2013-14 1st Division Season

198 games

Final

Promoted

Silkeborg

66 pts

Hobro · 65 pts

Relegated

Marienlyst

15 pts

Hvidovre · 36 pts

Biggest Overachiever

Hobro

17.06 points above expected

65 points · 47.94 expected points

Biggest Disappointment

Marienlyst

20.84 points below expected

15 points · 35.84 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	20	6	7	66	67	38	+29	52.00	+14.00
2	Hobro Promoted	33	20	5	8	65	58	36	+22	47.94	+17.06
3	Lyngby	33	18	3	12	57	58	41	+17	49.02	+7.98
4	Bronshoj	33	16	5	12	53	47	39	+8	42.59	+10.41
5	Horsens	33	15	7	11	52	60	48	+12	54.43	-2.43
6	HB Koge	33	13	10	10	49	39	31	+8	45.90	+3.10
7	Vejle BK	33	12	11	10	47	49	38	+11	50.91	-3.91
8	Fredericia	33	12	7	14	43	47	45	+2	45.35	-2.35
9	Vendsyssel	33	12	2	19	38	35	59	-24	36.57	+1.43
10	AB Gladsaxe	33	9	9	15	36	42	57	-15	35.14	+0.86
11	Hvidovre Relegated	33	10	6	17	36	43	63	-20	39.91	-3.91
12	Marienlyst Relegated	33	4	3	26	15	28	78	-50	35.84	-20.84

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	Hobro	65	47.94	+17.06
2	Silkeborg	66	52.00	+14.00
3	Bronshoj	53	42.59	+10.41
4	Lyngby	57	49.02	+7.98
5	HB Koge	49	45.90	+3.10

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Marienlyst	15	35.84	-20.84
2	Vejle BK	47	50.91	-3.91
3	Hvidovre	36	39.91	-3.91
4	Horsens	52	54.43	-2.43
5	Fredericia	43	45.35	-2.35

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	Bronshoj	8	Nov 23 – Apr 26	1 in 3,470
2	Hobro	5	Jul 28 – Aug 25	1 in 385
3	Silkeborg	6	Nov 7 – Mar 27	1 in 259
4	AB Gladsaxe	3	Mar 30 – Apr 12	1 in 140
5	Lyngby	4	Sep 1 – Sep 22	1 in 64

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Marienlyst	11	Nov 27 – May 11	1 in 4,052
2	Bronshoj	4	Jul 28 – Aug 17	1 in 55
3	Fredericia	4	Nov 10 – Mar 20	1 in 49
4	Silkeborg	3	Sep 29 – Oct 6	1 in 43
5	Hobro	3	Mar 27 – Apr 12	1 in 41

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Bronshoj	9	Nov 17 – Apr 26	1 in 37
2	Silkeborg	11	Apr 17 – Jun 9	1 in 21
3	Hobro	8	Oct 14 – Mar 20	1 in 17
4	Lyngby	6	Oct 6 – Nov 10	1 in 9
5	HB Koge	4	Apr 17 – May 4	1 in 7

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Horsens	6	Apr 17 – May 16	1 in 27
2	AB Gladsaxe	10	Sep 29 – Mar 23	1 in 22
3	Marienlyst	11	Nov 27 – May 11	1 in 21
4	HB Koge	5	Apr 21 – May 16	1 in 10
5	Vejle BK	4	Nov 23 – Apr 6	1 in 10

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	1498	66	+28	11	8.8	+2.2
Hobro	1436	65	+15	10	7.8	+2.2
Lyngby	1431	57	-16	4	6.9	-2.9
Bronshoj	1410	53	-12	5	7.1	-2.1
Horsens	1431	52	-3	7	8.6	-1.6
HB Koge	1391	49	+9	8	7.2	+0.8
Vejle BK	1424	47	-7	7	7.4	-0.4
Fredericia	1380	43	-1	7	6.3	+0.7
Vendsyssel	1285	38	-8	6	4.9	+1.1
AB Gladsaxe	1326	36	+27	8	6.5	+1.5
Hvidovre	1303	36	-18	6	5.8	+0.2
Marienlyst	1235	15	-13	4	4.1	-0.1

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	AG	BRO	FRE	HK	HOB	HOR	HVI	LYN	MAR	SIL	VB	VEN
AB Gladsaxe	—	1-2-0 3.27	1-1-1 3.08	1-1-1 3.38	2-1-0 2.92	0-2-1 2.63	1-1-1 3.58	0-0-3 2.80	2-0-1 4.00	0-1-2 3.09	1-0-2 2.91	0-0-3 4.03
Bronshoj	0-2-1 4.84	—	2-0-1 3.84	1-1-1 3.90	0-0-3 3.55	0-1-2 3.37	2-0-1 4.66	2-0-1 3.49	3-0-0 4.80	1-0-2 3.35	2-1-0 3.28	3-0-0 4.68
Fredericia	1-1-1 5.03	1-0-2 4.23	—	2-1-0 3.94	1-0-2 3.75	1-1-1 3.44	1-1-1 4.68	1-0-2 3.91	2-1-0 4.82	0-0-3 3.43	1-1-1 3.65	1-1-1 4.56
HB Koge	1-1-1 4.71	1-1-1 4.17	0-1-2 4.13	—	0-1-2 3.73	3-0-0 3.21	2-0-1 4.59	2-0-1 3.78	1-1-1 4.78	1-2-0 3.27	0-3-0 3.50	2-0-1 4.76
Hobro	0-1-2 5.22	3-0-0 4.54	2-0-1 4.33	2-1-0 4.35	—	2-0-1 3.45	2-1-0 4.72	1-1-1 3.99	3-0-0 4.95	1-0-2 3.57	1-1-1 3.97	3-0-0 5.07
Horsens	1-2-0 5.56	2-1-0 4.72	1-1-1 4.65	0-0-3 4.89	1-0-2 4.64	—	2-0-1 5.19	3-0-0 4.42	1-1-1 5.78	2-0-1 4.34	0-2-1 4.38	2-0-1 5.29
Hvidovre	1-1-1 4.51	1-0-2 3.43	1-1-1 3.42	1-0-2 3.50	0-1-2 3.40	1-0-2 2.95	—	0-0-3 3.08	3-0-0 4.50	0-1-2 2.95	0-1-2 3.04	2-1-0 4.09
Lyngby	3-0-0 5.36	1-0-2 4.59	2-0-1 4.16	1-0-2 4.29	1-1-1 4.09	0-0-3 3.66	3-0-0 5.03	—	3-0-0 5.03	0-1-2 3.71	1-1-1 3.79	3-0-0 5.02
Marienlyst	1-0-2 4.09	0-0-3 3.36	0-1-2 3.30	1-1-1 3.35	0-0-3 3.21	1-1-1 2.44	0-0-3 3.58	0-0-3 3.10	—	0-0-3 2.84	1-0-2 3.04	0-0-3 3.85
Silkeborg	2-1-0 5.03	2-0-1 4.75	3-0-0 4.67	0-2-1 4.83	2-0-1 4.52	1-0-2 3.74	2-1-0 5.19	2-1-0 4.37	3-0-0 5.33	—	1-1-1 4.13	2-0-1 5.37
Vejle BK	2-0-1 5.25	0-1-2 4.81	1-1-1 4.44	0-3-0 4.58	1-1-1 4.11	1-2-0 3.70	2-1-0 5.08	1-1-1 4.29	2-0-1 5.12	1-1-1 3.96	—	1-0-2 5.37
Vendsyssel	3-0-0 4.05	0-0-3 3.43	1-1-1 3.54	1-0-2 3.35	0-0-3 3.04	1-0-2 2.86	0-1-2 3.98	0-0-3 3.11	3-0-0 4.23	1-0-2 2.79	2-0-1 2.79	—

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	0.77	+11.0
Allowed	0.76	-8.9
Differential	0.93	+6.0

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	5.56%	6.82%	6.82%	5.05%	1.52%	0.51%	26.26%
1	6.82%	8.59%	8.59%	4.80%	2.27%	0.25%	31.31%
2	6.82%	8.59%	3.03%	2.27%	0.25%	1.01%	21.97%
3	5.05%	4.80%	2.27%	1.52%	0.51%	—	14.14%
4	1.52%	2.27%	0.25%	0.51%	—	—	4.55%
5+	0.51%	0.25%	1.01%	—	—	—	1.77%
Total	26.26%	31.31%	21.97%	14.14%	4.55%	1.77%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.45	1.45	+0.00
SD	1.24	1.24	1.91
CV	0.86	0.86	—
Max	5	5	+5
Min	0	0	-5

Games Played: 198

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	9.09%	6.06%	3.03%	3.03%	3.03%	30.30%
1	6.06%	9.09%	9.09%	3.03%	3.03%	3.03%	33.33%
2	3.03%	9.09%	6.06%	—	—	—	18.18%
3	6.06%	—	—	6.06%	3.03%	—	15.15%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	24.24%	27.27%	21.21%	12.12%	9.09%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.27	1.73	-0.45
SD	1.15	1.51	2.02
CV	0.91	0.87	—
Max	4	5	+4
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	6.06%	6.06%	—	—	—	15.15%
1	15.15%	9.09%	15.15%	6.06%	3.03%	—	48.48%
2	3.03%	9.09%	3.03%	—	—	—	15.15%
3	9.09%	9.09%	3.03%	—	—	—	21.21%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	30.30%	33.33%	27.27%	6.06%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.18	+0.24
SD	1.00	1.04	1.60
CV	0.70	0.88	—
Max	3	4	+3
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.36	+0.06
SD	1.30	1.41	2.08
CV	0.91	1.03	—
Max	4	5	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	9.09%	6.06%	—	—	—	27.27%
1	9.09%	15.15%	12.12%	3.03%	—	—	39.39%
2	9.09%	12.12%	—	—	—	—	21.21%
3	6.06%	3.03%	—	3.03%	—	—	12.12%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	36.36%	39.39%	18.18%	6.06%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.18	0.94	+0.24
SD	0.98	0.90	1.35
CV	0.83	0.96	—
Max	3	3	+3
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	6.06%	6.06%	—	—	18.18%
1	12.12%	6.06%	6.06%	—	—	—	24.24%
2	9.09%	18.18%	6.06%	3.03%	—	—	36.36%
3	9.09%	3.03%	—	—	—	—	12.12%
4	—	—	—	3.03%	—	—	3.03%
5+	3.03%	—	3.03%	—	—	—	6.06%
Total	36.36%	30.30%	21.21%	12.12%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.76	1.09	+0.67
SD	1.32	1.04	1.80
CV	0.75	0.95	—
Max	5	3	+5
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	6.06%	6.06%	3.03%	—	—	21.21%
1	9.09%	9.09%	6.06%	3.03%	—	—	27.27%
2	3.03%	9.09%	3.03%	6.06%	—	3.03%	24.24%
3	—	6.06%	—	3.03%	—	—	9.09%
4	—	12.12%	—	—	—	—	12.12%
5+	—	—	6.06%	—	—	—	6.06%
Total	18.18%	42.42%	21.21%	15.15%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.82	1.45	+0.36
SD	1.51	1.15	1.80
CV	0.83	0.79	—
Max	5	5	+3
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	15.15%	6.06%	6.06%	—	33.33%
1	3.03%	9.09%	3.03%	3.03%	6.06%	—	24.24%
2	12.12%	3.03%	3.03%	3.03%	3.03%	3.03%	27.27%
3	—	3.03%	3.03%	3.03%	—	—	9.09%
4	3.03%	3.03%	—	—	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	21.21%	21.21%	24.24%	15.15%	15.15%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.30	1.91	-0.61
SD	1.21	1.47	2.12
CV	0.93	0.77	—
Max	4	5	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	3.03%	9.09%	6.06%	—	—	24.24%
1	3.03%	3.03%	6.06%	9.09%	—	—	21.21%
2	9.09%	9.09%	—	3.03%	—	—	21.21%
3	12.12%	9.09%	3.03%	—	—	—	24.24%
4	3.03%	3.03%	—	—	—	—	6.06%
5+	—	—	3.03%	—	—	—	3.03%
Total	33.33%	27.27%	21.21%	18.18%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.76	1.24	+0.52
SD	1.39	1.12	2.06
CV	0.79	0.90	—
Max	5	3	+4
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	3.03%	12.12%	18.18%	3.03%	—	36.36%
1	3.03%	6.06%	12.12%	12.12%	9.09%	—	42.42%
2	3.03%	6.06%	3.03%	9.09%	—	—	21.21%
3	—	—	—	—	—	—	—
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	6.06%	15.15%	27.27%	39.39%	12.12%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.85	2.36	-1.52
SD	0.76	1.08	1.46
CV	0.89	0.46	—
Max	2	4	+2
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	6.06%	—	3.03%	—	3.03%	15.15%
1	3.03%	9.09%	6.06%	3.03%	—	—	21.21%
2	18.18%	9.09%	3.03%	—	—	—	30.30%
3	3.03%	6.06%	6.06%	3.03%	—	—	18.18%
4	3.03%	3.03%	3.03%	—	—	—	9.09%
5+	3.03%	3.03%	—	—	—	—	6.06%
Total	33.33%	36.36%	18.18%	9.09%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.03	1.15	+0.88
SD	1.40	1.18	2.04
CV	0.69	1.02	—
Max	5	5	+5
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	15.15%	12.12%	—	—	—	—	27.27%
1	3.03%	9.09%	12.12%	6.06%	—	—	30.30%
2	6.06%	—	9.09%	—	—	—	15.15%
3	6.06%	6.06%	9.09%	—	—	—	21.21%
4	3.03%	—	—	3.03%	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	33.33%	27.27%	30.30%	9.09%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.48	1.15	+0.33
SD	1.28	1.00	1.45
CV	0.86	0.87	—
Max	4	3	+4
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	12.12%	9.09%	12.12%	3.03%	—	39.39%
1	6.06%	3.03%	6.06%	6.06%	6.06%	—	27.27%
2	3.03%	18.18%	—	—	—	—	21.21%
3	—	6.06%	3.03%	—	3.03%	—	12.12%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	12.12%	39.39%	18.18%	18.18%	12.12%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.06	1.79	-0.73
SD	1.06	1.24	1.77
CV	1.00	0.70	—
Max	3	4	+2
Min	0	0	-4

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	1498	66	52.00	+14.00	97.0%	36	44	47	51	56	64	68
Hobro	1436	65	47.94	+17.06	99.0%	26	33	43	47	53	61	66
Horsens	1431	52	54.43	-2.43	37.0%	37	44	49	55	58	65	68
Lyngby	1431	57	49.02	+7.98	89.0%	30	36	45	49	54	59	62
Vejle BK	1424	47	50.91	-3.91	27.0%	35	39	46	51	55	62	65
Bronshoj	1410	53	42.59	+10.41	93.0%	24	31	38	42	49	55	64
HB Koge	1391	49	45.90	+3.10	75.0%	27	35	41	46	49	58	62
Fredericia	1380	43	45.35	-2.35	36.0%	28	34	41	46	49	56	59
AB Gladsaxe	1326	36	35.14	+0.86	55.0%	14	23	31	36	39	47	48
Hvidovre	1303	36	39.91	-3.91	29.0%	23	29	35	40	44	49	54
Vendsyssel	1285	38	36.57	+1.43	66.0%	19	25	32	36	41	49	53
Marienlyst	1235	15	35.84	-20.84	0.0%	19	23	30	35	40	48	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

+12.63%

Slight Edge

46.97%18.69%34.34%

Elo Value

Home Edge

147 Elo

0.007 goals per Elo point

044.10400

Scoring Tilt

Expected

+0.24 goals

Neutral

-2+0.30+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

4.9

Wide Open

123410

Champion Preseason Odds

21%

Silkeborg, 2nd of 12

LongshotFavorite

Title Margin

Expected

0.03/gm

Photo Finish

00.130.5/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 5.51 * Some Luck: 5.51 to 8.26 * Lucky: 8.26 to 11.02 * Wild Swing: 11.02 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 1.68 * Close: 1.68 to 2.52 * Off: 2.52 to 3.36 * Way Off: 3.36 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 1.04 * A Surprise: 1.04 to 1.66 * Several Surprises: 1.66 to 2.29 * Many Surprises: 2.29 and up.

Luck Spread

Expected

9.62 points

Lucky

06.8917

Average Finish Error

Expected

2.00

02.105

Biggest Overachiever

Expected 95.83%

99.00%

Hobro

50100

Biggest Underachiever

Expected 4.17%

0.00%

Marienlyst

050

Season Outliers

Expected

3 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

1 of 2

As Expected

01.02

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

0.16

Even

00.130.20.5

Noll-Scully

Elo SD: 76.11

1.81

Strong Separation

0.751.51.82.153

Interquartile Edge

65%

Slight Edge

50%63.5%74.5%100%

Best vs. Worst

Baseline

82%

Even

50%82%100%

Close Games

Expected

55%

Some Drama

0%57%100%

Blowouts

Expected

21%

Frequent

0%19%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

0.63

Hard to Predict

00.642

Matchup Imbalance

0.23

Very Even

00.340.420.5

Strangeness

Expected

1.82

Chaotic

01.002

Repeatability

0.20

Weak Carryover

00.380.570.71

Upset Rate

Expected

32%

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 0.11 * Near Noise Ceiling: 0.11 to 0.17 * Above Noise: 0.17 to 0.22 * Well Above Noise: 0.22 and up.

Probability calibration

0.03

Miscalibrated

0.010.050.10.51

Calibration slope

Ideal

0.96

Calibrated

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.078

Well Within Noise

00.1100.25

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%	12.00%	18.00%	16.00%	14.00%	8.00%	5.00%	3.00%	2.00%	1.00%	—	—
Hobro	13.00%	10.00%	11.00%	11.00%	10.00%	10.00%	11.00%	6.00%	7.00%	5.00%	3.00%	3.00%
Lyngby	7.00%	12.00%	16.00%	11.00%	20.00%	11.00%	9.00%	7.00%	1.00%	3.00%	1.00%	2.00%
Bronshoj	3.00%	6.00%	6.00%	6.00%	8.00%	10.00%	11.00%	12.00%	9.00%	11.00%	10.00%	8.00%
Horsens	33.00%	17.00%	18.00%	12.00%	6.00%	5.00%	5.00%	2.00%	—	—	2.00%	—
HB Koge	5.00%	5.00%	9.00%	12.00%	10.00%	12.00%	11.00%	17.00%	8.00%	6.00%	4.00%	1.00%
Vejle BK	16.00%	21.00%	13.00%	12.00%	9.00%	10.00%	7.00%	3.00%	6.00%	3.00%	—	—
Fredericia	1.00%	13.00%	2.00%	10.00%	13.00%	10.00%	20.00%	9.00%	10.00%	6.00%	4.00%	2.00%
Vendsyssel	—	1.00%	3.00%	2.00%	2.00%	7.00%	3.00%	7.00%	10.00%	19.00%	23.00%	23.00%
AB Gladsaxe	—	—	1.00%	2.00%	2.00%	2.00%	4.00%	8.00%	17.00%	15.00%	23.00%	26.00%
Hvidovre	—	2.00%	3.00%	3.00%	5.00%	9.00%	11.00%	17.00%	18.00%	14.00%	6.00%	12.00%
Marienlyst	1.00%	1.00%	—	3.00%	1.00%	6.00%	3.00%	9.00%	12.00%	17.00%	24.00%	23.00%

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
Horsens	50.00%	48.00%	2.00%
Vejle BK	37.00%	63.00%	—
Silkeborg	33.00%	67.00%	—
Hobro	23.00%	71.00%	6.00%
Lyngby	19.00%	78.00%	3.00%
Fredericia	14.00%	80.00%	6.00%
HB Koge	10.00%	85.00%	5.00%
Bronshoj	9.00%	73.00%	18.00%
Hvidovre	2.00%	80.00%	18.00%
Marienlyst	2.00%	51.00%	47.00%
Vendsyssel	1.00%	53.00%	46.00%
AB Gladsaxe	—	51.00%	49.00%

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
2013-07-25	Lyngby	W 2-0	41.7	1358	1386	33.47%	31.06%	35.47%	+0.11	+10.6	3
2013-07-25	@ HB Koge	L 0-2	41.7	1386	1358	35.47%	31.06%	33.47%	-0.11	-10.6	0
2013-07-28	AB Gladsaxe	W 4-1	40.6	1434	1346	49.61%	28.52%	21.87%	+0.90	+8.9	3
2013-07-28	@ Horsens	L 1-4	40.6	1346	1434	21.87%	28.52%	49.61%	-0.90	-8.9	0
2013-07-28	Bronshoj	W 4-1	42.2	1415	1366	44.27%	30.00%	25.72%	+0.63	+10.2	3
2013-07-28	@ Silkeborg	L 1-4	42.2	1366	1415	25.72%	30.00%	44.27%	-0.63	-10.2	0
2013-07-28	Hobro	L 1-2	51.8	1361	1348	39.21%	30.82%	29.97%	+0.38	-5.7	0
2013-07-28	@ Hvidovre	W 2-1	51.8	1348	1361	29.97%	30.82%	39.21%	-0.38	+5.7	3
2013-07-28	Marienlyst	W 3-0	40.6	1367	1412	31.23%	30.95%	37.82%	+0.00	+16.2	3
2013-07-28	@ Fredericia	L 0-3	40.6	1412	1367	37.82%	30.95%	31.23%	+0.00	-16.2	0
2013-07-28	Vendsyssel	L 1-3	50.1	1399	1358	43.17%	30.23%	26.60%	+0.57	-10.6	0
2013-07-28	@ Vejle BK	W 3-1	50.1	1358	1399	26.60%	30.23%	43.17%	-0.57	+10.6	3
2013-08-01	HB Koge	D 1-1	54.8	1396	1369	41.30%	30.55%	28.15%	+0.48	-0.4	1
2013-08-01	@ Marienlyst	D 1-1	54.8	1369	1396	28.15%	30.55%	41.30%	-0.48	+0.4	4
2013-08-01	Lyngby	W 2-0	40.3	1388	1376	39.26%	30.82%	29.92%	+0.38	+9.4	3
2013-08-01	@ Vejle BK	L 0-2	40.3	1376	1388	29.92%	30.82%	39.26%	-0.38	-9.4	0
2013-08-02	Fredericia	D 1-1	54.2	1355	1383	33.39%	31.06%	35.55%	+0.11	+0.1	1
2013-08-02	@ Hvidovre	D 1-1	54.2	1383	1355	35.55%	31.06%	33.39%	-0.11	-0.1	4
2013-08-03	AB Gladsaxe	L 1-2	51.9	1356	1337	40.19%	30.71%	29.10%	+0.43	-5.8	0
2013-08-03	@ Bronshoj	W 2-1	51.9	1337	1356	29.10%	30.71%	40.19%	-0.43	+5.8	3
2013-08-04	Horsens	L 0-1	44.4	1369	1443	27.60%	30.45%	41.95%	-0.20	-4.7	3
2013-08-04	@ Vendsyssel	W 1-0	44.4	1443	1369	41.95%	30.45%	27.60%	+0.20	+4.7	6
2013-08-04	Silkeborg	W 5-0	42.0	1354	1425	27.95%	30.52%	41.53%	-0.18	+27.8	6
2013-08-04	@ Hobro	L 0-5	42.0	1425	1354	41.53%	30.52%	27.95%	+0.18	-27.9	3
2013-08-08	Silkeborg	W 1-0	44.5	1447	1397	44.55%	29.94%	25.51%	+0.64	+4.4	9
2013-08-08	@ Horsens	L 0-1	44.5	1397	1447	25.51%	29.94%	44.55%	-0.64	-4.4	3
2013-08-09	Hobro	L 1-2	53.0	1395	1382	39.37%	30.80%	29.82%	+0.39	-5.7	1
2013-08-09	@ Marienlyst	W 2-1	53.0	1382	1395	29.82%	30.80%	39.37%	-0.39	+5.7	9
2013-08-10	Hvidovre	L 1-3	47.6	1350	1355	36.82%	31.01%	32.17%	+0.27	-9.5	0
2013-08-10	@ Bronshoj	W 3-1	47.6	1355	1350	32.17%	31.01%	36.82%	-0.27	+9.5	4
2013-08-11	Fredericia	L 1-3	47.9	1369	1383	35.44%	31.06%	33.50%	+0.20	-9.2	4
2013-08-11	@ HB Koge	W 3-1	47.9	1383	1369	33.50%	31.06%	35.44%	-0.20	+9.2	7
2013-08-11	Vejle BK	L 1-3	46.0	1343	1397	29.92%	30.82%	39.27%	-0.07	-8.2	3
2013-08-11	@ AB Gladsaxe	W 3-1	46.0	1397	1343	39.27%	30.82%	29.92%	+0.07	+8.2	6
2013-08-11	Vendsyssel	W 3-1	46.3	1366	1364	37.76%	30.95%	31.29%	+0.31	+8.4	3
2013-08-11	@ Lyngby	L 1-3	46.3	1364	1366	31.29%	30.95%	37.76%	-0.31	-8.4	3
2013-08-15	Lyngby	W 3-2	55.2	1393	1375	40.05%	30.73%	29.22%	+0.42	+4.4	6
2013-08-15	@ Silkeborg	L 2-3	55.2	1375	1393	29.22%	30.73%	40.05%	-0.42	-4.4	3
2013-08-17	Bronshoj	W 1-0	42.2	1388	1341	44.08%	30.04%	25.87%	+0.62	+4.5	12
2013-08-17	@ Hobro	L 0-1	42.2	1341	1388	25.87%	30.04%	44.08%	-0.62	-4.5	0
2013-08-18	AB Gladsaxe	W 4-0	35.8	1364	1335	41.69%	30.49%	27.82%	+0.50	+16.9	7
2013-08-18	@ Hvidovre	L 0-4	35.8	1335	1364	27.82%	30.49%	41.69%	-0.50	-16.9	3
2013-08-18	HB Koge	D 0-0	50.5	1406	1360	43.91%	30.08%	26.01%	+0.61	-0.6	7
2013-08-18	@ Vejle BK	D 0-0	50.5	1360	1406	26.01%	30.08%	43.91%	-0.61	+0.6	5
2013-08-18	Horsens	L 2-5	47.8	1393	1452	29.36%	30.74%	39.90%	-0.10	-9.9	7
2013-08-18	@ Fredericia	W 5-2	47.8	1452	1393	39.90%	30.74%	29.36%	+0.10	+9.9	12
2013-08-18	Marienlyst	W 2-1	51.5	1356	1390	32.68%	31.03%	36.29%	+0.07	+5.4	6
2013-08-18	@ Vendsyssel	L 1-2	51.5	1390	1356	36.29%	31.03%	32.68%	-0.07	-5.4	1
2013-08-22	Vejle BK	D 1-1	55.1	1383	1405	34.30%	31.07%	34.63%	+0.15	+0.0	8
2013-08-22	@ Fredericia	D 1-1	55.1	1405	1383	34.63%	31.07%	34.30%	-0.15	-0.0	8
2013-08-23	Vendsyssel	W 2-1	49.8	1361	1361	37.40%	30.98%	31.63%	+0.29	+4.9	8
2013-08-23	@ HB Koge	L 1-2	49.8	1361	1361	31.63%	30.98%	37.40%	-0.29	-4.9	6
2013-08-25	Bronshoj	L 1-3	49.1	1370	1336	42.27%	30.40%	27.34%	+0.53	-10.4	3
2013-08-25	@ Lyngby	W 3-1	49.1	1336	1370	27.34%	30.40%	42.27%	-0.53	+10.5	3
2013-08-25	Hobro	L 2-5	53.0	1462	1392	47.15%	29.28%	23.57%	+0.77	-13.9	12
2013-08-25	@ Horsens	W 5-2	53.0	1392	1462	23.57%	29.28%	47.15%	-0.77	+13.9	15
2013-08-25	Hvidovre	W 4-2	50.7	1397	1381	39.73%	30.76%	29.51%	+0.41	+7.2	9
2013-08-25	@ Silkeborg	L 2-4	50.7	1381	1397	29.51%	30.76%	39.73%	-0.41	-7.2	7
2013-08-25	Marienlyst	W 2-0	42.6	1318	1384	28.47%	30.61%	40.92%	-0.15	+11.8	6
2013-08-25	@ AB Gladsaxe	L 0-2	42.6	1384	1318	40.92%	30.61%	28.47%	+0.15	-11.8	1
2013-08-31	Fredericia	L 1-3	46.6	1347	1383	32.37%	31.02%	36.61%	+0.06	-8.6	3
2013-08-31	@ Bronshoj	W 3-1	46.6	1383	1347	36.61%	31.02%	32.37%	-0.06	+8.7	11
2013-08-31	Vejle BK	W 2-1	52.1	1372	1405	32.83%	31.04%	36.13%	+0.08	+5.4	4
2013-08-31	@ Marienlyst	L 1-2	52.1	1405	1372	36.13%	31.04%	32.83%	-0.08	-5.4	8
2013-09-01	Hobro	W 2-0	42.9	1360	1406	30.99%	30.93%	38.08%	-0.02	+11.2	6
2013-09-01	@ Lyngby	L 0-2	42.9	1406	1360	38.08%	30.93%	30.99%	+0.02	-11.2	15
2013-09-01	Horsens	W 1-0	49.1	1365	1448	26.62%	30.23%	43.14%	-0.26	+6.5	11
2013-09-01	@ HB Koge	L 0-1	49.1	1448	1365	43.14%	30.23%	26.62%	+0.26	-6.5	12
2013-09-01	Hvidovre	D 1-1	54.1	1356	1374	34.94%	31.07%	33.99%	+0.18	-0.0	7
2013-09-01	@ Vendsyssel	D 1-1	54.1	1374	1356	33.99%	31.07%	34.94%	-0.18	+0.0	8
2013-09-01	Silkeborg	D 1-1	54.3	1330	1404	27.48%	30.43%	42.09%	-0.21	+0.4	7
2013-09-01	@ AB Gladsaxe	D 1-1	54.3	1404	1330	42.09%	30.43%	27.48%	+0.21	-0.4	10
2013-09-07	Bronshoj	L 1-2	52.9	1378	1338	43.07%	30.25%	26.68%	+0.57	-6.1	4
2013-09-07	@ Marienlyst	W 2-1	52.9	1338	1378	26.68%	30.25%	43.07%	-0.57	+6.1	6
2013-09-08	AB Gladsaxe	W 1-0	42.5	1356	1330	41.21%	30.57%	28.22%	+0.48	+4.8	10
2013-09-08	@ Vendsyssel	L 0-1	42.5	1330	1356	28.22%	30.57%	41.21%	-0.48	-4.8	7
2013-09-08	Horsens	L 1-4	43.9	1374	1441	28.38%	30.59%	41.03%	-0.16	-11.1	8
2013-09-08	@ Hvidovre	W 4-1	43.9	1441	1374	41.03%	30.59%	28.38%	+0.16	+11.1	15
2013-09-08	Lyngby	L 2-5	49.3	1391	1371	40.40%	30.68%	28.92%	+0.44	-12.4	11
2013-09-08	@ Fredericia	W 5-2	49.3	1371	1391	28.92%	30.68%	40.40%	-0.44	+12.4	9
2013-09-09	HB Koge	W 2-1	49.5	1395	1372	40.74%	30.63%	28.62%	+0.46	+4.6	18
2013-09-09	@ Hobro	L 1-2	49.5	1372	1395	28.62%	30.63%	40.74%	-0.46	-4.5	11
2013-09-12	Vejle BK	L 2-3	61.6	1452	1400	44.87%	29.87%	25.26%	+0.66	-6.0	15
2013-09-12	@ Horsens	W 3-2	61.6	1400	1452	25.26%	29.87%	44.87%	-0.66	+6.0	11
2013-09-13	Hvidovre	W 2-0	40.1	1367	1363	38.11%	30.92%	30.96%	+0.33	+9.7	14
2013-09-13	@ HB Koge	L 0-2	40.1	1363	1367	30.96%	30.92%	38.11%	-0.33	-9.7	8
2013-09-14	Vendsyssel	W 3-0	38.2	1344	1361	35.08%	31.07%	33.85%	+0.19	+15.0	9
2013-09-14	@ Bronshoj	L 0-3	38.2	1361	1344	33.85%	31.07%	35.08%	-0.19	-15.0	10
2013-09-15	Fredericia	W 2-0	40.2	1404	1379	41.00%	30.60%	28.40%	+0.47	+9.1	13
2013-09-15	@ Silkeborg	L 0-2	40.2	1379	1404	28.40%	30.60%	41.00%	-0.47	-9.1	11
2013-09-15	Hobro	D 2-2	60.3	1325	1399	27.54%	30.44%	42.02%	-0.20	+0.3	8
2013-09-15	@ AB Gladsaxe	D 2-2	60.3	1399	1325	42.02%	30.44%	27.54%	+0.20	-0.3	19
2013-09-15	Marienlyst	W 4-0	37.4	1383	1372	39.15%	30.83%	30.02%	+0.38	+17.9	12
2013-09-15	@ Lyngby	L 0-4	37.4	1372	1383	30.02%	30.83%	39.15%	-0.38	-17.9	4
2013-09-19	Silkeborg	L 1-2	49.8	1354	1413	29.35%	30.74%	39.91%	-0.10	-4.7	4
2013-09-19	@ Marienlyst	W 2-1	49.8	1413	1354	39.91%	30.74%	29.35%	+0.10	+4.6	16
2013-09-19	Vejle BK	W 2-1	51.6	1399	1406	36.56%	31.02%	32.42%	+0.26	+5.0	22
2013-09-19	@ Hobro	L 1-2	51.6	1406	1399	32.42%	31.02%	36.56%	-0.26	-5.0	11
2013-09-20	HB Koge	W 2-1	51.6	1326	1377	30.32%	30.86%	38.82%	-0.05	+5.7	11
2013-09-20	@ AB Gladsaxe	L 1-2	51.6	1377	1326	38.82%	30.86%	30.32%	+0.05	-5.7	14
2013-09-21	Horsens	L 1-2	49.4	1359	1446	26.09%	30.10%	43.81%	-0.29	-4.2	9
2013-09-21	@ Bronshoj	W 2-1	49.4	1446	1359	43.81%	30.10%	26.09%	+0.29	+4.2	18
2013-09-22	Fredericia	W 2-1	50.7	1346	1370	34.06%	31.07%	34.87%	+0.14	+5.2	13
2013-09-22	@ Vendsyssel	L 1-2	50.7	1370	1346	34.87%	31.07%	34.06%	-0.14	-5.3	11
2013-09-22	Hvidovre	W 2-0	38.7	1401	1353	44.21%	30.02%	25.77%	+0.62	+8.4	15
2013-09-22	@ Lyngby	L 0-2	38.7	1353	1401	25.77%	30.02%	44.21%	-0.62	-8.4	8
2013-09-28	Vendsyssel	W 2-1	48.1	1404	1351	44.89%	29.86%	25.25%	+0.66	+4.1	25
2013-09-28	@ Hobro	L 1-2	48.1	1351	1404	25.25%	29.86%	44.89%	-0.66	-4.1	13
2013-09-29	AB Gladsaxe	D 1-1	53.8	1365	1331	42.23%	30.40%	27.37%	+0.53	-0.4	12
2013-09-29	@ Fredericia	D 1-1	53.8	1331	1365	27.37%	30.40%	42.23%	-0.53	+0.5	12
2013-09-29	Bronshoj	L 0-1	48.1	1401	1355	43.90%	30.08%	26.01%	+0.61	-6.6	11
2013-09-29	@ Vejle BK	W 1-0	48.1	1355	1401	26.01%	30.08%	43.90%	-0.61	+6.6	12
2013-09-29	HB Koge	L 1-2	54.4	1418	1371	43.97%	30.07%	25.96%	+0.61	-6.2	16
2013-09-29	@ Silkeborg	W 2-1	54.4	1371	1418	25.96%	30.07%	43.97%	-0.61	+6.2	17
2013-09-29	Lyngby	W 3-1	47.5	1451	1410	43.26%	30.21%	26.53%	+0.58	+7.4	21
2013-09-29	@ Horsens	L 1-3	47.5	1410	1451	26.53%	30.21%	43.26%	-0.58	-7.4	15
2013-09-29	Marienlyst	W 3-2	55.0	1345	1349	36.90%	31.00%	32.09%	+0.27	+4.7	11
2013-09-29	@ Hvidovre	L 2-3	55.0	1349	1345	32.09%	31.00%	36.90%	-0.27	-4.7	4
2013-10-02	Silkeborg	W 3-0	40.1	1394	1411	35.01%	31.07%	33.92%	+0.18	+15.0	14
2013-10-02	@ Vejle BK	L 0-3	40.1	1411	1394	33.92%	31.07%	35.01%	-0.18	-15.0	16
2013-10-03	Hobro	W 3-0	40.5	1364	1408	31.31%	30.95%	37.74%	+0.00	+16.1	15
2013-10-03	@ Fredericia	L 0-3	40.5	1408	1364	37.74%	30.95%	31.31%	+0.00	-16.1	25
2013-10-06	AB Gladsaxe	W 2-1	47.0	1402	1332	47.30%	29.24%	23.46%	+0.78	+3.9	18
2013-10-06	@ Lyngby	L 1-2	47.0	1332	1402	23.46%	29.24%	47.30%	-0.78	-3.9	12
2013-10-06	Bronshoj	D 1-1	54.3	1378	1362	39.77%	30.76%	29.47%	+0.41	-0.3	18
2013-10-06	@ HB Koge	D 1-1	54.3	1362	1378	29.47%	30.76%	39.77%	-0.41	+0.3	13
2013-10-06	Hvidovre	W 2-0	38.3	1409	1350	45.78%	29.65%	24.57%	+0.70	+8.0	17
2013-10-06	@ Vejle BK	L 0-2	38.3	1350	1409	24.57%	29.65%	45.78%	-0.70	-8.1	11
2013-10-06	Marienlyst	D 2-2	62.7	1458	1344	52.97%	27.29%	19.74%	+1.07	-0.8	22
2013-10-06	@ Horsens	D 2-2	62.7	1344	1458	19.74%	27.29%	52.97%	-1.07	+0.8	5
2013-10-06	Vendsyssel	L 1-2	53.6	1396	1347	44.38%	29.98%	25.64%	+0.63	-6.3	16
2013-10-06	@ Silkeborg	W 2-1	53.6	1347	1396	25.64%	29.98%	44.38%	-0.63	+6.3	16
2013-10-11	Vejle BK	L 0-4	36.6	1342	1417	27.40%	30.41%	42.19%	-0.21	-16.7	11
2013-10-11	@ Hvidovre	W 4-0	36.6	1417	1342	42.19%	30.41%	27.40%	+0.21	+16.7	20
2013-10-12	Lyngby	L 1-2	50.4	1362	1406	31.27%	30.95%	37.78%	+0.00	-4.9	13
2013-10-12	@ Bronshoj	W 2-1	50.4	1406	1362	37.78%	30.95%	31.27%	+0.00	+4.9	21
2013-10-13	Fredericia	L 0-4	38.2	1353	1380	33.63%	31.06%	35.31%	+0.12	-19.5	16
2013-10-13	@ Vendsyssel	W 4-0	38.2	1380	1353	35.31%	31.06%	33.63%	-0.12	+19.5	18
2013-10-13	Horsens	D 3-3	66.1	1328	1457	21.92%	28.55%	49.53%	-0.58	+0.5	13
2013-10-13	@ AB Gladsaxe	D 3-3	66.1	1457	1328	49.53%	28.55%	21.92%	+0.58	-0.5	23
2013-10-14	Hobro	L 0-2	42.1	1377	1392	35.37%	31.06%	33.57%	+0.20	-10.6	18
2013-10-14	@ HB Koge	W 2-0	42.1	1392	1377	33.57%	31.06%	35.37%	-0.20	+10.6	28
2013-10-17	HB Koge	L 1-3	53.0	1457	1367	49.89%	28.43%	21.68%	+0.91	-11.8	23
2013-10-17	@ Horsens	W 3-1	53.0	1367	1457	21.68%	28.43%	49.89%	-0.91	+11.8	21
2013-10-18	Vendsyssel	W 4-3	55.4	1403	1334	47.05%	29.31%	23.64%	+0.77	+3.6	31
2013-10-18	@ Hobro	L 3-4	55.4	1334	1403	23.64%	29.31%	47.05%	-0.77	-3.6	16
2013-10-20	AB Gladsaxe	W 5-0	35.5	1390	1328	46.11%	29.56%	24.32%	+0.72	+18.7	19
2013-10-20	@ Silkeborg	L 0-5	35.5	1328	1390	24.32%	29.56%	46.11%	-0.72	-18.7	13
2013-10-20	Bronshoj	D 0-0	51.4	1434	1357	48.14%	28.99%	22.87%	+0.82	-0.9	21
2013-10-20	@ Vejle BK	D 0-0	51.4	1357	1434	22.87%	28.99%	48.14%	-0.82	+0.9	14
2013-10-20	Hvidovre	W 4-1	40.1	1400	1325	47.89%	29.07%	23.04%	+0.81	+9.3	21
2013-10-20	@ Fredericia	L 1-4	40.1	1325	1400	23.04%	29.07%	47.89%	-0.81	-9.3	11
2013-10-20	Marienlyst	W 3-1	44.1	1411	1345	46.65%	29.42%	23.93%	+0.75	+6.8	24
2013-10-20	@ Lyngby	L 1-3	44.1	1345	1411	23.93%	29.42%	46.65%	-0.75	-6.8	5
2013-10-24	Hobro	D 1-1	54.3	1316	1406	25.70%	29.99%	44.31%	-0.32	+0.6	12
2013-10-24	@ Hvidovre	D 1-1	54.3	1406	1316	44.31%	29.99%	25.70%	+0.32	-0.6	32
2013-10-26	Fredericia	W 2-1	52.6	1358	1409	30.34%	30.86%	38.80%	-0.05	+5.7	17
2013-10-26	@ Bronshoj	L 1-2	52.6	1409	1358	38.80%	30.86%	30.34%	+0.05	-5.7	21
2013-10-26	Vejle BK	L 0-3	36.4	1338	1433	25.29%	29.88%	44.84%	-0.34	-12.0	5
2013-10-26	@ Marienlyst	W 3-0	36.4	1433	1338	44.84%	29.88%	25.29%	+0.34	+12.0	24
2013-10-27	AB Gladsaxe	W 1-0	40.7	1378	1310	47.07%	29.30%	23.62%	+0.77	+4.1	24
2013-10-27	@ HB Koge	L 0-1	40.7	1310	1378	23.62%	29.30%	47.07%	-0.77	-4.1	13
2013-10-27	Horsens	L 1-4	41.1	1330	1445	23.29%	29.17%	47.54%	-0.48	-9.4	16
2013-10-27	@ Vendsyssel	W 4-1	41.1	1445	1330	47.54%	29.17%	23.29%	+0.48	+9.4	26
2013-10-27	Silkeborg	D 0-0	51.6	1418	1409	38.77%	30.87%	30.37%	+0.36	-0.3	25
2013-10-27	@ Lyngby	D 0-0	51.6	1409	1418	30.37%	30.87%	38.77%	-0.36	+0.3	20
2013-11-02	Bronshoj	W 2-1	48.8	1406	1364	43.43%	30.18%	26.39%	+0.59	+4.3	35
2013-11-02	@ Hobro	L 1-2	48.8	1364	1406	26.39%	30.18%	43.43%	-0.59	-4.3	17
2013-11-03	HB Koge	D 1-1	55.4	1409	1383	41.23%	30.56%	28.21%	+0.48	-0.4	21
2013-11-03	@ Silkeborg	D 1-1	55.4	1383	1409	28.21%	30.56%	41.23%	-0.48	+0.4	25
2013-11-03	Hvidovre	L 0-2	46.8	1454	1316	56.07%	25.96%	17.97%	+1.24	-14.9	26
2013-11-03	@ Horsens	W 2-0	46.8	1316	1454	17.97%	25.96%	56.07%	-1.24	+14.9	15
2013-11-03	Lyngby	D 0-0	52.7	1445	1417	41.37%	30.54%	28.09%	+0.49	-0.5	25
2013-11-03	@ Vejle BK	D 0-0	52.7	1417	1445	28.09%	30.54%	41.37%	-0.49	+0.5	26
2013-11-03	Marienlyst	W 4-1	40.1	1404	1326	48.19%	28.98%	22.83%	+0.82	+9.2	24
2013-11-03	@ Fredericia	L 1-4	40.1	1326	1404	22.83%	28.98%	48.19%	-0.82	-9.2	5
2013-11-03	Vendsyssel	L 0-2	40.2	1306	1321	35.27%	31.06%	33.67%	+0.19	-10.6	13
2013-11-03	@ AB Gladsaxe	W 2-0	40.2	1321	1306	33.67%	31.06%	35.27%	-0.19	+10.6	19
2013-11-07	Silkeborg	L 1-2	55.6	1444	1409	42.54%	30.35%	27.11%	+0.54	-6.1	25
2013-11-07	@ Vejle BK	W 2-1	55.6	1409	1444	27.11%	30.35%	42.54%	-0.54	+6.1	24
2013-11-08	AB Gladsaxe	D 0-0	48.6	1331	1295	42.59%	30.34%	27.07%	+0.54	-0.5	16
2013-11-08	@ Hvidovre	D 0-0	48.6	1295	1331	27.07%	30.34%	42.59%	-0.54	+0.5	14
2013-11-09	Horsens	L 1-2	49.5	1359	1439	26.86%	30.29%	42.84%	-0.24	-4.3	17
2013-11-09	@ Bronshoj	W 2-1	49.5	1439	1359	42.84%	30.29%	26.86%	+0.24	+4.3	29
2013-11-10	Fredericia	W 1-0	46.0	1418	1413	38.22%	30.92%	30.87%	+0.33	+5.1	29
2013-11-10	@ Lyngby	L 0-1	46.0	1413	1418	30.87%	30.92%	38.22%	-0.33	-5.1	24
2013-11-10	HB Koge	W 2-1	51.8	1332	1383	30.33%	30.86%	38.81%	-0.05	+5.7	22
2013-11-10	@ Vendsyssel	L 1-2	51.8	1383	1332	38.81%	30.86%	30.33%	+0.05	-5.7	25
2013-11-14	Lyngby	W 3-0	40.5	1410	1423	35.63%	31.06%	33.32%	+0.21	+14.8	38
2013-11-14	@ Hobro	L 0-3	40.5	1423	1410	33.32%	31.06%	35.63%	-0.21	-14.8	29
2013-11-17	Bronshoj	D 1-1	53.2	1295	1355	29.31%	30.74%	39.95%	-0.10	+0.3	15
2013-11-17	@ AB Gladsaxe	D 1-1	53.2	1355	1295	39.95%	30.74%	29.31%	+0.10	-0.3	18
2013-11-17	Hvidovre	W 3-0	35.6	1377	1331	44.07%	30.05%	25.89%	+0.62	+12.2	28
2013-11-17	@ HB Koge	L 0-3	35.6	1331	1377	25.89%	30.05%	44.07%	-0.62	-12.2	16
2013-11-17	Marienlyst	W 4-1	38.7	1444	1317	54.62%	26.60%	18.78%	+1.16	+7.7	32
2013-11-17	@ Horsens	L 1-4	38.7	1317	1444	18.78%	26.60%	54.62%	-1.16	-7.6	5
2013-11-17	Vendsyssel	W 2-0	37.4	1415	1337	48.22%	28.97%	22.81%	+0.83	+7.5	27
2013-11-17	@ Silkeborg	L 0-2	37.4	1337	1415	22.81%	28.97%	48.22%	-0.83	-7.5	22
2013-11-18	Vejle BK	L 1-3	49.3	1408	1438	33.10%	31.05%	35.85%	+0.09	-8.8	24
2013-11-18	@ Fredericia	W 3-1	49.3	1438	1408	35.85%	31.05%	33.10%	-0.09	+8.8	28
2013-11-21	Horsens	L 1-2	52.7	1408	1451	31.41%	30.96%	37.63%	+0.01	-4.9	29
2013-11-21	@ Lyngby	W 2-1	52.7	1451	1408	37.63%	30.96%	31.41%	-0.01	+4.9	35
2013-11-22	Vendsyssel	W 2-0	39.8	1318	1330	35.85%	31.05%	33.10%	+0.22	+10.1	19
2013-11-22	@ Hvidovre	L 0-2	39.8	1330	1318	33.10%	31.05%	35.85%	-0.22	-10.1	22
2013-11-23	AB Gladsaxe	W 2-1	47.9	1309	1296	39.44%	30.80%	29.77%	+0.39	+4.7	8
2013-11-23	@ Marienlyst	L 1-2	47.9	1296	1309	29.77%	30.80%	39.44%	-0.39	-4.7	15
2013-11-23	HB Koge	W 1-0	45.9	1355	1390	32.52%	31.03%	36.46%	+0.06	+5.8	21
2013-11-23	@ Bronshoj	L 0-1	45.9	1390	1355	36.46%	31.03%	32.52%	-0.06	-5.8	28
2013-11-23	Hobro	D 2-2	63.5	1447	1425	40.66%	30.65%	28.70%	+0.45	-0.3	29
2013-11-23	@ Vejle BK	D 2-2	63.5	1425	1447	28.70%	30.65%	40.66%	-0.45	+0.3	39
2013-11-24	Silkeborg	L 0-2	42.9	1399	1422	34.14%	31.07%	34.79%	+0.14	-10.4	24
2013-11-24	@ Fredericia	W 2-0	42.9	1422	1399	34.79%	31.07%	34.14%	-0.14	+10.4	30
2013-11-27	Hobro	L 0-1	41.5	1314	1425	23.63%	29.31%	47.06%	-0.45	-4.1	8
2013-11-27	@ Marienlyst	W 1-0	41.5	1425	1314	47.06%	29.31%	23.63%	+0.45	+4.1	42
2013-12-01	Silkeborg	L 1-3	43.2	1310	1433	22.53%	28.84%	48.62%	-0.53	-6.5	8
2013-12-01	@ Marienlyst	W 3-1	43.2	1433	1310	48.62%	28.84%	22.53%	+0.53	+6.5	33
2014-03-20	Fredericia	W 1-0	44.2	1429	1389	43.22%	30.22%	26.56%	+0.58	+4.6	45
2014-03-20	@ Hobro	L 0-1	44.2	1389	1429	26.56%	30.22%	43.22%	-0.58	-4.6	24
2014-03-22	Bronshoj	L 0-3	37.3	1320	1360	31.72%	30.98%	37.29%	+0.02	-14.3	22
2014-03-22	@ Vendsyssel	W 3-0	37.3	1360	1320	37.29%	30.98%	31.72%	-0.02	+14.3	24
2014-03-23	Hvidovre	W 2-0	36.4	1439	1328	52.58%	27.44%	19.98%	+1.05	+6.7	36
2014-03-23	@ Silkeborg	L 0-2	36.4	1328	1439	19.98%	27.44%	52.58%	-1.05	-6.7	19
2014-03-23	Lyngby	L 0-3	34.5	1291	1403	23.50%	29.26%	47.24%	-0.46	-11.2	15
2014-03-23	@ AB Gladsaxe	W 3-0	34.5	1403	1291	47.24%	29.26%	23.50%	+0.46	+11.2	32
2014-03-23	Marienlyst	W 3-0	34.0	1384	1304	48.60%	28.85%	22.55%	+0.84	+10.8	31
2014-03-23	@ HB Koge	L 0-3	34.0	1304	1384	22.55%	28.85%	48.60%	-0.84	-10.8	8
2014-03-23	Vejle BK	D 0-0	53.9	1456	1447	38.82%	30.86%	30.32%	+0.36	-0.3	36
2014-03-23	@ Horsens	D 0-0	53.9	1447	1456	30.32%	30.86%	38.82%	-0.36	+0.3	30
2014-03-27	Silkeborg	L 0-1	48.9	1434	1446	35.78%	31.05%	33.17%	+0.22	-5.7	45
2014-03-27	@ Hobro	W 1-0	48.9	1446	1434	33.17%	31.05%	35.78%	-0.22	+5.7	39
2014-03-29	Hvidovre	W 1-0	41.5	1375	1322	44.90%	29.86%	25.24%	+0.66	+4.4	27
2014-03-29	@ Bronshoj	L 0-1	41.5	1322	1375	25.24%	29.86%	44.90%	-0.66	-4.4	19
2014-03-29	Vendsyssel	L 2-3	55.2	1293	1305	35.69%	31.05%	33.26%	+0.21	-5.1	8
2014-03-29	@ Marienlyst	W 3-2	55.2	1305	1293	33.26%	31.05%	35.69%	-0.21	+5.1	25
2014-03-30	AB Gladsaxe	L 0-1	50.6	1447	1280	59.67%	24.22%	16.11%	+1.44	-8.3	30
2014-03-30	@ Vejle BK	W 1-0	50.6	1280	1447	16.11%	24.22%	59.67%	-1.44	+8.3	18
2014-03-30	HB Koge	L 1-2	53.9	1415	1395	40.32%	30.69%	28.99%	+0.43	-5.8	32
2014-03-30	@ Lyngby	W 2-1	53.9	1395	1415	28.99%	30.69%	40.32%	-0.43	+5.8	34
2014-03-30	Horsens	W 3-0	43.1	1384	1456	27.80%	30.49%	41.71%	-0.19	+17.3	27
2014-03-30	@ Fredericia	L 0-3	43.1	1456	1384	41.71%	30.49%	27.80%	+0.19	-17.3	36
2014-04-03	Hobro	W 2-0	42.9	1439	1428	38.99%	30.84%	30.17%	+0.37	+9.5	39
2014-04-03	@ Horsens	L 0-2	42.9	1428	1439	30.17%	30.84%	38.99%	-0.37	-9.5	45
2014-04-04	Marienlyst	W 2-0	37.7	1317	1288	41.70%	30.49%	27.81%	+0.50	+8.9	22
2014-04-04	@ Hvidovre	L 0-2	37.7	1288	1317	27.81%	30.49%	41.70%	-0.50	-8.9	8
2014-04-06	Bronshoj	L 0-1	50.5	1451	1379	47.54%	29.17%	23.29%	+0.79	-7.0	39
2014-04-06	@ Silkeborg	W 1-0	50.5	1379	1451	23.29%	29.17%	47.54%	-0.79	+7.0	30
2014-04-06	Fredericia	W 1-0	47.9	1288	1401	23.41%	29.22%	47.37%	-0.47	+7.0	21
2014-04-06	@ AB Gladsaxe	L 0-1	47.9	1401	1288	47.37%	29.22%	23.41%	+0.47	-7.0	27
2014-04-06	Lyngby	L 0-3	35.3	1310	1409	24.89%	29.75%	45.36%	-0.37	-11.8	25
2014-04-06	@ Vendsyssel	W 3-0	35.3	1409	1310	45.36%	29.75%	24.89%	+0.37	+11.8	35
2014-04-06	Vejle BK	D 1-1	56.4	1400	1439	32.04%	31.00%	36.96%	+0.04	+0.1	35
2014-04-06	@ HB Koge	D 1-1	56.4	1439	1400	36.96%	31.00%	32.04%	-0.04	-0.1	31
2014-04-12	AB Gladsaxe	L 1-2	55.2	1419	1295	54.24%	26.76%	19.00%	+1.14	-7.3	45
2014-04-12	@ Hobro	W 2-1	55.2	1295	1419	19.00%	26.76%	54.24%	-1.14	+7.3	24
2014-04-12	Bronshoj	L 1-3	42.8	1279	1386	23.99%	29.44%	46.57%	-0.43	-6.8	8
2014-04-12	@ Marienlyst	W 3-1	42.8	1386	1279	46.57%	29.44%	23.99%	+0.43	+6.8	33
2014-04-12	Horsens	L 1-3	51.8	1444	1448	36.96%	31.00%	32.04%	+0.27	-9.5	39
2014-04-12	@ Silkeborg	W 3-1	51.8	1448	1444	32.04%	31.00%	36.96%	-0.27	+9.5	42
2014-04-13	HB Koge	W 1-0	45.7	1394	1401	36.59%	31.02%	32.39%	+0.26	+5.3	30
2014-04-13	@ Fredericia	L 0-1	45.7	1401	1394	32.39%	31.02%	36.59%	-0.26	-5.3	35
2014-04-13	Hvidovre	W 3-2	51.7	1421	1326	50.45%	28.24%	21.31%	+0.94	+3.4	38
2014-04-13	@ Lyngby	L 2-3	51.7	1326	1421	21.31%	28.24%	50.45%	-0.94	-3.4	22
2014-04-13	Vendsyssel	W 1-0	38.7	1439	1299	56.33%	25.84%	17.83%	+1.25	+3.1	34
2014-04-13	@ Vejle BK	L 0-1	38.7	1299	1439	17.83%	25.84%	56.33%	-1.25	-3.1	25
2014-04-17	Fredericia	W 2-1	52.8	1323	1400	27.26%	30.38%	42.37%	-0.22	+6.0	25
2014-04-17	@ Hvidovre	L 1-2	52.8	1400	1323	42.37%	30.38%	27.26%	+0.22	-6.0	30
2014-04-17	Horsens	W 2-1	55.1	1395	1458	28.97%	30.69%	40.34%	-0.12	+5.8	38
2014-04-17	@ HB Koge	L 1-2	55.1	1458	1395	40.34%	30.69%	28.97%	+0.12	-5.8	42
2014-04-17	Lyngby	L 0-3	32.9	1272	1424	20.04%	27.48%	52.49%	-0.73	-9.7	8
2014-04-17	@ Marienlyst	W 3-0	32.9	1424	1272	52.49%	27.48%	20.04%	+0.73	+9.7	41
2014-04-17	Silkeborg	L 1-5	38.0	1302	1435	21.64%	28.41%	49.95%	-0.60	-11.4	24
2014-04-17	@ AB Gladsaxe	W 5-1	38.0	1435	1302	49.95%	28.41%	21.64%	+0.60	+11.4	42
2014-04-17	Vejle BK	W 2-1	54.1	1393	1442	30.63%	30.89%	38.47%	-0.03	+5.6	36
2014-04-17	@ Bronshoj	L 1-2	54.1	1442	1393	38.47%	30.89%	30.63%	+0.03	-5.6	34
2014-04-18	Hobro	L 1-3	43.0	1295	1411	23.15%	29.11%	47.73%	-0.49	-6.6	25
2014-04-18	@ Vendsyssel	W 3-1	43.0	1411	1295	47.73%	29.11%	23.15%	+0.49	+6.6	48
2014-04-20	AB Gladsaxe	D 0-0	51.8	1452	1291	58.87%	24.62%	16.51%	+1.39	-1.5	43
2014-04-20	@ Horsens	D 0-0	51.8	1291	1452	16.51%	24.62%	58.87%	-1.39	+1.5	25
2014-04-21	Bronshoj	L 0-3	43.1	1434	1398	42.45%	30.36%	27.18%	+0.54	-17.6	41
2014-04-21	@ Lyngby	W 3-0	43.1	1398	1434	27.18%	30.36%	42.45%	-0.54	+17.6	39
2014-04-21	HB Koge	D 0-0	51.5	1418	1401	39.88%	30.75%	29.38%	+0.41	-0.3	49
2014-04-21	@ Hobro	D 0-0	51.5	1401	1418	29.38%	30.75%	39.88%	-0.41	+0.3	39
2014-04-21	Hvidovre	D 2-2	61.8	1436	1329	52.15%	27.61%	20.24%	+1.03	-0.8	35
2014-04-21	@ Vejle BK	D 2-2	61.8	1329	1436	20.24%	27.61%	52.15%	-1.03	+0.8	26
2014-04-21	Marienlyst	W 2-0	32.7	1446	1262	61.67%	23.18%	15.15%	+1.55	+4.9	45
2014-04-21	@ Silkeborg	L 0-2	32.7	1262	1446	15.15%	23.18%	61.67%	-1.55	-4.9	8
2014-04-21	Vendsyssel	D 0-0	50.0	1394	1289	51.83%	27.73%	20.44%	+1.01	-1.1	31
2014-04-21	@ Fredericia	D 0-0	50.0	1289	1394	20.44%	27.73%	51.83%	-1.01	+1.1	26
2014-04-25	Lyngby	L 0-3	36.3	1330	1416	26.18%	30.12%	43.70%	-0.29	-12.3	26
2014-04-25	@ Hvidovre	W 3-0	36.3	1416	1330	43.70%	30.12%	26.18%	+0.29	+12.3	44
2014-04-26	Marienlyst	W 2-0	33.2	1416	1257	58.62%	24.75%	16.64%	+1.38	+5.5	42
2014-04-26	@ Bronshoj	L 0-2	33.2	1257	1416	16.64%	24.75%	58.62%	-1.38	-5.5	8
2014-04-27	Fredericia	D 0-0	50.9	1402	1393	38.77%	30.87%	30.36%	+0.36	-0.3	40
2014-04-27	@ HB Koge	D 0-0	50.9	1393	1402	30.36%	30.87%	38.77%	-0.36	+0.3	32
2014-04-27	Hobro	W 3-0	42.1	1292	1418	22.30%	28.74%	48.96%	-0.55	+19.5	28
2014-04-27	@ AB Gladsaxe	L 0-3	42.1	1418	1292	48.96%	28.74%	22.30%	+0.55	-19.6	49
2014-04-27	Silkeborg	L 2-3	61.2	1450	1451	37.35%	30.98%	31.67%	+0.29	-5.2	43
2014-04-27	@ Horsens	W 3-2	61.2	1451	1450	31.67%	30.98%	37.35%	-0.29	+5.2	48
2014-04-27	Vejle BK	W 1-0	49.2	1290	1436	20.55%	27.80%	51.65%	-0.69	+7.4	29
2014-04-27	@ Vendsyssel	L 0-1	49.2	1436	1290	51.65%	27.80%	20.55%	+0.69	-7.4	35
2014-04-30	Hvidovre	L 1-4	40.8	1252	1317	28.57%	30.62%	40.81%	-0.15	-11.1	8
2014-04-30	@ Marienlyst	W 4-1	40.8	1317	1252	40.81%	30.62%	28.57%	+0.15	+11.1	29
2014-05-01	Horsens	W 2-0	44.6	1398	1445	30.91%	30.92%	38.17%	-0.02	+11.2	52
2014-05-01	@ Hobro	L 0-2	44.6	1445	1398	38.17%	30.92%	30.91%	+0.02	-11.2	43
2014-05-03	Silkeborg	L 0-2	44.0	1422	1456	32.52%	31.03%	36.45%	+0.06	-10.0	42
2014-05-03	@ Bronshoj	W 2-0	44.0	1456	1422	36.45%	31.03%	32.52%	-0.06	+10.0	51
2014-05-04	AB Gladsaxe	W 1-0	40.5	1393	1312	48.67%	28.83%	22.50%	+0.85	+4.0	35
2014-05-04	@ Fredericia	L 0-1	40.5	1312	1393	22.50%	28.83%	48.67%	-0.85	-4.0	28
2014-05-04	HB Koge	D 0-0	51.8	1428	1401	41.29%	30.55%	28.15%	+0.48	-0.4	36
2014-05-04	@ Vejle BK	D 0-0	51.8	1401	1428	28.15%	30.55%	41.29%	-0.48	+0.4	41
2014-05-04	Vendsyssel	W 4-1	38.0	1428	1297	55.19%	26.35%	18.46%	+1.19	+7.5	47
2014-05-04	@ Lyngby	L 1-4	38.0	1297	1428	18.46%	26.35%	55.19%	-1.19	-7.5	29
2014-05-09	Bronshoj	L 1-3	44.8	1329	1412	26.55%	30.22%	43.23%	-0.26	-7.4	29
2014-05-09	@ Hvidovre	W 3-1	44.8	1412	1329	43.23%	30.22%	26.55%	+0.26	+7.4	45
2014-05-09	Hobro	W 2-1	50.8	1466	1409	45.49%	29.72%	24.79%	+0.69	+4.1	54
2014-05-09	@ Silkeborg	L 1-2	50.8	1409	1466	24.79%	29.72%	45.49%	-0.69	-4.1	52
2014-05-09	Lyngby	L 1-2	52.4	1402	1436	32.61%	31.03%	36.36%	+0.07	-5.0	41
2014-05-09	@ HB Koge	W 2-1	52.4	1436	1402	36.36%	31.03%	32.61%	-0.07	+5.0	50
2014-05-10	Fredericia	D 1-1	56.4	1434	1397	42.72%	30.32%	26.97%	+0.55	-0.5	44
2014-05-10	@ Horsens	D 1-1	56.4	1397	1434	26.97%	30.32%	42.72%	-0.55	+0.5	36
2014-05-11	Marienlyst	W 3-1	42.5	1290	1241	44.38%	29.98%	25.64%	+0.63	+7.2	32
2014-05-11	@ Vendsyssel	L 1-3	42.5	1241	1290	25.64%	29.98%	44.38%	-0.63	-7.2	8
2014-05-11	Vejle BK	L 3-4	55.0	1308	1428	22.81%	28.97%	48.22%	-0.51	-3.5	28
2014-05-11	@ AB Gladsaxe	W 4-3	55.0	1428	1308	48.22%	28.97%	22.81%	+0.51	+3.5	39
2014-05-16	HB Koge	W 2-0	44.6	1233	1397	19.19%	26.90%	53.91%	-0.81	+14.5	11
2014-05-16	@ Marienlyst	L 0-2	44.6	1397	1233	53.91%	26.90%	19.19%	+0.81	-14.5	41
2014-05-16	Hobro	L 0-3	40.7	1397	1405	36.34%	31.03%	32.63%	+0.25	-15.7	36
2014-05-16	@ Fredericia	W 3-0	40.7	1405	1397	32.63%	31.03%	36.34%	-0.25	+15.7	55
2014-05-16	Horsens	D 1-1	57.1	1431	1433	37.18%	30.99%	31.83%	+0.28	-0.2	40
2014-05-16	@ Vejle BK	D 1-1	57.1	1433	1431	31.83%	30.99%	37.18%	-0.28	+0.2	45
2014-05-16	Silkeborg	D 3-3	66.5	1321	1471	20.25%	27.61%	52.14%	-0.71	+0.6	30
2014-05-16	@ Hvidovre	D 3-3	66.5	1471	1321	52.14%	27.61%	20.25%	+0.71	-0.6	55
2014-05-17	Vendsyssel	W 1-0	39.0	1419	1297	54.02%	26.86%	19.12%	+1.13	+3.4	48
2014-05-17	@ Bronshoj	L 0-1	39.0	1297	1419	19.12%	26.86%	54.02%	-1.13	-3.4	32
2014-05-18	AB Gladsaxe	W 2-0	35.0	1441	1305	55.85%	26.06%	18.09%	+1.23	+6.0	53
2014-05-18	@ Lyngby	L 0-2	35.0	1305	1441	18.09%	26.06%	55.85%	-1.23	-6.0	28
2014-05-21	Bronshoj	W 2-0	43.4	1382	1422	31.81%	30.99%	37.20%	+0.03	+11.0	44
2014-05-21	@ HB Koge	L 0-2	43.4	1422	1382	37.20%	30.99%	31.81%	-0.03	-11.0	48
2014-05-21	Fredericia	W 4-0	36.4	1470	1382	49.67%	28.50%	21.82%	+0.90	+13.8	58
2014-05-21	@ Silkeborg	L 0-4	36.4	1382	1470	21.82%	28.50%	49.67%	-0.90	-13.8	36
2014-05-21	Hvidovre	L 0-2	39.6	1294	1322	33.47%	31.06%	35.47%	+0.11	-10.2	32
2014-05-21	@ Vendsyssel	W 2-0	39.6	1322	1294	35.47%	31.06%	33.47%	-0.11	+10.2	33
2014-05-21	Lyngby	W 1-0	48.2	1433	1447	35.56%	31.06%	33.38%	+0.21	+5.4	48
2014-05-21	@ Horsens	L 0-1	48.2	1447	1433	33.38%	31.06%	35.56%	-0.21	-5.4	53
2014-05-21	Marienlyst	W 3-0	34.1	1299	1248	44.59%	29.93%	25.48%	+0.64	+12.1	31
2014-05-21	@ AB Gladsaxe	L 0-3	34.1	1248	1299	25.48%	29.93%	44.59%	-0.64	-12.1	11
2014-05-21	Vejle BK	L 2-3	59.3	1421	1431	36.05%	31.04%	32.91%	+0.23	-5.1	55
2014-05-21	@ Hobro	W 3-2	59.3	1431	1421	32.91%	31.04%	36.05%	-0.23	+5.1	43
2014-05-24	AB Gladsaxe	D 2-2	61.0	1411	1311	51.29%	27.93%	20.78%	+0.98	-0.7	49
2014-05-24	@ Bronshoj	D 2-2	61.0	1311	1411	20.78%	27.93%	51.29%	-0.98	+0.7	32
2014-05-24	Horsens	W 1-0	49.8	1236	1439	16.50%	24.62%	58.88%	-1.08	+8.2	14
2014-05-24	@ Marienlyst	L 0-1	49.8	1439	1236	58.88%	24.62%	16.50%	+1.08	-8.2	48
2014-05-25	Fredericia	L 0-1	49.7	1436	1368	47.00%	29.32%	23.68%	+0.76	-6.9	43
2014-05-25	@ Vejle BK	W 1-0	49.7	1368	1436	23.68%	29.32%	47.00%	-0.76	+6.9	39
2014-05-25	HB Koge	W 1-0	46.6	1332	1393	29.10%	30.71%	40.19%	-0.12	+6.2	36
2014-05-25	@ Hvidovre	L 0-1	46.6	1393	1332	40.19%	30.71%	29.10%	+0.12	-6.2	44
2014-05-25	Hobro	D 1-1	57.0	1442	1416	41.13%	30.58%	28.29%	+0.47	-0.4	54
2014-05-25	@ Lyngby	D 1-1	57.0	1416	1442	28.29%	30.58%	41.13%	-0.47	+0.4	56
2014-05-26	Silkeborg	L 0-3	32.2	1283	1484	16.68%	24.79%	58.53%	-1.06	-8.0	32
2014-05-26	@ Vendsyssel	W 3-0	32.2	1484	1283	58.53%	24.79%	16.68%	+1.06	+8.0	61
2014-05-29	Bronshoj	D 1-1	56.5	1431	1411	40.34%	30.69%	28.97%	+0.44	-0.3	49
2014-05-29	@ Horsens	D 1-1	56.5	1411	1431	28.97%	30.69%	40.34%	-0.44	+0.3	50
2014-05-29	Hvidovre	W 4-0	37.7	1311	1338	33.65%	31.06%	35.29%	+0.12	+20.1	35
2014-05-29	@ AB Gladsaxe	L 0-4	37.7	1338	1311	35.29%	31.06%	33.65%	-0.12	-20.1	36
2014-05-29	Lyngby	W 2-0	44.7	1375	1441	28.46%	30.61%	40.93%	-0.15	+11.8	42
2014-05-29	@ Fredericia	L 0-2	44.7	1441	1375	40.93%	30.61%	28.46%	+0.15	-11.8	54
2014-05-29	Marienlyst	W 3-0	30.2	1416	1244	60.24%	23.93%	15.83%	+1.47	+7.5	59
2014-05-29	@ Hobro	L 0-3	30.2	1244	1416	15.83%	23.93%	60.24%	-1.47	-7.5	14
2014-05-29	Vejle BK	D 2-2	65.4	1492	1429	46.20%	29.54%	24.26%	+0.72	-0.5	62
2014-05-29	@ Silkeborg	D 2-2	65.4	1429	1492	24.26%	29.54%	46.20%	-0.72	+0.5	44
2014-05-29	Vendsyssel	W 1-0	38.8	1387	1275	52.69%	27.40%	19.91%	+1.06	+3.5	47
2014-05-29	@ HB Koge	L 0-1	38.8	1275	1387	19.91%	27.40%	52.69%	-1.06	-3.5	32
2014-06-01	AB Gladsaxe	W 2-1	51.0	1272	1331	29.31%	30.74%	39.95%	-0.10	+5.8	35
2014-06-01	@ Vendsyssel	L 1-2	51.0	1331	1272	39.95%	30.74%	29.31%	+0.10	-5.8	35
2014-06-01	Fredericia	D 1-1	53.9	1237	1386	20.21%	27.59%	52.20%	-0.72	+1.0	15
2014-06-01	@ Marienlyst	D 1-1	53.9	1386	1237	52.20%	27.59%	20.21%	+0.72	-1.0	43
2014-06-01	Hobro	L 0-1	47.6	1411	1424	35.66%	31.05%	33.29%	+0.21	-5.7	50
2014-06-01	@ Bronshoj	W 1-0	47.6	1424	1411	33.29%	31.05%	35.66%	-0.21	+5.7	62
2014-06-01	Horsens	L 2-5	43.5	1318	1430	23.50%	29.25%	47.25%	-0.46	-8.2	36
2014-06-01	@ Hvidovre	W 5-2	43.5	1430	1318	47.25%	29.25%	23.50%	+0.46	+8.2	52
2014-06-01	Silkeborg	D 1-1	58.0	1391	1491	24.67%	29.68%	45.65%	-0.38	+0.6	48
2014-06-01	@ HB Koge	D 1-1	58.0	1491	1391	45.65%	29.68%	24.67%	+0.38	-0.6	63
2014-06-01	Vejle BK	W 3-1	49.2	1429	1430	37.44%	30.97%	31.58%	+0.30	+8.5	57
2014-06-01	@ Lyngby	L 1-3	49.2	1430	1429	31.58%	30.97%	37.44%	-0.30	-8.5	44
2014-06-07	Marienlyst	W 3-2	47.2	1421	1238	61.61%	23.21%	15.18%	+1.55	+2.3	47
2014-06-07	@ Vejle BK	L 2-3	47.2	1238	1421	15.18%	23.21%	61.61%	-1.55	-2.3	15
2014-06-09	Bronshoj	L 2-3	57.4	1385	1405	34.65%	31.07%	34.28%	+0.16	-5.0	43
2014-06-09	@ Fredericia	W 3-2	57.4	1405	1385	34.28%	31.07%	34.65%	-0.16	+5.0	53
2014-06-09	HB Koge	D 3-3	64.3	1326	1391	28.57%	30.63%	40.80%	-0.15	+0.2	36
2014-06-09	@ AB Gladsaxe	D 3-3	64.3	1391	1326	40.80%	30.63%	28.57%	+0.15	-0.2	49
2014-06-09	Hvidovre	W 2-0	35.6	1429	1310	53.72%	26.98%	19.30%	+1.11	+6.4	65
2014-06-09	@ Hobro	L 0-2	35.6	1310	1429	19.30%	26.98%	53.72%	-1.11	-6.4	36
2014-06-09	Lyngby	W 3-1	49.2	1490	1438	44.86%	29.87%	25.27%	+0.66	+7.1	66
2014-06-09	@ Silkeborg	L 1-3	49.2	1438	1490	25.27%	29.87%	44.86%	-0.66	-7.1	57
2014-06-09	Vendsyssel	L 1-2	55.9	1439	1278	58.87%	24.62%	16.51%	+1.39	-7.7	52
2014-06-09	@ Horsens	W 2-1	55.9	1278	1439	16.51%	24.62%	58.87%	-1.39	+7.7	38

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	2014-03-30	16.11%	AB Gladsaxe	1280	1	@ Vejle BK	1447	0
2	2014-05-24	16.50%	@ Marienlyst	1236	1	Horsens	1439	0
3	2014-06-09	16.51%	Vendsyssel	1278	2	@ Horsens	1439	1
4	2013-11-03	17.97%	Hvidovre	1316	2	@ Horsens	1454	0
5	2014-04-12	19.00%	AB Gladsaxe	1295	2	@ Hobro	1419	1
6	2014-05-16	19.19%	@ Marienlyst	1233	2	HB Koge	1397	0
7	2014-04-27	20.55%	@ Vendsyssel	1290	1	Vejle BK	1436	0
8	2013-10-17	21.68%	HB Koge	1367	3	@ Horsens	1457	1
9	2014-04-27	22.30%	@ AB Gladsaxe	1292	3	Hobro	1418	0
10	2014-04-06	23.29%	Bronshoj	1379	1	@ Silkeborg	1451	0
11	2014-04-06	23.41%	@ AB Gladsaxe	1288	1	Fredericia	1401	0
12	2013-08-25	23.57%	Hobro	1392	5	@ Horsens	1462	2
13	2014-05-25	23.68%	Fredericia	1368	1	@ Vejle BK	1436	0
14	2013-09-12	25.26%	Vejle BK	1400	3	@ Horsens	1452	2
15	2013-10-06	25.64%	Vendsyssel	1347	2	@ Silkeborg	1396	1
16	2013-09-29	25.96%	HB Koge	1371	2	@ Silkeborg	1418	1
17	2013-09-29	26.01%	Bronshoj	1355	1	@ Vejle BK	1401	0
18	2013-07-28	26.60%	Vendsyssel	1358	3	@ Vejle BK	1399	1
19	2013-09-01	26.62%	@ HB Koge	1365	1	Horsens	1448	0
20	2013-09-07	26.68%	Bronshoj	1338	2	@ Marienlyst	1378	1
21	2013-11-07	27.11%	Silkeborg	1409	2	@ Vejle BK	1444	1
22	2014-04-21	27.18%	Bronshoj	1398	3	@ Lyngby	1434	0
23	2014-04-17	27.26%	@ Hvidovre	1323	2	Fredericia	1400	1
24	2013-08-25	27.34%	Bronshoj	1336	3	@ Lyngby	1370	1
25	2014-03-30	27.80%	@ Fredericia	1384	3	Horsens	1456	0

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	2013-08-04	27.85	@ Hobro	5	1354	27.95%	Silkeborg	0	1425	41.53%	30.52%
2	2014-05-29	20.11	@ AB Gladsaxe	4	1311	33.65%	Hvidovre	0	1338	35.29%	31.06%
3	2014-04-27	19.55	@ AB Gladsaxe	3	1292	22.30%	Hobro	0	1418	48.96%	28.74%
4	2013-10-13	19.45	Fredericia	4	1380	35.31%	@ Vendsyssel	0	1353	33.63%	31.06%
5	2013-10-20	18.68	@ Silkeborg	5	1390	46.11%	AB Gladsaxe	0	1328	24.32%	29.56%
6	2013-09-15	17.92	@ Lyngby	4	1383	39.15%	Marienlyst	0	1372	30.02%	30.83%
7	2014-04-21	17.58	Bronshoj	3	1398	27.18%	@ Lyngby	0	1434	42.45%	30.36%
8	2014-03-30	17.35	@ Fredericia	3	1384	27.80%	Horsens	0	1456	41.71%	30.49%
9	2013-08-18	16.92	@ Hvidovre	4	1364	41.69%	AB Gladsaxe	0	1335	27.82%	30.49%
10	2013-10-11	16.71	Vejle BK	4	1417	42.19%	@ Hvidovre	0	1342	27.40%	30.41%
11	2013-07-28	16.16	@ Fredericia	3	1367	31.23%	Marienlyst	0	1412	37.82%	30.95%
12	2013-10-03	16.14	@ Fredericia	3	1364	31.31%	Hobro	0	1408	37.74%	30.95%
13	2014-05-16	15.72	Hobro	3	1405	32.63%	@ Fredericia	0	1397	36.34%	31.03%
14	2013-10-02	14.98	@ Vejle BK	3	1394	35.01%	Silkeborg	0	1411	33.92%	31.07%
15	2013-09-14	14.96	@ Bronshoj	3	1344	35.08%	Vendsyssel	0	1361	33.85%	31.07%
16	2013-11-03	14.90	Hvidovre	2	1316	17.97%	@ Horsens	0	1454	56.07%	25.96%
17	2013-11-14	14.80	@ Hobro	3	1410	35.63%	Lyngby	0	1423	33.32%	31.06%
18	2014-05-16	14.47	@ Marienlyst	2	1233	19.19%	HB Koge	0	1397	53.91%	26.90%
19	2014-03-22	14.28	Bronshoj	3	1360	37.29%	@ Vendsyssel	0	1320	31.72%	30.98%
20	2013-08-25	13.88	Hobro	5	1392	23.57%	@ Horsens	2	1462	47.15%	29.28%
21	2014-05-21	13.75	@ Silkeborg	4	1470	49.67%	Fredericia	0	1382	21.82%	28.50%
22	2013-09-08	12.38	Lyngby	5	1371	28.92%	@ Fredericia	2	1391	40.40%	30.68%
23	2014-04-25	12.33	Lyngby	3	1416	43.70%	@ Hvidovre	0	1330	26.18%	30.12%
24	2013-11-17	12.22	@ HB Koge	3	1377	44.07%	Hvidovre	0	1331	25.89%	30.05%
25	2014-05-21	12.07	@ AB Gladsaxe	3	1299	44.59%	Marienlyst	0	1248	25.48%	29.93%

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	2014-05-16	66.5	@ Hvidovre	3	1321	20.25%	Silkeborg	3	1471	52.14%	27.61%
2	2013-10-13	66.1	@ AB Gladsaxe	3	1328	21.92%	Horsens	3	1457	49.53%	28.55%
3	2014-05-29	65.4	@ Silkeborg	2	1492	46.20%	Vejle BK	2	1429	24.26%	29.54%
4	2014-06-09	64.3	@ AB Gladsaxe	3	1326	28.57%	HB Koge	3	1391	40.80%	30.63%
5	2013-11-23	63.5	@ Vejle BK	2	1447	40.66%	Hobro	2	1425	28.70%	30.65%
6	2013-10-06	62.7	@ Horsens	2	1458	52.97%	Marienlyst	2	1344	19.74%	27.29%
7	2014-04-21	61.8	@ Vejle BK	2	1436	52.15%	Hvidovre	2	1329	20.24%	27.61%
8	2013-09-12	61.6	Vejle BK	3	1400	25.26%	@ Horsens	2	1452	44.87%	29.87%
9	2014-04-27	61.2	Silkeborg	3	1451	31.67%	@ Horsens	2	1450	37.35%	30.98%
10	2014-05-24	61.0	@ Bronshoj	2	1411	51.29%	AB Gladsaxe	2	1311	20.78%	27.93%
11	2013-09-15	60.3	@ AB Gladsaxe	2	1325	27.54%	Hobro	2	1399	42.02%	30.44%
12	2014-05-21	59.3	Vejle BK	3	1431	32.91%	@ Hobro	2	1421	36.05%	31.04%
13	2014-06-01	58.0	@ HB Koge	1	1391	24.67%	Silkeborg	1	1491	45.65%	29.68%
14	2014-06-09	57.4	Bronshoj	3	1405	34.28%	@ Fredericia	2	1385	34.65%	31.07%
15	2014-05-16	57.1	@ Vejle BK	1	1431	37.18%	Horsens	1	1433	31.83%	30.99%
16	2014-05-25	57.0	@ Lyngby	1	1442	41.13%	Hobro	1	1416	28.29%	30.58%
17	2014-05-29	56.5	@ Horsens	1	1431	40.34%	Bronshoj	1	1411	28.97%	30.69%
18	2014-04-06	56.4	@ HB Koge	1	1400	32.04%	Vejle BK	1	1439	36.96%	31.00%
19	2014-05-10	56.4	@ Horsens	1	1434	42.72%	Fredericia	1	1397	26.97%	30.32%
20	2014-06-09	55.9	Vendsyssel	2	1278	16.51%	@ Horsens	1	1439	58.87%	24.62%
21	2013-11-07	55.6	Silkeborg	2	1409	27.11%	@ Vejle BK	1	1444	42.54%	30.35%
22	2013-10-18	55.4	@ Hobro	4	1403	47.05%	Vendsyssel	3	1334	23.64%	29.31%
23	2013-11-03	55.4	@ Silkeborg	1	1409	41.23%	HB Koge	1	1383	28.21%	30.56%
24	2013-08-15	55.2	@ Silkeborg	3	1393	40.05%	Lyngby	2	1375	29.22%	30.73%
25	2014-03-29	55.2	Vendsyssel	3	1305	33.26%	@ Marienlyst	2	1293	35.69%	31.05%

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2014-05-29	30.2	@ Hobro	3	1416	60.24%	Marienlyst	0	1244	15.83%	23.93%
2	2014-05-26	32.2	Silkeborg	3	1484	58.53%	@ Vendsyssel	0	1283	16.68%	24.79%
3	2014-04-21	32.7	@ Silkeborg	2	1446	61.67%	Marienlyst	0	1262	15.15%	23.18%
4	2014-04-17	32.9	Lyngby	3	1424	52.49%	@ Marienlyst	0	1272	20.04%	27.48%
5	2014-04-26	33.2	@ Bronshoj	2	1416	58.62%	Marienlyst	0	1257	16.64%	24.75%
6	2014-03-23	34.0	@ HB Koge	3	1384	48.60%	Marienlyst	0	1304	22.55%	28.85%
7	2014-05-21	34.1	@ AB Gladsaxe	3	1299	44.59%	Marienlyst	0	1248	25.48%	29.93%
8	2014-03-23	34.5	Lyngby	3	1403	47.24%	@ AB Gladsaxe	0	1291	23.50%	29.26%
9	2014-05-18	35.0	@ Lyngby	2	1441	55.85%	AB Gladsaxe	0	1305	18.09%	26.06%
10	2014-04-06	35.3	Lyngby	3	1409	45.36%	@ Vendsyssel	0	1310	24.89%	29.75%
11	2013-10-20	35.5	@ Silkeborg	5	1390	46.11%	AB Gladsaxe	0	1328	24.32%	29.56%
12	2013-11-17	35.6	@ HB Koge	3	1377	44.07%	Hvidovre	0	1331	25.89%	30.05%
13	2014-06-09	35.6	@ Hobro	2	1429	53.72%	Hvidovre	0	1310	19.30%	26.98%
14	2013-08-18	35.8	@ Hvidovre	4	1364	41.69%	AB Gladsaxe	0	1335	27.82%	30.49%
15	2014-04-25	36.3	Lyngby	3	1416	43.70%	@ Hvidovre	0	1330	26.18%	30.12%
16	2013-10-26	36.4	Vejle BK	3	1433	44.84%	@ Marienlyst	0	1338	25.29%	29.88%
17	2014-03-23	36.4	@ Silkeborg	2	1439	52.58%	Hvidovre	0	1328	19.98%	27.44%
18	2014-05-21	36.4	@ Silkeborg	4	1470	49.67%	Fredericia	0	1382	21.82%	28.50%
19	2013-10-11	36.6	Vejle BK	4	1417	42.19%	@ Hvidovre	0	1342	27.40%	30.41%
20	2014-03-22	37.3	Bronshoj	3	1360	37.29%	@ Vendsyssel	0	1320	31.72%	30.98%
21	2013-09-15	37.4	@ Lyngby	4	1383	39.15%	Marienlyst	0	1372	30.02%	30.83%
22	2013-11-17	37.4	@ Silkeborg	2	1415	48.22%	Vendsyssel	0	1337	22.81%	28.97%
23	2014-04-04	37.7	@ Hvidovre	2	1317	41.70%	Marienlyst	0	1288	27.81%	30.49%
24	2014-05-29	37.7	@ AB Gladsaxe	4	1311	33.65%	Hvidovre	0	1338	35.29%	31.06%
25	2014-04-17	38.0	Silkeborg	5	1435	49.95%	@ AB Gladsaxe	1	1302	21.64%	28.41%