 26.51% 30.06% -14.0 23
2015-03-02 @ Esbjerg W 3-1 1593 1588 30.06% 26.51% 43.43% +14.0 28
2015-03-07 Sonderjyske W 4-0 1519 1545 40.42% 26.71% 32.87% +24.9 28
2015-03-07 @ Nordsjaelland L 0-4 1545 1519 32.87% 26.71% 40.42% -24.8 26
2015-03-08 Brondby W 3-1 1633 1564 52.93% 25.06% 22.01% +8.1 38
2015-03-08 @ FC Copenhagen L 1-3 1564 1633 22.01% 25.06% 52.93% -8.1 28
2015-03-08 Esbjerg W 3-0 1665 1574 55.43% 24.45% 20.12% +12.6 47
2015-03-08 @ Midtjylland L 0-3 1574 1665 20.12% 24.45% 55.43% -12.6 23
2015-03-08 Hobro L 0-1 1410 1488 33.05% 26.71% 40.24% -7.0 7
2015-03-08 @ Silkeborg W 1-0 1488 1410 40.24% 26.71% 33.05% +7.0 27
2015-03-08 Randers W 2-1 1607 1584 47.17% 26.10% 26.73% +5.6 31
2015-03-08 @ Aalborg L 1-2 1584 1607 26.73% 26.10% 47.17% -5.6 34
2015-03-09 Odense L 1-2 1432 1520 31.76% 26.64% 41.60% -6.4 15
2015-03-09 @ Vestsjaelland W 2-1 1520 1432 41.60% 26.64% 31.76% +6.4 25
2015-03-13 Midtjylland L 1-2 1578 1677 30.36% 26.54% 43.10% -6.2 34
2015-03-13 @ Randers W 2-1 1677 1578 43.10% 26.54% 30.36% +6.2 50
2015-03-14 Silkeborg L 1-4 1520 1403 58.48% 23.57% 17.95% -25.3 26
2015-03-14 @ Sonderjyske W 4-1 1403 1520 17.95% 23.57% 58.48% +25.3 10
2015-03-15 FC Copenhagen L 0-1 1562 1641 32.94% 26.71% 40.35% -7.0 23
2015-03-15 @ Esbjerg W 1-0 1641 1562 40.35% 26.71% 32.94% +7.0 41
2015-03-15 Odense W 2-0 1556 1526 47.96% 25.98% 26.06% +10.9 31
2015-03-15 @ Brondby L 0-2 1526 1556 26.06% 25.98% 47.96% -10.9 25
2015-03-15 Vestsjaelland W 2-0 1543 1425 58.61% 23.53% 17.87% +7.7 31
2015-03-15 @ Nordsjaelland L 0-2 1425 1543 17.87% 23.53% 58.61% -7.7 15
2015-03-16 Aalborg W 1-0 1495 1612 28.18% 26.30% 45.52% +8.9 30
2015-03-16 @ Hobro L 0-1 1612 1495 45.52% 26.30% 28.18% -8.9 31
2015-03-20 Esbjerg L 0-2 1515 1555 38.56% 26.77% 34.67% -14.8 25
2015-03-20 @ Odense W 2-0 1555 1515 34.67% 26.77% 38.56% +14.8 26
2015-03-21 Hobro W 3-0 1683 1504 64.97% 21.19% 13.84% +8.6 53
2015-03-21 @ Midtjylland L 0-3 1504 1683 13.84% 21.19% 64.97% -8.6 30
2015-03-22 Brondby L 0-1 1418 1567 24.60% 25.70% 49.69% -5.5 15
2015-03-22 @ Vestsjaelland W 1-0 1567 1418 49.69% 25.70% 24.60% +5.5 34
2015-03-22 Nordsjaelland D 2-2 1428 1551 27.48% 26.21% 46.31% +0.6 11
2015-03-22 @ Silkeborg D 2-2 1551 1428 46.31% 26.21% 27.48% -0.6 32
2015-03-22 Randers D 1-1 1648 1572 53.80% 24.86% 21.34% -1.4 42
2015-03-22 @ FC Copenhagen D 1-1 1572 1648 21.34% 24.86% 53.80% +1.4 35
2015-03-22 Sonderjyske L 1-4 1604 1495 57.57% 23.85% 18.58% -24.9 31
2015-03-22 @ Aalborg W 4-1 1495 1604 18.58% 23.85% 57.57% +24.9 29
2015-04-04 Nordsjaelland L 1-2 1520 1551 39.76% 26.73% 33.51% -7.6 29
2015-04-04 @ Sonderjyske W 2-1 1551 1520 33.51% 26.73% 39.76% +7.6 35
2015-04-05 Midtjylland D 3-3 1570 1692 27.56% 26.22% 46.22% +0.5 27
2015-04-05 @ Esbjerg D 3-3 1692 1570 46.22% 26.22% 27.56% -0.5 54
2015-04-05 Silkeborg D 2-2 1496 1429 52.67% 25.12% 22.21% -1.0 31
2015-04-05 @ Hobro D 2-2 1429 1496 22.21% 25.12% 52.67% +1.0 12
2015-04-06 Aalborg D 1-1 1573 1579 43.30% 26.52% 30.18% -0.5 36
2015-04-06 @ Randers D 1-1 1579 1573 30.18% 26.52% 43.30% +0.5 32
2015-04-06 FC Copenhagen D 0-0 1572 1647 33.59% 26.74% 39.68% +0.3 35
2015-04-06 @ Brondby D 0-0 1647 1572 39.68% 26.74% 33.59% -0.3 43
2015-04-07 Vestsjaelland L 1-2 1501 1412 55.25% 24.50% 20.25% -9.8 25
2015-04-07 @ Odense W 2-1 1412 1501 20.25% 24.50% 55.25% +9.8 18
2015-04-10 Esbjerg W 3-1 1495 1570 33.49% 26.73% 39.78% +13.1 34
2015-04-10 @ Hobro L 1-3 1570 1495 39.78% 26.73% 33.49% -13.1 27
2015-04-11 Vestsjaelland D 1-1 1573 1422 62.10% 22.32% 15.58% -2.1 37
2015-04-11 @ Randers D 1-1 1422 1573 15.58% 22.32% 62.10% +2.0 19
2015-04-12 Brondby L 0-1 1512 1572 35.56% 26.79% 37.65% -7.4 29
2015-04-12 @ Sonderjyske W 1-0 1572 1512 37.65% 26.79% 35.56% +7.4 38
2015-04-12 Midtjylland L 1-2 1579 1691 28.75% 26.37% 44.88% -5.9 32
2015-04-12 @ Aalborg W 2-1 1691 1579 44.88% 26.37% 28.75% +5.9 57
2015-04-12 Odense L 1-2 1558 1491 52.71% 25.11% 22.18% -9.5 35
2015-04-12 @ Nordsjaelland W 2-1 1491 1558 22.18% 25.11% 52.71% +9.4 28
2015-04-13 FC Copenhagen L 0-4 1430 1647 18.44% 23.78% 57.77% -15.1 12
2015-04-13 @ Silkeborg W 4-0 1647 1430 57.77% 23.78% 18.44% +15.1 46
2015-04-17 Silkeborg W 1-0 1697 1415 74.34% 16.71% 8.95% +1.9 60
2015-04-17 @ Midtjylland L 0-1 1415 1697 8.95% 16.71% 74.34% -1.9 12
2015-04-18 Aalborg W 2-1 1424 1573 24.58% 25.70% 49.72% +9.0 22
2015-04-18 @ Vestsjaelland L 1-2 1573 1424 49.72% 25.70% 24.58% -9.0 32
2015-04-19 Hobro L 0-1 1580 1508 53.27% 24.98% 21.74% -10.1 38
2015-04-19 @ Brondby W 1-0 1508 1580 21.74% 24.98% 53.27% +10.1 37
2015-04-19 Nordsjaelland W 2-0 1662 1549 58.03% 23.71% 18.27% +7.9 49
2015-04-19 @ FC Copenhagen L 0-2 1549 1662 18.27% 23.71% 58.03% -7.9 35
2015-04-19 Sonderjyske D 0-0 1500 1505 43.45% 26.51% 30.05% -0.6 29
2015-04-19 @ Odense D 0-0 1505 1500 30.05% 26.51% 43.45% +0.6 30
2015-04-20 Randers D 0-0 1557 1571 42.18% 26.60% 31.21% -0.5 28
2015-04-20 @ Esbjerg D 0-0 1571 1557 31.21% 26.60% 42.18% +0.5 38
2015-04-24 Odense L 0-2 1557 1500 51.42% 25.38% 23.20% -18.5 28
2015-04-24 @ Esbjerg W 2-0 1500 1557 23.20% 25.38% 51.42% +18.5 32
2015-04-25 Silkeborg W 1-0 1541 1413 59.69% 23.17% 17.13% +3.9 38
2015-04-25 @ Nordsjaelland L 0-1 1413 1541 17.13% 23.17% 59.69% -3.9 12
2015-04-26 Aalborg L 0-3 1505 1564 35.76% 26.79% 37.45% -20.3 30
2015-04-26 @ Sonderjyske W 3-0 1564 1505 37.45% 26.79% 35.76% +20.3 35
2015-04-26 FC Copenhagen W 3-0 1571 1670 30.46% 26.54% 43.00% +23.3 41
2015-04-26 @ Randers L 0-3 1670 1571 43.00% 26.54% 30.46% -23.3 49
2015-04-26 Vestsjaelland W 4-0 1570 1433 60.62% 22.86% 16.52% +13.5 41
2015-04-26 @ Brondby L 0-4 1433 1570 16.52% 22.86% 60.62% -13.5 22
2015-04-27 Midtjylland D 0-0 1518 1699 21.45% 24.89% 53.66% +1.5 38
2015-04-27 @ Hobro D 0-0 1699 1518 53.66% 24.89% 21.45% -1.5 61
2015-05-01 Hobro W 5-0 1585 1520 52.43% 25.17% 22.40% +22.3 38
2015-05-01 @ Aalborg L 0-5 1520 1585 22.40% 25.17% 52.43% -22.3 38
2015-05-02 Sonderjyske D 2-2 1409 1485 33.36% 26.73% 39.91% +0.2 13
2015-05-02 @ Silkeborg D 2-2 1485 1409 39.91% 26.73% 33.36% -0.2 31
2015-05-03 Brondby L 0-2 1518 1583 34.92% 26.78% 38.31% -13.7 32
2015-05-03 @ Odense W 2-0 1583 1518 38.31% 26.78% 34.92% +13.7 44
2015-05-03 Esbjerg W 2-1 1646 1538 57.50% 23.87% 18.63% +4.0 52
2015-05-03 @ FC Copenhagen L 1-2 1538 1646 18.63% 23.87% 57.50% -4.0 28
2015-05-03 Nordsjaelland W 2-1 1419 1545 27.22% 26.17% 46.61% +8.5 25
2015-05-03 @ Vestsjaelland L 1-2 1545 1419 46.61% 26.17% 27.22% -8.5 38
2015-05-04 Randers W 5-2 1698 1594 56.94% 24.03% 19.03% +8.7 64
2015-05-04 @ Midtjylland L 2-5 1594 1698 19.03% 24.03% 56.94% -8.7 41
2015-05-08 Nordsjaelland W 2-0 1586 1536 50.51% 25.56% 23.93% +10.1 44
2015-05-08 @ Randers L 0-2 1536 1586 23.93% 25.56% 50.51% -10.1 38
2015-05-09 Silkeborg W 5-2 1534 1409 59.36% 23.29% 17.36% +8.0 31
2015-05-09 @ Esbjerg L 2-5 1409 1534 17.36% 23.29% 59.36% -8.0 13
2015-05-10 Aalborg D 1-1 1597 1607 42.69% 26.57% 30.74% -0.5 45
2015-05-10 @ Brondby D 1-1 1607 1597 30.74% 26.57% 42.69% +0.5 39
2015-05-10 Midtjylland W 3-1 1505 1706 19.65% 24.28% 56.07% +17.2 35
2015-05-10 @ Odense L 1-3 1706 1505 56.07% 24.28% 19.65% -17.2 64
2015-05-10 Sonderjyske D 2-2 1497 1485 45.70% 26.28% 28.02% -0.5 39
2015-05-10 @ Hobro D 2-2 1485 1497 28.02% 26.28% 45.70% +0.5 32
2015-05-11 FC Copenhagen L 0-1 1428 1650 18.02% 23.60% 58.38% -4.1 25
2015-05-11 @ Vestsjaelland W 1-0 1650 1428 58.38% 23.60% 18.02% +4.1 55
2015-05-15 Odense L 0-2 1607 1522 54.89% 24.59% 20.52% -19.6 39
2015-05-15 @ Aalborg W 2-0 1522 1607 20.52% 24.59% 54.89% +19.6 38
2015-05-17 Brondby L 0-2 1401 1596 20.19% 24.48% 55.33% -8.7 13
2015-05-17 @ Silkeborg W 2-0 1596 1401 55.33% 24.48% 20.19% +8.7 48
2015-05-17 FC Copenhagen W 2-0 1689 1654 48.65% 25.88% 25.48% +10.7 67
2015-05-17 @ Midtjylland L 0-2 1654 1689 25.48% 25.88% 48.65% -10.7 55
2015-05-17 Vestsjaelland L 0-1 1497 1424 53.37% 24.96% 21.67% -10.1 39
2015-05-17 @ Hobro W 1-0 1424 1497 21.67% 24.96% 53.37% +10.1 28
2015-05-18 Esbjerg L 1-3 1526 1542 41.87% 26.63% 31.51% -13.6 38
2015-05-18 @ Nordsjaelland W 3-1 1542 1526 31.51% 26.63% 41.87% +13.6 34
2015-05-18 Randers D 1-1 1485 1596 28.98% 26.40% 44.62% +0.6 33
2015-05-18 @ Sonderjyske D 1-1 1596 1485 44.62% 26.40% 28.98% -0.6 45
2015-05-20 Aalborg W 1-0 1644 1588 51.31% 25.40% 23.28% +5.2 58
2015-05-20 @ FC Copenhagen L 0-1 1588 1644 23.28% 25.40% 51.31% -5.2 39
2015-05-20 Silkeborg D 1-1 1541 1392 61.93% 22.39% 15.69% -2.0 39
2015-05-20 @ Odense D 1-1 1392 1541 15.69% 22.39% 61.93% +2.0 14
2015-05-21 Hobro L 0-1 1595 1487 57.54% 23.85% 18.60% -10.8 45
2015-05-21 @ Randers W 1-0 1487 1595 18.60% 23.85% 57.54% +10.8 42
2015-05-21 Midtjylland D 0-0 1434 1700 15.00% 21.97% 63.03% +2.4 29
2015-05-21 @ Vestsjaelland D 0-0 1700 1434 63.03% 21.97% 15.00% -2.4 68
2015-05-21 Nordsjaelland W 3-1 1605 1512 55.72% 24.37% 19.91% +7.4 51
2015-05-21 @ Brondby L 1-3 1512 1605 19.91% 24.37% 55.72% -7.4 38
2015-05-21 Sonderjyske L 2-3 1556 1486 52.97% 25.05% 21.98% -9.0 34
2015-05-21 @ Esbjerg W 3-2 1486 1556 21.98% 25.05% 52.97% +9.0 36
2015-05-24 Vestsjaelland D 1-1 1495 1436 51.65% 25.33% 23.01% -1.2 37
2015-05-24 @ Sonderjyske D 1-1 1436 1495 23.01% 25.33% 51.65% +1.2 30
2015-05-25 Brondby L 2-3 1697 1613 54.81% 24.61% 20.58% -9.3 68
2015-05-25 @ Midtjylland W 3-2 1613 1697 20.58% 24.61% 54.81% +9.3 54
2015-05-25 Hobro W 4-2 1505 1497 45.09% 26.35% 28.56% +9.1 41
2015-05-25 @ Nordsjaelland L 2-4 1497 1505 28.56% 26.35% 45.09% -9.1 42
2015-05-25 Odense W 1-0 1649 1539 57.65% 23.82% 18.53% +4.2 61
2015-05-25 @ FC Copenhagen L 0-1 1539 1649 18.53% 23.82% 57.65% -4.2 39
2015-05-25 Randers L 0-2 1394 1584 20.67% 24.64% 54.69% -8.9 14
2015-05-25 @ Silkeborg W 2-0 1584 1394 54.69% 24.64% 20.67% +8.9 48
2015-05-26 Esbjerg W 1-0 1583 1547 48.80% 25.85% 25.34% +5.6 42
2015-05-26 @ Aalborg L 0-1 1547 1583 25.34% 25.85% 48.80% -5.6 34
2015-05-31 Aalborg L 1-2 1386 1588 19.58% 24.25% 56.17% -4.2 14
2015-05-31 @ Silkeborg W 2-1 1588 1386 56.17% 24.25% 19.58% +4.2 45
2015-05-31 Brondby D 1-1 1593 1622 40.09% 26.72% 33.19% -0.3 49
2015-05-31 @ Randers D 1-1 1622 1593 33.19% 26.72% 40.09% +0.3 55
2015-05-31 FC Copenhagen L 1-2 1494 1653 23.56% 25.47% 50.98% -5.0 37
2015-05-31 @ Sonderjyske W 2-1 1653 1494 50.98% 25.47% 23.56% +5.0 64
2015-05-31 Midtjylland W 1-0 1514 1688 22.12% 25.09% 52.79% +10.0 44
2015-05-31 @ Nordsjaelland L 0-1 1688 1514 52.79% 25.09% 22.12% -10.0 68
2015-05-31 Odense D 2-2 1488 1535 37.49% 26.79% 35.72% -0.0 43
2015-05-31 @ Hobro D 2-2 1535 1488 35.72% 26.79% 37.49% +0.1 40
2015-05-31 Vestsjaelland W 2-1 1541 1438 56.94% 24.03% 19.03% +4.1 37
2015-05-31 @ Esbjerg L 1-2 1438 1541 19.03% 24.03% 56.94% -4.1 30
2015-06-07 Esbjerg L 0-1 1622 1545 53.89% 24.84% 21.27% -10.2 55
2015-06-07 @ Brondby W 1-0 1545 1622 21.27% 24.84% 53.89% +10.2 40
2015-06-07 Hobro W 1-0 1658 1488 64.08% 21.56% 14.37% +3.3 67
2015-06-07 @ FC Copenhagen L 0-1 1488 1658 14.37% 21.56% 64.08% -3.3 43
2015-06-07 Nordsjaelland W 1-0 1592 1524 52.82% 25.08% 22.10% +5.0 48
2015-06-07 @ Aalborg L 0-1 1524 1592 22.10% 25.08% 52.82% -5.0 44
2015-06-07 Randers L 0-2 1535 1593 35.93% 26.79% 37.28% -14.0 40
2015-06-07 @ Odense W 2-0 1593 1535 37.28% 26.79% 35.93% +14.0 52
2015-06-07 Silkeborg W 3-1 1434 1381 50.85% 25.49% 23.66% +8.7 33
2015-06-07 @ Vestsjaelland L 1-3 1381 1434 23.66% 25.49% 50.85% -8.7 14
2015-06-07 Sonderjyske W 2-1 1678 1489 65.98% 20.76% 13.25% +2.8 71
2015-06-07 @ Midtjylland L 1-2 1489 1678 13.25% 20.76% 65.98% -2.8 37

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 2015-03-01 12.86% Silkeborg 1398 2 @ Randers 1595 1
2 2014-08-10 16.32% Hobro 1473 3 @ FC Copenhagen 1613 0
3 2015-03-14 17.95% Silkeborg 1403 4 @ Sonderjyske 1520 1
4 2015-03-22 18.58% Sonderjyske 1495 4 @ Aalborg 1604 1
5 2015-05-21 18.60% Hobro 1487 1 @ Randers 1595 0
6 2015-05-10 19.65% @ Odense 1505 3 Midtjylland 1706 1
7 2014-07-20 20.00% Hobro 1451 2 @ Odense 1542 1
8 2015-04-07 20.25% Vestsjaelland 1412 2 @ Odense 1501 1
9 2015-05-15 20.52% Odense 1522 2 @ Aalborg 1607 0
10 2015-05-25 20.58% Brondby 1613 3 @ Midtjylland 1697 2
11 2015-06-07 21.27% Esbjerg 1545 1 @ Brondby 1622 0
12 2015-05-17 21.67% Vestsjaelland 1424 1 @ Hobro 1497 0
13 2015-04-19 21.74% Hobro 1508 1 @ Brondby 1580 0
14 2015-05-21 21.98% Sonderjyske 1486 3 @ Esbjerg 1556 2
15 2015-05-31 22.12% @ Nordsjaelland 1514 1 Midtjylland 1688 0
16 2015-04-12 22.18% Odense 1491 2 @ Nordsjaelland 1558 1
17 2014-09-14 22.38% Randers 1525 2 @ Brondby 1590 0
18 2015-04-24 23.20% Odense 1500 2 @ Esbjerg 1557 0
19 2014-08-09 24.22% Nordsjaelland 1560 2 @ Aalborg 1607 1
20 2014-10-18 24.49% Sonderjyske 1521 3 @ Nordsjaelland 1565 2
21 2015-04-18 24.58% @ Vestsjaelland 1424 2 Aalborg 1573 1
22 2014-07-21 24.88% Randers 1531 1 @ Esbjerg 1571 0
23 2015-03-01 26.51% @ Odense 1511 1 FC Copenhagen 1642 0
24 2014-08-17 27.15% Odense 1522 2 @ Randers 1542 0
25 2015-05-03 27.22% @ Vestsjaelland 1419 2 Nordsjaelland 1545 1

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 2014-08-10 31.00 Hobro 3 1473 16.32% @ FC Copenhagen 0 1613 60.93% 22.75%
2 2015-03-14 25.27 Silkeborg 4 1403 17.95% @ Sonderjyske 1 1520 58.48% 23.57%
3 2015-03-22 24.94 Sonderjyske 4 1495 18.58% @ Aalborg 1 1604 57.57% 23.85%
4 2015-03-07 24.86 @ Nordsjaelland 4 1519 40.42% Sonderjyske 0 1545 32.87% 26.71%
5 2014-11-09 24.70 @ Hobro 3 1476 27.48% Brondby 0 1599 46.31% 26.21%
6 2014-08-31 23.88 Brondby 3 1567 29.21% @ Nordsjaelland 0 1569 44.37% 26.42%
7 2015-04-26 23.29 @ Randers 3 1571 30.46% FC Copenhagen 0 1670 43.00% 26.54%
8 2015-05-01 22.33 @ Aalborg 5 1585 52.43% Hobro 0 1520 22.40% 25.17%
9 2015-02-20 22.31 Randers 3 1573 32.63% @ Nordsjaelland 0 1548 40.68% 26.69%
10 2014-12-07 21.02 @ FC Copenhagen 3 1616 35.62% Midtjylland 0 1676 37.59% 26.79%
11 2014-10-19 20.75 @ Brondby 5 1572 54.69% Vestsjaelland 0 1488 20.67% 24.64%
12 2015-04-26 20.26 Aalborg 3 1564 37.45% @ Sonderjyske 0 1505 35.76% 26.79%
13 2015-05-15 19.57 Odense 2 1522 20.52% @ Aalborg 0 1607 54.89% 24.59%
14 2014-09-14 18.84 Randers 2 1525 22.38% @ Brondby 0 1590 52.45% 25.17%
15 2015-04-24 18.53 Odense 2 1500 23.20% @ Esbjerg 0 1557 51.42% 25.38%
16 2014-10-03 18.40 Midtjylland 5 1631 45.41% @ Hobro 1 1515 28.27% 26.31%
17 2015-05-10 17.25 @ Odense 3 1505 19.65% Midtjylland 1 1706 56.07% 24.28%
18 2014-08-17 17.12 Odense 2 1522 27.15% @ Randers 0 1542 46.69% 26.16%
19 2014-08-03 16.77 @ Hobro 2 1456 28.20% Brondby 0 1573 45.50% 26.30%
20 2014-10-26 16.10 @ Randers 3 1544 47.29% Odense 0 1519 26.63% 26.08%
21 2014-11-01 15.57 Esbjerg 4 1565 41.76% @ Vestsjaelland 1 1475 31.60% 26.63%
22 2015-04-13 15.10 FC Copenhagen 4 1647 57.77% @ Silkeborg 0 1430 18.44% 23.78%
23 2014-09-14 14.86 @ Esbjerg 3 1545 50.14% Vestsjaelland 0 1498 24.23% 25.62%
24 2015-03-20 14.75 Esbjerg 2 1555 34.67% @ Odense 0 1515 38.56% 26.77%
25 2014-08-01 14.44 Sonderjyske 2 1530 35.73% @ Silkeborg 0 1483 37.48% 26.79%