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

9.04 points above expected

61 points · 51.96 expected points

Biggest Disappointment

Helsingor

11.10 points below expected

31 points · 42.10 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	51.96	+9.04
2	Viborg	33	17	9	7	60	61	37	+24	58.94	+1.06
3	Lyngby Promoted	33	15	7	11	52	51	47	+4	43.12	+8.88
4	Naestved	33	13	11	9	50	43	40	+3	47.98	+2.02
5	Fremad Amager	33	13	11	9	50	42	45	-3	42.21	+7.79
6	Fredericia	33	14	5	14	47	51	47	+4	46.56	+0.44
7	HB Koge	33	12	9	12	45	52	47	+5	51.32	-6.32
8	Nykobing	33	12	9	12	45	44	47	-3	47.14	-2.14
9	FC Roskilde	33	9	8	16	35	57	66	-9	39.66	-4.66
10	Hvidovre	33	9	8	16	35	39	49	-10	33.63	+1.37
11	Helsingor Relegated	33	6	13	14	31	35	43	-8	42.10	-11.10
12	Thisted Relegated	33	7	9	17	30	35	61	-26	33.91	-3.91

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	51.96	+9.04
2	Lyngby	52	43.12	+8.88
3	Fremad Amager	50	42.21	+7.79
4	Naestved	50	47.98	+2.02
5	Hvidovre	35	33.63	+1.37

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Helsingor	31	42.10	-11.10
2	HB Koge	45	51.32	-6.32
3	FC Roskilde	35	39.66	-4.66
4	Thisted	30	33.91	-3.91
5	Nykobing	45	47.14	-2.14

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 consecutive wins or ties; Winless counts consecutive losses or ties.

Most Unlikely Winning Streaks

#	Team	Games	Dates	Probability
1	FC Roskilde	4	Oct 28 – Nov 18	1 in 292
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 189
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 91
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

Position Race

Each team’s league position across the whole season. Colored teams are the season’s headline finishers — champion, promoted, and relegated; everyone else is gray as context.

Recent Form

Each team’s last 5 games, hottest first. Form shows the results (navy win, gray draw, red loss, newest on the right); the bars show Elo change over the window, points taken, points expected from the odds, and actual minus expected. Beside each team: current Elo and season points.

Team	Elo	Season Pts	Elo Δ (5)	Points (5)	Expected (5)	Actual − Exp
Silkeborg	1569	61	+41	13	8.4	+4.6
Viborg	1596	60	+40	13	8.7	+4.3
Lyngby	1515	52	+22	10	7.3	+2.7
Fremad Amager	1464	50	-5	9	6.6	+2.4
Naestved	1474	50	-16	5	7.9	-2.9
Fredericia	1454	47	-17	4	7.2	-3.2
Nykobing	1449	45	+27	10	6.7	+3.3
HB Koge	1487	45	-2	8	8.1	-0.1
Hvidovre	1383	35	-8	4	5.1	-1.1
FC Roskilde	1440	35	-40	3	6.0	-3.0
Helsingor	1404	31	-12	3	5.5	-2.5
Thisted	1310	30	-30	1	4.1	-3.1

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 4.54	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 5.12	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 4.66	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 5.74	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 4.39	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 3.60	1-2-0 3.04	0-2-1 3.48	2-0-1 2.47	2-0-1 3.74	—	0-1-2 3.24	2-1-0 3.23	0-0-3 3.34	0-0-3 3.12	1-1-1 3.78	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 4.91	—	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 4.20	0-1-2 4.92	2-0-1 4.14	—	2-0-1 3.76	1-1-1 3.43	1-2-0 5.51	1-1-1 2.85
Nykobing	0-2-1 5.26	1-0-2 3.86	1-0-2 4.47	1-1-1 3.64	1-2-0 4.39	3-0-0 4.80	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 5.05	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 4.35	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 6.02	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

	R²	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.

View:

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.07%	7.32%	5.05%	3.03%	1.26%	0.76%	24.49%
1	7.32%	11.62%	7.58%	5.56%	1.52%	0.51%	34.09%
2	5.05%	7.58%	6.57%	2.02%	1.01%	0.25%	22.47%
3	3.03%	5.56%	2.02%	1.52%	0.76%	—	12.88%
4	1.26%	1.52%	1.01%	0.76%	—	—	4.55%
5+	0.76%	0.51%	0.25%	—	—	—	1.52%
Total	24.49%	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 →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	—	6.06%	3.03%	—	15.15%
1	—	9.09%	9.09%	12.12%	6.06%	—	36.36%
2	3.03%	6.06%	12.12%	6.06%	—	3.03%	30.30%
3	3.03%	3.03%	3.03%	—	—	—	9.09%
4	—	3.03%	—	—	—	—	3.03%
5+	3.03%	3.03%	—	—	—	—	6.06%
Total	12.12%	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 →	0	1	2	3	4	5+	Total
0	6.06%	6.06%	3.03%	3.03%	—	—	18.18%
1	9.09%	—	21.21%	—	—	3.03%	33.33%
2	3.03%	9.09%	6.06%	6.06%	—	—	24.24%
3	12.12%	9.09%	—	3.03%	—	—	24.24%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	30.30%	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 →	0	1	2	3	4	5+	Total
0	12.12%	3.03%	6.06%	—	6.06%	—	27.27%
1	18.18%	6.06%	3.03%	6.06%	—	—	33.33%
2	6.06%	9.09%	15.15%	—	—	—	30.30%
3	—	—	—	—	3.03%	—	3.03%
4	—	—	3.03%	3.03%	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	36.36%	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 →	0	1	2	3	4	5+	Total
0	6.06%	12.12%	3.03%	—	—	—	21.21%
1	9.09%	12.12%	6.06%	9.09%	3.03%	—	39.39%
2	3.03%	—	6.06%	—	3.03%	—	12.12%
3	6.06%	6.06%	3.03%	3.03%	—	—	18.18%
4	3.03%	—	—	3.03%	—	—	6.06%
5+	—	—	3.03%	—	—	—	3.03%
Total	27.27%	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 →	0	1	2	3	4	5+	Total
0	9.09%	12.12%	6.06%	3.03%	—	—	30.30%
1	—	24.24%	18.18%	3.03%	—	—	45.45%
2	3.03%	6.06%	3.03%	—	—	—	12.12%
3	3.03%	6.06%	—	3.03%	—	—	12.12%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	15.15%	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 →	0	1	2	3	4	5+	Total
0	6.06%	12.12%	18.18%	3.03%	—	—	39.39%
1	3.03%	9.09%	3.03%	3.03%	—	—	18.18%
2	9.09%	9.09%	9.09%	3.03%	3.03%	—	33.33%
3	—	3.03%	—	—	3.03%	—	6.06%
4	—	—	—	—	—	—	—
5+	—	3.03%	—	—	—	—	3.03%
Total	18.18%	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 →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	3.03%	3.03%	3.03%	3.03%	18.18%
1	12.12%	12.12%	6.06%	6.06%	3.03%	—	39.39%
2	6.06%	9.09%	6.06%	—	—	—	21.21%
3	6.06%	3.03%	—	—	3.03%	—	12.12%
4	3.03%	6.06%	—	—	—	—	9.09%
5+	—	—	—	—	—	—	—
Total	30.30%	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 →	0	1	2	3	4	5+	Total
0	9.09%	3.03%	3.03%	3.03%	—	—	18.18%
1	15.15%	24.24%	9.09%	6.06%	—	—	54.55%
2	—	6.06%	—	—	3.03%	—	9.09%
3	—	9.09%	6.06%	—	—	—	15.15%
4	—	3.03%	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	24.24%	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 →	0	1	2	3	4	5+	Total
0	9.09%	9.09%	3.03%	6.06%	—	3.03%	30.30%
1	3.03%	9.09%	6.06%	3.03%	3.03%	—	24.24%
2	15.15%	6.06%	6.06%	—	3.03%	—	30.30%
3	3.03%	6.06%	—	3.03%	—	—	12.12%
4	—	—	3.03%	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	30.30%	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 →	0	1	2	3	4	5+	Total
0	9.09%	3.03%	6.06%	3.03%	—	—	21.21%
1	6.06%	9.09%	3.03%	6.06%	—	—	24.24%
2	6.06%	12.12%	3.03%	3.03%	—	—	24.24%
3	3.03%	9.09%	3.03%	—	—	—	15.15%
4	—	3.03%	6.06%	3.03%	—	—	12.12%
5+	3.03%	—	—	—	—	—	3.03%
Total	27.27%	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 →	0	1	2	3	4	5+	Total
0	9.09%	9.09%	6.06%	3.03%	3.03%	3.03%	33.33%
1	6.06%	12.12%	6.06%	9.09%	3.03%	3.03%	39.39%
2	—	9.09%	3.03%	6.06%	—	—	18.18%
3	—	—	3.03%	3.03%	—	—	6.06%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	18.18%	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 →	0	1	2	3	4	5+	Total
0	3.03%	12.12%	3.03%	3.03%	—	—	21.21%
1	6.06%	12.12%	—	3.03%	—	—	21.21%
2	6.06%	9.09%	9.09%	—	—	—	24.24%
3	—	12.12%	6.06%	3.03%	—	—	21.21%
4	6.06%	3.03%	—	—	—	—	9.09%
5+	3.03%	—	—	—	—	—	3.03%
Total	24.24%	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

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	1569	61	51.96	+9.04	88.0%	34	39	45	52	58	63	79
Viborg	1568	60	58.94	+1.06	54.0%	43	46	53	59	64	70	76
Lyngby	1523	52	43.12	+8.88	88.0%	28	31	37	43	48	56	65
HB Koge	1487	45	51.32	-6.32	18.0%	35	40	47	51	56	62	70
Naestved	1474	50	47.98	+2.02	60.0%	28	35	44	48	53	58	62
Fremad Amager	1464	50	42.21	+7.79	88.0%	27	32	38	42	46	54	60
Fredericia	1454	47	46.56	+0.44	55.0%	32	36	41	46	50	58	70
Nykobing	1449	45	47.14	-2.14	45.0%	32	37	43	47	51	57	61
FC Roskilde	1440	35	39.66	-4.66	30.0%	24	29	35	38	45	53	56
Helsingor	1404	31	42.10	-11.10	3.0%	28	32	36	42	47	55	60
Hvidovre	1383	35	33.63	+1.37	57.0%	14	22	27	34	39	45	50
Thisted	1310	30	33.91	-3.91	28.0%	21	24	30	34	37	45	53

Point 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).

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.

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 11.5% * Slight Edge: 11.5% to 19% * Clear Edge: 19% to 28.5% * Strong Edge: 28.5% 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%

No Edge

41.41%26.77%31.82%

Elo Value

Home Edge: 33.44 Elo pts.

271 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 3 * Open: 3 to 4 * Wide Open: 4 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 0.06 * Tight Race: 0.06 to 0.13 * Comfortable: 0.13 to 0.24 * Runaway: 0.24 and up.

Title-Race Openness

3.1

Open

123410

Champion Preseason Odds

21%

Silkeborg, 2nd of 12

LongshotFavorite

Title Margin

Expected

0.03/gm

Photo Finish

00.180.5/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 5.65 * Some Luck: 5.65 to 8.47 * Lucky: 8.47 to 11.29 * Wild Swing: 11.29 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 1.61 * Close: 1.61 to 2.42 * Off: 2.42 to 3.23 * Way Off: 3.23 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 0.85 * A Surprise: 0.85 to 1.36 * Several Surprises: 1.36 to 1.87 * Many Surprises: 1.87 and up.

Luck Spread

Expected

6.01 points

Some Luck

07.0618

Average Finish Error

Expected

1.83

02.025

Biggest Overachiever

Expected 95.83%

88.00%

Silkeborg

50100

Biggest Underachiever

Expected 4.17%

3.00%

Helsingor

050

Season Outliers

Expected

1 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 0.13 * Even: 0.13 to 0.17 * Top-Heavy: 0.17 to 0.2 * Lopsided: 0.2 and up.
Noll-Scully: Take a league where every match is a coin flip and nobody is better than anybody. You would still get a table, with a leader and a bottom club, purely by luck, and you can work out how far apart that table would be. This is the real table measured against it. At 1.00 the season was no more spread out than pure chance; at 2.00 it was twice as spread out, which takes genuine differences in quality. Dividing by the luck figure is what makes seasons of different lengths comparable, because a short season spreads a table by luck alone far more than a long one does. Elo SD in the corner is the same question in rating points: how far apart the teams finished on the ratings.
Coin-Flip Parity: under 1.5 * Moderate Separation: 1.5 to 1.8 * Strong Separation: 1.8 to 2.15 * Wide Separation: 2.15 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 63.5% * Slight Edge: 63.5% to 68% * Clear Edge: 68% to 74.5% * Wide Edge: 74.5% 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 85% * Clear Edge: 85% to 91% * Strong Edge: 91% to 95% * Dominant: 95% 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 54.5% * Some Drama: 54.5% to 60% * Frequent: 60% to 65% * Very Frequent: 65% 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 14.5% * Occasional: 14.5% to 18.5% * Frequent: 18.5% to 23.5% * Very Frequent: 23.5% and up.

Gini Index

0.13

Balanced

00.130.20.5

Noll-Scully

Elo SD: 77.62

1.40

Coin-Flip Parity

0.751.51.82.153

Interquartile Edge

59%

Even

50%63.5%74.5%100%

Best vs. Worst

Baseline

84%

Even

50%82%100%

Close Games

Expected

62%

Frequent

0%60%100%

Blowouts

Expected

15%

Occasional

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 0.34 * Slight Separation: 0.34 to 0.42 * Notable Separation: 0.42 to 0.51 * Lopsided: 0.51 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 0.38 * Some Carryover: 0.38 to 0.57 * Strong Carryover: 0.57 to 0.7 * Near-Lock: 0.7 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 18% * As Expected: 18% to 22% * Upset-Prone: 22% to 25% * Very Upset-Prone: 25% 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 15.5% * As Expected: 15.5% to 18.5% * Shaky Favorites: 18.5% to 22% * Very Shaky: 22% and up.

Brier Score

Expected

0.65

Hard to Predict

00.642

Matchup Imbalance

0.25

Very Even

00.340.420.5

Strangeness

Expected

0.70

Very Predictable

01.002

Repeatability

0.54

Some Carryover

00.380.570.71

Upset Rate

Expected

29%

Very Upset-Prone

0%27%50%

Clear Favorite Upset Rate

Expected

25%

Very Shaky

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

0.07

Borderline

0.010.050.10.51

Calibration slope

Ideal

0.69

Overconfident

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.040

Well Within Noise

00.1190.3

Final Table Odds

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).

Team	1	2	3	4	5	6	7	8	9	10	11	12
Silkeborg	21.00%	21.00%	11.00%	10.00%	8.00%	9.00%	6.00%	8.00%	2.00%	3.00%	1.00%	—
Viborg	51.00%	20.00%	12.00%	8.00%	1.00%	6.00%	1.00%	1.00%	—	—	—	—
Lyngby	2.00%	5.00%	6.00%	7.00%	12.00%	11.00%	10.00%	13.00%	6.00%	16.00%	9.00%	3.00%
Naestved	3.00%	9.00%	21.00%	16.00%	12.00%	10.00%	7.00%	11.00%	4.00%	2.00%	3.00%	2.00%
Fremad Amager	1.00%	4.00%	2.00%	8.00%	9.00%	8.00%	12.00%	11.00%	18.00%	14.00%	8.00%	5.00%
Fredericia	4.00%	7.00%	13.00%	12.00%	15.00%	9.00%	9.00%	12.00%	11.00%	6.00%	1.00%	1.00%
HB Koge	12.00%	20.00%	16.00%	16.00%	9.00%	11.00%	9.00%	3.00%	2.00%	2.00%	—	—
Nykobing	4.00%	8.00%	13.00%	10.00%	16.00%	12.00%	16.00%	10.00%	9.00%	1.00%	1.00%	—
FC Roskilde	—	1.00%	3.00%	6.00%	6.00%	6.00%	9.00%	11.00%	13.00%	14.00%	20.00%	11.00%
Hvidovre	—	—	—	1.00%	3.00%	6.00%	7.00%	4.00%	16.00%	9.00%	16.00%	38.00%
Helsingor	2.00%	5.00%	2.00%	5.00%	7.00%	11.00%	12.00%	12.00%	12.00%	12.00%	14.00%	6.00%
Thisted	—	—	1.00%	1.00%	2.00%	1.00%	2.00%	4.00%	7.00%	21.00%	27.00%	34.00%

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.

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	51.00%	32.00%	17.00%	—
Silkeborg	21.00%	32.00%	46.00%	1.00%
HB Koge	12.00%	36.00%	52.00%	—
Nykobing	4.00%	21.00%	74.00%	1.00%
Fredericia	4.00%	20.00%	74.00%	2.00%
Naestved	3.00%	30.00%	62.00%	5.00%
Lyngby	2.00%	11.00%	75.00%	12.00%
Fremad Amager	1.00%	6.00%	80.00%	13.00%
Helsingor	2.00%	7.00%	71.00%	20.00%
FC Roskilde	—	4.00%	65.00%	31.00%
Hvidovre	—	—	46.00%	54.00%
Thisted	—	1.00%	38.00%	61.00%

Filter by Team:

Overall Game Log

Summary of every completed game this season. Sort any column by clicking its header.

Date	Opponent	Score	Excitement	Pre Elo	Opp Elo	Win %	Tie %	Loss %	Proj. Margin	Elo Δ	Points
2018-07-29	FC Roskilde	W 5-2	47.5	1509	1438	49.77%	27.71%	22.52%	+0.39	+12.1	3
2018-07-29	@ HB Koge	L 2-5	47.5	1438	1509	22.52%	27.71%	49.77%	-0.39	-12.1	0
2018-07-29	Fredericia	W 3-2	56.6	1455	1445	41.76%	28.93%	29.32%	+0.16	+6.7	3
2018-07-29	@ Naestved	L 2-3	56.6	1445	1455	29.32%	28.93%	41.76%	-0.16	-6.7	0
2018-07-29	Fremad Amager	W 3-1	47.8	1470	1443	44.12%	28.68%	27.21%	+0.22	+11.6	3
2018-07-29	@ Helsingor	L 1-3	47.8	1443	1470	27.21%	28.68%	44.12%	-0.22	-11.6	0
2018-07-29	Hvidovre	D 1-1	56.8	1461	1395	49.19%	27.83%	22.98%	+0.37	-1.3	1
2018-07-29	@ Lyngby	D 1-1	56.8	1395	1461	22.98%	27.83%	49.19%	-0.37	+1.3	1
2018-07-29	Nykobing	D 0-0	58.0	1542	1476	49.15%	27.84%	23.01%	+0.37	-1.4	1
2018-07-29	@ Viborg	D 0-0	58.0	1476	1542	23.01%	27.84%	49.15%	-0.37	+1.4	1
2018-07-29	Thisted	D 0-0	54.3	1502	1407	52.74%	26.98%	20.27%	+0.48	-1.8	1
2018-07-29	@ Silkeborg	D 0-0	54.3	1407	1502	20.27%	26.98%	52.74%	-0.48	+1.8	1
2018-08-05	Fredericia	L 0-3	41.9	1426	1438	38.67%	29.13%	32.20%	+0.08	-25.2	0
2018-08-05	@ FC Roskilde	W 3-0	41.9	1438	1426	32.20%	29.13%	38.67%	-0.08	+25.2	3
2018-08-05	Fremad Amager	D 2-2	61.4	1396	1431	35.39%	29.21%	35.40%	-0.01	+0.0	2
2018-08-05	@ Hvidovre	D 2-2	61.4	1431	1396	35.40%	29.21%	35.39%	+0.01	+0.0	1
2018-08-05	Naestved	D 1-1	59.3	1482	1462	43.16%	28.79%	28.05%	+0.20	-0.7	4
2018-08-05	@ Helsingor	D 1-1	59.3	1462	1482	28.05%	28.79%	43.16%	-0.20	+0.7	4
2018-08-05	Nykobing	L 0-2	42.3	1409	1477	30.84%	29.05%	40.11%	-0.13	-14.7	1
2018-08-05	@ Thisted	W 2-0	42.3	1477	1409	40.11%	29.05%	30.84%	+0.13	+14.7	4
2018-08-05	Silkeborg	W 1-0	50.1	1460	1501	34.63%	29.20%	36.17%	-0.03	+8.8	4
2018-08-05	@ Lyngby	L 0-1	50.1	1501	1460	36.17%	29.20%	34.63%	+0.03	-8.8	1
2018-08-05	Viborg	W 1-0	53.0	1521	1541	37.70%	29.17%	33.13%	+0.05	+8.2	6
2018-08-05	@ HB Koge	L 0-1	53.0	1541	1521	33.13%	29.17%	37.70%	-0.05	-8.2	1
2018-08-12	FC Roskilde	D 0-0	53.7	1492	1401	52.23%	27.12%	20.65%	+0.46	-1.7	5
2018-08-12	@ Nykobing	D 0-0	53.7	1401	1492	20.65%	27.12%	52.23%	-0.46	+1.7	1
2018-08-12	HB Koge	L 0-3	46.4	1492	1530	35.04%	29.20%	35.75%	-0.02	-23.5	1
2018-08-12	@ Silkeborg	W 3-0	46.4	1530	1492	35.75%	29.20%	35.04%	+0.02	+23.5	9
2018-08-12	Helsingor	D 1-1	62.1	1532	1481	47.26%	28.20%	24.54%	+0.31	-1.1	2
2018-08-12	@ Viborg	D 1-1	62.1	1481	1532	24.54%	28.20%	47.26%	-0.31	+1.1	5
2018-08-12	Hvidovre	D 0-0	52.5	1464	1396	49.32%	27.80%	22.87%	+0.37	-1.4	4
2018-08-12	@ Fredericia	D 0-0	52.5	1396	1464	22.87%	27.80%	49.32%	-0.37	+1.4	3
2018-08-12	Lyngby	D 2-2	63.5	1431	1469	35.10%	29.20%	35.70%	-0.01	+0.0	2
2018-08-12	@ Fremad Amager	D 2-2	63.5	1469	1431	35.70%	29.20%	35.10%	+0.01	-0.0	5
2018-08-12	Thisted	D 1-1	56.8	1462	1394	49.43%	27.78%	22.79%	+0.38	-1.3	5
2018-08-12	@ Naestved	D 1-1	56.8	1394	1462	22.79%	27.78%	49.43%	-0.38	+1.3	2
2018-08-19	Fredericia	L 0-1	51.5	1482	1462	43.15%	28.79%	28.06%	+0.20	-10.0	5
2018-08-19	@ Helsingor	W 1-0	51.5	1462	1482	28.06%	28.79%	43.15%	-0.20	+10.0	7
2018-08-19	Fremad Amager	W 2-0	41.0	1531	1431	53.26%	26.84%	19.90%	+0.49	+10.2	5
2018-08-19	@ Viborg	L 0-2	41.0	1431	1531	19.90%	26.84%	53.26%	-0.49	-10.2	2
2018-08-19	Lyngby	W 4-0	42.4	1395	1469	30.20%	29.01%	40.79%	-0.15	+34.3	5
2018-08-19	@ Thisted	L 0-4	42.4	1469	1395	40.79%	29.01%	30.20%	+0.15	-34.3	5
2018-08-19	Naestved	W 2-1	53.1	1398	1461	31.49%	29.10%	39.42%	-0.11	+8.8	6
2018-08-19	@ Hvidovre	L 1-2	53.1	1461	1398	39.42%	29.10%	31.49%	+0.11	-8.8	5
2018-08-19	Nykobing	W 1-0	49.0	1553	1490	48.74%	27.92%	23.34%	+0.36	+6.3	12
2018-08-19	@ HB Koge	L 0-1	49.0	1490	1553	23.34%	27.92%	48.74%	-0.36	-6.3	5
2018-08-19	Silkeborg	L 0-1	45.6	1403	1468	31.19%	29.08%	39.73%	-0.12	-7.9	1
2018-08-19	@ FC Roskilde	W 1-0	45.6	1468	1403	39.73%	29.08%	31.19%	+0.12	+7.9	4
2018-08-22	FC Roskilde	D 1-1	55.5	1421	1395	44.01%	28.69%	27.30%	+0.22	-0.8	3
2018-08-22	@ Fremad Amager	D 1-1	55.5	1395	1421	27.30%	28.69%	44.01%	-0.22	+0.8	2
2018-08-22	HB Koge	W 1-0	54.6	1452	1559	26.15%	28.51%	45.34%	-0.27	+10.4	8
2018-08-22	@ Naestved	L 0-1	54.6	1559	1452	45.34%	28.51%	26.15%	+0.27	-10.4	12
2018-08-22	Helsingor	W 1-0	48.4	1406	1472	31.18%	29.08%	39.74%	-0.12	+9.4	9
2018-08-22	@ Hvidovre	L 0-1	48.4	1472	1406	39.74%	29.08%	31.18%	+0.12	-9.4	5
2018-08-22	Nykobing	W 4-1	48.6	1434	1484	33.39%	29.18%	37.44%	-0.06	+20.8	8
2018-08-22	@ Lyngby	L 1-4	48.6	1484	1434	37.44%	29.18%	33.39%	+0.06	-20.8	5
2018-08-22	Thisted	L 1-2	56.3	1472	1430	46.14%	28.39%	25.47%	+0.28	-9.9	7
2018-08-22	@ Fredericia	W 2-1	56.3	1430	1472	25.47%	28.39%	46.14%	-0.28	+9.9	8
2018-08-22	Viborg	L 2-3	61.5	1476	1542	31.27%	29.08%	39.65%	-0.12	-7.1	4
2018-08-22	@ Silkeborg	W 3-2	61.5	1542	1476	39.65%	29.08%	31.27%	+0.12	+7.1	8
2018-08-26	Fredericia	D 2-2	68.1	1549	1462	51.65%	27.27%	21.08%	+0.44	-1.1	9
2018-08-26	@ Viborg	D 2-2	68.1	1462	1549	21.08%	27.27%	51.65%	-0.44	+1.1	8
2018-08-26	Fremad Amager	L 0-1	50.2	1463	1420	46.18%	28.38%	25.44%	+0.28	-10.5	5
2018-08-26	@ Nykobing	W 1-0	50.2	1420	1463	25.44%	28.38%	46.18%	-0.28	+10.5	6
2018-08-26	Hvidovre	W 4-3	57.1	1549	1416	57.10%	25.63%	17.27%	+0.62	+4.1	15
2018-08-26	@ HB Koge	L 3-4	57.1	1416	1549	17.27%	25.63%	57.10%	-0.62	-4.1	9
2018-08-26	Lyngby	W 2-1	52.0	1463	1455	41.45%	28.95%	29.60%	+0.15	+7.1	8
2018-08-26	@ Helsingor	L 1-2	52.0	1455	1463	29.60%	28.95%	41.45%	-0.15	-7.1	8
2018-08-26	Naestved	W 3-1	49.3	1469	1463	41.30%	28.97%	29.73%	+0.15	+12.4	7
2018-08-26	@ Silkeborg	L 1-3	49.3	1463	1469	29.73%	28.97%	41.30%	-0.15	-12.4	8
2018-08-26	Thisted	D 2-2	61.6	1396	1440	34.16%	29.19%	36.65%	-0.04	+0.1	3
2018-08-26	@ FC Roskilde	D 2-2	61.6	1440	1396	36.65%	29.19%	34.16%	+0.04	-0.1	9
2018-09-01	FC Roskilde	W 3-1	44.6	1450	1396	47.70%	28.12%	24.17%	+0.33	+10.5	11
2018-09-01	@ Naestved	L 1-3	44.6	1396	1450	24.17%	28.12%	47.70%	-0.33	-10.5	3
2018-09-01	HB Koge	W 3-1	56.3	1463	1553	28.17%	28.80%	43.03%	-0.21	+16.3	11
2018-09-01	@ Fredericia	L 1-3	56.3	1553	1463	43.03%	28.80%	28.17%	+0.21	-16.3	15
2018-09-01	Viborg	L 0-5	43.5	1448	1547	27.03%	28.65%	44.32%	-0.24	-31.1	8
2018-09-01	@ Lyngby	W 5-0	43.5	1547	1448	44.32%	28.65%	27.03%	+0.24	+31.1	12
2018-09-02	Helsingor	D 0-0	54.1	1453	1470	37.97%	29.16%	32.87%	+0.06	-0.3	6
2018-09-02	@ Nykobing	D 0-0	54.1	1470	1453	32.87%	29.16%	37.97%	-0.06	+0.2	9
2018-09-02	Hvidovre	W 1-0	43.7	1439	1412	44.19%	28.67%	27.14%	+0.23	+7.1	12
2018-09-02	@ Thisted	L 0-1	43.7	1412	1439	27.14%	28.67%	44.19%	-0.23	-7.1	9
2018-09-02	Silkeborg	W 2-0	45.2	1431	1482	33.23%	29.17%	37.60%	-0.06	+17.0	9
2018-09-02	@ Fremad Amager	L 0-2	45.2	1482	1431	37.60%	29.17%	33.23%	+0.06	-17.0	7
2018-09-09	Lyngby	L 1-4	44.8	1385	1417	35.88%	29.20%	34.91%	+0.01	-20.1	3
2018-09-09	@ FC Roskilde	W 4-1	44.8	1417	1385	34.91%	29.20%	35.88%	-0.01	+20.1	11
2018-09-09	Naestved	W 2-1	52.3	1579	1461	55.35%	26.22%	18.43%	+0.56	+4.8	15
2018-09-09	@ Viborg	L 1-2	52.3	1461	1579	18.43%	26.22%	55.35%	-0.56	-4.8	11
2018-09-09	Nykobing	L 1-2	56.8	1480	1452	44.10%	28.68%	27.22%	+0.22	-9.6	11
2018-09-09	@ Fredericia	W 2-1	56.8	1452	1480	27.22%	28.68%	44.10%	-0.22	+9.6	9
2018-09-09	Thisted	L 0-1	50.7	1470	1447	43.64%	28.73%	27.63%	+0.21	-10.1	9
2018-09-09	@ Helsingor	W 1-0	50.7	1447	1470	27.63%	28.73%	43.64%	-0.21	+10.1	15
2018-09-10	Silkeborg	L 2-4	52.0	1404	1465	31.94%	29.12%	38.94%	-0.10	-11.7	9
2018-09-10	@ Hvidovre	W 4-2	52.0	1465	1404	38.94%	29.12%	31.94%	+0.10	+11.7	10
2018-09-16	FC Roskilde	W 3-2	51.0	1583	1365	65.96%	21.90%	12.14%	+0.93	+2.9	18
2018-09-16	@ Viborg	L 2-3	51.0	1365	1583	12.14%	21.90%	65.96%	-0.93	-2.9	3
2018-09-16	Fredericia	L 1-3	51.1	1448	1470	37.29%	29.18%	33.53%	+0.04	-14.6	9
2018-09-16	@ Fremad Amager	W 3-1	51.1	1470	1448	33.53%	29.18%	37.29%	-0.04	+14.6	14
2018-09-16	HB Koge	L 1-3	51.4	1457	1537	29.34%	28.93%	41.73%	-0.17	-12.3	15
2018-09-16	@ Thisted	W 3-1	51.4	1537	1457	41.73%	28.93%	29.34%	+0.17	+12.3	18
2018-09-16	Helsingor	W 3-0	41.2	1476	1460	42.62%	28.85%	28.54%	+0.18	+20.2	13
2018-09-16	@ Silkeborg	L 0-3	41.2	1460	1476	28.54%	28.85%	42.62%	-0.18	-20.2	9
2018-09-16	Hvidovre	W 2-0	38.5	1462	1393	49.54%	27.76%	22.70%	+0.38	+11.5	12
2018-09-16	@ Nykobing	L 0-2	38.5	1393	1462	22.70%	27.76%	49.54%	-0.38	-11.5	9
2018-09-16	Naestved	L 1-3	50.4	1437	1456	37.74%	29.17%	33.10%	+0.05	-14.8	11
2018-09-16	@ Lyngby	W 3-1	50.4	1456	1437	33.10%	29.17%	37.74%	-0.05	+14.8	14
2018-09-19	Fremad Amager	W 4-0	38.9	1549	1433	55.12%	26.29%	18.59%	+0.55	+18.2	21
2018-09-19	@ HB Koge	L 0-4	38.9	1433	1549	18.59%	26.29%	55.12%	-0.55	-18.2	9
2018-09-23	Fremad Amager	W 2-1	49.1	1471	1415	47.84%	28.10%	24.06%	+0.33	+6.1	17
2018-09-23	@ Naestved	L 1-2	49.1	1415	1471	24.06%	28.10%	47.84%	-0.33	-6.1	9
2018-09-23	Helsingor	D 2-2	68.4	1567	1440	56.44%	25.86%	17.70%	+0.59	-1.4	22
2018-09-23	@ HB Koge	D 2-2	68.4	1440	1567	17.70%	25.86%	56.44%	-0.59	+1.5	10
2018-09-23	Hvidovre	W 3-0	37.5	1362	1381	37.69%	29.17%	33.14%	+0.05	+22.6	6
2018-09-23	@ FC Roskilde	L 0-3	37.5	1381	1362	33.14%	29.17%	37.69%	-0.05	-22.6	9
2018-09-23	Lyngby	W 2-0	40.4	1485	1422	48.67%	27.94%	23.39%	+0.35	+11.8	17
2018-09-23	@ Fredericia	L 0-2	40.4	1422	1485	23.39%	27.94%	48.67%	-0.35	-11.8	11
2018-09-23	Nykobing	W 3-1	50.0	1497	1474	43.53%	28.75%	27.72%	+0.21	+11.8	16
2018-09-23	@ Silkeborg	L 1-3	50.0	1474	1497	27.72%	28.75%	43.53%	-0.21	-11.8	12
2018-09-23	Viborg	D 3-3	72.8	1444	1586	22.49%	27.70%	49.81%	-0.40	+0.8	16
2018-09-23	@ Thisted	D 3-3	72.8	1586	1444	49.81%	27.70%	22.49%	+0.40	-0.8	19
2018-09-30	FC Roskilde	W 3-0	36.2	1441	1385	47.98%	28.07%	23.95%	+0.33	+17.5	13
2018-09-30	@ Helsingor	L 0-3	36.2	1385	1441	23.95%	28.07%	47.98%	-0.33	-17.5	6
2018-09-30	HB Koge	D 2-2	66.8	1411	1566	21.23%	27.31%	51.46%	-0.45	+1.1	12
2018-09-30	@ Lyngby	D 2-2	66.8	1566	1411	51.46%	27.31%	21.23%	+0.45	-1.1	23
2018-09-30	Naestved	W 4-2	54.5	1462	1477	38.29%	29.15%	32.56%	+0.07	+11.9	15
2018-09-30	@ Nykobing	L 2-4	54.5	1477	1462	32.56%	29.15%	38.29%	-0.07	-11.9	17
2018-09-30	Silkeborg	L 1-2	58.0	1496	1508	38.75%	29.13%	32.12%	+0.08	-8.7	17
2018-09-30	@ Fredericia	W 2-1	58.0	1508	1496	32.12%	29.13%	38.75%	-0.08	+8.7	19
2018-09-30	Thisted	D 0-0	51.9	1409	1445	35.28%	29.21%	35.52%	-0.01	+0.0	10
2018-09-30	@ Fremad Amager	D 0-0	51.9	1445	1409	35.52%	29.21%	35.28%	+0.01	-0.0	17
2018-09-30	Viborg	L 1-3	44.2	1359	1585	15.69%	24.71%	59.61%	-0.71	-7.0	9
2018-09-30	@ Hvidovre	W 3-1	44.2	1585	1359	59.61%	24.71%	15.69%	+0.71	+7.0	22
2018-10-05	HB Koge	W 3-1	56.2	1592	1565	44.17%	28.67%	27.16%	+0.23	+11.6	25
2018-10-05	@ Viborg	L 1-3	56.2	1565	1592	27.16%	28.67%	44.17%	-0.23	-11.6	23
2018-10-07	Fredericia	L 0-3	42.9	1445	1488	34.35%	29.20%	36.46%	-0.03	-23.2	17
2018-10-07	@ Thisted	W 3-0	42.9	1488	1445	36.46%	29.20%	34.35%	+0.03	+23.1	20
2018-10-07	Helsingor	D 1-1	58.6	1465	1459	41.23%	28.97%	29.80%	+0.15	-0.5	18
2018-10-07	@ Naestved	D 1-1	58.6	1459	1465	29.80%	28.97%	41.23%	-0.15	+0.5	14
2018-10-07	Hvidovre	D 2-2	60.3	1409	1352	48.04%	28.06%	23.90%	+0.34	-0.9	11
2018-10-07	@ Fremad Amager	D 2-2	60.3	1352	1409	23.90%	28.06%	48.04%	-0.34	+0.9	10
2018-10-07	Lyngby	L 1-2	59.0	1517	1412	53.91%	26.65%	19.44%	+0.51	-11.3	19
2018-10-07	@ Silkeborg	W 2-1	59.0	1412	1517	19.44%	26.65%	53.91%	-0.51	+11.3	15
2018-10-07	Nykobing	D 2-2	62.0	1367	1474	26.20%	28.52%	45.28%	-0.27	+0.7	7
2018-10-07	@ FC Roskilde	D 2-2	62.0	1474	1367	45.28%	28.52%	26.20%	+0.27	-0.7	16
2018-10-14	Nykobing	L 1-2	55.3	1459	1473	38.50%	29.14%	32.36%	+0.07	-8.7	14
2018-10-14	@ Helsingor	W 2-1	55.3	1473	1459	32.36%	29.14%	38.50%	-0.07	+8.7	19
2018-10-14	Silkeborg	L 1-2	62.1	1553	1506	46.78%	28.28%	24.93%	+0.30	-10.0	23
2018-10-14	@ HB Koge	W 2-1	62.1	1506	1553	24.93%	28.28%	46.78%	-0.30	+10.0	22
2018-10-14	Thisted	W 5-1	44.1	1353	1422	30.72%	29.05%	40.24%	-0.13	+28.3	13
2018-10-14	@ Hvidovre	L 1-5	44.1	1422	1353	40.24%	29.05%	30.72%	+0.13	-28.3	17
2018-10-16	Naestved	D 1-1	55.9	1368	1464	27.34%	28.69%	43.96%	-0.23	+0.8	8
2018-10-16	@ FC Roskilde	D 1-1	55.9	1464	1368	43.96%	28.69%	27.34%	+0.23	-0.8	19
2018-10-18	HB Koge	W 2-0	49.4	1381	1543	20.60%	27.10%	52.30%	-0.48	+22.0	16
2018-10-18	@ Hvidovre	L 0-2	49.4	1543	1381	52.30%	27.10%	20.60%	+0.48	-22.0	23
2018-10-21	FC Roskilde	W 3-2	52.4	1394	1369	43.84%	28.71%	27.45%	+0.22	+6.4	20
2018-10-21	@ Thisted	L 2-3	52.4	1369	1394	27.45%	28.71%	43.84%	-0.22	-6.4	8
2018-10-21	Fredericia	L 0-3	45.7	1482	1511	36.26%	29.20%	34.54%	+0.02	-24.1	19
2018-10-21	@ Nykobing	W 3-0	45.7	1511	1482	34.54%	29.20%	36.26%	-0.02	+24.1	23
2018-10-21	Helsingor	W 2-0	43.2	1408	1451	34.34%	29.20%	36.46%	-0.03	+16.6	14
2018-10-21	@ Fremad Amager	L 0-2	43.2	1451	1408	36.46%	29.20%	34.34%	+0.03	-16.6	14
2018-10-21	Lyngby	W 1-0	44.2	1464	1423	45.90%	28.43%	25.67%	+0.27	+6.8	22
2018-10-21	@ Naestved	L 0-1	44.2	1423	1464	25.67%	28.43%	45.90%	-0.27	-6.8	15
2018-10-21	Silkeborg	D 1-1	66.1	1604	1516	51.88%	27.21%	20.91%	+0.45	-1.5	26
2018-10-21	@ Viborg	D 1-1	66.1	1516	1604	20.91%	27.21%	51.88%	-0.45	+1.5	23
2018-10-24	Fremad Amager	D 0-0	51.6	1416	1425	39.19%	29.11%	31.71%	+0.09	-0.4	16
2018-10-24	@ Lyngby	D 0-0	51.6	1425	1416	31.71%	29.11%	39.19%	-0.09	+0.4	15
2018-10-25	Viborg	L 1-2	60.2	1535	1603	30.97%	29.06%	39.97%	-0.13	-7.4	23
2018-10-25	@ Fredericia	W 2-1	60.2	1603	1535	39.97%	29.06%	30.97%	+0.13	+7.4	29
2018-10-28	Fremad Amager	L 1-2	59.8	1528	1425	53.57%	26.75%	19.68%	+0.50	-11.2	23
2018-10-28	@ Fredericia	W 2-1	59.8	1425	1528	19.68%	26.75%	53.57%	-0.50	+11.2	18
2018-10-28	Helsingor	D 1-1	56.2	1416	1434	37.80%	29.17%	33.03%	+0.06	-0.2	17
2018-10-28	@ Lyngby	D 1-1	56.2	1434	1416	33.03%	29.17%	37.80%	-0.06	+0.2	15
2018-10-28	Hvidovre	W 3-2	53.3	1517	1403	54.97%	26.33%	18.70%	+0.55	+4.6	26
2018-10-28	@ Silkeborg	L 2-3	53.3	1403	1517	18.70%	26.33%	54.97%	-0.55	-4.6	16
2018-10-28	Naestved	L 0-1	54.3	1521	1470	47.20%	28.21%	24.59%	+0.31	-10.7	23
2018-10-28	@ HB Koge	W 1-0	54.3	1470	1521	24.59%	28.21%	47.20%	-0.31	+10.7	25
2018-10-28	Thisted	D 1-1	56.8	1458	1400	48.06%	28.06%	23.88%	+0.34	-1.2	20
2018-10-28	@ Nykobing	D 1-1	56.8	1400	1458	23.88%	28.06%	48.06%	-0.34	+1.2	21
2018-10-28	Viborg	W 3-1	58.8	1362	1610	14.37%	23.80%	61.83%	-0.79	+21.8	11
2018-10-28	@ FC Roskilde	L 1-3	58.8	1610	1362	61.83%	23.80%	14.37%	+0.79	-21.8	29
2018-11-04	FC Roskilde	L 1-7	50.9	1516	1384	57.02%	25.66%	17.32%	+0.61	-54.0	23
2018-11-04	@ Fredericia	W 7-1	50.9	1384	1516	17.32%	25.66%	57.02%	-0.61	+54.0	14
2018-11-04	Lyngby	L 0-1	57.7	1588	1416	61.35%	24.00%	14.65%	+0.76	-13.3	29
2018-11-04	@ Viborg	W 1-0	57.7	1416	1588	14.65%	24.00%	61.35%	-0.76	+13.3	20
2018-11-04	Naestved	W 1-0	48.8	1436	1481	34.05%	29.19%	36.76%	-0.04	+8.9	21
2018-11-04	@ Fremad Amager	L 0-1	48.8	1481	1436	36.76%	29.19%	34.05%	+0.04	-8.9	25
2018-11-04	Nykobing	L 0-2	41.8	1398	1456	32.20%	29.13%	38.67%	-0.09	-15.2	16
2018-11-04	@ Hvidovre	W 2-0	41.8	1456	1398	38.67%	29.13%	32.20%	+0.09	+15.2	23
2018-11-04	Silkeborg	D 1-1	59.8	1434	1522	28.45%	28.84%	42.71%	-0.20	+0.7	16
2018-11-04	@ Helsingor	D 1-1	59.8	1522	1434	42.71%	28.84%	28.45%	+0.20	-0.7	27
2018-11-04	Thisted	D 1-1	58.9	1510	1401	54.36%	26.52%	19.12%	+0.53	-1.8	24
2018-11-04	@ HB Koge	D 1-1	58.9	1401	1510	19.12%	26.52%	54.36%	-0.53	+1.8	22
2018-11-11	Fredericia	L 1-3	49.7	1429	1462	35.64%	29.20%	35.15%	+0.00	-14.2	20
2018-11-11	@ Lyngby	W 3-1	49.7	1462	1429	35.15%	29.20%	35.64%	+0.00	+14.2	26
2018-11-11	Fremad Amager	L 0-1	45.9	1403	1445	34.41%	29.20%	36.39%	-0.03	-8.5	22
2018-11-11	@ Thisted	W 1-0	45.9	1445	1403	36.39%	29.20%	34.41%	+0.03	+8.5	24
2018-11-11	HB Koge	W 4-1	50.4	1438	1509	30.54%	29.03%	40.42%	-0.14	+22.0	17
2018-11-11	@ FC Roskilde	L 1-4	50.4	1509	1438	40.42%	29.03%	30.54%	+0.14	-22.0	24
2018-11-11	Hvidovre	D 1-1	56.9	1472	1383	52.00%	27.18%	20.82%	+0.45	-1.5	26
2018-11-11	@ Naestved	D 1-1	56.9	1383	1472	20.82%	27.18%	52.00%	-0.45	+1.5	17
2018-11-11	Silkeborg	W 3-1	53.9	1472	1521	33.39%	29.18%	37.44%	-0.06	+14.7	26
2018-11-11	@ Nykobing	L 1-3	53.9	1521	1472	37.44%	29.18%	33.39%	+0.06	-14.7	27
2018-11-12	Viborg	L 1-3	49.7	1435	1575	22.70%	27.76%	49.54%	-0.39	-10.0	16
2018-11-12	@ Helsingor	W 3-1	49.7	1575	1435	49.54%	27.76%	22.70%	+0.39	+10.0	32
2018-11-18	Fredericia	W 2-0	45.2	1385	1477	27.90%	28.77%	43.33%	-0.22	+18.9	20
2018-11-18	@ Hvidovre	L 0-2	45.2	1477	1385	43.33%	28.77%	27.90%	+0.22	-18.9	26
2018-11-18	Fremad Amager	D 0-0	55.7	1507	1454	47.46%	28.17%	24.37%	+0.32	-1.2	28
2018-11-18	@ Silkeborg	D 0-0	55.7	1454	1507	24.37%	28.17%	47.46%	-0.32	+1.2	25
2018-11-18	Helsingor	W 2-1	49.9	1460	1425	45.12%	28.54%	26.34%	+0.25	+6.5	20
2018-11-18	@ FC Roskilde	L 1-2	49.9	1425	1460	26.34%	28.54%	45.12%	-0.25	-6.5	16
2018-11-18	Lyngby	W 3-0	37.8	1487	1415	49.90%	27.68%	22.42%	+0.39	+16.6	27
2018-11-18	@ HB Koge	L 0-3	37.8	1415	1487	22.42%	27.68%	49.90%	-0.39	-16.6	20
2018-11-18	Nykobing	W 1-0	48.9	1471	1486	38.21%	29.15%	32.64%	+0.07	+8.2	29
2018-11-18	@ Naestved	L 0-1	48.9	1486	1471	32.64%	29.15%	38.21%	-0.07	-8.1	26
2018-11-18	Thisted	W 2-0	38.6	1585	1395	63.17%	23.21%	13.62%	+0.83	+7.0	35
2018-11-18	@ Viborg	L 0-2	38.6	1395	1585	13.62%	23.21%	63.17%	-0.83	-7.0	22
2018-11-25	FC Roskilde	W 4-0	42.2	1398	1466	30.86%	29.06%	40.09%	-0.13	+33.8	23
2018-11-25	@ Lyngby	L 0-4	42.2	1466	1398	40.09%	29.06%	30.86%	+0.13	-33.8	20
2018-11-25	HB Koge	W 1-0	50.4	1455	1503	33.55%	29.18%	37.27%	-0.06	+9.0	28
2018-11-25	@ Fremad Amager	L 0-1	50.4	1503	1455	37.27%	29.18%	33.55%	+0.06	-9.0	27
2018-11-25	Hvidovre	W 2-0	39.8	1419	1403	42.48%	28.86%	28.66%	+0.18	+13.9	19
2018-11-25	@ Helsingor	L 0-2	39.8	1403	1419	28.66%	28.86%	42.48%	-0.18	-13.9	20
2018-11-25	Naestved	W 3-0	42.7	1458	1479	37.40%	29.18%	33.42%	+0.04	+22.7	29
2018-11-25	@ Fredericia	L 0-3	42.7	1479	1458	33.42%	29.18%	37.40%	-0.04	-22.7	29
2018-11-25	Silkeborg	L 1-4	43.7	1388	1505	24.98%	28.29%	46.73%	-0.31	-15.3	22
2018-11-25	@ Thisted	W 4-1	43.7	1505	1388	46.73%	28.29%	24.98%	+0.31	+15.3	31
2018-11-25	Viborg	W 3-0	51.2	1478	1592	25.42%	28.38%	46.20%	-0.30	+28.9	29
2018-11-25	@ Nykobing	L 0-3	51.2	1592	1478	46.20%	28.38%	25.42%	+0.30	-28.9	35
2019-03-03	FC Roskilde	W 3-1	46.9	1521	1433	51.84%	27.22%	20.94%	+0.45	+9.3	34
2019-03-03	@ Silkeborg	L 1-3	46.9	1433	1521	20.94%	27.22%	51.84%	-0.45	-9.3	20
2019-03-03	Fredericia	D 3-3	70.3	1494	1480	42.33%	28.87%	28.80%	+0.18	-0.4	28
2019-03-03	@ HB Koge	D 3-3	70.3	1480	1494	28.80%	28.87%	42.33%	-0.18	+0.4	30
2019-03-03	Helsingor	L 1-3	46.2	1372	1433	31.93%	29.12%	38.95%	-0.10	-13.1	22
2019-03-03	@ Thisted	W 3-1	46.2	1433	1372	38.95%	29.12%	31.93%	+0.10	+13.1	22
2019-03-03	Lyngby	L 0-1	45.2	1390	1432	34.39%	29.20%	36.41%	-0.03	-8.5	20
2019-03-03	@ Hvidovre	W 1-0	45.2	1432	1390	36.41%	29.20%	34.39%	+0.03	+8.5	26
2019-03-03	Nykobing	L 0-2	46.3	1464	1507	34.27%	29.20%	36.53%	-0.04	-15.9	28
2019-03-03	@ Fremad Amager	W 2-0	46.3	1507	1464	36.53%	29.20%	34.27%	+0.04	+15.9	32
2019-03-03	Viborg	W 1-0	54.8	1456	1563	26.19%	28.52%	45.29%	-0.27	+10.4	32
2019-03-03	@ Naestved	L 0-1	54.8	1563	1456	45.29%	28.52%	26.19%	+0.27	-10.4	35
2019-03-10	FC Roskilde	D 2-2	62.8	1448	1423	43.77%	28.72%	27.51%	+0.21	-0.6	29
2019-03-10	@ Fremad Amager	D 2-2	62.8	1423	1448	27.51%	28.72%	43.77%	-0.21	+0.6	21
2019-03-10	HB Koge	D 1-1	62.1	1523	1494	44.35%	28.65%	27.00%	+0.23	-0.8	33
2019-03-10	@ Nykobing	D 1-1	62.1	1494	1523	27.00%	28.65%	44.35%	-0.23	+0.8	29
2019-03-10	Helsingor	W 1-0	45.7	1481	1446	45.15%	28.54%	26.31%	+0.25	+6.9	33
2019-03-10	@ Fredericia	L 0-1	45.7	1446	1481	26.31%	28.54%	45.15%	-0.25	-6.9	22
2019-03-10	Hvidovre	L 0-2	51.5	1553	1381	61.23%	24.05%	14.72%	+0.76	-25.0	35
2019-03-10	@ Viborg	W 2-0	51.5	1381	1553	14.72%	24.05%	61.23%	-0.76	+25.0	23
2019-03-10	Silkeborg	D 0-0	56.8	1467	1530	31.53%	29.10%	39.37%	-0.11	+0.4	33
2019-03-10	@ Naestved	D 0-0	56.8	1530	1467	39.37%	29.10%	31.53%	+0.11	-0.4	35
2019-03-10	Thisted	W 3-1	42.5	1440	1359	51.01%	27.42%	21.56%	+0.42	+9.6	29
2019-03-10	@ Lyngby	L 1-3	42.5	1359	1440	21.56%	27.42%	51.01%	-0.42	-9.5	22
2019-03-17	FC Roskilde	L 0-2	42.8	1406	1424	37.89%	29.16%	32.95%	+0.06	-17.1	23
2019-03-17	@ Hvidovre	W 2-0	42.8	1424	1406	32.95%	29.16%	37.89%	-0.06	+17.1	24
2019-03-17	Fredericia	W 2-1	54.3	1529	1488	46.04%	28.40%	25.55%	+0.28	+6.4	38
2019-03-17	@ Silkeborg	L 1-2	54.3	1488	1529	25.55%	28.40%	46.04%	-0.28	-6.4	33
2019-03-17	HB Koge	L 0-2	44.4	1439	1495	32.49%	29.15%	38.36%	-0.08	-15.3	22
2019-03-17	@ Helsingor	W 2-0	44.4	1495	1439	38.36%	29.15%	32.49%	+0.08	+15.3	32
2019-03-17	Lyngby	D 1-1	60.7	1522	1450	49.92%	27.67%	22.40%	+0.39	-1.3	34
2019-03-17	@ Nykobing	D 1-1	60.7	1450	1522	22.40%	27.67%	49.92%	-0.39	+1.3	30
2019-03-17	Naestved	L 2-3	52.7	1350	1467	25.02%	28.30%	46.68%	-0.31	-5.9	22
2019-03-17	@ Thisted	W 3-2	52.7	1467	1350	46.68%	28.30%	25.02%	+0.31	+5.9	36
2019-03-17	Viborg	L 0-1	48.5	1447	1528	29.35%	28.93%	41.72%	-0.17	-7.5	29
2019-03-17	@ Fremad Amager	W 1-0	48.5	1528	1447	41.72%	28.93%	29.35%	+0.17	+7.5	38
2019-03-20	Silkeborg	W 2-0	49.2	1451	1536	28.80%	28.87%	42.33%	-0.19	+18.6	33
2019-03-20	@ Lyngby	L 0-2	49.2	1536	1451	42.33%	28.87%	28.80%	+0.19	-18.6	38
2019-03-24	Helsingor	D 1-1	60.6	1535	1423	54.65%	26.43%	18.92%	+0.54	-1.8	39
2019-03-24	@ Viborg	D 1-1	60.6	1423	1535	18.92%	26.43%	54.65%	-0.54	+1.8	23
2019-03-24	Hvidovre	L 1-2	58.4	1510	1389	55.74%	26.09%	18.17%	+0.57	-11.6	32
2019-03-24	@ HB Koge	W 2-1	58.4	1389	1510	18.17%	26.09%	55.74%	-0.57	+11.6	26
2019-03-24	Nykobing	W 2-1	57.1	1481	1521	34.78%	29.20%	36.01%	-0.02	+8.2	36
2019-03-24	@ Fredericia	L 1-2	57.1	1521	1481	36.01%	29.20%	34.78%	+0.02	-8.2	34
2019-03-24	Thisted	W 2-1	44.9	1441	1344	52.95%	26.92%	20.12%	+0.48	+5.2	27
2019-03-24	@ FC Roskilde	L 1-2	44.9	1344	1441	20.12%	26.92%	52.95%	-0.48	-5.2	22
2019-03-31	FC Roskilde	W 2-1	51.7	1425	1446	37.45%	29.18%	33.38%	+0.05	+7.8	26
2019-03-31	@ Helsingor	L 1-2	51.7	1446	1425	33.38%	29.18%	37.45%	-0.05	-7.8	27
2019-03-31	Fredericia	W 1-0	49.4	1440	1490	33.38%	29.18%	37.44%	-0.06	+9.0	32
2019-03-31	@ Fremad Amager	L 0-1	49.4	1490	1440	37.44%	29.18%	33.38%	+0.06	-9.0	36
2019-03-31	HB Koge	W 4-2	55.9	1517	1499	42.97%	28.81%	28.22%	+0.19	+10.7	41
2019-03-31	@ Silkeborg	L 2-4	55.9	1499	1517	28.22%	28.81%	42.97%	-0.19	-10.7	32
2019-03-31	Hvidovre	D 0-0	49.4	1339	1401	31.70%	29.11%	39.19%	-0.11	+0.4	23
2019-03-31	@ Thisted	D 0-0	49.4	1401	1339	39.19%	29.11%	31.70%	+0.11	-0.4	27
2019-03-31	Naestved	L 1-2	59.2	1513	1473	45.76%	28.45%	25.80%	+0.27	-9.9	34
2019-03-31	@ Nykobing	W 2-1	59.2	1473	1513	25.80%	28.45%	45.76%	-0.27	+9.9	39
2019-03-31	Viborg	L 1-4	49.8	1470	1533	31.49%	29.10%	39.41%	-0.11	-18.3	33
2019-03-31	@ Lyngby	W 4-1	49.8	1533	1470	39.41%	29.10%	31.49%	+0.11	+18.3	42
2019-04-07	Helsingor	W 2-1	51.2	1400	1433	35.75%	29.20%	35.05%	+0.00	+8.1	30
2019-04-07	@ Hvidovre	L 1-2	51.2	1433	1400	35.05%	29.20%	35.75%	+0.00	-8.1	26
2019-04-07	Lyngby	L 0-3	45.7	1481	1451	44.35%	28.65%	27.01%	+0.23	-28.0	36
2019-04-07	@ Fredericia	W 3-0	45.7	1451	1481	27.01%	28.65%	44.35%	-0.23	+28.0	36
2019-04-07	Nykobing	D 2-2	69.4	1552	1503	46.96%	28.25%	24.78%	+0.30	-0.8	43
2019-04-07	@ Viborg	D 2-2	69.4	1503	1552	24.78%	28.25%	46.96%	-0.30	+0.8	35
2019-04-07	Silkeborg	L 1-2	53.3	1438	1528	28.19%	28.81%	43.00%	-0.21	-6.9	27
2019-04-07	@ FC Roskilde	W 2-1	53.3	1528	1438	43.00%	28.81%	28.19%	+0.21	+6.9	44
2019-04-07	Thisted	W 1-0	39.0	1449	1339	54.45%	26.49%	19.06%	+0.53	+5.2	35
2019-04-07	@ Fremad Amager	L 0-1	39.0	1339	1449	19.06%	26.49%	54.45%	-0.53	-5.2	23
2019-04-08	HB Koge	D 0-0	55.8	1483	1488	39.69%	29.08%	31.23%	+0.10	-0.4	40
2019-04-08	@ Naestved	D 0-0	55.8	1488	1483	31.23%	29.08%	39.69%	-0.10	+0.4	33
2019-04-11	Naestved	L 1-3	57.5	1535	1482	47.41%	28.18%	24.41%	+0.32	-17.6	44
2019-04-11	@ Silkeborg	W 3-1	57.5	1482	1535	24.41%	28.18%	47.41%	-0.32	+17.6	43
2019-04-14	FC Roskilde	L 0-5	47.8	1504	1431	49.89%	27.68%	22.43%	+0.39	-49.5	35
2019-04-14	@ Nykobing	W 5-0	47.8	1431	1504	22.43%	27.68%	49.89%	-0.39	+49.5	30
2019-04-14	Fredericia	D 0-0	52.6	1425	1453	36.50%	29.20%	34.31%	+0.02	-0.1	27
2019-04-14	@ Helsingor	D 0-0	52.6	1453	1425	34.31%	29.20%	36.50%	-0.02	+0.1	37
2019-04-14	Fremad Amager	D 1-1	59.4	1488	1454	45.03%	28.55%	26.41%	+0.25	-0.9	34
2019-04-14	@ HB Koge	D 1-1	59.4	1454	1488	26.41%	28.55%	45.03%	-0.25	+0.9	36
2019-04-14	Hvidovre	W 1-0	43.1	1479	1408	49.79%	27.70%	22.50%	+0.39	+6.1	39
2019-04-14	@ Lyngby	L 0-1	43.1	1408	1479	22.50%	27.70%	49.79%	-0.39	-6.1	30
2019-04-14	Viborg	L 0-4	34.5	1334	1551	16.33%	25.10%	58.57%	-0.68	-16.0	23
2019-04-14	@ Thisted	W 4-0	34.5	1551	1334	58.57%	25.10%	16.33%	+0.68	+16.1	46
2019-04-21	FC Roskilde	D 2-2	64.8	1455	1481	36.74%	29.19%	34.07%	+0.03	-0.1	37
2019-04-21	@ Fremad Amager	D 2-2	64.8	1481	1455	34.07%	29.19%	36.74%	-0.03	+0.1	31
2019-04-21	HB Koge	W 1-0	49.1	1453	1487	35.47%	29.21%	35.32%	+0.00	+8.6	40
2019-04-21	@ Fredericia	L 0-1	49.1	1487	1453	35.32%	29.21%	35.47%	+0.00	-8.6	34
2019-04-21	Naestved	D 1-1	64.2	1567	1500	49.26%	27.82%	22.93%	+0.37	-1.3	47
2019-04-21	@ Viborg	D 1-1	64.2	1500	1567	22.93%	27.82%	49.26%	-0.37	+1.3	44
2019-04-21	Nykobing	W 3-0	40.7	1486	1454	44.68%	28.60%	26.72%	+0.24	+19.2	42
2019-04-21	@ Lyngby	L 0-3	40.7	1454	1486	26.72%	28.60%	44.68%	-0.24	-19.1	35
2019-04-21	Silkeborg	L 0-2	41.5	1402	1517	25.26%	28.35%	46.39%	-0.30	-12.6	30
2019-04-21	@ Hvidovre	W 2-0	41.5	1517	1402	46.39%	28.35%	25.26%	+0.30	+12.6	47
2019-04-21	Thisted	L 1-2	54.2	1425	1318	54.12%	26.59%	19.29%	+0.52	-11.3	27
2019-04-21	@ Helsingor	W 2-1	54.2	1318	1425	19.29%	26.59%	54.12%	-0.52	+11.3	26
2019-04-24	Fremad Amager	D 0-0	55.5	1501	1455	46.63%	28.31%	25.06%	+0.29	-1.2	45
2019-04-24	@ Naestved	D 0-0	55.5	1455	1501	25.06%	28.31%	46.63%	-0.29	+1.1	38
2019-04-27	Viborg	W 1-0	55.1	1479	1566	28.52%	28.84%	42.63%	-0.20	+9.9	37
2019-04-27	@ HB Koge	L 0-1	55.1	1566	1479	42.63%	28.84%	28.52%	+0.20	-9.9	47
2019-04-28	Fredericia	L 1-2	58.2	1500	1461	45.65%	28.47%	25.89%	+0.27	-9.8	45
2019-04-28	@ Naestved	W 2-1	58.2	1461	1500	25.89%	28.47%	45.65%	-0.27	+9.9	43
2019-04-28	Fremad Amager	L 2-4	54.3	1435	1456	37.42%	29.18%	33.40%	+0.05	-13.1	35
2019-04-28	@ Nykobing	W 4-2	54.3	1456	1435	33.40%	29.18%	37.42%	-0.05	+13.1	41
2019-04-28	Helsingor	D 1-1	60.1	1530	1413	55.18%	26.27%	18.55%	+0.55	-1.8	48
2019-04-28	@ Silkeborg	D 1-1	60.1	1413	1530	18.55%	26.27%	55.18%	-0.55	+1.8	28
2019-04-28	Hvidovre	D 1-1	57.4	1481	1390	52.27%	27.11%	20.62%	+0.46	-1.6	32
2019-04-28	@ FC Roskilde	D 1-1	57.4	1390	1481	20.62%	27.11%	52.27%	-0.46	+1.6	31
2019-04-28	Lyngby	W 2-1	56.1	1329	1505	19.45%	26.66%	53.88%	-0.53	+11.3	29
2019-04-28	@ Thisted	L 1-2	56.1	1505	1329	53.88%	26.66%	19.45%	+0.53	-11.3	42
2019-05-03	Silkeborg	L 0-1	50.4	1471	1528	32.38%	29.14%	38.48%	-0.09	-8.1	43
2019-05-03	@ Fredericia	W 1-0	50.4	1528	1471	38.48%	29.14%	32.38%	+0.09	+8.1	51
2019-05-05	FC Roskilde	W 3-1	50.3	1556	1479	50.41%	27.56%	22.02%	+0.41	+9.7	50
2019-05-05	@ Viborg	L 1-3	50.3	1479	1556	22.02%	27.56%	50.41%	-0.41	-9.7	32
2019-05-05	Fremad Amager	L 1-2	52.0	1415	1469	32.79%	29.16%	38.05%	-0.08	-7.7	28
2019-05-05	@ Helsingor	W 2-1	52.0	1469	1415	38.05%	29.16%	32.79%	+0.08	+7.7	44
2019-05-05	HB Koge	D 1-1	60.7	1493	1489	41.05%	28.99%	29.96%	+0.14	-0.5	43
2019-05-05	@ Lyngby	D 1-1	60.7	1489	1493	29.96%	28.99%	41.05%	-0.14	+0.5	38
2019-05-05	Naestved	W 3-1	51.8	1391	1490	27.06%	28.65%	44.29%	-0.24	+16.7	34
2019-05-05	@ Hvidovre	L 1-3	51.8	1490	1391	44.29%	28.65%	27.06%	+0.24	-16.7	45
2019-05-05	Nykobing	L 0-1	42.3	1340	1422	29.18%	28.91%	41.91%	-0.18	-7.5	29
2019-05-05	@ Thisted	W 1-0	42.3	1422	1340	41.91%	28.91%	29.18%	+0.18	+7.5	38
2019-05-08	FC Roskilde	W 4-1	47.2	1474	1470	40.92%	29.00%	30.08%	+0.14	+17.7	48
2019-05-08	@ Naestved	L 1-4	47.2	1470	1474	30.08%	29.00%	40.92%	-0.14	-17.7	32
2019-05-08	Helsingor	D 0-0	53.7	1489	1408	51.07%	27.41%	21.52%	+0.43	-1.6	39
2019-05-08	@ HB Koge	D 0-0	53.7	1408	1489	21.52%	27.41%	51.07%	-0.43	+1.6	29
2019-05-08	Hvidovre	W 2-0	39.9	1429	1408	43.34%	28.77%	27.89%	+0.20	+13.7	41
2019-05-08	@ Nykobing	L 0-2	39.9	1408	1429	27.89%	28.77%	43.34%	-0.20	-13.7	34
2019-05-08	Lyngby	W 4-3	63.0	1477	1493	38.15%	29.15%	32.70%	+0.06	+7.1	47
2019-05-08	@ Fremad Amager	L 3-4	63.0	1493	1477	32.70%	29.15%	38.15%	-0.06	-7.1	43
2019-05-08	Thisted	W 5-0	33.0	1536	1333	64.48%	22.61%	12.91%	+0.88	+15.4	54
2019-05-08	@ Silkeborg	L 0-5	33.0	1333	1536	12.91%	22.61%	64.48%	-0.88	-15.4	29
2019-05-09	Fredericia	W 2-1	52.4	1565	1463	53.57%	26.75%	19.68%	+0.50	+5.1	53
2019-05-09	@ Viborg	L 1-2	52.4	1463	1565	19.68%	26.75%	53.57%	-0.50	-5.1	43
2019-05-12	Fremad Amager	L 1-2	50.3	1394	1484	28.16%	28.80%	43.04%	-0.21	-6.9	34
2019-05-12	@ Hvidovre	W 2-1	50.3	1484	1394	43.04%	28.80%	28.16%	+0.21	+6.9	50
2019-05-12	Lyngby	L 1-2	54.6	1452	1486	35.62%	29.20%	35.17%	+0.00	-8.2	32
2019-05-12	@ FC Roskilde	W 2-1	54.6	1486	1452	35.17%	29.20%	35.62%	+0.00	+8.2	46
2019-05-12	Naestved	D 1-1	57.8	1409	1491	29.12%	28.91%	41.98%	-0.18	+0.6	30
2019-05-12	@ Helsingor	D 1-1	57.8	1491	1409	41.98%	28.91%	29.12%	+0.18	-0.6	49
2019-05-12	Nykobing	L 1-3	54.0	1488	1443	46.41%	28.35%	25.24%	+0.29	-17.3	39
2019-05-12	@ HB Koge	W 3-1	54.0	1443	1488	25.24%	28.35%	46.41%	-0.29	+17.3	44
2019-05-12	Thisted	W 2-1	43.2	1458	1317	57.91%	25.34%	16.74%	+0.64	+4.3	46
2019-05-12	@ Fredericia	L 1-2	43.2	1317	1458	16.74%	25.34%	57.91%	-0.64	-4.3	29
2019-05-14	Viborg	D 2-2	71.4	1551	1571	37.72%	29.17%	33.11%	+0.05	-0.2	55
2019-05-14	@ Silkeborg	D 2-2	71.4	1571	1551	33.11%	29.17%	37.72%	-0.05	+0.2	54
2019-05-19	Fredericia	W 3-2	58.0	1444	1462	37.81%	29.17%	33.02%	+0.06	+7.4	35
2019-05-19	@ FC Roskilde	L 2-3	58.0	1462	1444	33.02%	29.17%	37.81%	-0.06	-7.3	46
2019-05-19	HB Koge	L 2-3	50.5	1313	1470	21.05%	27.26%	51.69%	-0.46	-5.1	29
2019-05-19	@ Thisted	W 3-2	50.5	1470	1313	51.69%	27.26%	21.05%	+0.46	+5.1	42
2019-05-19	Helsingor	D 3-3	67.0	1460	1410	47.15%	28.22%	24.63%	+0.31	-0.7	45
2019-05-19	@ Nykobing	D 3-3	67.0	1410	1460	24.63%	28.22%	47.15%	-0.31	+0.7	31
2019-05-19	Naestved	W 2-0	45.5	1494	1491	40.85%	29.00%	30.15%	+0.14	+14.5	49
2019-05-19	@ Lyngby	L 0-2	45.5	1491	1494	30.15%	29.00%	40.85%	-0.14	-14.5	49
2019-05-19	Silkeborg	L 3-4	65.4	1491	1551	31.90%	29.12%	38.98%	-0.10	-7.0	50
2019-05-19	@ Fremad Amager	W 4-3	65.4	1551	1491	38.98%	29.12%	31.90%	+0.10	+7.0	58
2019-05-19	Viborg	L 0-1	44.0	1387	1571	18.82%	26.39%	54.78%	-0.55	-5.2	34
2019-05-19	@ Hvidovre	W 1-0	44.0	1571	1387	54.78%	26.39%	18.82%	+0.55	+5.2	57
2019-05-25	FC Roskilde	W 3-1	48.3	1475	1451	43.70%	28.73%	27.57%	+0.21	+11.7	45
2019-05-25	@ HB Koge	L 1-3	48.3	1451	1475	27.57%	28.73%	43.70%	-0.21	-11.7	35
2019-05-25	Fremad Amager	W 4-0	42.6	1576	1484	52.32%	27.09%	20.58%	+0.46	+20.1	60
2019-05-25	@ Viborg	L 0-4	42.6	1484	1576	20.58%	27.09%	52.32%	-0.46	-20.1	50
2019-05-25	Hvidovre	D 2-2	62.1	1455	1382	49.99%	27.66%	22.35%	+0.39	-1.0	47
2019-05-25	@ Fredericia	D 2-2	62.1	1382	1455	22.35%	27.66%	49.99%	-0.39	+1.0	35
2019-05-25	Lyngby	L 1-2	51.3	1410	1508	27.20%	28.67%	44.13%	-0.24	-6.7	31
2019-05-25	@ Helsingor	W 2-1	51.3	1508	1410	44.13%	28.67%	27.20%	+0.24	+6.7	52
2019-05-25	Nykobing	W 2-0	43.1	1558	1460	53.14%	26.87%	19.99%	+0.49	+10.3	61
2019-05-25	@ Silkeborg	L 0-2	43.1	1460	1558	19.99%	26.87%	53.14%	-0.49	-10.3	45
2019-05-25	Thisted	D 1-1	56.1	1476	1308	60.90%	24.19%	14.91%	+0.75	-2.4	50
2019-05-25	@ Naestved	D 1-1	56.1	1308	1476	14.91%	24.19%	60.90%	-0.75	+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 %	Proj. Margin	Elo Δ	Record
2019-05-30	Vendsyssel	W 2-1	1515	1532	38.09%	29.16%	32.75%	+0.06	+7.7	1-0
2019-05-30	@ Lyngby	L 1-2	1532	1515	32.75%	29.16%	38.09%	-0.06	-7.7	0-1
2019-05-30	Viborg	W 1-0	1550	1596	33.87%	29.19%	36.94%	-0.05	+8.9	1-0
2019-05-30	@ Hobro	L 0-1	1596	1550	36.94%	29.19%	33.87%	+0.05	-8.9	0-1
2019-06-02	Hobro	L 0-2	1587	1559	44.25%	28.66%	27.09%	+0.23	-19.2	0-2
2019-06-02	@ Viborg	W 2-0	1559	1587	27.09%	28.66%	44.25%	-0.23	+19.2	2-0
2019-06-02	Lyngby	D 2-2	1524	1523	40.54%	29.03%	30.44%	+0.13	-0.3	0-1-1
2019-06-02	@ Vendsyssel	D 2-2	1523	1524	30.44%	29.03%	40.54%	-0.13	+0.4	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
#	Date	Underdog Win %	Team	Elo	Score	Team	Elo	Score
1	2018-10-28	14.37%	@ FC Roskilde	1362	3	Viborg	1610	1
2	2018-11-04	14.65%	Lyngby	1416	1	@ Viborg	1588	0
3	2019-03-10	14.72%	Hvidovre	1381	2	@ Viborg	1553	0
4	2018-11-04	17.32%	FC Roskilde	1384	7	@ Fredericia	1516	1
5	2019-03-24	18.17%	Hvidovre	1389	2	@ HB Koge	1510	1
6	2019-04-21	19.29%	Thisted	1318	2	@ Helsingor	1425	1
7	2018-10-07	19.44%	Lyngby	1412	2	@ Silkeborg	1517	1
8	2019-04-28	19.45%	@ Thisted	1329	2	Lyngby	1505	1
9	2018-10-28	19.68%	Fremad Amager	1425	2	@ Fredericia	1528	1
10	2018-10-18	20.60%	@ Hvidovre	1381	2	HB Koge	1543	0
11	2019-04-14	22.43%	FC Roskilde	1431	5	@ Nykobing	1504	0
12	2019-04-11	24.41%	Naestved	1482	3	@ Silkeborg	1535	1
13	2018-10-28	24.59%	Naestved	1470	1	@ HB Koge	1521	0
14	2018-10-14	24.93%	Silkeborg	1506	2	@ HB Koge	1553	1
15	2019-05-12	25.24%	Nykobing	1443	3	@ HB Koge	1488	1
16	2018-11-25	25.42%	@ Nykobing	1478	3	Viborg	1592	0
17	2018-08-26	25.44%	Fremad Amager	1420	1	@ Nykobing	1463	0
18	2018-08-22	25.47%	Thisted	1430	2	@ Fredericia	1472	1
19	2019-03-31	25.80%	Naestved	1473	2	@ Nykobing	1513	1
20	2019-04-28	25.89%	Fredericia	1461	2	@ Naestved	1500	1
21	2018-08-22	26.15%	@ Naestved	1452	1	HB Koge	1559	0
22	2019-03-03	26.19%	@ Naestved	1456	1	Viborg	1563	0
23	2019-04-07	27.01%	Lyngby	1451	3	@ Fredericia	1481	0
24	2019-05-05	27.06%	@ Hvidovre	1391	3	Naestved	1490	1
25	2018-09-09	27.22%	Nykobing	1452	2	@ Fredericia	1480	1

Biggest Elo Changes

The 25 games that resulted in the largest shift in Elo rating.

#	Date	Elo Δ	Winning Team				Losing Team				Tie %
#	Date	Elo Δ	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2018-11-04	54.05	FC Roskilde	7	1384	17.32%	@ Fredericia	1	1516	57.02%	25.66%
2	2019-04-14	49.48	FC Roskilde	5	1431	22.43%	@ Nykobing	0	1504	49.89%	27.68%
3	2018-08-19	34.27	@ Thisted	4	1395	30.20%	Lyngby	0	1469	40.79%	29.01%
4	2018-11-25	33.83	@ Lyngby	4	1398	30.86%	FC Roskilde	0	1466	40.09%	29.06%
5	2018-09-01	31.14	Viborg	5	1547	44.32%	@ Lyngby	0	1448	27.03%	28.65%
6	2018-11-25	28.89	@ Nykobing	3	1478	25.42%	Viborg	0	1592	46.20%	28.38%
7	2018-10-14	28.26	@ Hvidovre	5	1353	30.72%	Thisted	1	1422	40.24%	29.05%
8	2019-04-07	27.98	Lyngby	3	1451	27.01%	@ Fredericia	0	1481	44.35%	28.65%
9	2018-08-05	25.21	Fredericia	3	1438	32.20%	@ FC Roskilde	0	1426	38.67%	29.13%
10	2019-03-10	24.97	Hvidovre	2	1381	14.72%	@ Viborg	0	1553	61.23%	24.05%
11	2018-10-21	24.06	Fredericia	3	1511	34.54%	@ Nykobing	0	1482	36.26%	29.20%
12	2018-08-12	23.48	HB Koge	3	1530	35.75%	@ Silkeborg	0	1492	35.04%	29.20%
13	2018-10-07	23.15	Fredericia	3	1488	36.46%	@ Thisted	0	1445	34.35%	29.20%
14	2018-11-25	22.70	@ Fredericia	3	1458	37.40%	Naestved	0	1479	33.42%	29.18%
15	2018-09-23	22.56	@ FC Roskilde	3	1362	37.69%	Hvidovre	0	1381	33.14%	29.17%
16	2018-10-18	21.99	@ Hvidovre	2	1381	20.60%	HB Koge	0	1543	52.30%	27.10%
17	2018-11-11	21.97	@ FC Roskilde	4	1438	30.54%	HB Koge	1	1509	40.42%	29.03%
18	2018-10-28	21.79	@ FC Roskilde	3	1362	14.37%	Viborg	1	1610	61.83%	23.80%
19	2018-08-22	20.76	@ Lyngby	4	1434	33.39%	Nykobing	1	1484	37.44%	29.18%
20	2018-09-16	20.17	@ Silkeborg	3	1476	42.62%	Helsingor	0	1460	28.54%	28.85%
21	2018-09-09	20.14	Lyngby	4	1417	34.91%	@ FC Roskilde	1	1385	35.88%	29.20%
22	2019-05-25	20.06	@ Viborg	4	1576	52.32%	Fremad Amager	0	1484	20.58%	27.09%
23	2019-04-21	19.16	@ Lyngby	3	1486	44.68%	Nykobing	0	1454	26.72%	28.60%
24	2018-11-18	18.91	@ Hvidovre	2	1385	27.90%	Fredericia	0	1477	43.33%	28.77%
25	2019-03-20	18.58	@ Lyngby	2	1451	28.80%	Silkeborg	0	1536	42.33%	28.87%

Most & Least Exciting Games

The season’s games ranked by excitement rating (0–100) — a blend of closeness, upset, team quality, and scoring. An asterisk (*) after the date indicates a playoff game.

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2018-09-23	72.8	@ Thisted	3	1444	22.49%	Viborg	3	1586	49.81%	27.70%
2	2019-05-14	71.4	@ Silkeborg	2	1551	37.72%	Viborg	2	1571	33.11%	29.17%
3	2019-03-03	70.3	@ HB Koge	3	1494	42.33%	Fredericia	3	1480	28.80%	28.87%
4	2019-04-07	69.4	@ Viborg	2	1552	46.96%	Nykobing	2	1503	24.78%	28.25%
5	2018-09-23	68.4	@ HB Koge	2	1567	56.44%	Helsingor	2	1440	17.70%	25.86%
6	2018-08-26	68.1	@ Viborg	2	1549	51.65%	Fredericia	2	1462	21.08%	27.27%
7	2019-05-19	67.0	@ Nykobing	3	1460	47.15%	Helsingor	3	1410	24.63%	28.22%
8	2018-09-30	66.8	@ Lyngby	2	1411	21.23%	HB Koge	2	1566	51.46%	27.31%
9	2018-10-21	66.1	@ Viborg	1	1604	51.88%	Silkeborg	1	1516	20.91%	27.21%
10	2019-05-19	65.4	Silkeborg	4	1551	38.98%	@ Fremad Amager	3	1491	31.90%	29.12%
11	2019-04-21	64.8	@ Fremad Amager	2	1455	36.74%	FC Roskilde	2	1481	34.07%	29.19%
12	2019-04-21	64.2	@ Viborg	1	1567	49.26%	Naestved	1	1500	22.93%	27.82%
13	2018-08-12	63.5	@ Fremad Amager	2	1431	35.10%	Lyngby	2	1469	35.70%	29.20%
14	2019-05-08	63.0	@ Fremad Amager	4	1477	38.15%	Lyngby	3	1493	32.70%	29.15%
15	2019-03-10	62.8	@ Fremad Amager	2	1448	43.77%	FC Roskilde	2	1423	27.51%	28.72%
16	2018-08-12	62.1	@ Viborg	1	1532	47.26%	Helsingor	1	1481	24.54%	28.20%
17	2018-10-14	62.1	Silkeborg	2	1506	24.93%	@ HB Koge	1	1553	46.78%	28.28%
18	2019-03-10	62.1	@ Nykobing	1	1523	44.35%	HB Koge	1	1494	27.00%	28.65%
19	2019-05-25	62.1	@ Fredericia	2	1455	49.99%	Hvidovre	2	1382	22.35%	27.66%
20	2018-10-07	62.0	@ FC Roskilde	2	1367	26.20%	Nykobing	2	1474	45.28%	28.52%
21	2018-08-26	61.6	@ FC Roskilde	2	1396	34.16%	Thisted	2	1440	36.65%	29.19%
22	2018-08-22	61.5	Viborg	3	1542	39.65%	@ Silkeborg	2	1476	31.27%	29.08%
23	2018-08-05	61.4	@ Hvidovre	2	1396	35.39%	Fremad Amager	2	1431	35.40%	29.21%
24	2019-03-17	60.7	@ Nykobing	1	1522	49.92%	Lyngby	1	1450	22.40%	27.67%
25	2019-05-05	60.7	@ Lyngby	1	1493	41.05%	HB Koge	1	1489	29.96%	28.99%

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2019-05-08	33.0	@ Silkeborg	5	1536	64.48%	Thisted	0	1333	12.91%	22.61%
2	2019-04-14	34.5	Viborg	4	1551	58.57%	@ Thisted	0	1334	16.33%	25.10%
3	2018-09-30	36.2	@ Helsingor	3	1441	47.98%	FC Roskilde	0	1385	23.95%	28.07%
4	2018-09-23	37.5	@ FC Roskilde	3	1362	37.69%	Hvidovre	0	1381	33.14%	29.17%
5	2018-11-18	37.8	@ HB Koge	3	1487	49.90%	Lyngby	0	1415	22.42%	27.68%
6	2018-09-16	38.5	@ Nykobing	2	1462	49.54%	Hvidovre	0	1393	22.70%	27.76%
7	2018-11-18	38.6	@ Viborg	2	1585	63.17%	Thisted	0	1395	13.62%	23.21%
8	2018-09-19	38.9	@ HB Koge	4	1549	55.12%	Fremad Amager	0	1433	18.59%	26.29%
9	2019-04-07	39.0	@ Fremad Amager	1	1449	54.45%	Thisted	0	1339	19.06%	26.49%
10	2018-11-25	39.8	@ Helsingor	2	1419	42.48%	Hvidovre	0	1403	28.66%	28.86%
11	2019-05-08	39.9	@ Nykobing	2	1429	43.34%	Hvidovre	0	1408	27.89%	28.77%
12	2018-09-23	40.4	@ Fredericia	2	1485	48.67%	Lyngby	0	1422	23.39%	27.94%
13	2019-04-21	40.7	@ Lyngby	3	1486	44.68%	Nykobing	0	1454	26.72%	28.60%
14	2018-08-19	41.0	@ Viborg	2	1531	53.26%	Fremad Amager	0	1431	19.90%	26.84%
15	2018-09-16	41.2	@ Silkeborg	3	1476	42.62%	Helsingor	0	1460	28.54%	28.85%
16	2019-04-21	41.5	Silkeborg	2	1517	46.39%	@ Hvidovre	0	1402	25.26%	28.35%
17	2018-11-04	41.8	Nykobing	2	1456	38.67%	@ Hvidovre	0	1398	32.20%	29.13%
18	2018-08-05	41.9	Fredericia	3	1438	32.20%	@ FC Roskilde	0	1426	38.67%	29.13%
19	2018-11-25	42.2	@ Lyngby	4	1398	30.86%	FC Roskilde	0	1466	40.09%	29.06%
20	2018-08-05	42.3	Nykobing	2	1477	40.11%	@ Thisted	0	1409	30.84%	29.05%
21	2019-05-05	42.3	Nykobing	1	1422	41.91%	@ Thisted	0	1340	29.18%	28.91%
22	2018-08-19	42.4	@ Thisted	4	1395	30.20%	Lyngby	0	1469	40.79%	29.01%
23	2019-03-10	42.5	@ Lyngby	3	1440	51.01%	Thisted	1	1359	21.56%	27.42%
24	2019-05-25	42.6	@ Viborg	4	1576	52.32%	Fremad Amager	0	1484	20.58%	27.09%
25	2018-11-25	42.7	@ Fredericia	3	1458	37.40%	Naestved	0	1479	33.42%	29.18%