2014-15 1st Division Season

198 games

Final

Promoted

Viborg

65 pts

Aarhus GF · 61 pts

Relegated

Bronshoj

23 pts

AB Gladsaxe · 32 pts

Biggest Overachiever

Vendsyssel

7.59 points above expected

49 points · 41.41 expected points

Biggest Disappointment

Bronshoj

17.67 points below expected

23 points · 40.67 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	Viborg Promoted	33	17	14	2	65	47	20	+27	60.34	+4.66
2	Aarhus GF Promoted	33	17	10	6	61	59	33	+26	58.77	+2.23
3	Lyngby	33	14	9	10	51	49	37	+12	52.18	-1.18
4	Vendsyssel	33	13	10	10	49	35	29	+6	41.41	+7.59
5	Vejle BK	33	11	12	10	45	41	46	-5	42.37	+2.63
6	Horsens	33	10	12	11	42	43	42	+1	48.75	-6.75
7	HB Koge	33	10	12	11	42	33	35	-2	41.80	+0.20
8	Skive	33	8	17	8	41	40	42	-2	41.76	-0.76
9	FC Roskilde	33	10	8	15	38	40	38	+2	42.61	-4.61
10	Fredericia	33	6	16	11	34	28	40	-12	40.22	-6.22
11	AB Gladsaxe Relegated	33	8	8	17	32	35	61	-26	32.75	-0.75
12	Bronshoj Relegated	33	3	14	16	23	20	47	-27	40.67	-17.67

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	Vendsyssel	49	41.41	+7.59
2	Viborg	65	60.34	+4.66
3	Vejle BK	45	42.37	+2.63
4	Aarhus GF	61	58.77	+2.23
5	HB Koge	42	41.80	+0.20

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Bronshoj	23	40.67	-17.67
2	Horsens	42	48.75	-6.75
3	Fredericia	34	40.22	-6.22
4	FC Roskilde	38	42.61	-4.61
5	Lyngby	51	52.18	-1.18

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	AB Gladsaxe	4	Nov 2 – Nov 23	1 in 176
2	Vendsyssel	3	Aug 10 – Aug 24	1 in 41
3	Aarhus GF	5	Nov 6 – Mar 15	1 in 34
4	Lyngby	4	Oct 15 – Nov 2	1 in 32
5	Horsens	3	Aug 31 – Sep 17	1 in 19

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Horsens	3	Nov 24 – Mar 15	1 in 75
2	Lyngby	3	Apr 2 – Apr 11	1 in 57
3	Vendsyssel	3	May 24 – Jun 6	1 in 42
4	Bronshoj	4	Nov 23 – Mar 21	1 in 39
5	FC Roskilde	3	Nov 2 – Nov 14	1 in 19

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Bronshoj	9	Sep 13 – Nov 9	1 in 84
2	Viborg	16	Nov 2 – May 20	1 in 54
3	Aarhus GF	14	Nov 6 – May 7	1 in 52
4	Vejle BK	7	Apr 30 – Jun 6	1 in 46
5	Fredericia	6	Apr 19 – May 20	1 in 41

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Bronshoj	20	Oct 24 – Jun 6	1 in 1,332
2	Fredericia	16	Sep 28 – Apr 19	1 in 542
3	Lyngby	10	Nov 23 – May 2	1 in 514
4	Vendsyssel	10	Nov 9 – Apr 16	1 in 152
5	Horsens	9	Apr 12 – May 30	1 in 87

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
Viborg	1495	65	-1	8	10.4	-2.4
Aarhus GF	1486	61	-13	6	10.1	-4.1
Lyngby	1378	51	+9	8	7.5	+0.5
Vendsyssel	1332	49	-32	6	7.6	-1.6
Vejle BK	1340	45	+32	13	7.5	+5.5
HB Koge	1357	42	+37	8	6.1	+1.9
Horsens	1351	42	-9	6	7.6	-1.6
Skive	1330	41	+11	7	5.8	+1.2
FC Roskilde	1348	38	-22	3	6.5	-3.5
Fredericia	1287	34	+4	6	5.2	+0.8
AB Gladsaxe	1232	32	+8	6	3.6	+2.4
Bronshoj	1223	23	-23	2	4.7	-2.7

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	AG	BRO	FR	FRE	HK	HOR	LYN	SKI	VB	VEN	VIB
AB Gladsaxe	—	0-0-3 2.48	0-2-1 3.50	1-0-2 3.52	2-0-1 3.77	1-1-1 3.24	0-0-3 2.91	0-1-2 2.58	1-1-1 3.16	0-2-1 3.00	2-1-0 3.52	1-0-2 2.22
Aarhus GF	3-0-0 5.82	—	3-0-0 5.33	2-1-0 5.49	2-0-1 5.93	1-2-0 5.36	1-1-1 4.75	1-1-1 4.92	0-3-0 5.88	2-0-1 5.87	2-1-0 5.36	0-1-2 4.37
Bronshoj	1-2-0 4.72	0-0-3 2.95	—	0-2-1 4.05	0-3-0 3.86	1-0-2 3.80	0-2-1 3.45	0-2-1 2.66	1-2-0 3.37	0-0-3 3.63	0-1-2 4.06	0-0-3 2.58
FC Roskilde	2-0-1 4.70	0-1-2 2.77	1-2-0 4.15	—	2-0-1 4.47	0-1-2 4.42	1-0-2 3.90	0-1-2 3.12	1-0-2 4.44	2-1-0 4.19	1-0-2 3.92	0-2-1 2.58
Fredericia	1-0-2 4.44	1-0-2 2.38	0-3-0 4.36	1-0-2 3.75	—	0-3-0 4.06	0-3-0 3.28	2-1-0 3.05	1-2-0 4.07	0-1-2 4.19	0-2-1 3.61	0-1-2 2.46
HB Koge	1-1-1 4.98	0-2-1 2.90	2-0-1 4.41	2-1-0 3.79	0-3-0 4.14	—	1-1-1 3.89	1-0-2 2.95	1-2-0 3.70	1-1-1 3.79	1-1-1 3.92	0-0-3 2.91
Horsens	3-0-0 5.34	1-1-1 3.46	1-2-0 4.77	2-0-1 4.31	0-3-0 4.95	1-1-1 4.34	—	1-0-2 4.02	0-1-2 4.52	1-1-1 4.91	0-0-3 4.63	0-3-0 2.99
Lyngby	2-1-0 5.69	1-1-1 3.29	1-2-0 5.60	2-1-0 5.12	0-1-2 5.19	2-0-1 5.29	2-0-1 4.18	—	2-0-1 5.31	0-2-1 5.22	2-0-1 4.57	0-1-2 3.24
Skive	1-1-1 5.07	0-3-0 2.41	0-2-1 4.84	2-0-1 3.77	0-2-1 4.13	0-2-1 4.50	2-1-0 3.70	1-0-2 2.93	—	1-1-1 3.99	1-2-0 4.20	0-3-0 2.43
Vejle BK	1-2-0 5.25	1-0-2 2.42	3-0-0 4.61	0-1-2 4.01	2-1-0 4.02	1-1-1 4.42	1-1-1 3.30	1-2-0 3.01	1-1-1 4.21	—	0-1-2 4.43	0-2-1 2.25
Vendsyssel	0-1-2 4.72	0-1-2 2.88	2-1-0 4.15	2-0-1 4.28	1-2-0 4.60	1-1-1 4.30	3-0-0 3.59	1-0-2 3.65	0-2-1 4.01	2-1-0 3.78	—	1-1-1 2.73
Viborg	2-0-1 6.11	2-1-0 3.85	3-0-0 5.70	1-2-0 5.69	2-1-0 5.82	3-0-0 5.36	0-3-0 5.24	2-1-0 5.00	0-3-0 5.85	1-2-0 6.06	1-1-1 5.54	—

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	0.71	+9.8
Allowed	0.57	-8.8
Differential	0.91	+6.7

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	11.11%	8.59%	6.82%	2.78%	1.52%	0.25%	31.06%
1	8.59%	17.68%	7.32%	2.27%	—	0.76%	36.62%
2	6.82%	7.32%	5.56%	0.76%	0.25%	0.25%	20.96%
3	2.78%	2.27%	0.76%	1.52%	—	0.25%	7.58%
4	1.52%	—	0.25%	—	—	0.25%	2.02%
5+	0.25%	0.76%	0.25%	0.25%	0.25%	—	1.77%
Total	31.06%	36.62%	20.96%	7.58%	2.02%	1.77%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.19	1.19	+0.00
SD	1.14	1.14	1.62
CV	0.96	0.96	—
Max	7	7	+6
Min	0	0	-6

Games Played: 198

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.06	1.85	-0.79
SD	1.06	1.62	1.82
CV	1.00	0.88	—
Max	4	5	+2
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	6.06%	3.03%	3.03%	—	—	21.21%
1	9.09%	12.12%	3.03%	—	—	—	24.24%
2	3.03%	18.18%	9.09%	3.03%	—	—	33.33%
3	3.03%	3.03%	—	—	—	—	6.06%
4	6.06%	—	—	—	—	—	6.06%
5+	3.03%	3.03%	—	3.03%	—	—	9.09%
Total	33.33%	42.42%	15.15%	9.09%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.79	1.00	+0.79
SD	1.49	0.94	1.76
CV	0.84	0.94	—
Max	5	3	+5
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	18.18%	9.09%	9.09%	6.06%	3.03%	3.03%	48.48%
1	6.06%	18.18%	15.15%	3.03%	—	—	42.42%
2	3.03%	—	6.06%	—	—	—	9.09%
3	—	—	—	—	—	—	—
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	27.27%	27.27%	30.30%	9.09%	3.03%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.61	1.42	-0.82
SD	0.66	1.25	1.45
CV	1.09	0.88	—
Max	2	5	+2
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	21.21%	12.12%	—	—	—	39.39%
1	3.03%	12.12%	3.03%	3.03%	—	—	21.21%
2	12.12%	3.03%	6.06%	3.03%	3.03%	—	27.27%
3	6.06%	—	—	—	—	—	6.06%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	3.03%	—	—	—	3.03%
Total	30.30%	36.36%	24.24%	6.06%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.21	1.15	+0.06
SD	1.29	1.03	1.71
CV	1.07	0.90	—
Max	5	4	+4
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	18.18%	3.03%	9.09%	3.03%	3.03%	—	36.36%
1	9.09%	21.21%	12.12%	3.03%	—	—	45.45%
2	6.06%	3.03%	6.06%	—	—	—	15.15%
3	—	—	—	3.03%	—	—	3.03%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	33.33%	27.27%	27.27%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.85	1.21	-0.36
SD	0.80	1.11	1.29
CV	0.94	0.92	—
Max	3	4	+2
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	15.15%	12.12%	12.12%	—	—	—	39.39%
1	9.09%	21.21%	3.03%	—	—	3.03%	36.36%
2	3.03%	6.06%	—	3.03%	—	—	12.12%
3	3.03%	6.06%	—	—	—	—	9.09%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	33.33%	45.45%	15.15%	3.03%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.00	1.06	-0.06
SD	1.09	1.32	1.77
CV	1.09	1.25	—
Max	4	7	+4
Min	0	0	-6

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	6.06%	6.06%	3.03%	—	—	18.18%
1	9.09%	21.21%	15.15%	3.03%	—	—	48.48%
2	3.03%	6.06%	9.09%	—	—	—	18.18%
3	6.06%	6.06%	—	3.03%	—	—	15.15%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	21.21%	39.39%	30.30%	9.09%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.30	1.27	+0.03
SD	0.95	0.91	1.40
CV	0.73	0.72	—
Max	3	3	+3
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	12.12%	9.09%	—	—	—	33.33%
1	3.03%	12.12%	6.06%	3.03%	—	—	24.24%
2	9.09%	15.15%	3.03%	—	—	—	27.27%
3	—	3.03%	3.03%	—	—	—	6.06%
4	—	—	—	—	—	—	—
5+	—	6.06%	—	—	3.03%	—	9.09%
Total	24.24%	48.48%	21.21%	3.03%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.48	1.12	+0.36
SD	1.66	0.93	1.71
CV	1.12	0.83	—
Max	7	4	+6
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	3.03%	6.06%	3.03%	—	—	24.24%
1	9.09%	27.27%	9.09%	—	—	—	45.45%
2	—	9.09%	9.09%	—	—	—	18.18%
3	3.03%	—	3.03%	3.03%	—	—	9.09%
4	—	—	—	—	—	3.03%	3.03%
5+	—	—	—	—	—	—	—
Total	24.24%	39.39%	27.27%	6.06%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.21	1.27	-0.06
SD	1.02	1.10	1.09
CV	0.84	0.86	—
Max	4	5	+3
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.24	1.39	-0.15
SD	1.09	1.14	1.77
CV	0.88	0.82	—
Max	4	4	+4
Min	0	0	-4

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.06	0.88	+0.18
SD	1.00	1.05	1.61
CV	0.94	1.20	—
Max	4	4	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	3.03%	—	—	—	—	15.15%
1	15.15%	24.24%	3.03%	—	—	—	42.42%
2	18.18%	6.06%	3.03%	—	—	—	27.27%
3	9.09%	—	3.03%	3.03%	—	—	15.15%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	54.55%	33.33%	9.09%	3.03%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	0.61	+0.82
SD	0.94	0.79	1.10
CV	0.66	1.30	—
Max	3	3	+3
Min	0	0	-1

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
Viborg	1495	65	60.34	+4.66	76.0%	33	49	55	60	65	73	76
Aarhus GF	1486	61	58.77	+2.23	62.0%	42	47	53	59	64	69	77
Lyngby	1378	51	52.18	-1.18	45.0%	34	41	46	52	58	64	68
HB Koge	1357	42	41.80	+0.20	51.0%	23	27	36	42	47	52	58
Horsens	1351	42	48.75	-6.75	16.0%	31	36	45	49	53	59	63
FC Roskilde	1348	38	42.61	-4.61	34.0%	28	30	37	42	48	54	60
Vejle BK	1340	45	42.37	+2.63	73.0%	27	33	37	43	46	53	57
Vendsyssel	1332	49	41.41	+7.59	90.0%	25	32	37	42	45	52	62
Skive	1330	41	41.76	-0.76	49.0%	28	30	36	42	47	53	57
Fredericia	1287	34	40.22	-6.22	22.0%	22	30	35	40	45	49	56
AB Gladsaxe	1232	32	32.75	-0.75	52.0%	15	22	29	32	37	44	49
Bronshoj	1223	23	40.67	-17.67	1.0%	22	29	36	39	44	55	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

+1.52%

No Edge

32.83%35.86%31.31%

Elo Value

Home Edge: 5.26 Elo pts.

207 Elo

0.005 goals per Elo point

0600

Scoring Tilt

Expected

+0.02 goals

Neutral

-2+0.03+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

2.5

Top-Heavy

123410

Champion Preseason Odds

53%

Viborg, 1st of 12

LongshotFavorite

Title Margin

Expected

0.12/gm

Tight Race

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 5.61 * Some Luck: 5.61 to 8.41 * Lucky: 8.41 to 11.22 * Wild Swing: 11.22 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 1.66 * Close: 1.66 to 2.49 * Off: 2.49 to 3.32 * Way Off: 3.32 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 1.06 * A Surprise: 1.06 to 1.7 * Several Surprises: 1.7 to 2.33 * Many Surprises: 2.33 and up.

Luck Spread

Expected

6.30 points

Some Luck

07.0118

Average Finish Error

Expected

1.33

Pinpoint

02.075

Biggest Overachiever

Expected 95.83%

90.00%

Vendsyssel

50100

Biggest Underachiever

Expected 4.17%

1.00%

Bronshoj

050

Season Outliers

Expected

1 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

0 of 2

As Expected

01.12

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: 82.74

1.68

Moderate Separation

0.751.51.82.153

Interquartile Edge

56%

Even

50%63.5%74.5%100%

Best vs. Worst

Baseline

83%

Even

50%84%100%

Close Games

Expected

70%

Very Frequent

0%65%100%

Blowouts

Expected

11%

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

0.67

Coin-Flip

00.622

Matchup Imbalance

0.30

Very Even

00.340.420.5

Strangeness

Expected

0.85

As Expected

01.002

Repeatability

0.57

Strong Carryover

00.380.570.71

Upset Rate

Expected

25%

Upset-Prone

0%26%50%

Clear Favorite Upset Rate

Expected

24%

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 0.13 * Near Noise Ceiling: 0.13 to 0.2 * Above Noise: 0.2 to 0.26 * Well Above Noise: 0.26 and up.

Probability calibration

0.10

Borderline

0.010.050.10.51

Calibration slope

Ideal

0.86

Calibrated

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.101

Well Within Noise

00.1300.3

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
Viborg	53.00%	19.00%	15.00%	9.00%	1.00%	1.00%	1.00%	—	—	—	1.00%	—
Aarhus GF	32.00%	34.00%	17.00%	11.00%	1.00%	—	1.00%	4.00%	—	—	—	—
Lyngby	9.00%	24.00%	18.00%	14.00%	9.00%	12.00%	5.00%	3.00%	2.00%	3.00%	1.00%	—
Vendsyssel	1.00%	—	5.00%	7.00%	6.00%	14.00%	15.00%	9.00%	15.00%	12.00%	13.00%	3.00%
Vejle BK	—	4.00%	2.00%	9.00%	10.00%	12.00%	14.00%	11.00%	14.00%	13.00%	8.00%	3.00%
Horsens	2.00%	11.00%	17.00%	16.00%	25.00%	9.00%	6.00%	6.00%	3.00%	2.00%	1.00%	2.00%
HB Koge	1.00%	—	5.00%	10.00%	10.00%	11.00%	15.00%	13.00%	12.00%	5.00%	8.00%	10.00%
Skive	—	1.00%	8.00%	8.00%	11.00%	10.00%	9.00%	13.00%	11.00%	11.00%	12.00%	6.00%
FC Roskilde	—	2.00%	8.00%	7.00%	12.00%	12.00%	11.00%	8.00%	9.00%	14.00%	10.00%	7.00%
Fredericia	—	2.00%	1.00%	5.00%	7.00%	12.00%	10.00%	13.00%	13.00%	16.00%	11.00%	10.00%
AB Gladsaxe	—	—	—	1.00%	2.00%	—	8.00%	7.00%	4.00%	8.00%	15.00%	55.00%
Bronshoj	2.00%	3.00%	4.00%	3.00%	6.00%	7.00%	5.00%	13.00%	17.00%	16.00%	20.00%	4.00%

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
Viborg	72.00%	27.00%	1.00%
Aarhus GF	66.00%	34.00%	—
Lyngby	33.00%	66.00%	1.00%
Horsens	13.00%	84.00%	3.00%
Vejle BK	4.00%	85.00%	11.00%
FC Roskilde	2.00%	81.00%	17.00%
Vendsyssel	1.00%	83.00%	16.00%
HB Koge	1.00%	81.00%	18.00%
Skive	1.00%	81.00%	18.00%
Bronshoj	5.00%	71.00%	24.00%
Fredericia	2.00%	77.00%	21.00%
AB Gladsaxe	—	30.00%	70.00%

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
2014-07-25	AB Gladsaxe	W 1-0	37.4	1367	1298	52.95%	25.06%	22.00%	+0.36	+5.0	3
2014-07-25	@ Lyngby	L 0-1	37.4	1298	1367	22.00%	25.06%	52.95%	-0.36	-5.0	0
2014-07-25	HB Koge	D 1-1	54.1	1327	1341	42.15%	26.61%	31.25%	-0.04	-0.4	1
2014-07-25	@ Skive	D 1-1	54.1	1341	1327	31.25%	26.61%	42.15%	+0.04	+0.4	1
2014-07-26	Bronshoj	W 2-1	46.3	1363	1354	45.23%	26.33%	28.44%	+0.07	+5.9	3
2014-07-26	@ Vejle BK	L 1-2	46.3	1354	1363	28.44%	26.33%	45.23%	-0.07	-5.8	0
2014-07-27	FC Roskilde	D 2-2	61.5	1414	1327	54.99%	24.56%	20.45%	+0.44	-1.1	1
2014-07-27	@ Aarhus GF	D 2-2	61.5	1327	1414	20.45%	24.56%	54.99%	-0.44	+1.1	1
2014-07-27	Horsens	D 1-1	55.7	1395	1367	47.76%	26.01%	26.22%	+0.16	-0.9	1
2014-07-27	@ Viborg	D 1-1	55.7	1367	1395	26.22%	26.01%	47.76%	-0.16	+0.9	1
2014-07-28	Fredericia	W 2-1	48.1	1271	1334	35.22%	26.78%	38.00%	-0.28	+7.3	3
2014-07-28	@ Vendsyssel	L 1-2	48.1	1334	1271	38.00%	26.78%	35.22%	+0.28	-7.3	0
2014-08-01	Skive	L 2-3	55.1	1328	1327	44.25%	26.43%	29.32%	+0.03	-7.8	1
2014-08-01	@ FC Roskilde	W 3-2	55.1	1327	1328	29.32%	26.43%	44.25%	-0.03	+7.8	4
2014-08-03	Aarhus GF	L 0-5	39.1	1348	1413	34.97%	26.78%	38.25%	-0.29	-32.1	0
2014-08-03	@ Bronshoj	W 5-0	39.1	1413	1348	38.25%	26.78%	34.97%	+0.29	+32.1	4
2014-08-03	Lyngby	L 0-2	41.9	1368	1372	43.50%	26.50%	29.99%	+0.01	-16.2	1
2014-08-03	@ Horsens	W 2-0	41.9	1372	1368	29.99%	26.50%	43.50%	-0.01	+16.2	6
2014-08-03	Vejle BK	D 1-1	54.4	1327	1368	38.25%	26.78%	34.97%	-0.18	-0.1	1
2014-08-03	@ Fredericia	D 1-1	54.4	1368	1327	34.97%	26.78%	38.25%	+0.18	+0.1	4
2014-08-03	Vendsyssel	D 2-2	59.3	1293	1279	45.98%	26.25%	27.77%	+0.09	-0.6	1
2014-08-03	@ AB Gladsaxe	D 2-2	59.3	1279	1293	27.77%	26.25%	45.98%	-0.09	+0.6	4
2014-08-03	Viborg	L 2-3	53.9	1342	1395	36.61%	26.79%	36.60%	-0.23	-6.7	1
2014-08-03	@ HB Koge	W 3-2	53.9	1395	1342	36.60%	26.79%	36.61%	+0.23	+6.7	4
2014-08-08	Bronshoj	D 1-1	55.1	1388	1316	53.35%	24.96%	21.68%	+0.38	-1.3	7
2014-08-08	@ Lyngby	D 1-1	55.1	1316	1388	21.68%	24.96%	53.35%	-0.38	+1.3	1
2014-08-08	HB Koge	L 1-3	48.5	1369	1335	48.52%	25.90%	25.59%	+0.19	-15.3	4
2014-08-08	@ Vejle BK	W 3-1	48.5	1335	1369	25.59%	25.90%	48.52%	-0.19	+15.3	4
2014-08-08	Horsens	W 1-0	41.0	1335	1352	41.63%	26.64%	31.73%	-0.06	+6.8	7
2014-08-08	@ Skive	L 0-1	41.0	1352	1335	31.73%	26.64%	41.63%	+0.06	-6.8	1
2014-08-10	FC Roskilde	W 2-0	37.9	1279	1321	38.29%	26.78%	34.93%	-0.17	+13.7	7
2014-08-10	@ Vendsyssel	L 0-2	37.9	1321	1279	34.93%	26.78%	38.29%	+0.17	-13.7	1
2014-08-10	Fredericia	W 2-0	37.7	1293	1327	39.30%	26.75%	33.95%	-0.14	+13.4	4
2014-08-10	@ AB Gladsaxe	L 0-2	37.7	1327	1293	33.95%	26.75%	39.30%	+0.14	-13.4	1
2014-08-10	Viborg	L 0-2	45.8	1445	1401	49.74%	25.70%	24.57%	+0.23	-18.0	4
2014-08-10	@ Aarhus GF	W 2-0	45.8	1401	1445	24.57%	25.70%	49.74%	-0.23	+18.0	7
2014-08-14	Aarhus GF	D 0-0	50.6	1350	1427	33.33%	26.73%	39.94%	-0.34	+0.3	5
2014-08-14	@ HB Koge	D 0-0	50.6	1427	1350	39.94%	26.73%	33.33%	+0.34	-0.3	5
2014-08-16	Vendsyssel	L 0-1	44.8	1317	1293	47.28%	26.08%	26.64%	+0.14	-9.2	1
2014-08-16	@ Bronshoj	W 1-0	44.8	1293	1317	26.64%	26.08%	47.28%	-0.14	+9.2	10
2014-08-17	AB Gladsaxe	W 1-0	38.4	1345	1306	49.24%	25.78%	24.98%	+0.22	+5.6	4
2014-08-17	@ Horsens	L 0-1	38.4	1306	1345	24.98%	25.78%	49.24%	-0.22	-5.6	4
2014-08-17	Lyngby	W 2-1	49.5	1313	1387	33.69%	26.74%	39.57%	-0.33	+7.5	4
2014-08-17	@ Fredericia	L 1-2	49.5	1387	1313	39.57%	26.74%	33.69%	+0.33	-7.5	7
2014-08-17	Skive	D 0-0	50.9	1419	1341	53.99%	24.81%	21.20%	+0.40	-1.6	8
2014-08-17	@ Viborg	D 0-0	50.9	1341	1419	21.20%	24.81%	53.99%	-0.40	+1.6	8
2014-08-17	Vejle BK	D 2-2	59.8	1307	1353	37.55%	26.79%	35.66%	-0.20	-0.1	2
2014-08-17	@ FC Roskilde	D 2-2	59.8	1353	1307	35.66%	26.79%	37.55%	+0.20	+0.0	5
2014-08-22	HB Koge	D 1-1	54.0	1307	1350	37.96%	26.78%	35.26%	-0.18	-0.1	3
2014-08-22	@ FC Roskilde	D 1-1	54.0	1350	1307	35.26%	26.78%	37.96%	+0.18	+0.1	6
2014-08-23	Viborg	L 1-2	46.6	1308	1418	29.06%	26.41%	44.53%	-0.50	-6.0	1
2014-08-23	@ Bronshoj	W 2-1	46.6	1418	1308	44.53%	26.41%	29.06%	+0.50	+6.0	11
2014-08-24	Aarhus GF	L 1-5	38.7	1300	1426	27.15%	26.16%	46.69%	-0.58	-17.8	4
2014-08-24	@ AB Gladsaxe	W 5-1	38.7	1426	1300	46.69%	26.16%	27.15%	+0.58	+17.8	8
2014-08-24	Skive	W 2-0	37.6	1321	1343	41.00%	26.68%	32.32%	-0.08	+12.9	7
2014-08-24	@ Fredericia	L 0-2	37.6	1343	1321	32.32%	26.68%	41.00%	+0.08	-12.9	8
2014-08-24	Vejle BK	D 0-0	50.0	1380	1353	47.55%	26.04%	26.41%	+0.15	-1.0	8
2014-08-24	@ Lyngby	D 0-0	50.0	1353	1380	26.41%	26.04%	47.55%	-0.15	+1.0	6
2014-08-24	Vendsyssel	L 0-1	45.9	1351	1302	50.43%	25.57%	24.00%	+0.26	-9.7	4
2014-08-24	@ Horsens	W 1-0	45.9	1302	1351	24.00%	25.57%	50.43%	-0.26	+9.7	13
2014-08-28	Fredericia	W 2-1	43.6	1444	1334	57.73%	23.80%	18.47%	+0.56	+4.0	11
2014-08-28	@ Aarhus GF	L 1-2	43.6	1334	1444	18.47%	23.80%	57.73%	-0.56	-4.0	7
2014-08-29	AB Gladsaxe	D 1-1	54.3	1354	1283	53.24%	24.99%	21.77%	+0.37	-1.3	7
2014-08-29	@ Vejle BK	D 1-1	54.3	1283	1354	21.77%	24.99%	53.24%	-0.37	+1.3	5
2014-08-29	Lyngby	L 1-2	47.9	1312	1379	34.65%	26.77%	38.58%	-0.30	-6.8	13
2014-08-29	@ Vendsyssel	W 2-1	47.9	1379	1312	38.58%	26.77%	34.65%	+0.30	+6.8	11
2014-08-31	Bronshoj	D 1-1	54.0	1330	1302	47.75%	26.01%	26.23%	+0.16	-0.9	9
2014-08-31	@ Skive	D 1-1	54.0	1302	1330	26.23%	26.01%	47.75%	-0.16	+0.9	2
2014-08-31	FC Roskilde	D 1-1	55.8	1424	1307	58.48%	23.57%	17.95%	+0.59	-1.8	12
2014-08-31	@ Viborg	D 1-1	55.8	1307	1424	17.95%	23.57%	58.48%	-0.59	+1.8	4
2014-08-31	Horsens	L 0-2	41.7	1350	1341	45.28%	26.33%	28.39%	+0.07	-16.7	6
2014-08-31	@ HB Koge	W 2-0	41.7	1341	1350	28.39%	26.33%	45.28%	-0.07	+16.7	7
2014-09-04	Vendsyssel	L 0-2	42.6	1353	1305	50.32%	25.59%	24.09%	+0.26	-18.2	7
2014-09-04	@ Vejle BK	W 2-0	42.6	1305	1353	24.09%	25.59%	50.32%	-0.26	+18.2	16
2014-09-05	AB Gladsaxe	D 3-3	63.2	1329	1284	49.97%	25.66%	24.38%	+0.24	-0.7	10
2014-09-05	@ Skive	D 3-3	63.2	1284	1329	24.38%	25.66%	49.97%	-0.24	+0.7	6
2014-09-05	Bronshoj	W 2-1	44.5	1334	1303	48.13%	25.96%	25.91%	+0.17	+5.4	9
2014-09-05	@ HB Koge	L 1-2	44.5	1303	1334	25.91%	25.96%	48.13%	-0.17	-5.4	2
2014-09-07	Fredericia	D 2-2	61.7	1422	1330	55.66%	24.39%	19.95%	+0.47	-1.2	13
2014-09-07	@ Viborg	D 2-2	61.7	1330	1422	19.95%	24.39%	55.66%	-0.47	+1.2	8
2014-09-11	Aarhus GF	L 0-3	36.0	1323	1448	27.27%	26.18%	46.56%	-0.58	-16.4	16
2014-09-11	@ Vendsyssel	W 3-0	36.0	1448	1323	46.56%	26.18%	27.27%	+0.58	+16.4	14
2014-09-12	Viborg	L 0-2	36.0	1285	1421	25.99%	25.97%	48.04%	-0.63	-10.9	6
2014-09-12	@ AB Gladsaxe	W 2-0	36.0	1421	1285	48.04%	25.97%	25.99%	+0.63	+10.9	16
2014-09-13	FC Roskilde	D 1-1	53.6	1298	1308	42.56%	26.58%	30.86%	-0.03	-0.5	3
2014-09-13	@ Bronshoj	D 1-1	53.6	1308	1298	30.86%	26.58%	42.56%	+0.03	+0.5	5
2014-09-13	Skive	W 5-4	52.1	1385	1328	51.45%	25.37%	23.17%	+0.30	+4.5	14
2014-09-13	@ Lyngby	L 4-5	52.1	1328	1385	23.17%	25.37%	51.45%	-0.30	-4.5	10
2014-09-14	HB Koge	D 0-0	49.1	1331	1339	42.92%	26.55%	30.53%	-0.01	-0.6	9
2014-09-14	@ Fredericia	D 0-0	49.1	1339	1331	30.53%	26.55%	42.92%	+0.01	+0.6	10
2014-09-14	Vejle BK	W 3-0	34.6	1358	1335	47.15%	26.10%	26.75%	+0.14	+16.2	10
2014-09-14	@ Horsens	L 0-3	34.6	1335	1358	26.75%	26.10%	47.15%	-0.14	-16.2	7
2014-09-17	Horsens	L 0-1	42.0	1309	1374	34.87%	26.77%	38.35%	-0.29	-7.3	5
2014-09-17	@ FC Roskilde	W 1-0	42.0	1374	1309	38.35%	26.77%	34.87%	+0.29	+7.3	13
2014-09-18	Vejle BK	L 0-1	50.3	1464	1319	61.60%	22.51%	15.89%	+0.73	-11.4	14
2014-09-18	@ Aarhus GF	W 1-0	50.3	1319	1464	15.89%	22.51%	61.60%	-0.73	+11.4	10
2014-09-19	AB Gladsaxe	D 0-0	49.0	1340	1274	52.55%	25.14%	22.30%	+0.34	-1.4	11
2014-09-19	@ HB Koge	D 0-0	49.0	1274	1340	22.30%	25.14%	52.55%	-0.34	+1.4	7
2014-09-19	Vendsyssel	D 1-1	53.9	1324	1307	46.34%	26.20%	27.45%	+0.11	-0.8	11
2014-09-19	@ Skive	D 1-1	53.9	1307	1324	27.45%	26.20%	46.34%	-0.11	+0.8	17
2014-09-20	Horsens	D 1-1	54.2	1297	1381	32.28%	26.67%	41.04%	-0.38	+0.4	4
2014-09-20	@ Bronshoj	D 1-1	54.2	1381	1297	41.04%	26.67%	32.28%	+0.38	-0.4	14
2014-09-21	Fredericia	L 0-1	43.0	1302	1330	40.07%	26.72%	33.21%	-0.11	-8.1	5
2014-09-21	@ FC Roskilde	W 1-0	43.0	1330	1302	33.21%	26.72%	40.07%	+0.11	+8.1	12
2014-09-21	Lyngby	W 2-0	37.7	1432	1390	49.52%	25.73%	24.74%	+0.23	+10.4	19
2014-09-21	@ Viborg	L 0-2	37.7	1390	1432	24.74%	25.73%	49.52%	-0.23	-10.4	14
2014-09-26	Skive	L 1-2	50.5	1330	1323	44.97%	26.36%	28.67%	+0.06	-8.3	10
2014-09-26	@ Vejle BK	W 2-1	50.5	1323	1330	28.67%	26.36%	44.97%	-0.06	+8.3	14
2014-09-26	Viborg	L 0-1	40.1	1308	1442	26.18%	26.00%	47.82%	-0.62	-5.8	17
2014-09-26	@ Vendsyssel	W 1-0	40.1	1442	1308	47.82%	26.00%	26.18%	+0.62	+5.8	22
2014-09-28	Aarhus GF	L 1-2	50.4	1381	1453	33.94%	26.75%	39.31%	-0.32	-6.7	14
2014-09-28	@ Horsens	W 2-1	50.4	1453	1381	39.31%	26.75%	33.94%	+0.32	+6.7	17
2014-09-28	Bronshoj	D 0-0	49.0	1338	1297	49.44%	25.75%	24.82%	+0.22	-1.1	13
2014-09-28	@ Fredericia	D 0-0	49.0	1297	1338	24.82%	25.75%	49.44%	-0.22	+1.1	5
2014-09-28	FC Roskilde	L 0-4	38.2	1275	1294	41.51%	26.65%	31.84%	-0.06	-29.6	7
2014-09-28	@ AB Gladsaxe	W 4-0	38.2	1294	1275	31.84%	26.65%	41.51%	+0.06	+29.6	8
2014-09-28	HB Koge	W 2-0	35.7	1380	1338	49.47%	25.74%	24.79%	+0.22	+10.4	17
2014-09-28	@ Lyngby	L 0-2	35.7	1338	1380	24.79%	25.74%	49.47%	-0.22	-10.4	11
2014-10-03	FC Roskilde	W 3-1	40.5	1390	1323	52.65%	25.12%	22.23%	+0.35	+8.2	20
2014-10-03	@ Lyngby	L 1-3	40.5	1323	1390	22.23%	25.12%	52.65%	-0.35	-8.2	8
2014-10-04	AB Gladsaxe	W 1-0	37.1	1299	1246	50.95%	25.47%	23.57%	+0.28	+5.3	8
2014-10-04	@ Bronshoj	L 0-1	37.1	1246	1299	23.57%	25.47%	50.95%	-0.28	-5.3	7
2014-10-05	Fredericia	D 3-3	64.1	1374	1337	48.94%	25.83%	25.23%	+0.20	-0.6	15
2014-10-05	@ Horsens	D 3-3	64.1	1337	1374	25.23%	25.83%	48.94%	-0.20	+0.6	14
2014-10-05	Skive	D 0-0	52.0	1460	1331	59.72%	23.17%	17.12%	+0.64	-2.1	18
2014-10-05	@ Aarhus GF	D 0-0	52.0	1331	1460	17.12%	23.17%	59.72%	-0.64	+2.1	15
2014-10-05	Vendsyssel	L 0-1	45.0	1328	1302	47.52%	26.05%	26.43%	+0.15	-9.2	11
2014-10-05	@ HB Koge	W 1-0	45.0	1302	1328	26.43%	26.05%	47.52%	-0.15	+9.2	20
2014-10-06	Vejle BK	D 1-1	56.6	1448	1322	59.48%	23.24%	17.27%	+0.63	-1.8	23
2014-10-06	@ Viborg	D 1-1	56.6	1322	1448	17.27%	23.24%	59.48%	-0.63	+1.8	11
2014-10-12	Bronshoj	L 0-2	41.9	1334	1304	47.98%	25.98%	26.04%	+0.17	-17.5	15
2014-10-12	@ Skive	W 2-0	41.9	1304	1334	26.04%	25.98%	47.98%	-0.17	+17.5	11
2014-10-12	Lyngby	D 0-0	49.1	1240	1398	23.70%	25.50%	50.80%	-0.74	+1.3	8
2014-10-12	@ AB Gladsaxe	D 0-0	49.1	1398	1240	50.80%	25.50%	23.70%	+0.74	-1.3	21
2014-10-12	Vejle BK	D 1-1	53.9	1319	1324	43.38%	26.51%	30.11%	+0.00	-0.5	12
2014-10-12	@ HB Koge	D 1-1	53.9	1324	1319	30.11%	26.51%	43.38%	+0.00	+0.5	12
2014-10-12	Viborg	D 1-1	55.6	1315	1446	26.57%	26.07%	47.37%	-0.61	+0.8	9
2014-10-12	@ FC Roskilde	D 1-1	55.6	1446	1315	47.37%	26.07%	26.57%	+0.61	-0.9	24
2014-10-15	Lyngby	L 2-3	60.7	1458	1397	51.91%	25.28%	22.81%	+0.32	-8.9	18
2014-10-15	@ Aarhus GF	W 3-2	60.7	1397	1458	22.81%	25.28%	51.91%	-0.32	+8.9	24
2014-10-17	Fredericia	W 2-0	34.5	1445	1338	57.39%	23.90%	18.71%	+0.54	+8.1	27
2014-10-17	@ Viborg	L 0-2	34.5	1338	1445	18.71%	23.90%	57.39%	-0.54	-8.1	14
2014-10-18	FC Roskilde	L 0-2	41.1	1324	1316	45.16%	26.34%	28.50%	+0.07	-16.7	12
2014-10-18	@ Vejle BK	W 2-0	41.1	1316	1324	28.50%	26.34%	45.16%	-0.07	+16.7	12
2014-10-18	HB Koge	W 1-0	39.7	1321	1318	44.49%	26.41%	29.10%	+0.04	+6.3	14
2014-10-18	@ Bronshoj	L 0-1	39.7	1318	1321	29.10%	26.41%	44.49%	-0.04	-6.3	12
2014-10-18	Skive	W 2-1	43.3	1406	1316	55.38%	24.46%	20.16%	+0.46	+4.3	27
2014-10-18	@ Lyngby	L 1-2	43.3	1316	1406	20.16%	24.46%	55.38%	-0.46	-4.3	15
2014-10-19	AB Gladsaxe	W 3-1	37.2	1374	1242	60.14%	23.02%	16.84%	+0.66	+6.3	18
2014-10-19	@ Horsens	L 1-3	37.2	1242	1374	16.84%	23.02%	60.14%	-0.66	-6.3	8
2014-10-19	Vendsyssel	D 0-0	51.5	1449	1311	60.74%	22.81%	16.44%	+0.69	-2.2	19
2014-10-19	@ Aarhus GF	D 0-0	51.5	1311	1449	16.44%	22.81%	60.74%	-0.69	+2.2	21
2014-10-23	Horsens	L 1-2	55.3	1447	1380	52.63%	25.13%	22.25%	+0.35	-9.4	19
2014-10-23	@ Aarhus GF	W 2-1	55.3	1380	1447	22.25%	25.13%	52.63%	-0.35	+9.5	21
2014-10-24	AB Gladsaxe	W 2-1	42.2	1312	1235	53.81%	24.86%	21.33%	+0.39	+4.6	18
2014-10-24	@ Skive	L 1-2	42.2	1235	1312	21.33%	24.86%	53.81%	-0.39	-4.6	8
2014-10-24	Bronshoj	D 0-0	49.0	1332	1328	44.69%	26.39%	28.92%	+0.05	-0.7	13
2014-10-24	@ FC Roskilde	D 0-0	49.0	1328	1332	28.92%	26.39%	44.69%	-0.05	+0.7	15
2014-10-24	Lyngby	L 1-7	39.2	1312	1410	30.48%	26.55%	42.98%	-0.45	-28.3	12
2014-10-24	@ HB Koge	W 7-1	39.2	1410	1312	42.98%	26.55%	30.48%	+0.45	+28.3	30
2014-10-24	Viborg	W 1-0	47.1	1313	1453	25.57%	25.89%	48.54%	-0.65	+9.4	24
2014-10-24	@ Vendsyssel	L 0-1	47.1	1453	1313	48.54%	25.89%	25.57%	+0.65	-9.4	27
2014-10-26	Vejle BK	L 1-3	47.4	1330	1307	47.04%	26.11%	26.85%	+0.13	-14.9	14
2014-10-26	@ Fredericia	W 3-1	47.4	1307	1330	26.85%	26.11%	47.04%	-0.13	+14.9	15
2014-11-01	Fredericia	D 0-0	48.9	1328	1315	45.87%	26.26%	27.87%	+0.09	-0.8	16
2014-11-01	@ Bronshoj	D 0-0	48.9	1315	1328	27.87%	26.26%	45.87%	-0.09	+0.8	15
2014-11-02	Aarhus GF	W 3-0	39.2	1444	1437	44.94%	26.36%	28.69%	+0.06	+17.1	30
2014-11-02	@ Viborg	L 0-3	39.2	1437	1444	28.69%	26.36%	44.94%	-0.06	-17.1	19
2014-11-02	FC Roskilde	W 2-0	34.3	1438	1332	57.32%	23.92%	18.76%	+0.54	+8.1	33
2014-11-02	@ Lyngby	L 0-2	34.3	1332	1438	18.76%	23.92%	57.32%	-0.54	-8.1	13
2014-11-02	HB Koge	W 2-0	37.9	1231	1284	36.64%	26.79%	36.57%	-0.23	+14.2	11
2014-11-02	@ AB Gladsaxe	L 0-2	37.9	1284	1231	36.57%	26.79%	36.64%	+0.23	-14.2	12
2014-11-02	Skive	D 2-2	60.9	1389	1316	53.42%	24.95%	21.63%	+0.38	-1.0	22
2014-11-02	@ Horsens	D 2-2	60.9	1316	1389	21.63%	24.95%	53.42%	-0.38	+1.0	19
2014-11-02	Vendsyssel	L 0-4	39.4	1322	1323	44.02%	26.46%	29.52%	+0.02	-31.0	15
2014-11-02	@ Vejle BK	W 4-0	39.4	1323	1322	29.52%	26.46%	44.02%	-0.02	+31.0	27
2014-11-05	Horsens	W 2-1	48.5	1354	1388	39.19%	26.75%	34.06%	-0.14	+6.7	30
2014-11-05	@ Vendsyssel	L 1-2	48.5	1388	1354	34.06%	26.75%	39.19%	+0.14	-6.7	22
2014-11-06	Vejle BK	W 4-0	31.1	1420	1291	59.77%	23.15%	17.08%	+0.65	+14.0	22
2014-11-06	@ Aarhus GF	L 0-4	31.1	1291	1420	17.08%	23.15%	59.77%	-0.65	-14.0	15
2014-11-09	AB Gladsaxe	L 2-4	52.1	1324	1245	54.09%	24.79%	21.12%	+0.41	-15.0	13
2014-11-09	@ FC Roskilde	W 4-2	52.1	1245	1324	21.12%	24.79%	54.09%	-0.41	+15.0	14
2014-11-09	Bronshoj	D 2-2	60.4	1360	1328	48.37%	25.92%	25.71%	+0.18	-0.7	31
2014-11-09	@ Vendsyssel	D 2-2	60.4	1328	1360	25.71%	25.92%	48.37%	-0.18	+0.7	17
2014-11-09	Lyngby	D 1-1	55.6	1316	1447	26.59%	26.07%	47.34%	-0.61	+0.9	16
2014-11-09	@ Fredericia	D 1-1	55.6	1447	1316	47.34%	26.07%	26.59%	+0.61	-0.8	34
2014-11-09	Skive	W 1-0	41.4	1269	1317	37.34%	26.79%	35.88%	-0.21	+7.4	15
2014-11-09	@ HB Koge	L 0-1	41.4	1317	1269	35.88%	26.79%	37.34%	+0.21	-7.4	19
2014-11-10	Horsens	D 1-1	57.8	1461	1382	54.14%	24.78%	21.08%	+0.41	-1.4	31
2014-11-10	@ Viborg	D 1-1	57.8	1382	1461	21.08%	24.78%	54.14%	-0.41	+1.4	23
2014-11-14	FC Roskilde	W 1-0	39.6	1310	1309	44.20%	26.44%	29.36%	+0.03	+6.4	22
2014-11-14	@ Skive	L 0-1	39.6	1309	1310	29.36%	26.44%	44.20%	-0.03	-6.4	13
2014-11-15	Viborg	L 0-1	38.1	1277	1460	21.37%	24.87%	53.77%	-0.85	-4.8	15
2014-11-15	@ Vejle BK	W 1-0	38.1	1460	1277	53.77%	24.87%	21.37%	+0.85	+4.9	34
2014-11-16	Fredericia	W 1-0	41.7	1260	1317	36.08%	26.79%	37.13%	-0.25	+7.6	17
2014-11-16	@ AB Gladsaxe	L 0-1	41.7	1317	1260	37.13%	26.79%	36.08%	+0.25	-7.6	16
2014-11-16	Vendsyssel	W 2-1	45.0	1446	1360	54.96%	24.57%	20.47%	+0.44	+4.4	37
2014-11-16	@ Lyngby	L 1-2	45.0	1360	1446	20.47%	24.57%	54.96%	-0.44	-4.4	31
2014-11-23	AB Gladsaxe	L 0-1	46.8	1355	1267	55.14%	24.52%	20.33%	+0.45	-10.4	31
2014-11-23	@ Vendsyssel	W 1-0	46.8	1267	1355	20.33%	24.52%	55.14%	-0.45	+10.4	20
2014-11-23	Bronshoj	W 2-0	33.8	1464	1328	60.55%	22.88%	16.57%	+0.68	+7.1	37
2014-11-23	@ Viborg	L 0-2	33.8	1328	1464	16.57%	22.88%	60.55%	-0.68	-7.1	17
2014-11-23	Lyngby	W 1-0	45.1	1434	1450	41.85%	26.63%	31.52%	-0.05	+6.7	25
2014-11-23	@ Aarhus GF	L 0-1	45.1	1450	1434	31.52%	26.63%	41.85%	+0.05	-6.7	37
2014-11-23	Skive	D 1-1	53.7	1309	1316	43.05%	26.54%	30.41%	-0.01	-0.5	17
2014-11-23	@ Fredericia	D 1-1	53.7	1316	1309	30.41%	26.54%	43.05%	+0.01	+0.5	23
2014-11-24	Horsens	W 3-1	47.0	1272	1383	28.94%	26.39%	44.66%	-0.51	+14.3	18
2014-11-24	@ Vejle BK	L 1-3	47.0	1383	1272	44.66%	26.39%	28.94%	+0.51	-14.3	23
2014-11-26	Aarhus GF	L 1-2	46.8	1321	1441	27.87%	26.26%	45.87%	-0.55	-5.8	17
2014-11-26	@ Bronshoj	W 2-1	46.8	1441	1321	45.87%	26.26%	27.87%	+0.55	+5.8	28
2014-11-30	Aarhus GF	L 1-2	46.0	1308	1447	25.78%	25.93%	48.29%	-0.64	-5.4	17
2014-11-30	@ Fredericia	W 2-1	46.0	1447	1308	48.29%	25.93%	25.78%	+0.64	+5.4	31
2014-11-30	HB Koge	L 1-2	53.0	1369	1277	55.66%	24.39%	19.95%	+0.47	-9.9	23
2014-11-30	@ Horsens	W 2-1	53.0	1277	1369	19.95%	24.39%	55.66%	-0.47	+9.9	18
2015-03-12	Viborg	L 0-1	48.7	1443	1472	40.14%	26.72%	33.14%	-0.11	-8.1	37
2015-03-12	@ Lyngby	W 1-0	48.7	1472	1443	33.14%	26.72%	40.14%	+0.11	+8.1	40
2015-03-13	Vendsyssel	D 1-1	54.0	1317	1345	40.17%	26.72%	33.11%	-0.11	-0.3	24
2015-03-13	@ Skive	D 1-1	54.0	1345	1317	33.11%	26.72%	40.17%	+0.11	+0.3	32
2015-03-14	Vejle BK	L 0-1	44.9	1315	1287	47.85%	26.00%	26.15%	+0.16	-9.3	17
2015-03-14	@ Bronshoj	W 1-0	44.9	1287	1315	26.15%	26.00%	47.85%	-0.16	+9.3	21
2015-03-15	Aarhus GF	L 0-1	38.3	1278	1452	22.12%	25.09%	52.79%	-0.81	-5.0	20
2015-03-15	@ AB Gladsaxe	W 1-0	38.3	1452	1278	52.79%	25.09%	22.12%	+0.81	+5.0	34
2015-03-15	FC Roskilde	L 1-2	52.2	1359	1302	51.40%	25.38%	23.22%	+0.30	-9.3	23
2015-03-15	@ Horsens	W 2-1	52.2	1302	1359	23.22%	25.38%	51.40%	-0.30	+9.3	16
2015-03-15	Fredericia	D 0-0	48.4	1287	1303	41.79%	26.63%	31.58%	-0.05	-0.5	19
2015-03-15	@ HB Koge	D 0-0	48.4	1303	1287	31.58%	26.63%	41.79%	+0.05	+0.5	18
2015-03-19	Lyngby	D 1-1	55.2	1296	1435	25.66%	25.91%	48.43%	-0.65	+1.0	22
2015-03-19	@ Vejle BK	D 1-1	55.2	1435	1296	48.43%	25.91%	25.66%	+0.65	-1.0	38
2015-03-20	AB Gladsaxe	W 3-0	29.3	1480	1273	67.66%	20.02%	12.32%	+1.02	+7.6	43
2015-03-20	@ Viborg	L 0-3	29.3	1273	1480	12.32%	20.02%	67.66%	-1.02	-7.5	20
2015-03-21	Horsens	L 1-3	45.1	1306	1350	37.97%	26.78%	35.25%	-0.18	-12.6	17
2015-03-21	@ Bronshoj	W 3-1	45.1	1350	1306	35.25%	26.78%	37.97%	+0.18	+12.6	26
2015-03-22	FC Roskilde	L 0-3	38.8	1304	1312	42.94%	26.55%	30.51%	-0.01	-23.3	18
2015-03-22	@ Fredericia	W 3-0	38.8	1312	1304	30.51%	26.55%	42.94%	+0.01	+23.3	19
2015-03-22	HB Koge	D 0-0	49.0	1345	1286	51.67%	25.33%	23.00%	+0.31	-1.3	33
2015-03-22	@ Vendsyssel	D 0-0	49.0	1286	1345	23.00%	25.33%	51.67%	-0.31	+1.3	20
2015-03-22	Skive	D 2-2	62.7	1457	1316	61.03%	22.71%	16.26%	+0.70	-1.5	35
2015-03-22	@ Aarhus GF	D 2-2	62.7	1316	1457	16.26%	22.71%	61.03%	-0.70	+1.5	25
2015-03-25	HB Koge	L 0-1	45.6	1335	1288	50.24%	25.61%	24.15%	+0.25	-9.6	19
2015-03-25	@ FC Roskilde	W 1-0	45.6	1288	1335	24.15%	25.61%	50.24%	-0.25	+9.7	23
2015-03-26	Bronshoj	D 0-0	51.0	1434	1294	61.06%	22.70%	16.24%	+0.70	-2.2	39
2015-03-26	@ Lyngby	D 0-0	51.0	1294	1434	16.24%	22.70%	61.06%	-0.70	+2.2	18
2015-03-27	Viborg	D 0-0	51.7	1318	1487	22.58%	25.22%	52.20%	-0.79	+1.4	26
2015-03-27	@ Skive	D 0-0	51.7	1487	1318	52.20%	25.22%	22.58%	+0.79	-1.4	44
2015-03-29	Fredericia	D 1-1	54.4	1362	1280	54.48%	24.69%	20.83%	+0.42	-1.4	27
2015-03-29	@ Horsens	D 1-1	54.4	1280	1362	20.83%	24.69%	54.48%	-0.42	+1.4	19
2015-03-29	Vendsyssel	W 1-0	40.9	1325	1344	41.51%	26.65%	31.84%	-0.06	+6.8	22
2015-03-29	@ FC Roskilde	L 0-1	40.9	1344	1325	31.84%	26.65%	41.51%	+0.06	-6.8	33
2015-04-02	AB Gladsaxe	D 1-1	53.5	1296	1265	48.08%	25.96%	25.95%	+0.17	-0.9	19
2015-04-02	@ Bronshoj	D 1-1	53.5	1265	1296	25.95%	25.96%	48.08%	-0.17	+0.9	21
2015-04-02	FC Roskilde	W 1-0	37.4	1456	1332	59.19%	23.34%	17.47%	+0.62	+4.0	38
2015-04-02	@ Aarhus GF	L 0-1	37.4	1332	1456	17.47%	23.34%	59.19%	-0.62	-4.0	22
2015-04-02	Fredericia	D 0-0	48.9	1337	1282	51.22%	25.42%	23.36%	+0.29	-1.3	34
2015-04-02	@ Vendsyssel	D 0-0	48.9	1282	1337	23.36%	25.42%	51.22%	-0.29	+1.3	20
2015-04-02	HB Koge	W 2-0	31.9	1486	1297	65.92%	20.79%	13.29%	+0.93	+5.7	47
2015-04-02	@ Viborg	L 0-2	31.9	1297	1486	13.29%	20.79%	65.92%	-0.93	-5.7	23
2015-04-02	Lyngby	W 1-0	45.0	1361	1432	34.05%	26.75%	39.20%	-0.32	+7.9	30
2015-04-02	@ Horsens	L 0-1	45.0	1432	1361	39.20%	26.75%	34.05%	+0.32	-7.9	39
2015-04-02	Skive	W 2-1	46.5	1297	1319	40.97%	26.68%	32.35%	-0.08	+6.5	25
2015-04-02	@ Vejle BK	L 1-2	46.5	1319	1297	32.35%	26.68%	40.97%	+0.08	-6.5	26
2015-04-05	Aarhus GF	L 1-2	47.3	1336	1460	27.37%	26.19%	46.44%	-0.57	-5.7	34
2015-04-05	@ Vendsyssel	W 2-1	47.3	1460	1336	46.44%	26.19%	27.37%	+0.57	+5.7	41
2015-04-06	Bronshoj	W 1-0	39.5	1292	1295	43.60%	26.49%	29.91%	+0.01	+6.5	26
2015-04-06	@ HB Koge	L 0-1	39.5	1295	1292	29.91%	26.49%	43.60%	-0.01	-6.5	19
2015-04-06	Horsens	L 0-3	35.0	1266	1369	29.94%	26.50%	43.56%	-0.47	-17.7	21
2015-04-06	@ AB Gladsaxe	W 3-0	35.0	1369	1266	43.56%	26.50%	29.94%	+0.47	+17.7	33
2015-04-06	Lyngby	W 1-0	45.6	1313	1424	28.86%	26.38%	44.75%	-0.51	+8.8	29
2015-04-06	@ Skive	L 0-1	45.6	1424	1313	44.75%	26.38%	28.86%	+0.51	-8.8	39
2015-04-06	Vejle BK	W 2-0	35.4	1328	1303	47.32%	26.08%	26.61%	+0.14	+11.1	25
2015-04-06	@ FC Roskilde	L 0-2	35.4	1303	1328	26.61%	26.08%	47.32%	-0.14	-11.1	25
2015-04-06	Viborg	L 1-2	43.8	1283	1491	19.11%	24.06%	56.82%	-0.98	-4.1	20
2015-04-06	@ Fredericia	W 2-1	43.8	1491	1283	56.82%	24.06%	19.11%	+0.98	+4.1	50
2015-04-09	Vendsyssel	D 0-0	53.2	1496	1330	63.63%	21.73%	14.63%	+0.82	-2.4	51
2015-04-09	@ Viborg	D 0-0	53.2	1330	1496	14.63%	21.73%	63.63%	-0.82	+2.4	35
2015-04-11	FC Roskilde	L 0-2	38.7	1288	1339	36.94%	26.79%	36.27%	-0.22	-14.3	19
2015-04-11	@ Bronshoj	W 2-0	38.7	1339	1288	36.27%	26.79%	36.94%	+0.22	+14.3	28
2015-04-11	Fredericia	W 4-0	34.0	1292	1279	45.86%	26.26%	27.88%	+0.09	+21.8	28
2015-04-11	@ Vejle BK	L 0-4	34.0	1279	1292	27.88%	26.26%	45.86%	-0.09	-21.8	20
2015-04-11	HB Koge	L 1-3	50.9	1415	1298	58.53%	23.55%	17.92%	+0.59	-17.9	39
2015-04-11	@ Lyngby	W 3-1	50.9	1298	1415	17.92%	23.55%	58.53%	-0.59	+17.9	29
2015-04-12	Aarhus GF	D 1-1	57.5	1386	1465	33.03%	26.71%	40.25%	-0.35	+0.3	34
2015-04-12	@ Horsens	D 1-1	57.5	1465	1386	40.25%	26.71%	33.03%	+0.35	-0.3	42
2015-04-12	Skive	W 2-1	48.3	1249	1322	33.79%	26.74%	39.46%	-0.33	+7.5	24
2015-04-12	@ AB Gladsaxe	L 1-2	48.3	1322	1249	39.46%	26.74%	33.79%	+0.33	-7.5	29
2015-04-16	Aarhus GF	L 1-2	46.0	1316	1465	24.61%	25.70%	49.69%	-0.69	-5.2	29
2015-04-16	@ HB Koge	W 2-1	46.0	1465	1316	49.69%	25.70%	24.61%	+0.69	+5.2	45
2015-04-16	Vejle BK	D 0-0	48.9	1332	1314	46.47%	26.19%	27.34%	+0.11	-0.9	36
2015-04-16	@ Vendsyssel	D 0-0	48.9	1314	1332	27.34%	26.19%	46.47%	-0.11	+0.9	29
2015-04-17	Horsens	W 3-0	38.6	1314	1387	33.85%	26.75%	39.40%	-0.32	+21.8	32
2015-04-17	@ Skive	L 0-3	38.6	1387	1314	39.40%	26.75%	33.85%	+0.32	-21.8	34
2015-04-17	Lyngby	D 0-0	50.1	1353	1398	37.88%	26.78%	35.34%	-0.19	-0.1	29
2015-04-17	@ FC Roskilde	D 0-0	50.1	1398	1353	35.34%	26.78%	37.88%	+0.19	+0.1	40
2015-04-19	AB Gladsaxe	W 3-0	32.3	1311	1256	51.15%	25.43%	23.41%	+0.29	+14.4	32
2015-04-19	@ HB Koge	L 0-3	32.3	1256	1311	23.41%	25.43%	51.15%	-0.29	-14.4	24
2015-04-19	Bronshoj	D 0-0	48.0	1257	1274	41.71%	26.64%	31.66%	-0.06	-0.4	21
2015-04-19	@ Fredericia	D 0-0	48.0	1274	1257	31.66%	26.64%	41.71%	+0.06	+0.5	20
2015-04-19	Viborg	D 1-1	61.2	1470	1493	40.87%	26.68%	32.45%	-0.09	-0.3	46
2015-04-19	@ Aarhus GF	D 1-1	61.2	1493	1470	32.45%	26.68%	40.87%	+0.09	+0.3	52
2015-04-22	Vejle BK	D 1-1	53.2	1242	1315	33.74%	26.74%	39.52%	-0.33	+0.2	25
2015-04-22	@ AB Gladsaxe	D 1-1	53.2	1315	1242	39.52%	26.74%	33.74%	+0.33	-0.2	30
2015-04-24	HB Koge	D 1-1	54.1	1336	1325	45.50%	26.30%	28.20%	+0.08	-0.7	33
2015-04-24	@ Skive	D 1-1	54.1	1325	1336	28.20%	26.30%	45.50%	-0.08	+0.7	33
2015-04-25	Fredericia	L 0-2	45.0	1398	1257	61.08%	22.69%	16.22%	+0.71	-21.4	40
2015-04-25	@ Lyngby	W 2-0	45.0	1257	1398	16.22%	22.69%	61.08%	-0.71	+21.4	24
2015-04-25	Vendsyssel	L 0-3	36.7	1275	1331	36.05%	26.79%	37.16%	-0.25	-20.4	20
2015-04-25	@ Bronshoj	W 3-0	36.7	1331	1275	37.16%	26.79%	36.05%	+0.25	+20.4	39
2015-04-25	Viborg	D 0-0	52.8	1365	1493	26.86%	26.11%	47.03%	-0.59	+0.9	35
2015-04-25	@ Horsens	D 0-0	52.8	1493	1365	47.03%	26.11%	26.86%	+0.59	-0.9	53
2015-04-26	Aarhus GF	L 1-3	42.4	1315	1470	24.01%	25.57%	50.42%	-0.72	-8.8	30
2015-04-26	@ Vejle BK	W 3-1	42.4	1470	1315	50.42%	25.57%	24.01%	+0.72	+8.8	49
2015-04-26	FC Roskilde	L 2-5	41.4	1242	1353	28.85%	26.38%	44.76%	-0.51	-12.5	25
2015-04-26	@ AB Gladsaxe	W 5-2	41.4	1353	1242	44.76%	26.38%	28.85%	+0.51	+12.5	32
2015-04-30	Vejle BK	D 3-3	67.2	1492	1306	65.70%	20.88%	13.41%	+0.92	-1.4	54
2015-04-30	@ Viborg	D 3-3	67.2	1306	1492	13.41%	20.88%	65.70%	-0.92	+1.4	31
2015-05-02	Lyngby	W 2-0	38.5	1352	1376	40.67%	26.69%	32.64%	-0.09	+13.0	42
2015-05-02	@ Vendsyssel	L 0-2	38.5	1376	1352	32.64%	26.69%	40.67%	+0.09	-13.0	40
2015-05-03	AB Gladsaxe	W 1-0	37.1	1278	1229	50.41%	25.57%	24.01%	+0.26	+5.4	27
2015-05-03	@ Fredericia	L 0-1	37.1	1229	1278	24.01%	25.57%	50.41%	-0.26	-5.4	25
2015-05-03	Bronshoj	W 4-0	28.6	1479	1254	69.30%	19.26%	11.45%	+1.11	+9.1	52
2015-05-03	@ Aarhus GF	L 0-4	28.6	1254	1479	11.45%	19.26%	69.30%	-1.11	-9.1	20
2015-05-03	Horsens	D 1-1	54.3	1326	1366	38.45%	26.77%	34.77%	-0.17	-0.1	34
2015-05-03	@ HB Koge	D 1-1	54.3	1366	1326	34.77%	26.77%	38.45%	+0.17	+0.1	36
2015-05-03	Skive	W 3-0	34.4	1366	1335	48.11%	25.96%	25.93%	+0.17	+15.7	35
2015-05-03	@ FC Roskilde	L 0-3	34.4	1335	1366	25.93%	25.96%	48.11%	-0.17	-15.7	33
2015-05-07	Aarhus GF	L 0-2	40.7	1382	1488	29.51%	26.45%	44.04%	-0.49	-12.0	35
2015-05-07	@ FC Roskilde	W 2-0	40.7	1488	1382	44.04%	26.45%	29.51%	+0.49	+12.1	55
2015-05-08	Vejle BK	D 1-1	53.8	1319	1308	45.65%	26.29%	28.06%	+0.08	-0.7	34
2015-05-08	@ Skive	D 1-1	53.8	1308	1319	28.06%	26.29%	45.65%	-0.08	+0.7	32
2015-05-08	Viborg	L 0-1	40.3	1326	1491	22.95%	25.32%	51.73%	-0.77	-5.2	34
2015-05-08	@ HB Koge	W 1-0	40.3	1491	1326	51.73%	25.32%	22.95%	+0.77	+5.2	57
2015-05-10	Bronshoj	D 1-1	52.9	1224	1245	41.13%	26.67%	32.20%	-0.08	-0.4	26
2015-05-10	@ AB Gladsaxe	D 1-1	52.9	1245	1224	32.20%	26.67%	41.13%	+0.08	+0.4	21
2015-05-10	Horsens	W 2-1	46.9	1363	1366	43.66%	26.49%	29.85%	+0.01	+6.1	43
2015-05-10	@ Lyngby	L 1-2	46.9	1366	1363	29.85%	26.49%	43.66%	-0.01	-6.1	36
2015-05-10	Vendsyssel	D 1-1	53.9	1283	1365	32.66%	26.69%	40.64%	-0.37	+0.3	28
2015-05-10	@ Fredericia	D 1-1	53.9	1365	1283	40.64%	26.69%	32.66%	+0.37	-0.3	43
2015-05-13	FC Roskilde	W 1-0	39.3	1496	1370	59.55%	23.22%	17.23%	+0.64	+4.0	60
2015-05-13	@ Viborg	L 0-1	39.3	1370	1496	17.23%	23.22%	59.55%	-0.64	-3.9	35
2015-05-14	AB Gladsaxe	W 5-1	32.8	1369	1224	61.58%	22.51%	15.90%	+0.73	+10.8	46
2015-05-14	@ Lyngby	L 1-5	32.8	1224	1369	15.90%	22.51%	61.58%	-0.73	-10.8	26
2015-05-14	Fredericia	L 0-1	51.5	1500	1284	68.52%	19.62%	11.86%	+1.07	-12.4	55
2015-05-14	@ Aarhus GF	W 1-0	51.5	1284	1500	11.86%	19.62%	68.52%	-1.07	+12.4	31
2015-05-14	HB Koge	W 1-0	40.2	1308	1320	42.37%	26.59%	31.04%	-0.03	+6.7	35
2015-05-14	@ Vejle BK	L 0-1	40.2	1320	1308	31.04%	26.59%	42.37%	+0.03	-6.7	34
2015-05-16	Skive	D 0-0	48.2	1245	1319	33.76%	26.74%	39.50%	-0.33	+0.2	22
2015-05-16	@ Bronshoj	D 0-0	48.2	1319	1245	39.50%	26.74%	33.76%	+0.33	-0.2	35
2015-05-17	Vendsyssel	L 0-2	41.7	1360	1365	43.43%	26.51%	30.06%	+0.00	-16.2	36
2015-05-17	@ Horsens	W 2-0	41.7	1365	1360	30.06%	26.51%	43.43%	+0.00	+16.2	46
2015-05-19	HB Koge	D 1-1	57.8	1487	1314	64.42%	21.42%	14.16%	+0.86	-2.2	56
2015-05-19	@ Aarhus GF	D 1-1	57.8	1314	1487	14.16%	21.42%	64.42%	-0.86	+2.2	35
2015-05-20	AB Gladsaxe	W 3-1	37.7	1315	1213	56.81%	24.07%	19.12%	+0.52	+7.1	38
2015-05-20	@ Vejle BK	L 1-3	37.7	1213	1315	19.12%	24.07%	56.81%	-0.52	-7.1	26
2015-05-20	FC Roskilde	W 1-0	40.5	1381	1366	46.08%	26.24%	27.69%	+0.10	+6.1	49
2015-05-20	@ Vendsyssel	L 0-1	40.5	1366	1381	27.69%	26.24%	46.08%	-0.10	-6.1	35
2015-05-20	Horsens	D 1-1	53.8	1296	1344	37.37%	26.79%	35.84%	-0.20	-0.1	32
2015-05-20	@ Fredericia	D 1-1	53.8	1344	1296	35.84%	26.79%	37.37%	+0.20	+0.1	37
2015-05-20	Lyngby	L 1-2	44.5	1246	1380	26.18%	26.00%	47.82%	-0.62	-5.5	22
2015-05-20	@ Bronshoj	W 2-1	44.5	1380	1246	47.82%	26.00%	26.18%	+0.62	+5.5	49
2015-05-20	Skive	D 1-1	58.3	1500	1318	65.24%	21.08%	13.68%	+0.90	-2.3	61
2015-05-20	@ Viborg	D 1-1	58.3	1318	1500	13.68%	21.08%	65.24%	-0.90	+2.3	36
2015-05-23	Aarhus GF	D 1-1	56.7	1321	1485	23.07%	25.35%	51.59%	-0.77	+1.2	37
2015-05-23	@ Skive	D 1-1	56.7	1485	1321	51.59%	25.35%	23.07%	+0.77	-1.2	57
2015-05-24	Bronshoj	D 2-2	60.0	1344	1240	56.98%	24.02%	19.00%	+0.53	-1.2	38
2015-05-24	@ Horsens	D 2-2	60.0	1240	1344	19.00%	24.02%	56.98%	-0.53	+1.2	23
2015-05-24	Fredericia	W 2-0	34.2	1360	1296	52.24%	25.21%	22.55%	+0.33	+9.6	38
2015-05-24	@ FC Roskilde	L 0-2	34.2	1296	1360	22.55%	25.21%	52.24%	-0.33	-9.6	32
2015-05-24	Vendsyssel	W 4-0	38.7	1316	1387	34.12%	26.75%	39.13%	-0.32	+28.3	38
2015-05-24	@ HB Koge	L 0-4	38.7	1387	1316	39.13%	26.75%	34.12%	+0.32	-28.3	49
2015-05-24	Viborg	W 2-1	55.6	1206	1498	13.42%	20.89%	65.68%	-1.38	+11.3	29
2015-05-24	@ AB Gladsaxe	L 1-2	55.6	1498	1206	65.68%	20.89%	13.42%	+1.38	-11.3	61
2015-05-25	Vejle BK	L 1-2	52.9	1386	1322	52.26%	25.21%	22.54%	+0.33	-9.4	49
2015-05-25	@ Lyngby	W 2-1	52.9	1322	1386	22.54%	25.21%	52.26%	-0.33	+9.4	41
2015-05-30	Aarhus GF	D 2-2	63.6	1376	1484	29.32%	26.44%	44.24%	-0.49	+0.5	50
2015-05-30	@ Lyngby	D 2-2	63.6	1484	1376	44.24%	26.44%	29.32%	+0.49	-0.5	58
2015-05-30	FC Roskilde	W 2-0	38.3	1344	1369	40.63%	26.70%	32.68%	-0.09	+13.0	41
2015-05-30	@ HB Koge	L 0-2	38.3	1369	1344	32.68%	26.70%	40.63%	+0.09	-13.0	38
2015-05-30	Fredericia	D 2-2	59.6	1322	1286	48.74%	25.86%	25.40%	+0.20	-0.7	38
2015-05-30	@ Skive	D 2-2	59.6	1286	1322	25.40%	25.86%	48.74%	-0.20	+0.7	33
2015-05-30	Vejle BK	D 2-2	60.1	1343	1331	45.56%	26.30%	28.14%	+0.08	-0.5	39
2015-05-30	@ Horsens	D 2-2	60.1	1331	1343	28.14%	26.30%	45.56%	-0.08	+0.5	42
2015-05-30	Vendsyssel	W 2-0	41.6	1217	1358	25.41%	25.86%	48.73%	-0.66	+17.7	32
2015-05-30	@ AB Gladsaxe	L 0-2	41.6	1358	1217	48.73%	25.86%	25.41%	+0.66	-17.7	49
2015-05-30	Viborg	L 0-3	30.9	1241	1487	16.36%	22.77%	60.87%	-1.16	-10.2	23
2015-05-30	@ Bronshoj	W 3-0	30.9	1487	1241	60.87%	22.77%	16.36%	+1.16	+10.2	64
2015-06-06	AB Gladsaxe	W 5-3	39.7	1483	1235	71.47%	18.20%	10.34%	+1.22	+3.1	61
2015-06-06	@ Aarhus GF	L 3-5	39.7	1235	1483	10.34%	18.20%	71.47%	-1.22	-3.1	32
2015-06-06	Bronshoj	W 2-0	32.2	1332	1231	56.65%	24.11%	19.23%	+0.51	+8.3	45
2015-06-06	@ Vejle BK	L 0-2	32.2	1231	1332	19.23%	24.11%	56.65%	-0.51	-8.3	23
2015-06-06	HB Koge	D 1-1	53.8	1287	1357	34.18%	26.76%	39.06%	-0.31	+0.2	34
2015-06-06	@ Fredericia	D 1-1	53.8	1357	1287	39.06%	26.76%	34.18%	+0.31	-0.2	42
2015-06-06	Horsens	L 1-2	51.2	1356	1342	45.92%	26.26%	27.83%	+0.09	-8.5	38
2015-06-06	@ FC Roskilde	W 2-1	51.2	1342	1356	27.83%	26.26%	45.92%	-0.09	+8.4	42
2015-06-06	Lyngby	D 1-1	59.1	1497	1377	58.82%	23.46%	17.72%	+0.60	-1.8	65
2015-06-06	@ Viborg	D 1-1	59.1	1377	1497	17.72%	23.46%	58.82%	-0.60	+1.8	51
2015-06-06	Skive	L 1-2	51.0	1341	1321	46.65%	26.16%	27.18%	+0.12	-8.5	49
2015-06-06	@ Vendsyssel	W 2-1	51.0	1321	1341	27.18%	26.16%	46.65%	-0.12	+8.6	41

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	2015-05-14	11.86%	Fredericia	1284	1	@ Aarhus GF	1500	0
2	2015-05-24	13.42%	@ AB Gladsaxe	1206	2	Viborg	1498	1
3	2014-09-18	15.89%	Vejle BK	1319	1	@ Aarhus GF	1464	0
4	2015-04-25	16.22%	Fredericia	1257	2	@ Lyngby	1398	0
5	2015-04-11	17.92%	HB Koge	1298	3	@ Lyngby	1415	1
6	2014-11-30	19.95%	HB Koge	1277	2	@ Horsens	1369	1
7	2014-11-23	20.33%	AB Gladsaxe	1267	1	@ Vendsyssel	1355	0
8	2014-11-09	21.12%	AB Gladsaxe	1245	4	@ FC Roskilde	1324	2
9	2014-10-23	22.25%	Horsens	1380	2	@ Aarhus GF	1447	1
10	2015-05-25	22.54%	Vejle BK	1322	2	@ Lyngby	1386	1
11	2014-10-15	22.81%	Lyngby	1397	3	@ Aarhus GF	1458	2
12	2015-03-15	23.22%	FC Roskilde	1302	2	@ Horsens	1359	1
13	2014-08-24	24.00%	Vendsyssel	1302	1	@ Horsens	1351	0
14	2014-09-04	24.09%	Vendsyssel	1305	2	@ Vejle BK	1353	0
15	2015-03-25	24.15%	HB Koge	1288	1	@ FC Roskilde	1335	0
16	2014-08-10	24.57%	Viborg	1401	2	@ Aarhus GF	1445	0
17	2015-05-30	25.41%	@ AB Gladsaxe	1217	2	Vendsyssel	1358	0
18	2014-10-24	25.57%	@ Vendsyssel	1313	1	Viborg	1453	0
19	2014-08-08	25.59%	HB Koge	1335	3	@ Vejle BK	1369	1
20	2014-10-12	26.04%	Bronshoj	1304	2	@ Skive	1334	0
21	2015-03-14	26.15%	Vejle BK	1287	1	@ Bronshoj	1315	0
22	2014-10-05	26.43%	Vendsyssel	1302	1	@ HB Koge	1328	0
23	2014-08-16	26.64%	Vendsyssel	1293	1	@ Bronshoj	1317	0
24	2014-10-26	26.85%	Vejle BK	1307	3	@ Fredericia	1330	1
25	2015-06-06	27.18%	Skive	1321	2	@ Vendsyssel	1341	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	2014-08-03	32.09	Aarhus GF	5	1413	38.25%	@ Bronshoj	0	1348	34.97%	26.78%
2	2014-11-02	30.99	Vendsyssel	4	1323	29.52%	@ Vejle BK	0	1322	44.02%	26.46%
3	2014-09-28	29.61	FC Roskilde	4	1294	31.84%	@ AB Gladsaxe	0	1275	41.51%	26.65%
4	2014-10-24	28.31	Lyngby	7	1410	42.98%	@ HB Koge	1	1312	30.48%	26.55%
5	2015-05-24	28.30	@ HB Koge	4	1316	34.12%	Vendsyssel	0	1387	39.13%	26.75%
6	2015-03-22	23.27	FC Roskilde	3	1312	30.51%	@ Fredericia	0	1304	42.94%	26.55%
7	2015-04-11	21.83	@ Vejle BK	4	1292	45.86%	Fredericia	0	1279	27.88%	26.26%
8	2015-04-17	21.78	@ Skive	3	1314	33.85%	Horsens	0	1387	39.40%	26.75%
9	2015-04-25	21.39	Fredericia	2	1257	16.22%	@ Lyngby	0	1398	61.08%	22.69%
10	2015-04-25	20.38	Vendsyssel	3	1331	37.16%	@ Bronshoj	0	1275	36.05%	26.79%
11	2014-09-04	18.21	Vendsyssel	2	1305	24.09%	@ Vejle BK	0	1353	50.32%	25.59%
12	2014-08-10	18.03	Viborg	2	1401	24.57%	@ Aarhus GF	0	1445	49.74%	25.70%
13	2015-04-11	17.88	HB Koge	3	1298	17.92%	@ Lyngby	1	1415	58.53%	23.55%
14	2014-08-24	17.80	Aarhus GF	5	1426	46.69%	@ AB Gladsaxe	1	1300	27.15%	26.16%
15	2015-05-30	17.73	@ AB Gladsaxe	2	1217	25.41%	Vendsyssel	0	1358	48.73%	25.86%
16	2015-04-06	17.70	Horsens	3	1369	43.56%	@ AB Gladsaxe	0	1266	29.94%	26.50%
17	2014-10-12	17.51	Bronshoj	2	1304	26.04%	@ Skive	0	1334	47.98%	25.98%
18	2014-11-02	17.11	@ Viborg	3	1444	44.94%	Aarhus GF	0	1437	28.69%	26.36%
19	2014-08-31	16.71	Horsens	2	1341	28.39%	@ HB Koge	0	1350	45.28%	26.33%
20	2014-10-18	16.67	FC Roskilde	2	1316	28.50%	@ Vejle BK	0	1324	45.16%	26.34%
21	2014-09-11	16.41	Aarhus GF	3	1448	46.56%	@ Vendsyssel	0	1323	27.27%	26.18%
22	2014-08-03	16.18	Lyngby	2	1372	29.99%	@ Horsens	0	1368	43.50%	26.50%
23	2014-09-14	16.16	@ Horsens	3	1358	47.15%	Vejle BK	0	1335	26.75%	26.10%
24	2015-05-17	16.16	Vendsyssel	2	1365	30.06%	@ Horsens	0	1360	43.43%	26.51%
25	2015-05-03	15.74	@ FC Roskilde	3	1366	48.11%	Skive	0	1335	25.93%	25.96%

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	2015-04-30	67.2	@ Viborg	3	1492	65.70%	Vejle BK	3	1306	13.41%	20.88%
2	2014-10-05	64.1	@ Horsens	3	1374	48.94%	Fredericia	3	1337	25.23%	25.83%
3	2015-05-30	63.6	@ Lyngby	2	1376	29.32%	Aarhus GF	2	1484	44.24%	26.44%
4	2014-09-05	63.2	@ Skive	3	1329	49.97%	AB Gladsaxe	3	1284	24.38%	25.66%
5	2015-03-22	62.7	@ Aarhus GF	2	1457	61.03%	Skive	2	1316	16.26%	22.71%
6	2014-09-07	61.7	@ Viborg	2	1422	55.66%	Fredericia	2	1330	19.95%	24.39%
7	2014-07-27	61.5	@ Aarhus GF	2	1414	54.99%	FC Roskilde	2	1327	20.45%	24.56%
8	2015-04-19	61.2	@ Aarhus GF	1	1470	40.87%	Viborg	1	1493	32.45%	26.68%
9	2014-11-02	60.9	@ Horsens	2	1389	53.42%	Skive	2	1316	21.63%	24.95%
10	2014-10-15	60.7	Lyngby	3	1397	22.81%	@ Aarhus GF	2	1458	51.91%	25.28%
11	2014-11-09	60.4	@ Vendsyssel	2	1360	48.37%	Bronshoj	2	1328	25.71%	25.92%
12	2015-05-30	60.1	@ Horsens	2	1343	45.56%	Vejle BK	2	1331	28.14%	26.30%
13	2015-05-24	60.0	@ Horsens	2	1344	56.98%	Bronshoj	2	1240	19.00%	24.02%
14	2014-08-17	59.8	@ FC Roskilde	2	1307	37.55%	Vejle BK	2	1353	35.66%	26.79%
15	2015-05-30	59.6	@ Skive	2	1322	48.74%	Fredericia	2	1286	25.40%	25.86%
16	2014-08-03	59.3	@ AB Gladsaxe	2	1293	45.98%	Vendsyssel	2	1279	27.77%	26.25%
17	2015-06-06	59.1	@ Viborg	1	1497	58.82%	Lyngby	1	1377	17.72%	23.46%
18	2015-05-20	58.3	@ Viborg	1	1500	65.24%	Skive	1	1318	13.68%	21.08%
19	2014-11-10	57.8	@ Viborg	1	1461	54.14%	Horsens	1	1382	21.08%	24.78%
20	2015-05-19	57.8	@ Aarhus GF	1	1487	64.42%	HB Koge	1	1314	14.16%	21.42%
21	2015-04-12	57.5	@ Horsens	1	1386	33.03%	Aarhus GF	1	1465	40.25%	26.71%
22	2015-05-23	56.7	@ Skive	1	1321	23.07%	Aarhus GF	1	1485	51.59%	25.35%
23	2014-10-06	56.6	@ Viborg	1	1448	59.48%	Vejle BK	1	1322	17.27%	23.24%
24	2014-08-31	55.8	@ Viborg	1	1424	58.48%	FC Roskilde	1	1307	17.95%	23.57%
25	2014-07-27	55.7	@ Viborg	1	1395	47.76%	Horsens	1	1367	26.22%	26.01%

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2015-05-03	28.6	@ Aarhus GF	4	1479	69.30%	Bronshoj	0	1254	11.45%	19.26%
2	2015-03-20	29.3	@ Viborg	3	1480	67.66%	AB Gladsaxe	0	1273	12.32%	20.02%
3	2015-05-30	30.9	Viborg	3	1487	60.87%	@ Bronshoj	0	1241	16.36%	22.77%
4	2014-11-06	31.1	@ Aarhus GF	4	1420	59.77%	Vejle BK	0	1291	17.08%	23.15%
5	2015-04-02	31.9	@ Viborg	2	1486	65.92%	HB Koge	0	1297	13.29%	20.79%
6	2015-06-06	32.2	@ Vejle BK	2	1332	56.65%	Bronshoj	0	1231	19.23%	24.11%
7	2015-04-19	32.3	@ HB Koge	3	1311	51.15%	AB Gladsaxe	0	1256	23.41%	25.43%
8	2015-05-14	32.8	@ Lyngby	5	1369	61.58%	AB Gladsaxe	1	1224	15.90%	22.51%
9	2014-11-23	33.8	@ Viborg	2	1464	60.55%	Bronshoj	0	1328	16.57%	22.88%
10	2015-04-11	34.0	@ Vejle BK	4	1292	45.86%	Fredericia	0	1279	27.88%	26.26%
11	2015-05-24	34.2	@ FC Roskilde	2	1360	52.24%	Fredericia	0	1296	22.55%	25.21%
12	2014-11-02	34.3	@ Lyngby	2	1438	57.32%	FC Roskilde	0	1332	18.76%	23.92%
13	2015-05-03	34.4	@ FC Roskilde	3	1366	48.11%	Skive	0	1335	25.93%	25.96%
14	2014-10-17	34.5	@ Viborg	2	1445	57.39%	Fredericia	0	1338	18.71%	23.90%
15	2014-09-14	34.6	@ Horsens	3	1358	47.15%	Vejle BK	0	1335	26.75%	26.10%
16	2015-04-06	35.0	Horsens	3	1369	43.56%	@ AB Gladsaxe	0	1266	29.94%	26.50%
17	2015-04-06	35.4	@ FC Roskilde	2	1328	47.32%	Vejle BK	0	1303	26.61%	26.08%
18	2014-09-28	35.7	@ Lyngby	2	1380	49.47%	HB Koge	0	1338	24.79%	25.74%
19	2014-09-11	36.0	Aarhus GF	3	1448	46.56%	@ Vendsyssel	0	1323	27.27%	26.18%
20	2014-09-12	36.0	Viborg	2	1421	48.04%	@ AB Gladsaxe	0	1285	25.99%	25.97%
21	2015-04-25	36.7	Vendsyssel	3	1331	37.16%	@ Bronshoj	0	1275	36.05%	26.79%
22	2014-10-04	37.1	@ Bronshoj	1	1299	50.95%	AB Gladsaxe	0	1246	23.57%	25.47%
23	2015-05-03	37.1	@ Fredericia	1	1278	50.41%	AB Gladsaxe	0	1229	24.01%	25.57%
24	2014-10-19	37.2	@ Horsens	3	1374	60.14%	AB Gladsaxe	1	1242	16.84%	23.02%
25	2014-07-25	37.4	@ Lyngby	1	1367	52.95%	AB Gladsaxe	0	1298	22.00%	25.06%