Home / Leagues / Denmark / 1st Division / 2018-19

2018-19 1st Division Season

198 games

Final

Promoted

Silkeborg

61 pts

Lyngby · via playoff

Relegated

Thisted

30 pts

Helsingor · 31 pts

Biggest Overachiever

Silkeborg

9.49 points above expected

61 points · 51.51 expected points

Biggest Disappointment

Helsingor

11.26 points below expected

31 points · 42.26 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 Silkeborg Promoted 33 18 7 8 61 60 41 +19 51.51 +9.49
2 Viborg 33 17 9 7 60 61 37 +24 58.49 +1.51
3 Lyngby Promoted 33 15 7 11 52 51 47 +4 43.37 +8.63
4 Naestved 33 13 11 9 50 43 40 +3 46.54 +3.46
5 Fremad Amager 33 13 11 9 50 42 45 -3 42.12 +7.88
6 Fredericia 33 14 5 14 47 51 47 +4 46.28 +0.72
7 HB Koge 33 12 9 12 45 52 47 +5 52.17 -7.17
8 Nykobing 33 12 9 12 45 44 47 -3 46.09 -1.09
9 FC Roskilde 33 9 8 16 35 57 66 -9 39.13 -4.13
10 Hvidovre 33 9 8 16 35 39 49 -10 35.47 -0.47
11 Helsingor Relegated 33 6 13 14 31 35 43 -8 42.26 -11.26
12 Thisted Relegated 33 7 9 17 30 35 61 -26 34.82 -4.82

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
Silkeborg 1563 61 51.51 +9.49 91.3% 27 40 47 51 56 64 79
Viborg 1562 60 58.49 +1.51 60.4% 30 46 54 59 64 70 83
Lyngby 1518 52 43.37 +8.63 89.9% 19 32 38 43 48 55 74
HB Koge 1481 45 52.17 -7.17 17.7% 26 40 47 52 57 64 81
Naestved 1468 50 46.54 +3.46 71.1% 19 35 42 46 51 59 72
Fremad Amager 1458 50 42.12 +7.88 87.3% 15 30 37 42 47 54 69
Fredericia 1448 47 46.28 +0.72 56.7% 18 34 41 46 51 58 73
Nykobing 1444 45 46.09 -1.09 47.4% 20 34 41 46 51 58 72
FC Roskilde 1434 35 39.13 -4.13 30.8% 14 28 34 39 44 51 72
Helsingor 1398 31 42.26 -11.26 6.4% 12 31 37 42 47 54 69
Hvidovre 1378 35 35.47 -0.47 51.3% 11 24 31 35 40 47 65
Thisted 1305 30 34.82 -4.82 27.0% 12 24 30 35 39 47 63

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 FR FRE FA HK HEL HVI LYN NAE NYK SIL THI VIB
FC Roskilde
2-0-1
3.65
0-3-0
3.53
1-0-2
3.27
1-0-2
3.93
2-1-0
4.53
0-0-3
4.22
0-1-2
3.31
1-2-0
2.91
0-0-3
3.26
1-1-1
4.29
1-0-2
2.19
Fredericia
1-0-2
4.51
1-0-2
4.59
2-1-0
3.64
2-1-0
4.09
0-2-1
5.11
2-0-1
4.70
2-0-1
3.64
2-0-1
4.27
0-0-3
3.77
2-0-1
5.04
0-1-2
2.98
Fremad Amager
0-3-0
4.60
2-0-1
3.56
1-1-1
3.20
2-0-1
3.86
1-2-0
4.64
1-2-0
4.02
1-1-1
3.35
2-0-1
3.66
1-1-1
3.55
2-1-0
4.63
0-0-3
2.92
HB Koge
2-0-1
4.87
0-1-2
4.49
1-1-1
4.96
1-2-0
5.20
1-0-2
5.73
1-2-0
4.78
0-1-2
4.57
1-1-1
4.51
1-0-2
4.19
2-1-0
5.26
2-0-1
3.67
Helsingor
2-0-1
4.21
0-1-2
4.04
1-0-2
4.27
0-2-1
2.98
1-0-2
4.38
1-1-1
3.92
0-3-0
3.93
0-2-1
3.75
0-2-1
3.11
1-0-2
4.95
0-2-1
2.81
Hvidovre
0-1-2
3.61
1-2-0
3.04
0-2-1
3.50
2-0-1
2.48
2-0-1
3.75
0-1-2
3.25
2-1-0
3.24
0-0-3
3.35
0-0-3
3.12
1-1-1
3.79
1-0-2
2.23
Lyngby
3-0-0
3.90
1-0-2
3.44
0-2-1
4.10
0-2-1
3.38
1-1-1
4.21
2-1-0
4.90
1-0-2
3.99
2-1-0
3.87
3-0-0
3.33
1-0-2
5.20
1-0-2
3.01
Naestved
2-1-0
4.84
1-0-2
4.49
1-1-1
4.79
2-1-0
3.57
0-3-0
4.21
0-1-2
4.91
2-0-1
4.14
2-0-1
3.77
1-1-1
3.43
1-2-0
5.51
1-1-1
2.85
Nykobing
0-2-1
5.25
1-0-2
3.86
1-0-2
4.47
1-1-1
3.64
1-2-0
4.39
3-0-0
4.79
0-1-2
4.28
1-0-2
4.37
1-0-2
3.28
2-1-0
4.76
1-2-0
3.04
Silkeborg
3-0-0
4.89
3-0-0
4.37
1-1-1
4.59
2-0-1
3.95
1-2-0
5.05
3-0-0
5.04
0-0-3
4.82
1-1-1
4.70
2-0-1
4.87
2-1-0
5.70
0-2-1
3.55
Thisted
1-1-1
3.87
1-0-2
3.13
0-1-2
3.52
0-1-2
2.91
2-0-1
3.21
1-1-1
4.34
2-0-1
2.97
0-2-1
2.68
0-1-2
3.38
0-1-2
2.52
0-1-2
2.33
Viborg
2-0-1
6.08
2-1-0
5.19
3-0-0
5.25
1-0-2
4.46
1-2-0
5.37
2-0-1
6.01
2-0-1
5.17
1-1-1
5.32
0-2-1
5.11
1-2-0
4.59
2-1-0
5.91

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

Slope
Scored 0.49 +8.0
Allowed 0.47 -8.6
Differential 0.83 +7.2

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
07.07%7.32%5.05%3.03%1.26%0.76%24.49%
17.32%11.62%7.58%5.56%1.52%0.51%34.09%
25.05%7.58%6.57%2.02%1.01%0.25%22.47%
33.03%5.56%2.02%1.52%0.76%12.88%
41.26%1.52%1.01%0.76%4.55%
5+0.76%0.51%0.25%1.52%
Total24.49%34.09%22.47%12.88%4.55%1.52%100%

Summary Statistics

Scored Allowed Difference
Mean 1.44 1.44 +0.00
SD 1.22 1.22 1.79
CV 0.85 0.85
Max 7 7 +6
Min 0 0 -6

Games Played: 198

↓ Scored | Allowed →012345+Total
03.03%3.03%6.06%3.03%15.15%
19.09%9.09%12.12%6.06%36.36%
23.03%6.06%12.12%6.06%3.03%30.30%
33.03%3.03%3.03%9.09%
43.03%3.03%
5+3.03%3.03%6.06%
Total12.12%27.27%24.24%24.24%9.09%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.73 2.00 -0.27
SD 1.48 1.30 2.31
CV 0.86 0.65
Max 7 5 +6
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%6.06%3.03%3.03%18.18%
19.09%21.21%3.03%33.33%
23.03%9.09%6.06%6.06%24.24%
312.12%9.09%3.03%24.24%
4
5+
Total30.30%24.24%30.30%12.12%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.55 1.42 +0.12
SD 1.06 1.44 1.92
CV 0.69 1.01
Max 3 7 +3
Min 0 0 -6

Games Played: 33

↓ Scored | Allowed →012345+Total
012.12%3.03%6.06%6.06%27.27%
118.18%6.06%3.03%6.06%33.33%
26.06%9.09%15.15%30.30%
33.03%3.03%
43.03%3.03%6.06%
5+
Total36.36%18.18%27.27%9.09%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 1.36 -0.09
SD 1.10 1.32 1.51
CV 0.86 0.97
Max 4 4 +2
Min 0 0 -4

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%12.12%3.03%21.21%
19.09%12.12%6.06%9.09%3.03%39.39%
23.03%6.06%3.03%12.12%
36.06%6.06%3.03%3.03%18.18%
43.03%3.03%6.06%
5+3.03%3.03%
Total27.27%30.30%21.21%15.15%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.58 1.42 +0.15
SD 1.35 1.23 1.72
CV 0.85 0.86
Max 5 4 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%12.12%6.06%3.03%30.30%
124.24%18.18%3.03%45.45%
23.03%6.06%3.03%12.12%
33.03%6.06%3.03%12.12%
4
5+
Total15.15%48.48%27.27%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.30 -0.24
SD 0.97 0.85 1.28
CV 0.91 0.65
Max 3 3 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
06.06%12.12%18.18%3.03%39.39%
13.03%9.09%3.03%3.03%18.18%
29.09%9.09%9.09%3.03%3.03%33.33%
33.03%3.03%6.06%
4
5+3.03%3.03%
Total18.18%36.36%30.30%9.09%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 1.48 -0.30
SD 1.21 1.09 1.59
CV 1.02 0.74
Max 5 4 +4
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%3.03%3.03%3.03%3.03%3.03%18.18%
112.12%12.12%6.06%6.06%3.03%39.39%
26.06%9.09%6.06%21.21%
36.06%3.03%3.03%12.12%
43.03%6.06%9.09%
5+
Total30.30%33.33%15.15%9.09%9.09%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.55 1.42 +0.12
SD 1.20 1.41 2.13
CV 0.78 0.99
Max 4 5 +4
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%3.03%3.03%3.03%18.18%
115.15%24.24%9.09%6.06%54.55%
26.06%3.03%9.09%
39.09%6.06%15.15%
43.03%3.03%
5+
Total24.24%45.45%18.18%9.09%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.30 1.21 +0.09
SD 1.05 1.02 1.35
CV 0.80 0.84
Max 4 4 +3
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%3.03%6.06%3.03%30.30%
13.03%9.09%6.06%3.03%3.03%24.24%
215.15%6.06%6.06%3.03%30.30%
33.03%6.06%3.03%12.12%
43.03%3.03%
5+
Total30.30%30.30%18.18%12.12%6.06%3.03%100%

Summary Statistics

Scored Allowed Difference
Mean 1.33 1.42 -0.09
SD 1.14 1.37 1.88
CV 0.85 0.96
Max 4 5 +3
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%3.03%6.06%3.03%21.21%
16.06%9.09%3.03%6.06%24.24%
26.06%12.12%3.03%3.03%24.24%
33.03%9.09%3.03%15.15%
43.03%6.06%3.03%12.12%
5+3.03%3.03%
Total27.27%36.36%21.21%15.15%100%

Summary Statistics

Scored Allowed Difference
Mean 1.82 1.24 +0.58
SD 1.42 1.03 1.73
CV 0.78 0.83
Max 5 3 +5
Min 0 0 -3

Games Played: 33

↓ Scored | Allowed →012345+Total
09.09%9.09%6.06%3.03%3.03%3.03%33.33%
16.06%12.12%6.06%9.09%3.03%3.03%39.39%
29.09%3.03%6.06%18.18%
33.03%3.03%6.06%
43.03%3.03%
5+
Total18.18%30.30%18.18%21.21%6.06%6.06%100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.85 -0.79
SD 1.03 1.44 1.80
CV 0.97 0.78
Max 4 5 +4
Min 0 0 -5

Games Played: 33

↓ Scored | Allowed →012345+Total
03.03%12.12%3.03%3.03%21.21%
16.06%12.12%3.03%21.21%
26.06%9.09%9.09%24.24%
312.12%6.06%3.03%21.21%
46.06%3.03%9.09%
5+3.03%3.03%
Total24.24%48.48%18.18%9.09%100%

Summary Statistics

Scored Allowed Difference
Mean 1.85 1.12 +0.73
SD 1.39 0.89 1.77
CV 0.75 0.80
Max 5 3 +5
Min 0 0 -3

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 Silkeborg 61 51.51 +9.49
2 Lyngby 52 43.37 +8.63
3 Fremad Amager 50 42.12 +7.88
4 Naestved 50 46.54 +3.46
5 Viborg 60 58.49 +1.51

Biggest Disappointments

# Team Actual Sim vsSim
1 Helsingor 31 42.26 -11.26
2 HB Koge 45 52.17 -7.17
3 Thisted 30 34.82 -4.82
4 FC Roskilde 35 39.13 -4.13
5 Nykobing 45 46.09 -1.09

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 FC Roskilde 4 Oct 28 – Nov 18 1 in 291
2 Fremad Amager 4 Apr 28 – May 12 1 in 48
3 Silkeborg 4 Sep 10 – Sep 30 1 in 43
4 HB Koge 4 Jul 29 – Aug 19 1 in 31
5 Nykobing 3 May 5 – May 12 1 in 22

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Thisted 7 Nov 11 – Mar 24 1 in 190
2 HB Koge 4 Oct 5 – Oct 28 1 in 179
3 Viborg 3 Nov 25 – Mar 10 1 in 102
4 Hvidovre 6 Aug 26 – Sep 30 1 in 93
5 Fredericia 3 Oct 25 – Nov 4 1 in 73

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Fremad Amager 9 Sep 30 – Nov 25 1 in 83
2 Naestved 8 Mar 3 – Apr 24 1 in 54
3 Thisted 6 Aug 12 – Sep 9 1 in 23
4 Viborg 12 Aug 12 – Oct 25 1 in 22
5 Hvidovre 5 Jul 29 – Aug 22 1 in 16

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 HB Koge 8 Sep 23 – Nov 11 1 in 178
2 Nykobing 8 Mar 10 – Apr 28 1 in 60
3 Helsingor 9 Apr 7 – May 25 1 in 32
4 Thisted 12 Oct 28 – Apr 14 1 in 26
5 FC Roskilde 9 Jul 29 – Sep 16 1 in 19

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
Silkeborg14.77%19.73%17.16%13.63%10.49%8.30%5.54%4.45%2.57%1.79%1.16%0.41%
Viborg52.18%21.27%10.98%6.12%3.76%2.27%1.53%1.03%0.41%0.28%0.14%0.03%
Lyngby1.75%4.74%6.85%8.89%10.43%11.50%11.81%11.90%10.73%9.64%7.13%4.63%
Naestved4.71%8.26%11.52%12.03%12.34%12.04%10.23%9.67%8.00%5.24%3.75%2.21%
Fremad Amager1.30%3.33%5.33%6.99%9.36%10.09%11.40%11.76%12.23%11.83%9.96%6.42%
Fredericia4.04%8.35%11.40%12.26%12.13%11.58%10.63%9.53%7.68%6.04%4.27%2.09%
HB Koge15.63%20.86%17.77%13.48%9.90%7.89%5.36%3.95%2.60%1.48%0.80%0.28%
Nykobing3.74%7.65%10.17%12.16%11.98%11.61%11.50%9.49%8.66%6.33%4.51%2.20%
FC Roskilde0.45%1.56%2.37%4.08%5.27%7.39%9.34%11.43%13.49%15.96%15.66%13.00%
Hvidovre0.11%0.52%0.81%1.77%2.88%3.96%6.40%7.62%10.62%15.08%21.59%28.64%
Helsingor1.25%3.34%5.05%7.06%9.36%9.92%11.42%12.32%12.92%11.37%9.54%6.45%
Thisted0.07%0.39%0.59%1.53%2.10%3.45%4.84%6.85%10.09%14.96%21.49%33.64%

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
+9.60%
Slight Edge
41.41%26.77%31.82%
Elo Value
Home Edge: 33.44 Elo pts.
270 Elo
0.004 goals per Elo point
0800
Scoring Tilt
Expected
+0.19 goals
Neutral
-2+0.12+2

Title Race

How these are measured

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

Title-Race Openness
Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 4 * Open: 4 to 6 * Wide Open: 6 and up.
Champion Preseason Odds
Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd * 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
3.1
Top-Heavy
124610
Champion Preseason Odds
15%
Silkeborg, 3rd of 12
LongshotFavorite
Title Margin
Expected
0.03/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 5.74 * Some Luck: 5.74 to 8.61 * Lucky: 8.61 to 11.48 * Wild Swing: 11.48 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 1.71 * Close: 1.71 to 2.57 * Off: 2.57 to 3.42 * Way Off: 3.42 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 0.95 * A Surprise: 0.95 to 1.51 * Several Surprises: 1.51 to 2.08 * Many Surprises: 2.08 and up.
Luck Spread
Expected
6.20 points
Some Luck
07.1718
Average Finish Error
Expected
2.00
Close
02.145
Biggest Overachiever
Expected 95.83%
91.32%
Silkeborg
50100
Biggest Underachiever
Expected 4.17%
6.44%
Helsingor
050
Season Outliers
Expected
0 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected
1 of 2
A Surprise
00.92

Parity

How these are measured

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

Gini Index
How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.
Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully
How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge
Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst
Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts
Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.13
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.21
Moderate Separation
01.003
Interquartile Edge
59%
Even
50%60%70%80%100%
Best vs. Worst
Baseline
84%
Strong Edge
50%82%100%
Close Games
Expected
62%
Very Frequent
0%60%100%
Blowouts
Expected
15%
Frequent
0%16%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
0.65
Hard to Predict
00.642
Matchup Imbalance
0.25
Notable Separation
00.10.180.280.5
Strangeness
Expected
0.74
Very Predictable
01.002
Repeatability
0.54
Some Carryover
00.30.60.851
Upset Rate
Expected
29%
As Expected
0%27%50%
Clear Favorite Upset Rate
Expected
25%
Shaky Favorites
0%23%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 0.18 * Above Noise: 0.18 to 0.24 * Well Above Noise: 0.24 and up.
Probability calibration
0.06
Borderline
0.010.050.10.51
Calibration slope
Ideal
0.70
Overconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.040
Well Within Noise
00.1180.3

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 Direct promotion Qualified for promotion playoff Same level Direct relegation
Viborg 52.18% 32.25% 15.40% 0.17%
HB Koge 15.63% 38.63% 44.66% 1.08%
Silkeborg 14.77% 36.89% 46.77% 1.57%
Naestved 4.71% 19.78% 69.55% 5.96%
Fredericia 4.04% 19.75% 69.85% 6.36%
Nykobing 3.74% 17.82% 71.73% 6.71%
Lyngby 1.75% 11.59% 74.90% 11.76%
Helsingor 1.25% 8.39% 74.37% 15.99%
Fremad Amager 1.30% 8.66% 73.66% 16.38%
FC Roskilde 0.45% 3.93% 66.96% 28.66%
Hvidovre 0.11% 1.33% 48.33% 50.23%
Thisted 0.07% 0.98% 43.82% 55.13%

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
2018-07-29 FC Roskilde W 5-2 1504 1433 49.77% 27.71% 22.52% +12.2 3
2018-07-29 @ HB Koge L 2-5 1433 1504 22.52% 27.71% 49.77% -12.1 0
2018-07-29 Fredericia W 3-2 1449 1439 41.77% 28.93% 29.31% +6.7 3
2018-07-29 @ Naestved L 2-3 1439 1449 29.31% 28.93% 41.77% -6.7 0
2018-07-29 Fremad Amager W 3-1 1465 1437 44.12% 28.67% 27.21% +11.6 3
2018-07-29 @ Helsingor L 1-3 1437 1465 27.21% 28.67% 44.12% -11.6 0
2018-07-29 Hvidovre D 1-1 1456 1390 49.02% 27.87% 23.11% -1.3 1
2018-07-29 @ Lyngby D 1-1 1390 1456 23.11% 27.87% 49.02% +1.3 1
2018-07-29 Nykobing D 0-0 1536 1470 49.16% 27.84% 23.00% -1.4 1
2018-07-29 @ Viborg D 0-0 1470 1536 23.00% 27.84% 49.16% +1.4 1
2018-07-29 Thisted D 0-0 1497 1401 52.75% 26.98% 20.27% -1.8 1
2018-07-29 @ Silkeborg D 0-0 1401 1497 20.27% 26.98% 52.75% +1.8 1
2018-08-05 Fredericia L 0-3 1420 1433 38.67% 29.13% 32.20% -25.2 0
2018-08-05 @ FC Roskilde W 3-0 1433 1420 32.20% 29.13% 38.67% +25.2 3
2018-08-05 Fremad Amager D 2-2 1392 1426 35.59% 29.20% 35.21% -0.0 2
2018-08-05 @ Hvidovre D 2-2 1426 1392 35.21% 29.20% 35.59% +0.0 1
2018-08-05 Naestved D 1-1 1476 1456 43.15% 28.79% 28.06% -0.7 4
2018-08-05 @ Helsingor D 1-1 1456 1476 28.06% 28.79% 43.15% +0.7 4
2018-08-05 Nykobing L 0-2 1403 1472 30.84% 29.05% 40.11% -14.7 1
2018-08-05 @ Thisted W 2-0 1472 1403 40.11% 29.05% 30.84% +14.7 4
2018-08-05 Silkeborg W 1-0 1454 1495 34.63% 29.20% 36.16% +8.8 4
2018-08-05 @ Lyngby L 0-1 1495 1454 36.16% 29.20% 34.63% -8.8 1
2018-08-05 Viborg W 1-0 1516 1535 37.70% 29.17% 33.13% +8.2 6
2018-08-05 @ HB Koge L 0-1 1535 1516 33.13% 29.17% 37.70% -8.2 1
2018-08-12 FC Roskilde D 0-0 1486 1395 52.22% 27.12% 20.66% -1.7 5
2018-08-12 @ Nykobing D 0-0 1395 1486 20.66% 27.12% 52.22% +1.7 1
2018-08-12 HB Koge L 0-3 1486 1524 35.04% 29.20% 35.75% -23.5 1
2018-08-12 @ Silkeborg W 3-0 1524 1486 35.75% 29.20% 35.04% +23.5 9
2018-08-12 Helsingor D 1-1 1527 1475 47.25% 28.20% 24.54% -1.1 2
2018-08-12 @ Viborg D 1-1 1475 1527 24.54% 28.20% 47.25% +1.1 5
2018-08-12 Hvidovre D 0-0 1458 1392 49.16% 27.84% 23.00% -1.4 4
2018-08-12 @ Fredericia D 0-0 1392 1458 23.00% 27.84% 49.16% +1.4 3
2018-08-12 Lyngby D 2-2 1426 1463 35.10% 29.20% 35.70% +0.0 2
2018-08-12 @ Fremad Amager D 2-2 1463 1426 35.70% 29.20% 35.10% -0.0 5
2018-08-12 Thisted D 1-1 1457 1388 49.45% 27.78% 22.78% -1.3 5
2018-08-12 @ Naestved D 1-1 1388 1457 22.78% 27.78% 49.45% +1.3 2
2018-08-19 Fredericia L 0-1 1477 1456 43.15% 28.79% 28.06% -10.0 5
2018-08-19 @ Helsingor W 1-0 1456 1477 28.06% 28.79% 43.15% +10.0 7
2018-08-19 Fremad Amager W 2-0 1526 1426 53.26% 26.84% 19.90% +10.2 5
2018-08-19 @ Viborg L 0-2 1426 1526 19.90% 26.84% 53.26% -10.2 2
2018-08-19 Lyngby W 4-0 1390 1463 30.20% 29.01% 40.80% +34.3 5
2018-08-19 @ Thisted L 0-4 1463 1390 40.80% 29.01% 30.20% -34.3 5
2018-08-19 Naestved W 2-1 1393 1455 31.65% 29.11% 39.25% +8.8 6
2018-08-19 @ Hvidovre L 1-2 1455 1393 39.25% 29.11% 31.65% -8.8 5
2018-08-19 Nykobing W 1-0 1547 1485 48.74% 27.92% 23.33% +6.3 12
2018-08-19 @ HB Koge L 0-1 1485 1547 23.33% 27.92% 48.74% -6.2 5
2018-08-19 Silkeborg L 0-1 1397 1463 31.19% 29.08% 39.73% -7.9 1
2018-08-19 @ FC Roskilde W 1-0 1463 1397 39.73% 29.08% 31.19% +7.9 4
2018-08-22 FC Roskilde D 1-1 1415 1389 44.00% 28.69% 27.31% -0.8 3
2018-08-22 @ Fremad Amager D 1-1 1389 1415 27.31% 28.69% 44.00% +0.8 2
2018-08-22 HB Koge W 1-0 1447 1554 26.16% 28.51% 45.33% +10.4 8
2018-08-22 @ Naestved L 0-1 1554 1447 45.33% 28.51% 26.16% -10.4 12
2018-08-22 Helsingor W 1-0 1402 1467 31.35% 29.09% 39.57% +9.4 9
2018-08-22 @ Hvidovre L 0-1 1467 1402 39.57% 29.09% 31.35% -9.4 5
2018-08-22 Nykobing W 4-1 1429 1478 33.39% 29.18% 37.43% +20.8 8
2018-08-22 @ Lyngby L 1-4 1478 1429 37.43% 29.18% 33.39% -20.8 5
2018-08-22 Thisted L 1-2 1466 1424 46.14% 28.39% 25.47% -9.9 7
2018-08-22 @ Fredericia W 2-1 1424 1466 25.47% 28.39% 46.14% +9.9 8
2018-08-22 Viborg L 2-3 1471 1536 31.27% 29.08% 39.65% -7.1 4
2018-08-22 @ Silkeborg W 3-2 1536 1471 39.65% 29.08% 31.27% +7.0 8
2018-08-26 Fredericia D 2-2 1543 1457 51.64% 27.27% 21.09% -1.1 9
2018-08-26 @ Viborg D 2-2 1457 1543 21.09% 27.27% 51.64% +1.1 8
2018-08-26 Fremad Amager L 0-1 1458 1415 46.17% 28.38% 25.44% -10.5 5
2018-08-26 @ Nykobing W 1-0 1415 1458 25.44% 28.38% 46.17% +10.5 6
2018-08-26 Hvidovre W 4-3 1543 1411 56.96% 25.68% 17.36% +4.2 15
2018-08-26 @ HB Koge L 3-4 1411 1543 17.36% 25.68% 56.96% -4.2 9
2018-08-26 Lyngby W 2-1 1457 1450 41.45% 28.95% 29.60% +7.1 8
2018-08-26 @ Helsingor L 1-2 1450 1457 29.60% 28.95% 41.45% -7.1 8
2018-08-26 Naestved W 3-1 1464 1457 41.28% 28.97% 29.75% +12.4 7
2018-08-26 @ Silkeborg L 1-3 1457 1464 29.75% 28.97% 41.28% -12.4 8
2018-08-26 Thisted D 2-2 1390 1434 34.16% 29.19% 36.65% +0.1 3
2018-08-26 @ FC Roskilde D 2-2 1434 1390 36.65% 29.19% 34.16% -0.1 9
2018-09-01 FC Roskilde W 3-1 1445 1390 47.72% 28.12% 24.16% +10.5 11
2018-09-01 @ Naestved L 1-3 1390 1445 24.16% 28.12% 47.72% -10.5 3
2018-09-01 HB Koge W 3-1 1458 1547 28.17% 28.80% 43.03% +16.3 11
2018-09-01 @ Fredericia L 1-3 1547 1458 43.03% 28.80% 28.17% -16.3 15
2018-09-01 Viborg L 0-5 1442 1542 27.04% 28.65% 44.31% -31.1 8
2018-09-01 @ Lyngby W 5-0 1542 1442 44.31% 28.65% 27.04% +31.1 12
2018-09-02 Helsingor D 0-0 1447 1464 37.96% 29.16% 32.88% -0.3 6
2018-09-02 @ Nykobing D 0-0 1464 1447 32.88% 29.16% 37.96% +0.2 9
2018-09-02 Hvidovre W 1-0 1434 1407 44.03% 28.69% 27.29% +7.1 12
2018-09-02 @ Thisted L 0-1 1407 1434 27.29% 28.69% 44.03% -7.1 9
2018-09-02 Silkeborg W 2-0 1425 1476 33.22% 29.17% 37.60% +17.0 9
2018-09-02 @ Fremad Amager L 0-2 1476 1425 37.60% 29.17% 33.22% -17.0 7
2018-09-09 Lyngby L 1-4 1379 1411 35.88% 29.20% 34.91% -20.1 3
2018-09-09 @ FC Roskilde W 4-1 1411 1379 34.91% 29.20% 35.88% +20.1 11
2018-09-09 Naestved W 2-1 1573 1455 55.34% 26.22% 18.44% +4.8 15
2018-09-09 @ Viborg L 1-2 1455 1573 18.44% 26.22% 55.34% -4.8 11
2018-09-09 Nykobing L 1-2 1474 1447 44.11% 28.68% 27.22% -9.6 11
2018-09-09 @ Fredericia W 2-1 1447 1474 27.22% 28.68% 44.11% +9.6 9
2018-09-09 Thisted L 0-1 1465 1441 43.64% 28.73% 27.63% -10.1 9
2018-09-09 @ Helsingor W 1-0 1441 1465 27.63% 28.73% 43.64% +10.1 15
2018-09-10 Silkeborg L 2-4 1400 1459 32.10% 29.13% 38.77% -11.8 9
2018-09-10 @ Hvidovre W 4-2 1459 1400 38.77% 29.13% 32.10% +11.8 10
2018-09-16 FC Roskilde W 3-2 1578 1359 65.96% 21.90% 12.14% +2.9 18
2018-09-16 @ Viborg L 2-3 1359 1578 12.14% 21.90% 65.96% -2.9 3
2018-09-16 Fredericia L 1-3 1442 1464 37.28% 29.18% 33.54% -14.6 9
2018-09-16 @ Fremad Amager W 3-1 1464 1442 33.54% 29.18% 37.28% +14.6 14
2018-09-16 HB Koge L 1-3 1451 1531 29.34% 28.93% 41.73% -12.3 15
2018-09-16 @ Thisted W 3-1 1531 1451 41.73% 28.93% 29.34% +12.3 18
2018-09-16 Helsingor W 3-0 1471 1454 42.62% 28.84% 28.53% +20.2 13
2018-09-16 @ Silkeborg L 0-3 1454 1471 28.53% 28.84% 42.62% -20.2 9
2018-09-16 Hvidovre W 2-0 1456 1388 49.40% 27.79% 22.81% +11.6 12
2018-09-16 @ Nykobing L 0-2 1388 1456 22.81% 27.79% 49.40% -11.6 9
2018-09-16 Naestved L 1-3 1431 1450 37.72% 29.17% 33.11% -14.8 11
2018-09-16 @ Lyngby W 3-1 1450 1431 33.11% 29.17% 37.72% +14.8 14
2018-09-19 Fremad Amager W 4-0 1543 1428 55.13% 26.29% 18.59% +18.2 21
2018-09-19 @ HB Koge L 0-4 1428 1543 18.59% 26.29% 55.13% -18.2 9
2018-09-23 Fremad Amager W 2-1 1465 1409 47.85% 28.10% 24.05% +6.0 17
2018-09-23 @ Naestved L 1-2 1409 1465 24.05% 28.10% 47.85% -6.1 9
2018-09-23 Helsingor D 2-2 1562 1434 56.44% 25.86% 17.70% -1.5 22
2018-09-23 @ HB Koge D 2-2 1434 1562 17.70% 25.86% 56.44% +1.5 10
2018-09-23 Hvidovre W 3-0 1356 1377 37.54% 29.17% 33.29% +22.6 6
2018-09-23 @ FC Roskilde L 0-3 1377 1356 33.29% 29.17% 37.54% -22.6 9
2018-09-23 Lyngby W 2-0 1479 1417 48.68% 27.94% 23.39% +11.8 17
2018-09-23 @ Fredericia L 0-2 1417 1479 23.39% 27.94% 48.68% -11.8 11
2018-09-23 Nykobing W 3-1 1491 1468 43.54% 28.74% 27.72% +11.8 16
2018-09-23 @ Silkeborg L 1-3 1468 1491 27.72% 28.74% 43.54% -11.8 12
2018-09-23 Viborg D 3-3 1439 1581 22.49% 27.70% 49.81% +0.8 16
2018-09-23 @ Thisted D 3-3 1581 1439 49.81% 27.70% 22.49% -0.8 19
2018-09-30 FC Roskilde W 3-0 1436 1379 47.98% 28.07% 23.95% +17.5 13
2018-09-30 @ Helsingor L 0-3 1379 1436 23.95% 28.07% 47.98% -17.5 6
2018-09-30 HB Koge D 2-2 1405 1560 21.23% 27.31% 51.46% +1.1 12
2018-09-30 @ Lyngby D 2-2 1560 1405 51.46% 27.31% 21.23% -1.1 23
2018-09-30 Naestved W 4-2 1456 1471 38.28% 29.15% 32.57% +11.9 15
2018-09-30 @ Nykobing L 2-4 1471 1456 32.57% 29.15% 38.28% -11.9 17
2018-09-30 Silkeborg L 1-2 1491 1503 38.74% 29.13% 32.13% -8.7 17
2018-09-30 @ Fredericia W 2-1 1503 1491 32.13% 29.13% 38.74% +8.7 19
2018-09-30 Thisted D 0-0 1403 1439 35.27% 29.21% 35.52% +0.0 10
2018-09-30 @ Fremad Amager D 0-0 1439 1403 35.52% 29.21% 35.27% -0.0 17
2018-09-30 Viborg L 1-3 1354 1580 15.75% 24.75% 59.50% -7.1 9
2018-09-30 @ Hvidovre W 3-1 1580 1354 59.50% 24.75% 15.75% +7.1 22
2018-10-05 HB Koge W 3-1 1587 1559 44.17% 28.67% 27.16% +11.6 25
2018-10-05 @ Viborg L 1-3 1559 1587 27.16% 28.67% 44.17% -11.6 23
2018-10-07 Fredericia L 0-3 1439 1482 34.34% 29.20% 36.46% -23.2 17
2018-10-07 @ Thisted W 3-0 1482 1439 36.46% 29.20% 34.34% +23.1 20
2018-10-07 Helsingor D 1-1 1459 1453 41.24% 28.97% 29.79% -0.5 18
2018-10-07 @ Naestved D 1-1 1453 1459 29.79% 28.97% 41.24% +0.5 14
2018-10-07 Hvidovre D 2-2 1403 1347 47.92% 28.08% 24.00% -0.9 11
2018-10-07 @ Fremad Amager D 2-2 1347 1403 24.00% 28.08% 47.92% +0.8 10
2018-10-07 Lyngby L 1-2 1511 1406 53.91% 26.65% 19.43% -11.3 19
2018-10-07 @ Silkeborg W 2-1 1406 1511 19.43% 26.65% 53.91% +11.3 15
2018-10-07 Nykobing D 2-2 1361 1468 26.21% 28.52% 45.28% +0.7 7
2018-10-07 @ FC Roskilde D 2-2 1468 1361 45.28% 28.52% 26.21% -0.7 16
2018-10-14 Nykobing L 1-2 1454 1467 38.50% 29.14% 32.36% -8.6 14
2018-10-14 @ Helsingor W 2-1 1467 1454 32.36% 29.14% 38.50% +8.7 19
2018-10-14 Silkeborg L 1-2 1548 1500 46.78% 28.29% 24.94% -10.0 23
2018-10-14 @ HB Koge W 2-1 1500 1548 24.94% 28.29% 46.78% +10.0 22
2018-10-14 Thisted W 5-1 1348 1416 30.84% 29.05% 40.10% +28.2 13
2018-10-14 @ Hvidovre L 1-5 1416 1348 40.10% 29.05% 30.84% -28.2 17
2018-10-16 Naestved D 1-1 1362 1459 27.34% 28.69% 43.97% +0.8 8
2018-10-16 @ FC Roskilde D 1-1 1459 1362 43.97% 28.69% 27.34% -0.8 19
2018-10-18 HB Koge W 2-0 1376 1538 20.68% 27.13% 52.20% +22.0 16
2018-10-18 @ Hvidovre L 0-2 1538 1376 52.20% 27.13% 20.68% -22.0 23
2018-10-21 FC Roskilde W 3-2 1388 1363 43.84% 28.71% 27.45% +6.4 20
2018-10-21 @ Thisted L 2-3 1363 1388 27.45% 28.71% 43.84% -6.4 8
2018-10-21 Fredericia L 0-3 1476 1505 36.26% 29.20% 34.54% -24.0 19
2018-10-21 @ Nykobing W 3-0 1505 1476 34.54% 29.20% 36.26% +24.1 23
2018-10-21 Helsingor W 2-0 1402 1445 34.34% 29.20% 36.46% +16.6 14
2018-10-21 @ Fremad Amager L 0-2 1445 1402 36.46% 29.20% 34.34% -16.6 14
2018-10-21 Lyngby W 1-0 1458 1417 45.91% 28.42% 25.66% +6.8 22
2018-10-21 @ Naestved L 0-1 1417 1458 25.66% 28.42% 45.91% -6.8 15
2018-10-21 Silkeborg D 1-1 1598 1510 51.88% 27.21% 20.91% -1.5 26
2018-10-21 @ Viborg D 1-1 1510 1598 20.91% 27.21% 51.88% +1.5 23
2018-10-24 Fremad Amager D 0-0 1410 1419 39.19% 29.11% 31.71% -0.4 16
2018-10-24 @ Lyngby D 0-0 1419 1410 31.71% 29.11% 39.19% +0.4 15
2018-10-25 Viborg L 1-2 1529 1597 30.97% 29.06% 39.97% -7.4 23
2018-10-25 @ Fredericia W 2-1 1597 1529 39.97% 29.06% 30.97% +7.4 29
2018-10-28 Fremad Amager L 1-2 1522 1419 53.57% 26.75% 19.68% -11.2 23
2018-10-28 @ Fredericia W 2-1 1419 1522 19.68% 26.75% 53.57% +11.2 18
2018-10-28 Helsingor D 1-1 1410 1429 37.80% 29.17% 33.04% -0.2 17
2018-10-28 @ Lyngby D 1-1 1429 1410 33.04% 29.17% 37.80% +0.2 15
2018-10-28 Hvidovre W 3-2 1512 1398 54.87% 26.36% 18.76% +4.6 26
2018-10-28 @ Silkeborg L 2-3 1398 1512 18.76% 26.36% 54.87% -4.6 16
2018-10-28 Naestved L 0-1 1516 1465 47.19% 28.21% 24.59% -10.7 23
2018-10-28 @ HB Koge W 1-0 1465 1516 24.59% 28.21% 47.19% +10.7 25
2018-10-28 Thisted D 1-1 1452 1394 48.05% 28.06% 23.89% -1.2 20
2018-10-28 @ Nykobing D 1-1 1394 1452 23.89% 28.06% 48.05% +1.2 21
2018-10-28 Viborg W 3-1 1356 1604 14.38% 23.80% 61.82% +21.8 11
2018-10-28 @ FC Roskilde L 1-3 1604 1356 61.82% 23.80% 14.38% -21.8 29
2018-11-04 FC Roskilde L 1-7 1511 1378 57.01% 25.66% 17.32% -54.0 23
2018-11-04 @ Fredericia W 7-1 1378 1511 17.32% 25.66% 57.01% +54.0 14
2018-11-04 Lyngby L 0-1 1582 1410 61.35% 24.00% 14.65% -13.3 29
2018-11-04 @ Viborg W 1-0 1410 1582 14.65% 24.00% 61.35% +13.3 20
2018-11-04 Naestved W 1-0 1431 1476 34.03% 29.19% 36.77% +8.9 21
2018-11-04 @ Fremad Amager L 0-1 1476 1431 36.77% 29.19% 34.03% -8.9 25
2018-11-04 Nykobing L 0-2 1393 1451 32.31% 29.14% 38.55% -15.2 16
2018-11-04 @ Hvidovre W 2-0 1451 1393 38.55% 29.14% 32.31% +15.2 23
2018-11-04 Silkeborg D 1-1 1429 1516 28.45% 28.84% 42.71% +0.7 16
2018-11-04 @ Helsingor D 1-1 1516 1429 42.71% 28.84% 28.45% -0.7 27
2018-11-04 Thisted D 1-1 1505 1396 54.36% 26.52% 19.12% -1.8 24
2018-11-04 @ HB Koge D 1-1 1396 1505 19.12% 26.52% 54.36% +1.8 22
2018-11-11 Fredericia L 1-3 1423 1457 35.64% 29.20% 35.15% -14.2 20
2018-11-11 @ Lyngby W 3-1 1457 1423 35.15% 29.20% 35.64% +14.2 26
2018-11-11 Fremad Amager L 0-1 1397 1440 34.42% 29.20% 36.38% -8.5 22
2018-11-11 @ Thisted W 1-0 1440 1397 36.38% 29.20% 34.42% +8.5 24
2018-11-11 HB Koge W 4-1 1432 1503 30.55% 29.03% 40.42% +22.0 17
2018-11-11 @ FC Roskilde L 1-4 1503 1432 40.42% 29.03% 30.55% -22.0 24
2018-11-11 Hvidovre D 1-1 1467 1378 51.91% 27.20% 20.89% -1.5 26
2018-11-11 @ Naestved D 1-1 1378 1467 20.89% 27.20% 51.91% +1.5 17
2018-11-11 Silkeborg W 3-1 1466 1516 33.39% 29.18% 37.43% +14.7 26
2018-11-11 @ Nykobing L 1-3 1516 1466 37.43% 29.18% 33.39% -14.7 27
2018-11-12 Viborg L 1-3 1429 1569 22.71% 27.76% 49.54% -10.0 16
2018-11-12 @ Helsingor W 3-1 1569 1429 49.54% 27.76% 22.71% +10.0 32
2018-11-18 Fredericia W 2-0 1380 1471 28.00% 28.78% 43.22% +18.9 20
2018-11-18 @ Hvidovre L 0-2 1471 1380 43.22% 28.78% 28.00% -18.9 26
2018-11-18 Fremad Amager D 0-0 1501 1448 47.47% 28.17% 24.37% -1.2 28
2018-11-18 @ Silkeborg D 0-0 1448 1501 24.37% 28.17% 47.47% +1.2 25
2018-11-18 Helsingor W 2-1 1454 1419 45.12% 28.54% 26.34% +6.5 20
2018-11-18 @ FC Roskilde L 1-2 1419 1454 26.34% 28.54% 45.12% -6.5 16
2018-11-18 Lyngby W 3-0 1481 1409 49.91% 27.68% 22.41% +16.6 27
2018-11-18 @ HB Koge L 0-3 1409 1481 22.41% 27.68% 49.91% -16.6 20
2018-11-18 Nykobing W 1-0 1465 1481 38.22% 29.15% 32.63% +8.1 29
2018-11-18 @ Naestved L 0-1 1481 1465 32.63% 29.15% 38.22% -8.1 26
2018-11-18 Thisted W 2-0 1579 1389 63.16% 23.21% 13.63% +7.0 35
2018-11-18 @ Viborg L 0-2 1389 1579 13.63% 23.21% 63.16% -7.0 22
2018-11-25 FC Roskilde W 4-0 1392 1461 30.85% 29.06% 40.10% +33.8 23
2018-11-25 @ Lyngby L 0-4 1461 1392 40.10% 29.06% 30.85% -33.8 20
2018-11-25 HB Koge W 1-0 1449 1498 33.54% 29.18% 37.28% +9.0 28
2018-11-25 @ Fremad Amager L 0-1 1498 1449 37.28% 29.18% 33.54% -9.0 27
2018-11-25 Hvidovre W 2-0 1413 1399 42.38% 28.87% 28.75% +14.0 19
2018-11-25 @ Helsingor L 0-2 1399 1413 28.75% 28.87% 42.38% -14.0 20
2018-11-25 Naestved W 3-0 1452 1473 37.40% 29.18% 33.43% +22.7 29
2018-11-25 @ Fredericia L 0-3 1473 1452 33.43% 29.18% 37.40% -22.7 29
2018-11-25 Silkeborg L 1-4 1382 1500 24.98% 28.29% 46.72% -15.3 22
2018-11-25 @ Thisted W 4-1 1500 1382 46.72% 28.29% 24.98% +15.3 31
2018-11-25 Viborg W 3-0 1473 1586 25.42% 28.38% 46.20% +28.9 29
2018-11-25 @ Nykobing L 0-3 1586 1473 46.20% 28.38% 25.42% -28.9 35
2019-03-03 FC Roskilde W 3-1 1515 1427 51.84% 27.22% 20.94% +9.3 34
2019-03-03 @ Silkeborg L 1-3 1427 1515 20.94% 27.22% 51.84% -9.3 20
2019-03-03 Fredericia D 3-3 1489 1475 42.33% 28.87% 28.80% -0.4 28
2019-03-03 @ HB Koge D 3-3 1475 1489 28.80% 28.87% 42.33% +0.4 30
2019-03-03 Helsingor L 1-3 1367 1427 31.93% 29.12% 38.95% -13.1 22
2019-03-03 @ Thisted W 3-1 1427 1367 38.95% 29.12% 31.93% +13.1 22
2019-03-03 Lyngby L 0-1 1385 1426 34.49% 29.20% 36.31% -8.5 20
2019-03-03 @ Hvidovre W 1-0 1426 1385 36.31% 29.20% 34.49% +8.5 26
2019-03-03 Nykobing L 0-2 1458 1501 34.27% 29.20% 36.54% -15.9 28
2019-03-03 @ Fremad Amager W 2-0 1501 1458 36.54% 29.20% 34.27% +15.9 32
2019-03-03 Viborg W 1-0 1451 1557 26.20% 28.52% 45.29% +10.4 32
2019-03-03 @ Naestved L 0-1 1557 1451 45.29% 28.52% 26.20% -10.4 35
2019-03-10 FC Roskilde D 2-2 1442 1418 43.76% 28.72% 27.52% -0.6 29
2019-03-10 @ Fremad Amager D 2-2 1418 1442 27.52% 28.72% 43.76% +0.6 21
2019-03-10 HB Koge D 1-1 1517 1488 44.35% 28.65% 27.00% -0.8 33
2019-03-10 @ Nykobing D 1-1 1488 1517 27.00% 28.65% 44.35% +0.8 29
2019-03-10 Helsingor W 1-0 1475 1440 45.15% 28.54% 26.31% +6.9 33
2019-03-10 @ Fredericia L 0-1 1440 1475 26.31% 28.54% 45.15% -6.9 22
2019-03-10 Hvidovre L 0-2 1547 1376 61.16% 24.08% 14.76% -24.9 35
2019-03-10 @ Viborg W 2-0 1376 1547 14.76% 24.08% 61.16% +25.0 23
2019-03-10 Silkeborg D 0-0 1461 1524 31.53% 29.10% 39.37% +0.4 33
2019-03-10 @ Naestved D 0-0 1524 1461 39.37% 29.10% 31.53% -0.4 35
2019-03-10 Thisted W 3-1 1435 1354 51.01% 27.42% 21.57% +9.5 29
2019-03-10 @ Lyngby L 1-3 1354 1435 21.57% 27.42% 51.01% -9.5 22
2019-03-17 FC Roskilde L 0-2 1401 1418 37.98% 29.16% 32.86% -17.1 23
2019-03-17 @ Hvidovre W 2-0 1418 1401 32.86% 29.16% 37.98% +17.1 24
2019-03-17 Fredericia W 2-1 1524 1482 46.04% 28.40% 25.55% +6.4 38
2019-03-17 @ Silkeborg L 1-2 1482 1524 25.55% 28.40% 46.04% -6.4 33
2019-03-17 HB Koge L 0-2 1433 1489 32.49% 29.15% 38.36% -15.3 22
2019-03-17 @ Helsingor W 2-0 1489 1433 38.36% 29.15% 32.49% +15.3 32
2019-03-17 Lyngby D 1-1 1517 1444 49.92% 27.67% 22.40% -1.3 34
2019-03-17 @ Nykobing D 1-1 1444 1517 22.40% 27.67% 49.92% +1.3 30
2019-03-17 Naestved L 2-3 1344 1461 25.01% 28.30% 46.68% -5.9 22
2019-03-17 @ Thisted W 3-2 1461 1344 46.68% 28.30% 25.01% +5.9 36
2019-03-17 Viborg L 0-1 1442 1522 29.35% 28.93% 41.72% -7.5 29
2019-03-17 @ Fremad Amager W 1-0 1522 1442 41.72% 28.93% 29.35% +7.5 38
2019-03-20 Silkeborg W 2-0 1446 1530 28.80% 28.87% 42.33% +18.6 33
2019-03-20 @ Lyngby L 0-2 1530 1446 42.33% 28.87% 28.80% -18.6 38
2019-03-24 Helsingor D 1-1 1529 1418 54.65% 26.43% 18.92% -1.8 39
2019-03-24 @ Viborg D 1-1 1418 1529 18.92% 26.43% 54.65% +1.8 23
2019-03-24 Hvidovre L 1-2 1504 1384 55.67% 26.11% 18.22% -11.6 32
2019-03-24 @ HB Koge W 2-1 1384 1504 18.22% 26.11% 55.67% +11.6 26
2019-03-24 Nykobing W 2-1 1476 1515 34.78% 29.20% 36.01% +8.2 36
2019-03-24 @ Fredericia L 1-2 1515 1476 36.01% 29.20% 34.78% -8.2 34
2019-03-24 Thisted W 2-1 1435 1338 52.96% 26.92% 20.12% +5.2 27
2019-03-24 @ FC Roskilde L 1-2 1338 1435 20.12% 26.92% 52.96% -5.2 22
2019-03-31 FC Roskilde W 2-1 1420 1441 37.44% 29.18% 33.38% +7.8 26
2019-03-31 @ Helsingor L 1-2 1441 1420 33.38% 29.18% 37.44% -7.8 27
2019-03-31 Fredericia W 1-0 1434 1484 33.37% 29.18% 37.45% +9.0 32
2019-03-31 @ Fremad Amager L 0-1 1484 1434 37.45% 29.18% 33.37% -9.0 36
2019-03-31 HB Koge W 4-2 1512 1493 42.97% 28.81% 28.23% +10.7 41
2019-03-31 @ Silkeborg L 2-4 1493 1512 28.23% 28.81% 42.97% -10.7 32
2019-03-31 Hvidovre D 0-0 1333 1395 31.62% 29.10% 39.27% +0.4 23
2019-03-31 @ Thisted D 0-0 1395 1333 39.27% 29.10% 31.62% -0.4 27
2019-03-31 Naestved L 1-2 1507 1467 45.75% 28.45% 25.80% -9.9 34
2019-03-31 @ Nykobing W 2-1 1467 1507 25.80% 28.45% 45.75% +9.9 39
2019-03-31 Viborg L 1-4 1464 1528 31.49% 29.10% 39.41% -18.3 33
2019-03-31 @ Lyngby W 4-1 1528 1464 39.41% 29.10% 31.49% +18.3 42
2019-04-07 Helsingor W 2-1 1395 1427 35.83% 29.20% 34.97% +8.1 30
2019-04-07 @ Hvidovre L 1-2 1427 1395 34.97% 29.20% 35.83% -8.1 26
2019-04-07 Lyngby L 0-3 1475 1446 44.35% 28.65% 27.00% -28.0 36
2019-04-07 @ Fredericia W 3-0 1446 1475 27.00% 28.65% 44.35% +28.0 36
2019-04-07 Nykobing D 2-2 1546 1497 46.96% 28.25% 24.78% -0.8 43
2019-04-07 @ Viborg D 2-2 1497 1546 24.78% 28.25% 46.96% +0.8 35
2019-04-07 Silkeborg L 1-2 1433 1522 28.20% 28.81% 43.00% -6.9 27
2019-04-07 @ FC Roskilde W 2-1 1522 1433 43.00% 28.81% 28.20% +6.9 44
2019-04-07 Thisted W 1-0 1443 1333 54.44% 26.50% 19.06% +5.2 35
2019-04-07 @ Fremad Amager L 0-1 1333 1443 19.06% 26.50% 54.44% -5.2 23
2019-04-08 HB Koge D 0-0 1477 1482 39.70% 29.08% 31.22% -0.4 40
2019-04-08 @ Naestved D 0-0 1482 1477 31.22% 29.08% 39.70% +0.4 33
2019-04-11 Naestved L 1-3 1529 1477 47.41% 28.18% 24.41% -17.6 44
2019-04-11 @ Silkeborg W 3-1 1477 1529 24.41% 28.18% 47.41% +17.6 43
2019-04-14 FC Roskilde L 0-5 1498 1426 49.89% 27.68% 22.43% -49.5 35
2019-04-14 @ Nykobing W 5-0 1426 1498 22.43% 27.68% 49.89% +49.5 30
2019-04-14 Fredericia D 0-0 1419 1447 36.50% 29.20% 34.30% -0.1 27
2019-04-14 @ Helsingor D 0-0 1447 1419 34.30% 29.20% 36.50% +0.1 37
2019-04-14 Fremad Amager D 1-1 1483 1448 45.04% 28.55% 26.41% -0.9 34
2019-04-14 @ HB Koge D 1-1 1448 1483 26.41% 28.55% 45.04% +0.9 36
2019-04-14 Hvidovre W 1-0 1474 1403 49.72% 27.72% 22.56% +6.1 39
2019-04-14 @ Lyngby L 0-1 1403 1474 22.56% 27.72% 49.72% -6.1 30
2019-04-14 Viborg L 0-4 1328 1545 16.33% 25.10% 58.57% -16.0 23
2019-04-14 @ Thisted W 4-0 1545 1328 58.57% 25.10% 16.33% +16.1 46
2019-04-21 FC Roskilde D 2-2 1449 1475 36.73% 29.19% 34.08% -0.1 37
2019-04-21 @ Fremad Amager D 2-2 1475 1449 34.08% 29.19% 36.73% +0.1 31
2019-04-21 HB Koge W 1-0 1447 1482 35.47% 29.21% 35.32% +8.6 40
2019-04-21 @ Fredericia L 0-1 1482 1447 35.32% 29.21% 35.47% -8.6 34
2019-04-21 Naestved D 1-1 1561 1494 49.25% 27.82% 22.93% -1.3 47
2019-04-21 @ Viborg D 1-1 1494 1561 22.93% 27.82% 49.25% +1.3 44
2019-04-21 Nykobing W 3-0 1480 1448 44.67% 28.60% 26.72% +19.2 42
2019-04-21 @ Lyngby L 0-3 1448 1480 26.72% 28.60% 44.67% -19.2 35
2019-04-21 Silkeborg L 0-2 1397 1512 25.32% 28.36% 46.31% -12.6 30
2019-04-21 @ Hvidovre W 2-0 1512 1397 46.31% 28.36% 25.32% +12.6 47
2019-04-21 Thisted L 1-2 1419 1312 54.12% 26.59% 19.29% -11.3 27
2019-04-21 @ Helsingor W 2-1 1312 1419 19.29% 26.59% 54.12% +11.3 26
2019-04-24 Fremad Amager D 0-0 1496 1449 46.64% 28.31% 25.06% -1.1 45
2019-04-24 @ Naestved D 0-0 1449 1496 25.06% 28.31% 46.64% +1.1 38
2019-04-27 Viborg W 1-0 1473 1560 28.52% 28.84% 42.63% +9.9 37
2019-04-27 @ HB Koge L 0-1 1560 1473 42.63% 28.84% 28.52% -9.9 47
2019-04-28 Fredericia L 1-2 1494 1456 45.65% 28.46% 25.89% -9.9 45
2019-04-28 @ Naestved W 2-1 1456 1494 25.89% 28.46% 45.65% +9.9 43
2019-04-28 Fremad Amager L 2-4 1429 1450 37.42% 29.18% 33.40% -13.1 35
2019-04-28 @ Nykobing W 4-2 1450 1429 33.40% 29.18% 37.42% +13.1 41
2019-04-28 Helsingor D 1-1 1524 1408 55.18% 26.27% 18.55% -1.8 48
2019-04-28 @ Silkeborg D 1-1 1408 1524 18.55% 26.27% 55.18% +1.8 28
2019-04-28 Hvidovre D 1-1 1475 1384 52.21% 27.12% 20.67% -1.6 32
2019-04-28 @ FC Roskilde D 1-1 1384 1475 20.67% 27.12% 52.21% +1.5 31
2019-04-28 Lyngby W 2-1 1323 1499 19.46% 26.66% 53.88% +11.3 29
2019-04-28 @ Thisted L 1-2 1499 1323 53.88% 26.66% 19.46% -11.3 42
2019-05-03 Silkeborg L 0-1 1465 1522 32.38% 29.14% 38.48% -8.1 43
2019-05-03 @ Fredericia W 1-0 1522 1465 38.48% 29.14% 32.38% +8.1 51
2019-05-05 FC Roskilde W 3-1 1550 1474 50.41% 27.57% 22.03% +9.7 50
2019-05-05 @ Viborg L 1-3 1474 1550 22.03% 27.57% 50.41% -9.7 32
2019-05-05 Fremad Amager L 1-2 1410 1464 32.80% 29.16% 38.04% -7.7 28
2019-05-05 @ Helsingor W 2-1 1464 1410 38.04% 29.16% 32.80% +7.7 44
2019-05-05 HB Koge D 1-1 1488 1483 41.05% 28.99% 29.96% -0.5 43
2019-05-05 @ Lyngby D 1-1 1483 1488 29.96% 28.99% 41.05% +0.5 38
2019-05-05 Naestved W 3-1 1386 1485 27.12% 28.66% 44.22% +16.7 34
2019-05-05 @ Hvidovre L 1-3 1485 1386 44.22% 28.66% 27.12% -16.6 45
2019-05-05 Nykobing L 0-1 1335 1416 29.18% 28.91% 41.90% -7.5 29
2019-05-05 @ Thisted W 1-0 1416 1335 41.90% 28.91% 29.18% +7.5 38
2019-05-08 FC Roskilde W 4-1 1468 1464 40.93% 29.00% 30.08% +17.7 48
2019-05-08 @ Naestved L 1-4 1464 1468 30.08% 29.00% 40.93% -17.7 32
2019-05-08 Helsingor D 0-0 1484 1402 51.06% 27.41% 21.52% -1.6 39
2019-05-08 @ HB Koge D 0-0 1402 1484 21.52% 27.41% 51.06% +1.6 29
2019-05-08 Hvidovre W 2-0 1424 1403 43.27% 28.78% 27.95% +13.7 41
2019-05-08 @ Nykobing L 0-2 1403 1424 27.95% 28.78% 43.27% -13.7 34
2019-05-08 Lyngby W 4-3 1471 1487 38.14% 29.15% 32.70% +7.1 47
2019-05-08 @ Fremad Amager L 3-4 1487 1471 32.70% 29.15% 38.14% -7.1 43
2019-05-08 Thisted W 5-0 1530 1327 64.48% 22.61% 12.91% +15.4 54
2019-05-08 @ Silkeborg L 0-5 1327 1530 12.91% 22.61% 64.48% -15.4 29
2019-05-09 Fredericia W 2-1 1560 1457 53.57% 26.75% 19.68% +5.1 53
2019-05-09 @ Viborg L 1-2 1457 1560 19.68% 26.75% 53.57% -5.1 43
2019-05-12 Fremad Amager L 1-2 1389 1478 28.22% 28.81% 42.97% -6.9 34
2019-05-12 @ Hvidovre W 2-1 1478 1389 42.97% 28.81% 28.22% +6.9 50
2019-05-12 Lyngby L 1-2 1446 1480 35.63% 29.20% 35.17% -8.2 32
2019-05-12 @ FC Roskilde W 2-1 1480 1446 35.17% 29.20% 35.63% +8.2 46
2019-05-12 Naestved D 1-1 1404 1486 29.11% 28.91% 41.98% +0.6 30
2019-05-12 @ Helsingor D 1-1 1486 1404 41.98% 28.91% 29.11% -0.6 49
2019-05-12 Nykobing L 1-3 1482 1437 46.41% 28.35% 25.24% -17.3 39
2019-05-12 @ HB Koge W 3-1 1437 1482 25.24% 28.35% 46.41% +17.3 44
2019-05-12 Thisted W 2-1 1452 1312 57.91% 25.35% 16.74% +4.3 46
2019-05-12 @ Fredericia L 1-2 1312 1452 16.74% 25.35% 57.91% -4.3 29
2019-05-14 Viborg D 2-2 1546 1565 37.72% 29.17% 33.11% -0.2 55
2019-05-14 @ Silkeborg D 2-2 1565 1546 33.11% 29.17% 37.72% +0.2 54
2019-05-19 Fredericia W 3-2 1438 1457 37.81% 29.17% 33.02% +7.3 35
2019-05-19 @ FC Roskilde L 2-3 1457 1438 33.02% 29.17% 37.81% -7.3 46
2019-05-19 HB Koge L 2-3 1307 1465 21.06% 27.26% 51.69% -5.1 29
2019-05-19 @ Thisted W 3-2 1465 1307 51.69% 27.26% 21.06% +5.1 42
2019-05-19 Helsingor D 3-3 1455 1404 47.15% 28.22% 24.63% -0.7 45
2019-05-19 @ Nykobing D 3-3 1404 1455 24.63% 28.22% 47.15% +0.7 31
2019-05-19 Naestved W 2-0 1488 1485 40.84% 29.00% 30.15% +14.5 49
2019-05-19 @ Lyngby L 0-2 1485 1488 30.15% 29.00% 40.84% -14.5 49
2019-05-19 Silkeborg L 3-4 1485 1546 31.90% 29.12% 38.99% -7.0 50
2019-05-19 @ Fremad Amager W 4-3 1546 1485 38.99% 29.12% 31.90% +7.0 58
2019-05-19 Viborg L 0-1 1382 1565 18.86% 26.41% 54.73% -5.2 34
2019-05-19 @ Hvidovre W 1-0 1565 1382 54.73% 26.41% 18.86% +5.2 57
2019-05-25 FC Roskilde W 3-1 1470 1446 43.70% 28.73% 27.58% +11.7 45
2019-05-25 @ HB Koge L 1-3 1446 1470 27.58% 28.73% 43.70% -11.7 35
2019-05-25 Fremad Amager W 4-0 1570 1478 52.33% 27.09% 20.58% +20.0 60
2019-05-25 @ Viborg L 0-4 1478 1570 20.58% 27.09% 52.33% -20.1 50
2019-05-25 Hvidovre D 2-2 1449 1377 49.93% 27.67% 22.39% -1.0 47
2019-05-25 @ Fredericia D 2-2 1377 1449 22.39% 27.67% 49.93% +1.0 35
2019-05-25 Lyngby L 1-2 1405 1503 27.20% 28.67% 44.12% -6.7 31
2019-05-25 @ Helsingor W 2-1 1503 1405 44.12% 28.67% 27.20% +6.7 52
2019-05-25 Nykobing W 2-0 1553 1454 53.14% 26.87% 19.99% +10.3 61
2019-05-25 @ Silkeborg L 0-2 1454 1553 19.99% 26.87% 53.14% -10.3 45
2019-05-25 Thisted D 1-1 1471 1302 60.90% 24.19% 14.91% -2.3 50
2019-05-25 @ Naestved D 1-1 1302 1471 14.91% 24.19% 60.90% +2.3 30

Playoff Game Log

Every playoff game for the team selected at the top of the tab (empty if they didn't reach the postseason). Sort any column by clicking its header. @ before an opponent name indicates an away game; the record column shows the team's running playoff record.

Date Opponent Score Pre Elo Opp Elo Win % Tie % Loss % Elo Δ Record
2019-05-30 Vendsyssel W 2-1 1509 1526 38.08% 29.16% 32.76% +7.7 1-0
2019-05-30 @ Lyngby L 1-2 1526 1509 32.76% 29.16% 38.08% -7.7 0-1
2019-05-30 Viborg W 1-0 1544 1590 33.87% 29.19% 36.94% +8.9 1-0
2019-05-30 @ Hobro L 0-1 1590 1544 36.94% 29.19% 33.87% -8.9 0-1
2019-06-02 Hobro L 0-2 1581 1553 44.24% 28.66% 27.10% -19.2 0-2
2019-06-02 @ Viborg W 2-0 1553 1581 27.10% 28.66% 44.24% +19.2 2-0
2019-06-02 Lyngby D 2-2 1518 1517 40.55% 29.02% 30.43% -0.3 0-1-1
2019-06-02 @ Vendsyssel D 2-2 1517 1518 30.43% 29.02% 40.55% +0.3 1-0-1

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 2018-10-28 14.38% @ FC Roskilde 1356 3 Viborg 1604 1
2 2018-11-04 14.65% Lyngby 1410 1 @ Viborg 1582 0
3 2019-03-10 14.76% Hvidovre 1376 2 @ Viborg 1547 0
4 2018-11-04 17.32% FC Roskilde 1378 7 @ Fredericia 1511 1
5 2019-03-24 18.22% Hvidovre 1384 2 @ HB Koge 1504 1
6 2019-04-21 19.29% Thisted 1312 2 @ Helsingor 1419 1
7 2018-10-07 19.43% Lyngby 1406 2 @ Silkeborg 1511 1
8 2019-04-28 19.46% @ Thisted 1323 2 Lyngby 1499 1
9 2018-10-28 19.68% Fremad Amager 1419 2 @ Fredericia 1522 1
10 2018-10-18 20.68% @ Hvidovre 1376 2 HB Koge 1538 0
11 2019-04-14 22.43% FC Roskilde 1426 5 @ Nykobing 1498 0
12 2019-04-11 24.41% Naestved 1477 3 @ Silkeborg 1529 1
13 2018-10-28 24.59% Naestved 1465 1 @ HB Koge 1516 0
14 2018-10-14 24.94% Silkeborg 1500 2 @ HB Koge 1548 1
15 2019-05-12 25.24% Nykobing 1437 3 @ HB Koge 1482 1
16 2018-11-25 25.42% @ Nykobing 1473 3 Viborg 1586 0
17 2018-08-26 25.44% Fremad Amager 1415 1 @ Nykobing 1458 0
18 2018-08-22 25.47% Thisted 1424 2 @ Fredericia 1466 1
19 2019-03-31 25.80% Naestved 1467 2 @ Nykobing 1507 1
20 2019-04-28 25.89% Fredericia 1456 2 @ Naestved 1494 1
21 2018-08-22 26.16% @ Naestved 1447 1 HB Koge 1554 0
22 2019-03-03 26.20% @ Naestved 1451 1 Viborg 1557 0
23 2019-04-07 27.00% Lyngby 1446 3 @ Fredericia 1475 0
24 2019-05-05 27.12% @ Hvidovre 1386 3 Naestved 1485 1
25 2018-09-09 27.22% Nykobing 1447 2 @ Fredericia 1474 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 2018-11-04 54.03 FC Roskilde 7 1378 17.32% @ Fredericia 1 1511 57.01% 25.66%
2 2019-04-14 49.48 FC Roskilde 5 1426 22.43% @ Nykobing 0 1498 49.89% 27.68%
3 2018-08-19 34.27 @ Thisted 4 1390 30.20% Lyngby 0 1463 40.80% 29.01%
4 2018-11-25 33.83 @ Lyngby 4 1392 30.85% FC Roskilde 0 1461 40.10% 29.06%
5 2018-09-01 31.13 Viborg 5 1542 44.31% @ Lyngby 0 1442 27.04% 28.65%
6 2018-11-25 28.88 @ Nykobing 3 1473 25.42% Viborg 0 1586 46.20% 28.38%
7 2018-10-14 28.20 @ Hvidovre 5 1348 30.84% Thisted 1 1416 40.10% 29.05%
8 2019-04-07 27.98 Lyngby 3 1446 27.00% @ Fredericia 0 1475 44.35% 28.65%
9 2018-08-05 25.21 Fredericia 3 1433 32.20% @ FC Roskilde 0 1420 38.67% 29.13%
10 2019-03-10 24.95 Hvidovre 2 1376 14.76% @ Viborg 0 1547 61.16% 24.08%
11 2018-10-21 24.06 Fredericia 3 1505 34.54% @ Nykobing 0 1476 36.26% 29.20%
12 2018-08-12 23.48 HB Koge 3 1524 35.75% @ Silkeborg 0 1486 35.04% 29.20%
13 2018-10-07 23.15 Fredericia 3 1482 36.46% @ Thisted 0 1439 34.34% 29.20%
14 2018-11-25 22.70 @ Fredericia 3 1452 37.40% Naestved 0 1473 33.43% 29.18%
15 2018-09-23 22.63 @ FC Roskilde 3 1356 37.54% Hvidovre 0 1377 33.29% 29.17%
16 2018-11-11 21.97 @ FC Roskilde 4 1432 30.55% HB Koge 1 1503 40.42% 29.03%
17 2018-10-18 21.95 @ Hvidovre 2 1376 20.68% HB Koge 0 1538 52.20% 27.13%
18 2018-10-28 21.79 @ FC Roskilde 3 1356 14.38% Viborg 1 1604 61.82% 23.80%
19 2018-08-22 20.76 @ Lyngby 4 1429 33.39% Nykobing 1 1478 37.43% 29.18%
20 2018-09-16 20.17 @ Silkeborg 3 1471 42.62% Helsingor 0 1454 28.53% 28.84%
21 2018-09-09 20.13 Lyngby 4 1411 34.91% @ FC Roskilde 1 1379 35.88% 29.20%
22 2019-05-25 20.06 @ Viborg 4 1570 52.33% Fremad Amager 0 1478 20.58% 27.09%
23 2019-04-21 19.16 @ Lyngby 3 1480 44.67% Nykobing 0 1448 26.72% 28.60%
24 2018-11-18 18.88 @ Hvidovre 2 1380 28.00% Fredericia 0 1471 43.22% 28.78%
25 2019-03-20 18.58 @ Lyngby 2 1446 28.80% Silkeborg 0 1530 42.33% 28.87%