2019-20 1st Division Season

198 games

Final

Promoted

Vejle BK

68 pts

Relegated

Naestved

26 pts

FC Roskilde · 31 pts

Nyboking · 33 pts

Biggest Overachiever

Skive

13.80 points above expected

48 points · 34.20 expected points

Biggest Disappointment

Naestved

15.05 points below expected

26 points · 41.05 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	Vejle BK Promoted	33	20	8	5	68	63	31	+32	59.42	+8.58
2	Viborg	33	17	8	8	59	66	44	+22	59.39	-0.39
3	Fredericia	33	15	7	11	52	61	52	+9	48.83	+3.17
4	Fremad Amager	33	13	10	10	49	45	45	0	44.40	+4.60
5	Skive	33	13	9	11	48	46	46	0	34.20	+13.80
6	Kolding IF	33	13	8	12	47	50	49	+1	49.44	-2.44
7	Vendsyssel	33	12	8	13	44	35	40	-5	47.68	-3.68
8	Hvidovre	33	10	11	12	41	46	46	0	39.99	+1.01
9	HB Koge	33	9	13	11	40	43	47	-4	45.17	-5.17
10	Nykobing	33	7	12	14	33	47	64	-17	40.64	-7.64
11	FC Roskilde Relegated	33	8	7	18	31	44	61	-17	38.28	-7.28
12	Naestved Relegated	33	5	11	17	26	29	50	-21	41.05	-15.05

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	Skive	48	34.20	+13.80
2	Vejle BK	68	59.42	+8.58
3	Fremad Amager	49	44.40	+4.60
4	Fredericia	52	48.83	+3.17
5	Hvidovre	41	39.99	+1.01

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Naestved	26	41.05	-15.05
2	Nykobing	33	40.64	-7.64
3	FC Roskilde	31	38.28	-7.28
4	HB Koge	40	45.17	-5.17
5	Vendsyssel	44	47.68	-3.68

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	Skive	3	Jul 16 – Jul 25	1 in 47
2	Fredericia	3	Aug 4 – Aug 14	1 in 29
3	Kolding IF	4	Jul 28 – Aug 16	1 in 27
4	Vejle BK	5	Aug 25 – Sep 29	1 in 26
5	Fremad Amager	3	Jun 28 – Jul 4	1 in 16

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Vendsyssel	5	Aug 4 – Aug 24	1 in 385
2	Fredericia	4	Jun 23 – Jul 5	1 in 95
3	FC Roskilde	4	Aug 21 – Sep 8	1 in 41
4	Naestved	4	Jul 3 – Jul 19	1 in 36
5	Nykobing	5	Jul 1 – Jul 19	1 in 28

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Vejle BK	18	Aug 21 – Jun 5	1 in 229
2	Fredericia	8	Aug 4 – Sep 13	1 in 58
3	Fremad Amager	7	Jun 28 – Jul 25	1 in 51
4	Nykobing	6	Nov 3 – May 31	1 in 37
5	Skive	5	Jul 5 – Jul 25	1 in 25

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Naestved	11	Jun 10 – Jul 25	1 in 59
2	Nykobing	10	Sep 8 – Nov 7	1 in 53
3	HB Koge	6	Aug 30 – Oct 6	1 in 28
4	Vendsyssel	5	Aug 4 – Aug 24	1 in 22
5	FC Roskilde	8	Jun 11 – Jul 12	1 in 18

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
Vejle BK	1596	68	-3	10	9.8	+0.2
Viborg	1554	59	-6	8	8.7	-0.7
Fredericia	1482	52	-3	7	8.8	-1.8
Fremad Amager	1479	49	+34	11	5.5	+5.5
Skive	1413	48	+37	13	5.6	+7.4
Kolding IF	1467	47	-2	7	6.7	+0.3
Vendsyssel	1459	44	-23	3	7.0	-4.0
Hvidovre	1439	41	+10	8	7.5	+0.5
HB Koge	1450	40	-8	5	7.7	-2.7
Nykobing	1373	33	-20	1	4.6	-3.6
FC Roskilde	1397	31	+16	8	5.4	+2.6
Naestved	1359	26	-34	1	6.0	-5.0

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	HVI	KI	NAE	NYK	SKI	VB	VEN	VIB
FC Roskilde	—	1-0-2 3.44	1-0-2 3.50	0-1-2 3.97	0-1-2 3.97	1-1-1 3.08	2-0-1 3.66	1-2-0 4.01	1-2-0 4.82	0-0-3 2.30	1-0-2 3.51	0-0-3 2.67
Fredericia	2-0-1 4.86	—	1-0-2 4.94	1-2-0 4.28	2-0-1 5.24	3-0-0 4.29	2-1-0 5.17	1-2-0 5.10	0-1-2 5.46	1-0-2 2.97	1-0-2 4.42	1-1-1 3.18
Fremad Amager	2-0-1 4.79	2-0-1 3.36	—	1-1-1 3.87	0-1-2 4.46	0-3-0 3.74	3-0-0 4.53	1-1-1 4.52	0-2-1 5.35	1-1-1 3.09	3-0-0 3.36	0-1-2 3.25
HB Koge	2-1-0 4.32	0-2-1 4.02	1-1-1 4.41	—	0-3-0 4.47	2-0-1 3.99	0-2-1 4.93	1-0-2 4.56	0-1-2 4.97	1-1-1 2.90	1-1-1 3.67	1-1-1 2.76
Hvidovre	2-1-0 4.33	1-0-2 3.07	2-1-0 3.83	0-3-0 3.82	—	1-0-2 3.27	2-1-0 3.83	1-2-0 3.70	1-0-2 4.90	0-0-3 2.28	0-2-1 3.30	0-1-2 2.83
Kolding IF	1-1-1 5.23	0-0-3 4.00	0-3-0 4.55	1-0-2 4.29	2-0-1 5.03	—	2-1-0 4.62	1-1-1 4.56	3-0-0 5.47	0-1-2 3.63	0-1-2 4.08	3-0-0 2.91
Naestved	1-0-2 4.63	0-1-2 3.14	0-0-3 3.76	1-2-0 3.37	0-1-2 4.46	0-1-2 3.68	—	1-1-1 3.71	1-0-2 4.81	0-2-1 2.65	1-2-0 3.89	0-1-2 2.72
Nykobing	0-2-1 4.28	0-2-1 3.21	1-1-1 3.77	2-0-1 3.74	0-2-1 4.60	1-1-1 3.73	1-1-1 4.58	—	1-1-1 4.64	1-1-1 2.41	0-1-2 3.73	0-0-3 2.47
Skive	0-2-1 3.48	2-1-0 2.88	1-2-0 2.97	2-1-0 3.34	2-0-1 3.40	0-0-3 2.86	2-0-1 3.49	1-1-1 3.65	—	1-1-1 2.04	2-0-1 2.95	0-1-2 2.40
Vejle BK	3-0-0 6.08	2-0-1 5.35	1-1-1 5.23	1-1-1 5.43	3-0-0 6.10	2-1-0 4.67	1-2-0 5.70	1-1-1 5.97	1-1-1 6.37	—	3-0-0 4.73	2-1-0 4.45
Vendsyssel	2-0-1 4.79	2-0-1 3.87	0-0-3 4.94	1-1-1 4.62	1-2-0 5.00	2-1-0 4.21	0-2-1 4.39	2-1-0 4.58	1-0-2 5.37	0-0-3 3.58	—	1-1-1 2.85
Viborg	3-0-0 5.67	1-1-1 5.13	2-1-0 5.05	1-1-1 5.57	2-1-0 5.50	0-0-3 5.42	2-1-0 5.62	3-0-0 5.88	2-1-0 5.97	0-1-2 3.84	1-1-1 5.48	—

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	0.65	+8.8
Allowed	0.53	-9.9
Differential	0.95	+7.5

Scoreline Distribution

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

View:

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	7.32%	7.07%	2.27%	1.01%	0.51%	24.24%
1	7.32%	10.61%	6.82%	3.54%	1.26%	—	29.55%
2	7.07%	6.82%	11.11%	2.78%	2.02%	—	29.80%
3	2.27%	3.54%	2.78%	0.51%	1.01%	0.25%	10.35%
4	1.01%	1.26%	2.02%	1.01%	—	—	5.30%
5+	0.51%	—	—	0.25%	—	—	0.76%
Total	24.24%	29.55%	29.80%	10.35%	5.30%	0.76%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.45	1.45	+0.00
SD	1.16	1.16	1.61
CV	0.80	0.80	—
Max	5	5	+5
Min	0	0	-5

Games Played: 198

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	18.18%	3.03%	3.03%	—	30.30%
1	6.06%	3.03%	9.09%	—	3.03%	—	21.21%
2	6.06%	3.03%	15.15%	9.09%	3.03%	—	36.36%
3	—	6.06%	—	—	3.03%	—	9.09%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	18.18%	15.15%	42.42%	12.12%	12.12%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.33	1.85	-0.52
SD	1.11	1.23	1.73
CV	0.83	0.66	—
Max	4	4	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	6.06%	6.06%	—	—	—	12.12%
1	6.06%	3.03%	12.12%	3.03%	—	—	24.24%
2	9.09%	6.06%	18.18%	—	6.06%	—	39.39%
3	—	9.09%	9.09%	—	—	—	18.18%
4	—	—	—	3.03%	—	—	3.03%
5+	3.03%	—	—	—	—	—	3.03%
Total	18.18%	24.24%	45.45%	6.06%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.85	1.58	+0.27
SD	1.15	1.06	1.59
CV	0.62	0.67	—
Max	5	4	+5
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	—	3.03%	3.03%	3.03%	3.03%	24.24%
1	18.18%	3.03%	9.09%	6.06%	—	—	36.36%
2	3.03%	6.06%	15.15%	3.03%	—	—	27.27%
3	3.03%	—	—	—	—	—	3.03%
4	3.03%	3.03%	3.03%	—	—	—	9.09%
5+	—	—	—	—	—	—	—
Total	39.39%	12.12%	30.30%	12.12%	3.03%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.36	1.36	+0.00
SD	1.17	1.37	1.90
CV	0.86	1.00	—
Max	4	5	+4
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	6.06%	6.06%	—	—	—	18.18%
1	6.06%	18.18%	9.09%	6.06%	—	—	39.39%
2	6.06%	9.09%	15.15%	3.03%	3.03%	—	36.36%
3	—	3.03%	3.03%	—	—	—	6.06%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	18.18%	36.36%	33.33%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.30	1.42	-0.12
SD	0.85	1.00	1.17
CV	0.65	0.70	—
Max	3	4	+2
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	9.09%	3.03%	3.03%	—	—	21.21%
1	3.03%	21.21%	9.09%	—	3.03%	—	36.36%
2	12.12%	3.03%	6.06%	6.06%	—	—	27.27%
3	3.03%	3.03%	3.03%	—	—	3.03%	12.12%
4	—	—	3.03%	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	24.24%	36.36%	24.24%	9.09%	3.03%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.39	1.39	+0.00
SD	1.06	1.22	1.48
CV	0.76	0.88	—
Max	4	5	+3
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	9.09%	12.12%	3.03%	—	—	27.27%
1	3.03%	6.06%	6.06%	—	—	—	15.15%
2	9.09%	15.15%	15.15%	3.03%	—	—	42.42%
3	—	6.06%	—	—	3.03%	—	9.09%
4	—	—	3.03%	3.03%	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	15.15%	36.36%	36.36%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.52	1.48	+0.03
SD	1.18	0.97	1.40
CV	0.78	0.65	—
Max	4	4	+2
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	12.12%	12.12%	—	3.03%	—	33.33%
1	9.09%	21.21%	6.06%	12.12%	—	—	48.48%
2	—	3.03%	6.06%	6.06%	—	—	15.15%
3	3.03%	—	—	—	—	—	3.03%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	18.18%	36.36%	24.24%	18.18%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.88	1.52	-0.64
SD	0.78	1.09	1.32
CV	0.89	0.72	—
Max	3	4	+3
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	12.12%	3.03%	6.06%	3.03%	3.03%	36.36%
1	—	3.03%	3.03%	6.06%	—	—	12.12%
2	3.03%	3.03%	21.21%	3.03%	—	—	30.30%
3	—	3.03%	6.06%	3.03%	3.03%	—	15.15%
4	—	—	6.06%	—	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	12.12%	21.21%	39.39%	18.18%	6.06%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.94	-0.52
SD	1.30	1.20	1.66
CV	0.91	0.62	—
Max	4	5	+2
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	6.06%	6.06%	—	—	—	21.21%
1	9.09%	9.09%	6.06%	6.06%	—	—	30.30%
2	12.12%	9.09%	6.06%	—	9.09%	—	36.36%
3	—	3.03%	6.06%	3.03%	—	—	12.12%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	30.30%	27.27%	24.24%	9.09%	9.09%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.39	1.39	+0.00
SD	0.97	1.27	1.37
CV	0.69	0.91	—
Max	3	4	+2
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	3.03%	—	—	—	—	12.12%
1	15.15%	12.12%	6.06%	—	3.03%	—	36.36%
2	9.09%	6.06%	3.03%	—	3.03%	—	21.21%
3	9.09%	—	3.03%	—	—	—	12.12%
4	6.06%	6.06%	—	3.03%	—	—	15.15%
5+	—	—	—	3.03%	—	—	3.03%
Total	48.48%	27.27%	12.12%	6.06%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.91	0.94	+0.97
SD	1.38	1.20	1.65
CV	0.72	1.27	—
Max	5	4	+4
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	18.18%	9.09%	9.09%	—	—	42.42%
1	6.06%	15.15%	—	—	3.03%	—	24.24%
2	9.09%	9.09%	3.03%	—	—	—	21.21%
3	3.03%	3.03%	3.03%	—	—	—	9.09%
4	—	—	3.03%	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	24.24%	45.45%	18.18%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.06	1.21	-0.15
SD	1.14	1.02	1.66
CV	1.08	0.84	—
Max	4	4	+3
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	6.06%	—	—	—	12.12%
1	6.06%	12.12%	6.06%	3.03%	3.03%	—	30.30%
2	6.06%	9.09%	9.09%	—	—	—	24.24%
3	6.06%	6.06%	—	—	3.03%	—	15.15%
4	—	6.06%	6.06%	3.03%	—	—	15.15%
5+	3.03%	—	—	—	—	—	3.03%
Total	24.24%	36.36%	27.27%	6.06%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.00	1.33	+0.67
SD	1.37	1.11	1.78
CV	0.68	0.83	—
Max	5	4	+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
Vejle BK	1596	68	59.42	+8.58	84.0%	38	45	54	60	65	71	78
Viborg	1554	59	59.39	-0.39	49.0%	42	46	55	60	64	71	74
Fredericia	1482	52	48.83	+3.17	66.0%	32	37	44	49	54	59	75
Fremad Amager	1479	49	44.40	+4.60	77.0%	26	34	40	44	49	55	62
Kolding IF	1467	47	49.44	-2.44	46.0%	28	37	44	49	54	63	67
Vendsyssel	1459	44	47.68	-3.68	33.0%	29	34	43	48	54	60	67
HB Koge	1450	40	45.17	-5.17	26.0%	30	33	40	46	49	56	69
Hvidovre	1439	41	39.99	+1.01	59.0%	22	27	35	40	44	53	61
Skive	1413	48	34.20	+13.80	99.0%	20	25	31	34	38	42	57
FC Roskilde	1397	31	38.28	-7.28	17.0%	21	26	34	38	42	49	52
Nykobing	1373	33	40.64	-7.64	16.0%	22	28	35	41	45	51	59
Naestved	1359	26	41.05	-15.05	2.0%	22	30	36	41	45	54	59

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

+7.07%

No Edge

39.39%28.28%32.32%

Elo Value

Home Edge: 24.61 Elo pts.

242 Elo

0.004 goals per Elo point

0800

Scoring Tilt

Expected

+0.19 goals

Neutral

-2+0.10+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

2.7

Top-Heavy

123410

Champion Preseason Odds

45%

Vejle BK, 1st of 12

LongshotFavorite

Title Margin

Expected

0.27/gm

Runaway

00.190.5/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 5.91 * Some Luck: 5.91 to 8.87 * Lucky: 8.87 to 11.82 * Wild Swing: 11.82 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 1.64 * Close: 1.64 to 2.46 * Off: 2.46 to 3.29 * Way Off: 3.29 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 1.32 * A Surprise: 1.32 to 2.11 * Several Surprises: 2.11 to 2.9 * Many Surprises: 2.9 and up.

Luck Spread

Expected

7.48 points

Some Luck

07.3918

Average Finish Error

Expected

2.17

02.055

Biggest Overachiever

Expected 95.83%

99.00%

Skive

50100

Biggest Underachiever

Expected 4.17%

2.00%

Naestved

050

Season Outliers

Expected

2 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

2 of 3

A Surprise

01.33

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

0.14

Even

00.130.20.5

Noll-Scully

Elo SD: 69.02

1.60

Moderate Separation

0.751.51.82.153

Interquartile Edge

60%

Even

50%63.5%74.5%100%

Best vs. Worst

Baseline

80%

Even

50%80%100%

Close Games

Expected

64%

Frequent

0%65%100%

Blowouts

Expected

10%

Rare

0%12%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

00.622

Matchup Imbalance

0.27

Very Even

00.340.420.5

Strangeness

Expected

1.19

Wilder Than Modeled

01.002

Repeatability

0.41

Some Carryover

00.380.570.71

Upset Rate

Expected

26%

Very Upset-Prone

0%28%50%

Clear Favorite Upset Rate

Expected

27%

Very Shaky

0%24%50%

Calibration

How these are measured

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

Probability calibration: An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope: Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE): The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.12 * Near Noise Ceiling: 0.12 to 0.18 * Above Noise: 0.18 to 0.24 * Well Above Noise: 0.24 and up.

Probability calibration

0.23

Well Calibrated

0.010.050.10.51

Calibration slope

Ideal

0.80

Overconfident

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.123

Near Noise Ceiling

00.1200.3

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
Vejle BK	45.00%	24.00%	14.00%	6.00%	2.00%	3.00%	4.00%	1.00%	1.00%	—	—	—
Viborg	40.00%	29.00%	16.00%	5.00%	4.00%	2.00%	4.00%	—	—	—	—	—
Fredericia	3.00%	10.00%	15.00%	15.00%	17.00%	15.00%	7.00%	2.00%	8.00%	5.00%	—	3.00%
Fremad Amager	1.00%	2.00%	6.00%	12.00%	13.00%	11.00%	19.00%	13.00%	7.00%	10.00%	5.00%	1.00%
Skive	—	1.00%	—	—	—	2.00%	3.00%	6.00%	11.00%	17.00%	27.00%	33.00%
Kolding IF	6.00%	15.00%	10.00%	14.00%	15.00%	11.00%	7.00%	15.00%	4.00%	—	2.00%	1.00%
Vendsyssel	2.00%	10.00%	17.00%	17.00%	8.00%	14.00%	5.00%	10.00%	4.00%	6.00%	6.00%	1.00%
Hvidovre	1.00%	1.00%	5.00%	6.00%	6.00%	9.00%	9.00%	10.00%	13.00%	15.00%	7.00%	18.00%
HB Koge	1.00%	7.00%	4.00%	11.00%	13.00%	12.00%	17.00%	8.00%	11.00%	9.00%	5.00%	2.00%
Nykobing	—	—	6.00%	5.00%	9.00%	12.00%	5.00%	14.00%	12.00%	10.00%	12.00%	15.00%
FC Roskilde	—	—	1.00%	5.00%	4.00%	5.00%	6.00%	11.00%	17.00%	14.00%	21.00%	16.00%
Naestved	1.00%	1.00%	6.00%	4.00%	9.00%	4.00%	14.00%	10.00%	12.00%	14.00%	15.00%	10.00%

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	Same level	Direct relegation
Vejle BK	45.00%	55.00%	—
Viborg	40.00%	60.00%	—
Kolding IF	6.00%	91.00%	3.00%
Fredericia	3.00%	89.00%	8.00%
Vendsyssel	2.00%	85.00%	13.00%
Fremad Amager	1.00%	83.00%	16.00%
HB Koge	1.00%	83.00%	16.00%
Nykobing	—	63.00%	37.00%
Naestved	1.00%	60.00%	39.00%
Hvidovre	1.00%	59.00%	40.00%
FC Roskilde	—	49.00%	51.00%
Skive	—	23.00%	77.00%

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
2019-07-26	FC Roskilde	W 3-0	36.8	1521	1440	55.65%	22.23%	22.12%	+0.44	+10.8	3
2019-07-26	@ Viborg	L 0-3	36.8	1440	1521	22.12%	22.23%	55.65%	-0.44	-10.8	0
2019-07-27	Vejle BK	D 2-2	67.4	1455	1509	37.70%	24.00%	38.30%	-0.12	+0.0	1
2019-07-27	@ Fremad Amager	D 2-2	67.4	1509	1455	38.30%	24.00%	37.70%	+0.12	-0.0	1
2019-07-28	HB Koge	W 3-1	47.2	1446	1470	41.97%	23.92%	34.11%	+0.00	+9.4	3
2019-07-28	@ Nykobing	L 1-3	47.2	1470	1446	34.11%	23.92%	41.97%	+0.00	-9.4	0
2019-07-28	Hvidovre	W 2-1	46.3	1473	1404	54.21%	22.53%	23.27%	+0.39	+3.9	3
2019-07-28	@ Kolding IF	L 1-2	46.3	1404	1473	23.27%	22.53%	54.21%	-0.39	-3.9	0
2019-07-28	Naestved	W 3-1	47.9	1343	1462	29.19%	23.54%	47.27%	-0.39	+12.1	3
2019-07-28	@ Skive	L 1-3	47.9	1462	1343	47.27%	23.54%	29.19%	+0.39	-12.1	0
2019-07-28	Vendsyssel	L 1-2	53.6	1449	1495	38.87%	24.00%	37.13%	-0.09	-6.0	0
2019-07-28	@ Fredericia	W 2-1	53.6	1495	1449	37.13%	24.00%	38.87%	+0.09	+6.0	3
2019-08-03	Viborg	L 0-1	44.2	1400	1532	27.65%	23.35%	49.00%	-0.44	-4.8	0
2019-08-03	@ Hvidovre	W 1-0	44.2	1532	1400	49.00%	23.35%	27.65%	+0.44	+4.8	6
2019-08-04	Fredericia	L 1-3	50.7	1461	1443	47.65%	23.50%	28.84%	+0.17	-12.2	0
2019-08-04	@ HB Koge	W 3-1	50.7	1443	1461	28.84%	23.50%	47.65%	-0.17	+12.2	3
2019-08-04	Fremad Amager	L 0-1	52.0	1501	1455	51.28%	23.03%	25.69%	+0.29	-7.9	3
2019-08-04	@ Vendsyssel	W 1-0	52.0	1455	1501	25.69%	23.03%	51.28%	-0.29	+7.9	4
2019-08-04	Kolding IF	L 0-2	44.0	1449	1477	41.44%	23.94%	34.62%	-0.01	-12.6	0
2019-08-04	@ Naestved	W 2-0	44.0	1477	1449	34.62%	23.94%	41.44%	+0.01	+12.6	6
2019-08-04	Nykobing	L 2-4	58.2	1509	1455	52.32%	22.87%	24.81%	+0.32	-11.8	1
2019-08-04	@ Vejle BK	W 4-2	58.2	1455	1509	24.81%	22.87%	52.32%	-0.32	+11.8	6
2019-08-04	Skive	D 1-1	56.7	1429	1355	54.77%	22.42%	22.81%	+0.41	-1.1	1
2019-08-04	@ FC Roskilde	D 1-1	56.7	1355	1429	22.81%	22.42%	54.77%	-0.41	+1.1	4
2019-08-10	Vejle BK	L 0-3	45.1	1493	1497	44.66%	23.77%	31.57%	+0.08	-19.4	3
2019-08-10	@ Vendsyssel	W 3-0	45.1	1497	1493	31.57%	23.77%	44.66%	-0.08	+19.4	4
2019-08-11	FC Roskilde	W 4-3	56.0	1490	1428	53.32%	22.69%	23.99%	+0.36	+3.7	9
2019-08-11	@ Kolding IF	L 3-4	56.0	1428	1490	23.99%	22.69%	53.32%	-0.36	-3.7	1
2019-08-11	HB Koge	D 0-0	58.6	1537	1448	56.49%	22.05%	21.46%	+0.47	-1.4	7
2019-08-11	@ Viborg	D 0-0	58.6	1448	1537	21.46%	22.05%	56.49%	-0.47	+1.4	1
2019-08-11	Hvidovre	D 2-2	64.5	1467	1395	54.53%	22.46%	23.01%	+0.40	-0.8	7
2019-08-11	@ Nykobing	D 2-2	64.5	1395	1467	23.01%	22.46%	54.53%	-0.40	+0.8	1
2019-08-11	Naestved	W 3-1	44.7	1455	1437	47.75%	23.49%	28.76%	+0.18	+8.2	6
2019-08-11	@ Fredericia	L 1-3	44.7	1437	1455	28.76%	23.49%	47.75%	-0.18	-8.2	0
2019-08-11	Skive	D 0-0	53.4	1463	1356	58.63%	21.54%	19.83%	+0.54	-1.5	5
2019-08-11	@ Fremad Amager	D 0-0	53.4	1356	1463	19.83%	21.54%	58.63%	-0.54	+1.5	5
2019-08-14	Fredericia	L 0-1	53.2	1517	1463	52.28%	22.87%	24.85%	+0.32	-8.1	4
2019-08-14	@ Vejle BK	W 1-0	53.2	1463	1517	24.85%	22.87%	52.28%	-0.32	+8.1	9
2019-08-16	Kolding IF	L 1-2	53.7	1450	1493	39.17%	24.00%	36.83%	-0.08	-6.0	1
2019-08-16	@ HB Koge	W 2-1	53.7	1493	1450	36.83%	24.00%	39.17%	+0.08	+6.0	12
2019-08-16	Nykobing	L 2-3	60.0	1462	1466	44.64%	23.77%	31.59%	+0.08	-6.3	5
2019-08-16	@ Fremad Amager	W 3-2	60.0	1466	1462	31.59%	23.77%	44.64%	-0.08	+6.3	10
2019-08-16	Viborg	L 0-2	36.8	1358	1535	22.83%	22.42%	54.76%	-0.63	-7.7	5
2019-08-16	@ Skive	W 2-0	36.8	1535	1358	54.76%	22.42%	22.83%	+0.63	+7.7	10
2019-08-18	Hvidovre	D 1-1	57.4	1429	1396	49.61%	23.27%	27.12%	+0.24	-0.8	1
2019-08-18	@ Naestved	D 1-1	57.4	1396	1429	27.12%	23.27%	49.61%	-0.24	+0.8	2
2019-08-18	Vendsyssel	W 2-0	41.9	1424	1473	38.37%	24.00%	37.63%	-0.10	+11.7	4
2019-08-18	@ FC Roskilde	L 0-2	41.9	1473	1424	37.63%	24.00%	38.37%	+0.10	-11.7	3
2019-08-21	Fredericia	D 2-2	69.7	1543	1471	54.50%	22.47%	23.03%	+0.40	-0.8	11
2019-08-21	@ Viborg	D 2-2	69.7	1471	1543	23.03%	22.47%	54.50%	-0.40	+0.8	10
2019-08-21	Fremad Amager	D 0-0	53.5	1397	1455	37.08%	24.00%	38.92%	-0.14	+0.1	3
2019-08-21	@ Hvidovre	D 0-0	53.5	1455	1397	38.92%	24.00%	37.08%	+0.14	-0.1	6
2019-08-21	HB Koge	L 2-3	58.3	1436	1444	44.20%	23.80%	32.00%	+0.07	-6.3	4
2019-08-21	@ FC Roskilde	W 3-2	58.3	1444	1436	32.00%	23.80%	44.20%	-0.07	+6.3	4
2019-08-21	Naestved	L 0-1	50.1	1473	1428	51.18%	23.05%	25.78%	+0.29	-7.9	10
2019-08-21	@ Nykobing	W 1-0	50.1	1428	1473	25.78%	23.05%	51.18%	-0.29	+7.9	4
2019-08-21	Skive	L 0-1	49.5	1462	1350	59.16%	21.40%	19.44%	+0.56	-9.0	3
2019-08-21	@ Vendsyssel	W 1-0	49.5	1350	1462	19.44%	21.40%	59.16%	-0.56	+9.0	8
2019-08-21	Vejle BK	D 1-1	63.3	1499	1509	44.02%	23.81%	32.16%	+0.06	-0.4	13
2019-08-21	@ Kolding IF	D 1-1	63.3	1509	1499	32.16%	23.81%	44.02%	-0.06	+0.4	5
2019-08-24	Vendsyssel	W 3-0	38.1	1436	1453	42.95%	23.88%	33.17%	+0.03	+15.4	7
2019-08-24	@ Naestved	L 0-3	38.1	1453	1436	33.17%	23.88%	42.95%	-0.03	-15.4	3
2019-08-25	FC Roskilde	W 3-2	54.1	1397	1430	40.77%	23.96%	35.27%	-0.03	+5.3	6
2019-08-25	@ Hvidovre	L 2-3	54.1	1430	1397	35.27%	23.96%	40.77%	+0.03	-5.3	4
2019-08-25	Fremad Amager	W 3-1	46.1	1450	1455	44.57%	23.78%	31.65%	+0.08	+8.8	7
2019-08-25	@ HB Koge	L 1-3	46.1	1455	1450	31.65%	23.78%	44.57%	-0.08	-8.8	6
2019-08-25	Kolding IF	W 4-3	61.4	1472	1499	41.56%	23.94%	34.50%	-0.01	+5.0	13
2019-08-25	@ Fredericia	L 3-4	61.4	1499	1472	34.50%	23.94%	41.56%	+0.01	-5.0	13
2019-08-25	Nykobing	W 3-0	38.7	1542	1465	55.21%	22.33%	22.47%	+0.42	+11.0	14
2019-08-25	@ Viborg	L 0-3	38.7	1465	1542	22.47%	22.33%	55.21%	-0.42	-11.0	10
2019-08-25	Skive	W 2-1	43.3	1509	1359	63.30%	20.18%	16.52%	+0.72	+2.8	8
2019-08-25	@ Vejle BK	L 1-2	43.3	1359	1509	16.52%	20.18%	63.30%	-0.72	-2.8	8
2019-08-29	Viborg	W 4-1	50.8	1512	1553	39.52%	23.99%	36.49%	-0.07	+14.0	11
2019-08-29	@ Vejle BK	L 1-4	50.8	1553	1512	36.49%	23.99%	39.52%	+0.07	-14.0	14
2019-08-30	HB Koge	D 1-1	57.0	1356	1459	31.15%	23.74%	45.12%	-0.32	+0.5	9
2019-08-30	@ Skive	D 1-1	57.0	1459	1356	45.12%	23.74%	31.15%	+0.32	-0.5	8
2019-08-30	Kolding IF	W 3-2	58.3	1454	1494	39.65%	23.99%	36.36%	-0.06	+5.4	13
2019-08-30	@ Nykobing	L 2-3	58.3	1494	1454	36.36%	23.99%	39.65%	+0.06	-5.4	13
2019-08-30	Naestved	W 1-0	44.3	1446	1451	44.62%	23.77%	31.60%	+0.08	+5.4	9
2019-08-30	@ Fremad Amager	L 0-1	44.3	1451	1446	31.60%	23.77%	44.62%	-0.08	-5.4	7
2019-09-01	Fredericia	L 1-2	51.8	1424	1477	37.84%	24.00%	38.16%	-0.12	-5.9	4
2019-09-01	@ FC Roskilde	W 2-1	51.8	1477	1424	38.16%	24.00%	37.84%	+0.12	+5.9	16
2019-09-01	Hvidovre	W 1-0	41.0	1437	1402	49.94%	23.22%	26.83%	+0.25	+4.7	6
2019-09-01	@ Vendsyssel	L 0-1	41.0	1402	1437	26.83%	23.22%	49.94%	-0.25	-4.7	6
2019-09-06	Skive	W 4-2	44.5	1398	1357	50.68%	23.12%	26.20%	+0.27	+6.7	9
2019-09-06	@ Hvidovre	L 2-4	44.5	1357	1398	26.20%	23.12%	50.68%	-0.27	-6.7	9
2019-09-08	FC Roskilde	W 1-0	42.0	1446	1418	48.95%	23.35%	27.70%	+0.22	+4.8	10
2019-09-08	@ Naestved	L 0-1	42.0	1418	1446	27.70%	23.35%	48.95%	-0.22	-4.8	4
2019-09-08	Fremad Amager	D 0-0	56.6	1489	1452	50.17%	23.19%	26.64%	+0.25	-0.9	14
2019-09-08	@ Kolding IF	D 0-0	56.6	1452	1489	26.64%	23.19%	50.17%	-0.25	+0.9	10
2019-09-08	Nykobing	D 2-2	66.8	1483	1459	48.50%	23.41%	28.09%	+0.20	-0.5	17
2019-09-08	@ Fredericia	D 2-2	66.8	1459	1483	28.09%	23.41%	48.50%	-0.20	+0.5	14
2019-09-13	Fredericia	D 2-2	63.4	1350	1483	27.54%	23.33%	49.13%	-0.45	+0.5	10
2019-09-13	@ Skive	D 2-2	63.4	1483	1350	49.13%	23.33%	27.54%	+0.45	-0.5	18
2019-09-14	Viborg	L 1-2	53.6	1453	1539	33.22%	23.88%	42.90%	-0.26	-5.3	10
2019-09-14	@ Fremad Amager	W 2-1	53.6	1539	1453	42.90%	23.88%	33.22%	+0.26	+5.3	17
2019-09-15	Hvidovre	W 3-0	34.3	1526	1404	60.26%	21.10%	18.64%	+0.60	+9.2	14
2019-09-15	@ Vejle BK	L 0-3	34.3	1404	1526	18.64%	21.10%	60.26%	-0.60	-9.2	9
2019-09-15	Kolding IF	W 2-0	42.8	1442	1488	38.89%	24.00%	37.11%	-0.09	+11.5	9
2019-09-15	@ Vendsyssel	L 0-2	42.8	1488	1442	37.11%	24.00%	38.89%	+0.09	-11.5	14
2019-09-15	Naestved	D 1-1	59.8	1458	1451	46.33%	23.63%	30.04%	+0.13	-0.5	9
2019-09-15	@ HB Koge	D 1-1	59.8	1451	1458	30.04%	23.63%	46.33%	-0.13	+0.5	11
2019-09-15	Nykobing	W 3-1	46.8	1414	1460	38.83%	24.00%	37.17%	-0.09	+10.0	7
2019-09-15	@ FC Roskilde	L 1-3	46.8	1460	1414	37.17%	24.00%	38.83%	+0.09	-10.0	14
2019-09-19	FC Roskilde	W 2-0	37.8	1535	1424	59.15%	21.40%	19.45%	+0.56	+6.6	17
2019-09-19	@ Vejle BK	L 0-2	37.8	1424	1535	19.45%	21.40%	59.15%	-0.56	-6.6	7
2019-09-19	Vendsyssel	D 1-1	63.5	1544	1454	56.79%	21.98%	21.23%	+0.48	-1.3	18
2019-09-19	@ Viborg	D 1-1	63.5	1454	1544	21.23%	21.98%	56.79%	-0.48	+1.2	10
2019-09-20	HB Koge	D 2-2	63.7	1395	1458	36.46%	23.99%	39.55%	-0.16	+0.1	10
2019-09-20	@ Hvidovre	D 2-2	63.7	1458	1395	39.55%	23.99%	36.46%	+0.16	-0.1	10
2019-09-22	Fremad Amager	L 1-2	56.2	1482	1447	49.89%	23.23%	26.88%	+0.24	-7.3	18
2019-09-22	@ Fredericia	W 2-1	56.2	1447	1482	26.88%	23.23%	49.89%	-0.24	+7.3	13
2019-09-22	Skive	W 4-2	43.1	1476	1351	60.71%	20.97%	18.32%	+0.62	+4.8	17
2019-09-22	@ Kolding IF	L 2-4	43.1	1351	1476	18.32%	20.97%	60.71%	-0.62	-4.8	10
2019-09-22	Vendsyssel	L 0-3	42.0	1450	1455	44.56%	23.78%	31.66%	+0.08	-19.4	14
2019-09-22	@ Nykobing	W 3-0	42.0	1455	1450	31.66%	23.78%	44.56%	-0.08	+19.3	13
2019-09-28	Kolding IF	L 1-2	60.5	1543	1481	53.36%	22.68%	23.95%	+0.36	-7.7	18
2019-09-28	@ Viborg	W 2-1	60.5	1481	1543	23.95%	22.68%	53.36%	-0.36	+7.7	20
2019-09-28	Nykobing	D 3-3	66.1	1346	1430	33.48%	23.89%	42.62%	-0.25	+0.2	11
2019-09-28	@ Skive	D 3-3	66.1	1430	1346	42.62%	23.89%	33.48%	+0.25	-0.2	15
2019-09-29	FC Roskilde	W 2-1	47.3	1455	1417	50.29%	23.18%	26.54%	+0.26	+4.4	16
2019-09-29	@ Fremad Amager	L 1-2	47.3	1417	1455	26.54%	23.18%	50.29%	-0.26	-4.4	7
2019-09-29	HB Koge	W 2-1	50.1	1474	1458	47.51%	23.52%	28.97%	+0.17	+4.7	16
2019-09-29	@ Vendsyssel	L 1-2	50.1	1458	1474	28.97%	23.52%	47.51%	-0.17	-4.7	10
2019-09-29	Hvidovre	W 3-2	50.9	1475	1395	55.46%	22.27%	22.27%	+0.43	+3.6	21
2019-09-29	@ Fredericia	L 2-3	50.9	1395	1475	22.27%	22.27%	55.46%	-0.43	-3.6	10
2019-09-29	Vejle BK	L 2-3	58.8	1451	1542	32.70%	23.85%	43.45%	-0.27	-5.0	11
2019-09-29	@ Naestved	W 3-2	58.8	1542	1451	43.45%	23.85%	32.70%	+0.27	+5.0	20
2019-10-02	Vejle BK	D 0-0	58.6	1453	1547	32.29%	23.82%	43.89%	-0.29	+0.4	11
2019-10-02	@ HB Koge	D 0-0	58.6	1547	1453	43.89%	23.82%	32.29%	+0.29	-0.4	21
2019-10-03	Fredericia	L 1-2	56.7	1489	1478	46.70%	23.60%	29.70%	+0.14	-6.9	20
2019-10-03	@ Kolding IF	W 2-1	56.7	1478	1489	29.70%	23.60%	46.70%	-0.14	+6.9	24
2019-10-05	Naestved	W 3-1	46.1	1392	1446	37.61%	24.00%	38.39%	-0.12	+10.3	13
2019-10-05	@ Hvidovre	L 1-3	46.1	1446	1392	38.39%	24.00%	37.61%	+0.12	-10.3	11
2019-10-06	Fremad Amager	D 2-2	64.8	1430	1459	41.25%	23.95%	34.80%	-0.02	-0.2	16
2019-10-06	@ Nykobing	D 2-2	64.8	1459	1430	34.80%	23.95%	41.25%	+0.02	+0.2	17
2019-10-06	Skive	L 0-2	44.8	1453	1346	58.70%	21.52%	19.78%	+0.55	-16.8	11
2019-10-06	@ HB Koge	W 2-0	44.8	1346	1453	19.78%	21.52%	58.70%	-0.55	+16.8	14
2019-10-06	Vendsyssel	W 1-0	46.1	1546	1479	53.97%	22.57%	23.46%	+0.38	+4.2	24
2019-10-06	@ Vejle BK	L 0-1	46.1	1479	1546	23.46%	22.57%	53.97%	-0.38	-4.2	16
2019-10-06	Viborg	L 0-2	40.8	1413	1535	28.66%	23.48%	47.86%	-0.41	-9.4	7
2019-10-06	@ FC Roskilde	W 2-0	40.8	1535	1413	47.86%	23.48%	28.66%	+0.41	+9.4	21
2019-10-11	Nykobing	W 3-1	44.0	1482	1430	52.09%	22.90%	25.01%	+0.32	+7.2	23
2019-10-11	@ Kolding IF	L 1-3	44.0	1430	1482	25.01%	22.90%	52.09%	-0.32	-7.2	16
2019-10-12	Hvidovre	W 2-1	47.8	1363	1402	39.82%	23.99%	36.19%	-0.06	+5.7	17
2019-10-12	@ Skive	L 1-2	47.8	1402	1363	36.19%	23.99%	39.82%	+0.06	-5.7	13
2019-10-13	Naestved	D 1-1	60.0	1475	1436	50.43%	23.16%	26.42%	+0.26	-0.8	17
2019-10-13	@ Vendsyssel	D 1-1	60.0	1436	1475	26.42%	23.16%	50.43%	-0.26	+0.8	12
2019-10-18	Fremad Amager	W 5-0	39.7	1545	1459	56.18%	22.12%	21.70%	+0.46	+17.2	24
2019-10-18	@ Viborg	L 0-5	39.7	1459	1545	21.70%	22.12%	56.18%	-0.46	-17.1	17
2019-10-18	Vendsyssel	D 1-1	58.5	1396	1474	34.38%	23.93%	41.68%	-0.22	+0.2	14
2019-10-18	@ Hvidovre	D 1-1	58.5	1474	1396	41.68%	23.93%	34.38%	+0.22	-0.2	18
2019-10-19	Kolding IF	W 3-0	40.5	1550	1489	53.25%	22.70%	24.04%	+0.35	+11.7	27
2019-10-19	@ Vejle BK	L 0-3	40.5	1489	1550	24.04%	22.70%	53.25%	-0.35	-11.7	23
2019-10-20	FC Roskilde	W 2-1	46.5	1437	1403	49.73%	23.25%	27.01%	+0.24	+4.5	14
2019-10-20	@ HB Koge	L 1-2	46.5	1403	1437	27.01%	23.25%	49.73%	-0.24	-4.5	7
2019-10-20	Fredericia	L 0-5	41.2	1423	1485	36.48%	23.99%	39.53%	-0.16	-26.6	16
2019-10-20	@ Nykobing	W 5-0	41.2	1485	1423	39.53%	23.99%	36.48%	+0.16	+26.6	27
2019-10-20	Skive	W 1-0	38.9	1437	1368	54.12%	22.54%	23.34%	+0.38	+4.2	15
2019-10-20	@ Naestved	L 0-1	38.9	1368	1437	23.34%	22.54%	54.12%	-0.38	-4.2	17
2019-10-24	HB Koge	D 2-2	67.5	1512	1441	54.41%	22.49%	23.10%	+0.39	-0.8	28
2019-10-24	@ Fredericia	D 2-2	67.5	1441	1512	23.10%	22.49%	54.41%	-0.39	+0.8	15
2019-10-24	Viborg	L 1-3	48.7	1441	1562	28.88%	23.51%	47.61%	-0.40	-8.2	15
2019-10-24	@ Naestved	W 3-1	48.7	1562	1441	47.61%	23.51%	28.88%	+0.40	+8.2	27
2019-10-25	Hvidovre	L 0-2	43.9	1442	1397	51.29%	23.03%	25.68%	+0.29	-15.0	17
2019-10-25	@ Fremad Amager	W 2-0	43.9	1397	1442	25.68%	23.03%	51.29%	-0.29	+15.0	17
2019-10-25	Vejle BK	D 0-0	56.5	1364	1562	20.94%	21.89%	57.17%	-0.72	+1.4	18
2019-10-25	@ Skive	D 0-0	56.5	1562	1364	57.17%	21.89%	20.94%	+0.72	-1.4	28
2019-10-25	Vendsyssel	L 1-2	55.8	1477	1474	45.77%	23.68%	30.54%	+0.12	-6.8	23
2019-10-25	@ Kolding IF	W 2-1	55.8	1474	1477	30.54%	23.68%	45.77%	-0.12	+6.8	21
2019-10-27	Naestved	W 4-0	37.4	1399	1433	40.54%	23.97%	35.49%	-0.04	+21.2	10
2019-10-27	@ FC Roskilde	L 0-4	37.4	1433	1399	35.49%	23.97%	40.54%	+0.04	-21.2	15
2019-10-27	Viborg	L 1-2	49.2	1396	1570	23.14%	22.50%	54.37%	-0.62	-3.9	16
2019-10-27	@ Nykobing	W 2-1	49.2	1570	1396	54.37%	22.50%	23.14%	+0.62	+3.9	30
2019-11-01	FC Roskilde	L 1-3	44.7	1366	1420	37.67%	24.00%	38.33%	-0.12	-10.1	18
2019-11-01	@ Skive	W 3-1	44.7	1420	1366	38.33%	24.00%	37.67%	+0.12	+10.1	13
2019-11-01	Kolding IF	L 1-2	51.0	1412	1471	36.97%	24.00%	39.03%	-0.14	-5.8	17
2019-11-01	@ Hvidovre	W 2-1	51.0	1471	1412	39.03%	24.00%	36.97%	+0.14	+5.8	26
2019-11-02	Fremad Amager	W 4-0	36.3	1561	1427	61.57%	20.72%	17.71%	+0.65	+11.4	31
2019-11-02	@ Vejle BK	L 0-4	36.3	1427	1561	17.71%	20.72%	61.57%	-0.65	-11.4	17
2019-11-02	Viborg	W 2-1	59.1	1442	1574	27.58%	23.34%	49.08%	-0.44	+7.2	18
2019-11-02	@ HB Koge	L 1-2	59.1	1574	1442	49.08%	23.34%	27.58%	+0.44	-7.2	30
2019-11-03	Fredericia	D 1-1	60.2	1412	1511	31.53%	23.77%	44.70%	-0.31	+0.4	16
2019-11-03	@ Naestved	D 1-1	60.2	1511	1412	44.70%	23.77%	31.53%	+0.31	-0.4	29
2019-11-03	Nykobing	D 0-0	54.7	1481	1392	56.51%	22.04%	21.44%	+0.47	-1.4	22
2019-11-03	@ Vendsyssel	D 0-0	54.7	1392	1481	21.44%	22.04%	56.51%	-0.47	+1.4	17
2019-11-06	FC Roskilde	W 2-0	38.2	1511	1430	55.59%	22.25%	22.16%	+0.43	+7.5	32
2019-11-06	@ Fredericia	L 0-2	38.2	1430	1511	22.16%	22.25%	55.59%	-0.43	-7.5	13
2019-11-07	Vejle BK	D 0-0	57.8	1394	1572	22.71%	22.39%	54.90%	-0.64	+1.3	18
2019-11-07	@ Nykobing	D 0-0	57.8	1572	1394	54.90%	22.39%	22.71%	+0.64	-1.3	32
2019-11-08	Naestved	W 2-1	46.9	1567	1412	63.81%	20.01%	16.18%	+0.74	+2.8	33
2019-11-08	@ Viborg	L 1-2	46.9	1412	1567	16.18%	20.01%	63.81%	-0.74	-2.7	16
2019-11-10	HB Koge	L 0-2	46.0	1476	1449	48.92%	23.36%	27.73%	+0.21	-14.4	26
2019-11-10	@ Kolding IF	W 2-0	46.0	1449	1476	27.73%	23.36%	48.92%	-0.21	+14.4	21
2019-11-10	Hvidovre	L 0-2	42.7	1423	1406	47.55%	23.51%	28.94%	+0.17	-14.0	13
2019-11-10	@ FC Roskilde	W 2-0	42.7	1406	1423	28.94%	23.51%	47.55%	-0.17	+14.0	20
2019-11-10	Skive	L 0-2	47.9	1518	1356	64.60%	19.75%	15.66%	+0.77	-18.2	32
2019-11-10	@ Fredericia	W 2-0	47.9	1356	1518	15.66%	19.75%	64.60%	-0.77	+18.2	21
2019-11-10	Vendsyssel	W 3-0	40.3	1416	1479	36.35%	23.99%	39.66%	-0.16	+17.6	20
2019-11-10	@ Fremad Amager	L 0-3	40.3	1479	1416	39.66%	23.99%	36.35%	+0.16	-17.6	22
2019-11-15	Fredericia	L 2-3	56.6	1420	1500	34.06%	23.92%	42.02%	-0.23	-5.1	20
2019-11-15	@ Hvidovre	W 3-2	56.6	1500	1420	42.02%	23.92%	34.06%	+0.23	+5.1	35
2019-11-15	Nykobing	L 0-2	45.2	1464	1395	54.16%	22.53%	23.30%	+0.39	-15.7	21
2019-11-15	@ HB Koge	W 2-0	45.2	1395	1464	23.30%	22.53%	54.16%	-0.39	+15.7	21
2019-11-17	Fremad Amager	L 0-1	45.9	1409	1433	41.96%	23.92%	34.12%	+0.00	-6.7	16
2019-11-17	@ Naestved	W 1-0	45.9	1433	1409	34.12%	23.92%	41.96%	+0.00	+6.7	23
2019-11-17	Kolding IF	L 0-2	38.6	1374	1462	33.00%	23.87%	43.13%	-0.26	-10.5	21
2019-11-17	@ Skive	W 2-0	38.6	1462	1374	43.13%	23.87%	33.00%	+0.26	+10.5	29
2019-11-21	HB Koge	D 1-1	59.0	1440	1448	44.22%	23.80%	31.98%	+0.07	-0.4	24
2019-11-21	@ Fremad Amager	D 1-1	59.0	1448	1440	31.98%	23.80%	44.22%	-0.07	+0.4	22
2019-11-23	Vejle BK	L 0-4	38.5	1409	1571	24.32%	22.76%	52.92%	-0.57	-15.5	13
2019-11-23	@ FC Roskilde	W 4-0	38.5	1571	1409	52.92%	22.76%	24.32%	+0.57	+15.5	35
2019-11-23	Viborg	W 1-0	53.4	1462	1570	30.45%	23.67%	45.87%	-0.34	+7.2	25
2019-11-23	@ Vendsyssel	L 0-1	53.4	1570	1462	45.87%	23.67%	30.45%	+0.34	-7.2	33
2019-11-28	Vejle BK	L 3-4	69.8	1562	1586	41.98%	23.92%	34.10%	+0.00	-5.9	33
2019-11-28	@ Viborg	W 4-3	69.8	1586	1562	34.10%	23.92%	41.98%	+0.00	+5.9	38
2020-02-28	Hvidovre	D 1-1	62.9	1556	1415	62.46%	20.45%	17.09%	+0.69	-1.6	34
2020-02-28	@ Viborg	D 1-1	62.9	1415	1556	17.09%	20.45%	62.46%	-0.69	+1.6	21
2020-02-29	Fredericia	W 4-2	54.1	1440	1505	36.09%	23.98%	39.93%	-0.17	+9.5	27
2020-02-29	@ Fremad Amager	L 2-4	54.1	1505	1440	39.93%	23.98%	36.09%	+0.17	-9.5	35
2020-02-29	Naestved	D 1-1	59.0	1472	1403	54.30%	22.51%	23.19%	+0.39	-1.1	30
2020-02-29	@ Kolding IF	D 1-1	59.0	1403	1472	23.19%	22.51%	54.30%	-0.39	+1.1	17
2020-03-01	FC Roskilde	W 2-0	35.8	1469	1393	55.01%	22.37%	22.62%	+0.41	+7.6	28
2020-03-01	@ Vendsyssel	L 0-2	35.8	1393	1469	22.62%	22.37%	55.01%	-0.41	-7.6	13
2020-03-01	HB Koge	W 1-0	44.1	1592	1448	62.67%	20.38%	16.95%	+0.70	+3.1	41
2020-03-01	@ Vejle BK	L 0-1	44.1	1448	1592	16.95%	20.38%	62.67%	-0.70	-3.0	22
2020-03-01	Skive	W 4-2	44.6	1410	1363	51.49%	23.00%	25.51%	+0.30	+6.6	24
2020-03-01	@ Nykobing	L 2-4	44.6	1363	1410	25.51%	23.00%	51.49%	-0.30	-6.6	21
2020-03-06	Kolding IF	W 1-0	46.5	1385	1471	33.28%	23.88%	42.83%	-0.25	+6.8	16
2020-03-06	@ FC Roskilde	L 0-1	46.5	1471	1385	42.83%	23.88%	33.28%	+0.25	-6.9	30
2020-03-06	Vendsyssel	W 2-0	41.9	1445	1476	40.95%	23.96%	35.10%	-0.03	+11.1	25
2020-03-06	@ HB Koge	L 0-2	41.9	1476	1445	35.10%	23.96%	40.95%	+0.03	-11.1	28
2020-03-07	Vejle BK	L 0-1	45.3	1416	1595	22.68%	22.38%	54.94%	-0.64	-4.0	21
2020-03-07	@ Hvidovre	W 1-0	45.3	1595	1416	54.94%	22.38%	22.68%	+0.64	+4.0	44
2020-03-07	Viborg	L 1-3	53.0	1496	1555	36.94%	24.00%	39.06%	-0.14	-10.0	35
2020-03-07	@ Fredericia	W 3-1	53.0	1555	1496	39.06%	24.00%	36.94%	+0.14	+10.0	37
2020-03-08	Fremad Amager	W 2-1	50.9	1357	1449	32.43%	23.83%	43.74%	-0.28	+6.6	24
2020-03-08	@ Skive	L 1-2	50.9	1449	1357	43.74%	23.83%	32.43%	+0.28	-6.6	27
2020-03-08	Nykobing	D 0-0	52.8	1404	1417	43.45%	23.85%	32.71%	+0.05	-0.4	18
2020-03-08	@ Naestved	D 0-0	52.8	1417	1404	32.71%	23.85%	43.45%	-0.05	+0.4	25
2020-05-29	Skive	D 1-1	62.0	1565	1363	68.41%	18.33%	13.26%	+0.93	-2.0	38
2020-05-29	@ Viborg	D 1-1	62.0	1363	1565	13.26%	18.33%	68.41%	-0.93	+2.0	25
2020-05-30	Hvidovre	D 1-1	58.7	1456	1412	51.09%	23.06%	25.85%	+0.28	-0.9	26
2020-05-30	@ HB Koge	D 1-1	58.7	1412	1456	25.85%	23.06%	51.09%	-0.28	+0.9	22
2020-05-30	Kolding IF	D 2-2	65.4	1443	1465	42.25%	23.91%	33.84%	+0.01	-0.2	28
2020-05-30	@ Fremad Amager	D 2-2	65.4	1465	1443	33.84%	23.91%	42.25%	-0.01	+0.2	31
2020-05-31	FC Roskilde	D 2-2	62.8	1417	1392	48.66%	23.39%	27.95%	+0.21	-0.5	26
2020-05-31	@ Nykobing	D 2-2	62.8	1392	1417	27.95%	23.39%	48.66%	-0.21	+0.5	17
2020-05-31	Fredericia	L 0-1	49.5	1465	1486	42.49%	23.90%	33.61%	+0.02	-6.8	28
2020-05-31	@ Vendsyssel	W 1-0	49.5	1486	1465	33.61%	23.90%	42.49%	-0.02	+6.8	38
2020-05-31	Naestved	D 1-1	64.7	1599	1403	67.88%	18.54%	13.58%	+0.91	-2.0	45
2020-05-31	@ Vejle BK	D 1-1	64.7	1403	1599	13.58%	18.54%	67.88%	-0.91	+2.0	19
2020-06-05	Vejle BK	L 1-2	56.4	1492	1597	30.85%	23.71%	45.44%	-0.33	-5.0	38
2020-06-05	@ Fredericia	W 2-1	56.4	1597	1492	45.44%	23.71%	30.85%	+0.33	+5.0	48
2020-06-05	Vendsyssel	L 1-3	43.9	1365	1459	32.33%	23.82%	43.85%	-0.28	-9.0	25
2020-06-05	@ Skive	W 3-1	43.9	1459	1365	43.85%	23.82%	32.33%	+0.28	+9.0	31
2020-06-05	Viborg	W 3-1	54.4	1465	1563	31.71%	23.78%	44.51%	-0.30	+11.5	34
2020-06-05	@ Kolding IF	L 1-3	54.4	1563	1465	44.51%	23.78%	31.71%	+0.30	-11.5	38
2020-06-06	Fremad Amager	W 2-1	49.8	1393	1442	38.32%	24.00%	37.67%	-0.10	+5.8	20
2020-06-06	@ FC Roskilde	L 1-2	49.8	1442	1393	37.67%	24.00%	38.32%	+0.10	-5.8	28
2020-06-06	Nykobing	W 1-0	42.3	1413	1417	44.76%	23.76%	31.48%	+0.09	+5.4	25
2020-06-06	@ Hvidovre	L 0-1	42.3	1417	1413	31.48%	23.76%	44.76%	-0.09	-5.4	26
2020-06-07	HB Koge	W 2-1	50.5	1405	1455	38.25%	24.00%	37.75%	-0.11	+5.8	22
2020-06-07	@ Naestved	L 1-2	50.5	1455	1405	37.75%	24.00%	38.25%	+0.11	-5.9	26
2020-06-09	Hvidovre	D 1-1	59.2	1468	1418	51.73%	22.96%	25.31%	+0.30	-0.9	32
2020-06-09	@ Vendsyssel	D 1-1	59.2	1418	1468	25.31%	22.96%	51.73%	-0.30	+0.9	26
2020-06-09	Kolding IF	D 2-2	64.8	1412	1476	36.17%	23.99%	39.84%	-0.17	+0.1	27
2020-06-09	@ Nykobing	D 2-2	64.8	1476	1412	39.84%	23.99%	36.17%	+0.17	-0.1	35
2020-06-09	Skive	L 1-2	62.0	1602	1356	72.40%	16.64%	10.96%	+1.12	-10.0	48
2020-06-09	@ Vejle BK	W 2-1	62.0	1356	1602	10.96%	16.64%	72.40%	-1.12	+10.0	28
2020-06-10	Fredericia	D 2-2	66.4	1450	1487	40.00%	23.98%	36.02%	-0.05	-0.1	27
2020-06-10	@ HB Koge	D 2-2	66.4	1487	1450	36.02%	23.98%	40.00%	+0.05	+0.1	39
2020-06-10	Naestved	W 1-0	41.6	1437	1411	48.69%	23.39%	27.92%	+0.21	+4.9	31
2020-06-10	@ Fremad Amager	L 0-1	41.6	1411	1437	27.92%	23.39%	48.69%	-0.21	-4.9	22
2020-06-11	FC Roskilde	W 4-2	46.0	1551	1399	63.59%	20.09%	16.32%	+0.73	+4.3	41
2020-06-11	@ Viborg	L 2-4	46.0	1399	1551	16.32%	20.09%	63.59%	-0.73	-4.3	20
2020-06-12	Nykobing	W 3-2	53.6	1366	1412	38.93%	24.00%	37.07%	-0.09	+5.5	31
2020-06-12	@ Skive	L 2-3	53.6	1412	1366	37.07%	24.00%	38.93%	+0.09	-5.5	27
2020-06-13	Fremad Amager	W 3-1	44.8	1488	1441	51.35%	23.02%	25.63%	+0.29	+7.4	42
2020-06-13	@ Fredericia	L 1-3	44.8	1441	1488	25.63%	23.02%	51.35%	-0.29	-7.4	31
2020-06-13	Vejle BK	L 0-1	49.8	1476	1592	29.47%	23.57%	46.96%	-0.38	-5.1	35
2020-06-13	@ Kolding IF	W 1-0	49.8	1592	1476	46.96%	23.57%	29.47%	+0.38	+5.1	51
2020-06-13	Vendsyssel	D 0-0	54.1	1406	1467	36.78%	24.00%	39.22%	-0.15	+0.1	23
2020-06-13	@ Naestved	D 0-0	54.1	1467	1406	39.22%	24.00%	36.78%	+0.15	-0.1	33
2020-06-14	HB Koge	D 2-2	63.5	1394	1449	37.53%	24.00%	38.46%	-0.13	+0.0	21
2020-06-14	@ FC Roskilde	D 2-2	63.5	1449	1394	38.46%	24.00%	37.53%	+0.13	-0.0	28
2020-06-14	Viborg	L 1-4	44.4	1419	1556	27.12%	23.27%	49.61%	-0.46	-11.0	26
2020-06-14	@ Hvidovre	W 4-1	44.4	1556	1419	49.61%	23.27%	27.12%	+0.46	+11.0	44
2020-06-19	FC Roskilde	D 2-2	64.6	1471	1394	55.13%	22.34%	22.53%	+0.42	-0.8	36
2020-06-19	@ Kolding IF	D 2-2	64.6	1394	1471	22.53%	22.34%	55.13%	-0.42	+0.8	22
2020-06-19	Fredericia	L 0-2	52.4	1567	1495	54.52%	22.47%	23.02%	+0.40	-15.8	44
2020-06-19	@ Viborg	W 2-0	52.4	1495	1567	23.02%	22.47%	54.52%	-0.40	+15.8	45
2020-06-19	HB Koge	D 1-1	60.0	1467	1449	47.59%	23.51%	28.90%	+0.17	-0.6	34
2020-06-19	@ Vendsyssel	D 1-1	60.0	1449	1467	28.90%	23.51%	47.59%	-0.17	+0.6	29
2020-06-20	Skive	D 0-0	52.8	1434	1372	53.38%	22.68%	23.94%	+0.36	-1.1	32
2020-06-20	@ Fremad Amager	D 0-0	52.8	1372	1434	23.94%	22.68%	53.38%	-0.36	+1.1	32
2020-06-21	Hvidovre	W 5-3	48.8	1597	1408	67.21%	18.80%	13.99%	+0.88	+3.4	54
2020-06-21	@ Vejle BK	L 3-5	48.8	1408	1597	13.99%	18.80%	67.21%	-0.88	-3.4	26
2020-06-21	Naestved	W 2-1	47.2	1406	1406	45.26%	23.72%	31.01%	+0.10	+5.0	30
2020-06-21	@ Nykobing	L 1-2	47.2	1406	1406	31.01%	23.72%	45.26%	-0.10	-5.0	23
2020-06-23	Kolding IF	W 1-0	45.7	1450	1470	42.50%	23.90%	33.60%	+0.02	+5.7	32
2020-06-23	@ HB Koge	L 0-1	45.7	1470	1450	33.60%	23.90%	42.50%	-0.02	-5.7	36
2020-06-23	Vendsyssel	L 2-4	58.4	1511	1466	51.18%	23.05%	25.77%	+0.29	-11.6	45
2020-06-23	@ Fredericia	W 4-2	58.4	1466	1511	25.77%	23.05%	51.18%	-0.29	+11.6	37
2020-06-24	Vejle BK	D 1-1	63.7	1401	1601	20.78%	21.85%	57.37%	-0.72	+1.3	24
2020-06-24	@ Naestved	D 1-1	63.7	1601	1401	57.37%	21.85%	20.78%	+0.72	-1.3	55
2020-06-24	Viborg	L 0-1	42.2	1373	1551	22.77%	22.41%	54.82%	-0.63	-4.1	32
2020-06-24	@ Skive	W 1-0	42.2	1551	1373	54.82%	22.41%	22.77%	+0.63	+4.1	47
2020-06-25	Fremad Amager	W 3-0	37.1	1405	1433	41.41%	23.94%	34.65%	-0.01	+15.9	29
2020-06-25	@ Hvidovre	L 0-3	37.1	1433	1405	34.65%	23.94%	41.41%	+0.01	-15.9	32
2020-06-25	Nykobing	D 2-2	62.6	1395	1411	43.09%	23.87%	33.05%	+0.04	-0.2	23
2020-06-25	@ FC Roskilde	D 2-2	62.6	1411	1395	33.05%	23.87%	43.09%	-0.04	+0.2	31
2020-06-26	Kolding IF	D 2-2	66.7	1477	1465	47.03%	23.57%	29.40%	+0.16	-0.4	38
2020-06-26	@ Vendsyssel	D 2-2	66.7	1465	1477	29.40%	23.57%	47.03%	-0.16	+0.4	37
2020-06-27	Fredericia	W 2-0	43.2	1600	1499	57.91%	21.72%	20.38%	+0.52	+6.9	58
2020-06-27	@ Vejle BK	L 0-2	43.2	1499	1600	20.38%	21.72%	57.91%	-0.52	-6.9	45
2020-06-27	HB Koge	W 4-2	50.0	1555	1456	57.76%	21.75%	20.49%	+0.51	+5.4	50
2020-06-27	@ Viborg	L 2-4	50.0	1456	1555	20.49%	21.75%	57.76%	-0.51	-5.4	32
2020-06-27	Naestved	W 2-0	37.9	1369	1403	40.58%	23.97%	35.45%	-0.04	+11.2	35
2020-06-27	@ Skive	L 0-2	37.9	1403	1369	35.45%	23.97%	40.58%	+0.04	-11.1	24
2020-06-28	FC Roskilde	W 2-0	36.5	1417	1395	48.24%	23.44%	28.32%	+0.19	+9.3	35
2020-06-28	@ Fremad Amager	L 0-2	36.5	1395	1417	28.32%	23.44%	48.24%	-0.19	-9.3	23
2020-06-28	Hvidovre	D 1-1	57.4	1411	1421	43.99%	23.82%	32.20%	+0.06	-0.4	32
2020-06-28	@ Nykobing	D 1-1	57.4	1421	1411	32.20%	23.82%	43.99%	-0.06	+0.4	30
2020-06-30	Skive	W 2-1	44.7	1465	1380	56.12%	22.13%	21.75%	+0.45	+3.7	40
2020-06-30	@ Kolding IF	L 1-2	44.7	1380	1465	21.75%	22.13%	56.12%	-0.45	-3.7	35
2020-06-30	Vejle BK	W 2-1	61.4	1450	1606	24.96%	22.89%	52.14%	-0.54	+7.6	35
2020-06-30	@ HB Koge	L 1-2	61.4	1606	1450	52.14%	22.89%	24.96%	+0.54	-7.6	58
2020-06-30	Viborg	D 2-2	67.4	1391	1560	23.67%	22.62%	53.71%	-0.60	+0.8	25
2020-06-30	@ Naestved	D 2-2	67.4	1560	1391	53.71%	22.62%	23.67%	+0.60	-0.8	51
2020-07-01	Nykobing	W 4-0	35.5	1426	1411	47.34%	23.54%	29.12%	+0.16	+18.0	38
2020-07-01	@ Fremad Amager	L 0-4	35.5	1411	1426	29.12%	23.54%	47.34%	-0.16	-18.0	32
2020-07-01	Vendsyssel	L 2-3	54.3	1386	1477	32.57%	23.84%	43.59%	-0.28	-5.0	23
2020-07-01	@ FC Roskilde	W 3-2	54.3	1477	1386	43.59%	23.84%	32.57%	+0.28	+5.0	41
2020-07-02	Hvidovre	L 1-2	56.8	1492	1421	54.43%	22.48%	23.09%	+0.39	-7.9	45
2020-07-02	@ Fredericia	W 2-1	56.8	1421	1492	23.09%	22.48%	54.43%	-0.39	+7.9	33
2020-07-03	Kolding IF	L 0-1	44.1	1392	1469	34.56%	23.94%	41.50%	-0.21	-5.8	25
2020-07-03	@ Naestved	W 1-0	44.1	1469	1392	41.50%	23.94%	34.56%	+0.21	+5.8	43
2020-07-04	Fremad Amager	L 0-1	50.7	1482	1444	50.27%	23.18%	26.55%	+0.26	-7.8	41
2020-07-04	@ Vendsyssel	W 1-0	50.7	1444	1482	26.55%	23.18%	50.27%	-0.26	+7.8	41
2020-07-05	Fredericia	W 1-0	47.4	1376	1484	30.46%	23.67%	45.87%	-0.34	+7.2	38
2020-07-05	@ Skive	L 0-1	47.4	1484	1376	45.87%	23.67%	30.46%	+0.34	-7.2	45
2020-07-05	HB Koge	D 1-1	59.0	1429	1458	41.29%	23.95%	34.76%	-0.02	-0.2	34
2020-07-05	@ Hvidovre	D 1-1	59.0	1458	1429	34.76%	23.95%	41.29%	+0.02	+0.2	36
2020-07-06	FC Roskilde	W 4-1	38.5	1599	1381	69.94%	17.71%	12.35%	+1.00	+5.0	61
2020-07-06	@ Vejle BK	L 1-4	38.5	1381	1599	12.35%	17.71%	69.94%	-1.00	-5.0	23
2020-07-06	Nykobing	W 4-3	53.7	1559	1393	65.00%	19.61%	15.39%	+0.79	+2.4	54
2020-07-06	@ Viborg	L 3-4	53.7	1393	1559	15.39%	19.61%	65.00%	-0.79	-2.4	32
2020-07-10	Naestved	W 3-2	50.3	1477	1386	56.77%	21.99%	21.24%	+0.48	+3.4	48
2020-07-10	@ Fredericia	L 2-3	50.3	1386	1477	21.24%	21.99%	56.77%	-0.48	-3.4	25
2020-07-10	Vejle BK	L 0-2	45.3	1474	1604	27.86%	23.38%	48.76%	-0.43	-9.2	41
2020-07-10	@ Vendsyssel	W 2-0	45.3	1604	1474	48.76%	23.38%	27.86%	+0.43	+9.2	64
2020-07-10	Viborg	D 2-2	69.4	1452	1562	30.25%	23.65%	46.10%	-0.35	+0.4	42
2020-07-10	@ Fremad Amager	D 2-2	69.4	1562	1452	46.10%	23.65%	30.25%	+0.35	-0.4	55
2020-07-11	HB Koge	L 0-1	44.2	1391	1458	35.78%	23.98%	40.25%	-0.18	-5.9	32
2020-07-11	@ Nykobing	W 1-0	44.2	1458	1391	40.25%	23.98%	35.78%	+0.18	+5.9	39
2020-07-11	Hvidovre	L 0-2	45.9	1474	1429	51.28%	23.03%	25.68%	+0.29	-15.0	43
2020-07-11	@ Kolding IF	W 2-0	45.9	1429	1474	25.68%	23.03%	51.28%	-0.29	+15.0	37
2020-07-12	Skive	D 2-2	61.6	1376	1384	44.21%	23.80%	31.99%	+0.07	-0.3	24
2020-07-12	@ FC Roskilde	D 2-2	61.6	1384	1376	31.99%	23.80%	44.21%	-0.07	+0.3	39
2020-07-14	Kolding IF	W 2-0	40.4	1480	1460	48.10%	23.45%	28.45%	+0.19	+9.3	51
2020-07-14	@ Fredericia	L 0-2	40.4	1460	1480	28.45%	23.45%	48.10%	-0.19	-9.3	43
2020-07-14	Nykobing	W 1-0	40.0	1613	1385	70.87%	17.32%	11.82%	+1.05	+2.1	67
2020-07-14	@ Vejle BK	L 0-1	40.0	1385	1613	11.82%	17.32%	70.87%	-1.05	-2.1	32
2020-07-14	Vendsyssel	W 4-1	44.0	1561	1465	57.45%	21.83%	20.72%	+0.50	+8.6	58
2020-07-14	@ Viborg	L 1-4	44.0	1465	1561	20.72%	21.83%	57.45%	-0.50	-8.6	41
2020-07-15	Fremad Amager	L 0-1	49.5	1464	1453	46.85%	23.58%	29.57%	+0.15	-7.4	39
2020-07-15	@ HB Koge	W 1-0	49.5	1453	1464	29.57%	23.58%	46.85%	-0.15	+7.4	45
2020-07-16	FC Roskilde	L 0-2	40.8	1383	1375	46.32%	23.63%	30.04%	+0.13	-13.8	25
2020-07-16	@ Naestved	W 2-0	40.8	1375	1383	30.04%	23.63%	46.32%	-0.13	+13.8	27
2020-07-16	Skive	L 0-2	44.1	1444	1384	53.10%	22.73%	24.17%	+0.35	-15.4	37
2020-07-16	@ Hvidovre	W 2-0	44.1	1384	1444	24.17%	22.73%	53.10%	-0.35	+15.4	42
2020-07-19	Fredericia	W 1-0	47.7	1389	1490	31.38%	23.75%	44.87%	-0.31	+7.1	30
2020-07-19	@ FC Roskilde	L 0-1	47.7	1490	1389	44.87%	23.75%	31.38%	+0.31	-7.1	51
2020-07-19	Fremad Amager	D 2-2	65.6	1450	1460	43.95%	23.82%	32.23%	+0.06	-0.3	44
2020-07-19	@ Kolding IF	D 2-2	65.6	1460	1450	32.23%	23.82%	43.95%	-0.06	+0.3	46
2020-07-19	HB Koge	W 3-2	56.0	1399	1457	37.19%	24.00%	38.81%	-0.14	+5.7	45
2020-07-19	@ Skive	L 2-3	56.0	1457	1399	38.81%	24.00%	37.19%	+0.14	-5.7	39
2020-07-19	Hvidovre	L 0-2	38.9	1369	1428	36.95%	24.00%	39.05%	-0.14	-11.5	25
2020-07-19	@ Naestved	W 2-0	38.9	1428	1369	39.05%	24.00%	36.95%	+0.14	+11.5	40
2020-07-19	Vendsyssel	L 0-2	39.3	1383	1456	34.91%	23.95%	41.14%	-0.20	-11.0	32
2020-07-19	@ Nykobing	W 2-0	39.3	1456	1383	41.14%	23.95%	34.91%	+0.20	+11.0	44
2020-07-19	Viborg	D 1-1	69.2	1615	1570	51.22%	23.04%	25.74%	+0.29	-0.9	68
2020-07-19	@ Vejle BK	D 1-1	69.2	1570	1615	25.74%	23.04%	51.22%	-0.29	+0.9	59
2020-07-23	Nykobing	D 2-2	64.6	1483	1372	59.12%	21.41%	19.47%	+0.56	-1.0	52
2020-07-23	@ Fredericia	D 2-2	64.6	1372	1483	19.47%	21.41%	59.12%	-0.56	+1.0	33
2020-07-25	FC Roskilde	D 0-0	53.4	1440	1396	51.05%	23.07%	25.88%	+0.28	-1.0	41
2020-07-25	@ Hvidovre	D 0-0	53.4	1396	1440	25.88%	23.07%	51.05%	-0.28	+1.0	31
2020-07-25	Kolding IF	L 0-2	52.2	1571	1450	60.22%	21.11%	18.67%	+0.60	-17.2	59
2020-07-25	@ Viborg	W 2-0	52.2	1450	1571	18.67%	21.11%	60.22%	-0.60	+17.2	47
2020-07-25	Naestved	D 2-2	63.2	1451	1358	57.08%	21.91%	21.00%	+0.49	-0.9	40
2020-07-25	@ HB Koge	D 2-2	63.2	1358	1451	21.00%	21.91%	57.08%	-0.49	+0.9	26
2020-07-25	Skive	L 0-1	49.8	1467	1405	53.40%	22.68%	23.92%	+0.36	-8.2	44
2020-07-25	@ Vendsyssel	W 1-0	49.8	1405	1467	23.92%	22.68%	53.40%	-0.36	+8.2	48
2020-07-25	Vejle BK	W 4-1	55.4	1460	1614	25.18%	22.94%	51.89%	-0.53	+18.5	49
2020-07-25	@ Fremad Amager	L 1-4	55.4	1614	1460	51.89%	22.94%	25.18%	+0.53	-18.5	68

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	2020-06-09	10.96%	Skive	1356	2	@ Vejle BK	1602	1
2	2019-11-10	15.66%	Skive	1356	2	@ Fredericia	1518	0
3	2020-07-25	18.67%	Kolding IF	1450	2	@ Viborg	1571	0
4	2019-08-21	19.44%	Skive	1350	1	@ Vendsyssel	1462	0
5	2019-10-06	19.78%	Skive	1346	2	@ HB Koge	1453	0
6	2020-06-19	23.02%	Fredericia	1495	2	@ Viborg	1567	0
7	2020-07-02	23.09%	Hvidovre	1421	2	@ Fredericia	1492	1
8	2019-11-15	23.30%	Nykobing	1395	2	@ HB Koge	1464	0
9	2020-07-25	23.92%	Skive	1405	1	@ Vendsyssel	1467	0
10	2019-09-28	23.95%	Kolding IF	1481	2	@ Viborg	1543	1
11	2020-07-16	24.17%	Skive	1384	2	@ Hvidovre	1444	0
12	2019-08-04	24.81%	Nykobing	1455	4	@ Vejle BK	1509	2
13	2019-08-14	24.85%	Fredericia	1463	1	@ Vejle BK	1517	0
14	2020-06-30	24.96%	@ HB Koge	1450	2	Vejle BK	1606	1
15	2020-07-25	25.18%	@ Fremad Amager	1460	4	Vejle BK	1614	1
16	2019-10-25	25.68%	Hvidovre	1397	2	@ Fremad Amager	1442	0
17	2020-07-11	25.68%	Hvidovre	1429	2	@ Kolding IF	1474	0
18	2019-08-04	25.69%	Fremad Amager	1455	1	@ Vendsyssel	1501	0
19	2020-06-23	25.77%	Vendsyssel	1466	4	@ Fredericia	1511	2
20	2019-08-21	25.78%	Naestved	1428	1	@ Nykobing	1473	0
21	2020-07-04	26.55%	Fremad Amager	1444	1	@ Vendsyssel	1482	0
22	2019-09-22	26.88%	Fremad Amager	1447	2	@ Fredericia	1482	1
23	2019-11-02	27.58%	@ HB Koge	1442	2	Viborg	1574	1
24	2019-11-10	27.73%	HB Koge	1449	2	@ Kolding IF	1476	0
25	2019-08-04	28.84%	Fredericia	1443	3	@ HB Koge	1461	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	2019-10-20	26.64	Fredericia	5	1485	39.53%	@ Nykobing	0	1423	36.48%	23.99%
2	2019-10-27	21.16	@ FC Roskilde	4	1399	40.54%	Naestved	0	1433	35.49%	23.97%
3	2019-08-10	19.39	Vejle BK	3	1497	31.57%	@ Vendsyssel	0	1493	44.66%	23.77%
4	2019-09-22	19.35	Vendsyssel	3	1455	31.66%	@ Nykobing	0	1450	44.56%	23.78%
5	2020-07-25	18.52	@ Fremad Amager	4	1460	25.18%	Vejle BK	1	1614	51.89%	22.94%
6	2019-11-10	18.21	Skive	2	1356	15.66%	@ Fredericia	0	1518	64.60%	19.75%
7	2020-07-01	18.04	@ Fremad Amager	4	1426	47.34%	Nykobing	0	1411	29.12%	23.54%
8	2019-11-10	17.64	@ Fremad Amager	3	1416	36.35%	Vendsyssel	0	1479	39.66%	23.99%
9	2020-07-25	17.17	Kolding IF	2	1450	18.67%	@ Viborg	0	1571	60.22%	21.11%
10	2019-10-18	17.15	@ Viborg	5	1545	56.18%	Fremad Amager	0	1459	21.70%	22.12%
11	2019-10-06	16.80	Skive	2	1346	19.78%	@ HB Koge	0	1453	58.70%	21.52%
12	2020-06-25	15.90	@ Hvidovre	3	1405	41.41%	Fremad Amager	0	1433	34.65%	23.94%
13	2020-06-19	15.77	Fredericia	2	1495	23.02%	@ Viborg	0	1567	54.52%	22.47%
14	2019-11-15	15.68	Nykobing	2	1395	23.30%	@ HB Koge	0	1464	54.16%	22.53%
15	2019-11-23	15.45	Vejle BK	4	1571	52.92%	@ FC Roskilde	0	1409	24.32%	22.76%
16	2020-07-16	15.41	Skive	2	1384	24.17%	@ Hvidovre	0	1444	53.10%	22.73%
17	2019-08-24	15.37	@ Naestved	3	1436	42.95%	Vendsyssel	0	1453	33.17%	23.88%
18	2019-10-25	14.97	Hvidovre	2	1397	25.68%	@ Fremad Amager	0	1442	51.29%	23.03%
19	2020-07-11	14.97	Hvidovre	2	1429	25.68%	@ Kolding IF	0	1474	51.28%	23.03%
20	2019-11-10	14.38	HB Koge	2	1449	27.73%	@ Kolding IF	0	1476	48.92%	23.36%
21	2019-11-10	14.05	Hvidovre	2	1406	28.94%	@ FC Roskilde	0	1423	47.55%	23.51%
22	2019-08-29	13.96	@ Vejle BK	4	1512	39.52%	Viborg	1	1553	36.49%	23.99%
23	2020-07-16	13.75	FC Roskilde	2	1375	30.04%	@ Naestved	0	1383	46.32%	23.63%
24	2019-08-04	12.57	Kolding IF	2	1477	34.62%	@ Naestved	0	1449	41.44%	23.94%
25	2019-08-04	12.19	Fredericia	3	1443	28.84%	@ HB Koge	1	1461	47.65%	23.50%

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	2019-11-28	69.8	Vejle BK	4	1586	34.10%	@ Viborg	3	1562	41.98%	23.92%
2	2019-08-21	69.7	@ Viborg	2	1543	54.50%	Fredericia	2	1471	23.03%	22.47%
3	2020-07-10	69.4	@ Fremad Amager	2	1452	30.25%	Viborg	2	1562	46.10%	23.65%
4	2020-07-19	69.2	@ Vejle BK	1	1615	51.22%	Viborg	1	1570	25.74%	23.04%
5	2019-10-24	67.5	@ Fredericia	2	1512	54.41%	HB Koge	2	1441	23.10%	22.49%
6	2019-07-27	67.4	@ Fremad Amager	2	1455	37.70%	Vejle BK	2	1509	38.30%	24.00%
7	2020-06-30	67.4	@ Naestved	2	1391	23.67%	Viborg	2	1560	53.71%	22.62%
8	2019-09-08	66.8	@ Fredericia	2	1483	48.50%	Nykobing	2	1459	28.09%	23.41%
9	2020-06-26	66.7	@ Vendsyssel	2	1477	47.03%	Kolding IF	2	1465	29.40%	23.57%
10	2020-06-10	66.4	@ HB Koge	2	1450	40.00%	Fredericia	2	1487	36.02%	23.98%
11	2019-09-28	66.1	@ Skive	3	1346	33.48%	Nykobing	3	1430	42.62%	23.89%
12	2020-07-19	65.6	@ Kolding IF	2	1450	43.95%	Fremad Amager	2	1460	32.23%	23.82%
13	2020-05-30	65.4	@ Fremad Amager	2	1443	42.25%	Kolding IF	2	1465	33.84%	23.91%
14	2019-10-06	64.8	@ Nykobing	2	1430	41.25%	Fremad Amager	2	1459	34.80%	23.95%
15	2020-06-09	64.8	@ Nykobing	2	1412	36.17%	Kolding IF	2	1476	39.84%	23.99%
16	2020-05-31	64.7	@ Vejle BK	1	1599	67.88%	Naestved	1	1403	13.58%	18.54%
17	2020-06-19	64.6	@ Kolding IF	2	1471	55.13%	FC Roskilde	2	1394	22.53%	22.34%
18	2020-07-23	64.6	@ Fredericia	2	1483	59.12%	Nykobing	2	1372	19.47%	21.41%
19	2019-08-11	64.5	@ Nykobing	2	1467	54.53%	Hvidovre	2	1395	23.01%	22.46%
20	2019-09-20	63.7	@ Hvidovre	2	1395	36.46%	HB Koge	2	1458	39.55%	23.99%
21	2020-06-24	63.7	@ Naestved	1	1401	20.78%	Vejle BK	1	1601	57.37%	21.85%
22	2019-09-19	63.5	@ Viborg	1	1544	56.79%	Vendsyssel	1	1454	21.23%	21.98%
23	2020-06-14	63.5	@ FC Roskilde	2	1394	37.53%	HB Koge	2	1449	38.46%	24.00%
24	2019-09-13	63.4	@ Skive	2	1350	27.54%	Fredericia	2	1483	49.13%	23.33%
25	2019-08-21	63.3	@ Kolding IF	1	1499	44.02%	Vejle BK	1	1509	32.16%	23.81%

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2019-09-15	34.3	@ Vejle BK	3	1526	60.26%	Hvidovre	0	1404	18.64%	21.10%
2	2020-07-01	35.5	@ Fremad Amager	4	1426	47.34%	Nykobing	0	1411	29.12%	23.54%
3	2020-03-01	35.8	@ Vendsyssel	2	1469	55.01%	FC Roskilde	0	1393	22.62%	22.37%
4	2019-11-02	36.3	@ Vejle BK	4	1561	61.57%	Fremad Amager	0	1427	17.71%	20.72%
5	2020-06-28	36.5	@ Fremad Amager	2	1417	48.24%	FC Roskilde	0	1395	28.32%	23.44%
6	2019-07-26	36.8	@ Viborg	3	1521	55.65%	FC Roskilde	0	1440	22.12%	22.23%
7	2019-08-16	36.8	Viborg	2	1535	54.76%	@ Skive	0	1358	22.83%	22.42%
8	2020-06-25	37.1	@ Hvidovre	3	1405	41.41%	Fremad Amager	0	1433	34.65%	23.94%
9	2019-10-27	37.4	@ FC Roskilde	4	1399	40.54%	Naestved	0	1433	35.49%	23.97%
10	2019-09-19	37.8	@ Vejle BK	2	1535	59.15%	FC Roskilde	0	1424	19.45%	21.40%
11	2020-06-27	37.9	@ Skive	2	1369	40.58%	Naestved	0	1403	35.45%	23.97%
12	2019-08-24	38.1	@ Naestved	3	1436	42.95%	Vendsyssel	0	1453	33.17%	23.88%
13	2019-11-06	38.2	@ Fredericia	2	1511	55.59%	FC Roskilde	0	1430	22.16%	22.25%
14	2019-11-23	38.5	Vejle BK	4	1571	52.92%	@ FC Roskilde	0	1409	24.32%	22.76%
15	2020-07-06	38.5	@ Vejle BK	4	1599	69.94%	FC Roskilde	1	1381	12.35%	17.71%
16	2019-11-17	38.6	Kolding IF	2	1462	43.13%	@ Skive	0	1374	33.00%	23.87%
17	2019-08-25	38.7	@ Viborg	3	1542	55.21%	Nykobing	0	1465	22.47%	22.33%
18	2019-10-20	38.9	@ Naestved	1	1437	54.12%	Skive	0	1368	23.34%	22.54%
19	2020-07-19	38.9	Hvidovre	2	1428	39.05%	@ Naestved	0	1369	36.95%	24.00%
20	2020-07-19	39.3	Vendsyssel	2	1456	41.14%	@ Nykobing	0	1383	34.91%	23.95%
21	2019-10-18	39.7	@ Viborg	5	1545	56.18%	Fremad Amager	0	1459	21.70%	22.12%
22	2020-07-14	40.0	@ Vejle BK	1	1613	70.87%	Nykobing	0	1385	11.82%	17.32%
23	2019-11-10	40.3	@ Fremad Amager	3	1416	36.35%	Vendsyssel	0	1479	39.66%	23.99%
24	2020-07-14	40.4	@ Fredericia	2	1480	48.10%	Kolding IF	0	1460	28.45%	23.45%
25	2019-10-19	40.5	@ Vejle BK	3	1550	53.25%	Kolding IF	0	1489	24.04%	22.70%