2013-14 Superliga Season

198 games

Final

Champion

Aalborg

62 points · 4th Title

Last Title: 2007-08

Relegated

Viborg

28 pts

Aarhus GF · 32 pts

Biggest Overachiever

Aalborg

12.75 points above expected

62 points · 49.25 expected points

Biggest Disappointment

Viborg

9.92 points below expected

28 points · 37.92 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	Aalborg Champion	33	18	8	7	62	60	38	+22	49.25	+12.75
2	FC Copenhagen	33	15	11	7	56	54	38	+16	54.33	+1.67
3	Midtjylland	33	16	7	10	55	61	38	+23	53.94	+1.06
4	Brondby	33	13	13	7	52	47	38	+9	44.28	+7.72
5	Esbjerg	33	13	9	11	48	47	38	+9	48.41	-0.41
6	Nordsjaelland	33	13	7	13	46	38	44	-6	46.73	-0.73
7	Randers	33	9	14	10	41	41	45	-4	41.09	-0.09
8	Odense	33	10	10	13	40	47	46	+1	43.68	-3.68
9	Vestsjaelland	33	8	14	11	38	31	42	-11	34.62	+3.38
10	Sonderjyske	33	10	8	15	38	41	53	-12	38.97	-0.97
11	Aarhus GF Relegated	33	9	5	19	32	38	60	-22	41.45	-9.45
12	Viborg Relegated	33	6	10	17	28	38	63	-25	37.92	-9.92

Going into Phase 2, the championship group halved its Phase 1 points (rounded up); the relegation group kept its full Phase 1 points. Each group then played its own round-robin to determine final standings.

Form

Each team's 5-game rolling points-per-game across the season. Hot streaks push above the dashed 1.5 PPG reference line; cold spells drop below. Each team gets a distinct color; the legend below the plot lets you read off which line is which. (First 4 games of each team have no rolling window, so the lines start at game 5.)

League Race

Cumulative points across the season for each team. Highlighted teams are drawn in color (top finishers for the Title Race, bottom finishers for the Relegation Race); the rest of the league appears in light gray as context. Switch views with the buttons below.

Season Summary

Every team's regular-season finish compared against 100,000 simulations. Click any column header to sort. Luck is the team's actual points minus the sim's mean — positive means the team beat the model. Percentile is where the actual result fell in the team's sim distribution (e.g. 90% = the team did this well or better in only 10% of sims).

Team	Elo	Points	Avg	Luck	Percentile	Min	5th	Q1	Median	Q3	95th	Max
FC Copenhagen	1669	56	54.33	+1.67	61.6%	27	42	50	54	59	66	78
Aalborg	1650	62	49.25	+12.75	96.2%	25	38	44	49	54	61	78
Midtjylland	1647	55	53.94	+1.06	58.3%	29	42	49	54	59	66	79
Brondby	1617	52	44.28	+7.72	87.4%	15	33	39	44	49	56	73
Esbjerg	1611	48	48.41	-0.41	50.4%	24	36	44	48	53	60	74
Nordsjaelland	1590	46	46.73	-0.73	48.9%	18	35	42	47	52	59	73
Odense	1570	40	43.68	-3.68	33.9%	17	32	39	44	49	56	71
Randers	1554	41	41.09	-0.09	53.1%	18	30	36	41	46	53	70
Sonderjyske	1551	38	38.97	-0.97	48.0%	16	27	34	39	44	51	67
Vestsjaelland	1501	38	34.62	+3.38	71.8%	10	24	30	34	39	46	61
Aarhus GF	1493	32	41.45	-9.45	10.4%	17	30	37	41	46	53	67
Viborg	1464	28	37.92	-9.92	9.0%	13	27	33	38	43	50	65

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	AAL	AG	BRO	ESB	FC	MID	NOR	ODE	RAN	SON	VES	VIB
Aalborg	—	2-1-0 5.01	2-1-0 4.56	1-1-1 4.14	2-0-1 3.65	2-1-0 3.56	1-1-1 4.16	2-1-0 4.49	1-0-2 4.67	2-0-1 4.70	0-2-1 5.34	3-0-0 4.98
Aarhus GF	0-1-2 3.13	—	0-0-3 3.97	1-0-2 3.44	0-2-1 2.88	0-0-3 3.26	1-0-2 3.82	1-0-2 3.76	1-1-1 4.10	2-0-1 4.21	1-1-1 4.47	2-0-1 4.39
Brondby	0-1-2 3.52	3-0-0 4.12	—	1-1-1 3.91	1-1-1 3.37	2-0-1 3.17	1-2-0 3.95	1-1-1 4.06	1-2-0 4.42	1-1-1 4.54	1-2-0 4.93	1-2-0 4.36
Esbjerg	1-1-1 3.95	2-0-1 4.65	1-1-1 4.16	—	0-3-0 3.41	0-2-1 3.62	3-0-0 3.99	2-0-1 4.58	0-0-3 4.69	2-0-1 5.05	1-1-1 5.15	1-1-1 5.09
FC Copenhagen	1-0-2 4.43	1-2-0 5.26	1-1-1 4.72	0-3-0 4.69	—	1-0-2 4.10	1-1-1 4.53	3-0-0 5.05	0-2-1 5.20	2-1-0 5.40	2-1-0 5.68	3-0-0 5.20
Midtjylland	0-1-2 4.52	3-0-0 4.86	1-0-2 4.94	1-2-0 4.46	2-0-1 3.97	—	1-0-2 4.86	0-1-2 4.99	2-1-0 5.00	2-0-1 5.27	2-1-0 5.67	2-1-0 5.37
Nordsjaelland	1-1-1 3.91	2-0-1 4.26	0-2-1 4.12	0-0-3 4.08	1-1-1 3.55	2-0-1 3.24	—	2-0-1 4.09	2-1-0 4.49	1-0-2 4.66	0-1-2 5.19	2-1-0 5.08
Odense	0-1-2 3.59	2-0-1 4.31	1-1-1 4.02	1-0-2 3.51	0-0-3 3.07	2-1-0 3.13	1-0-2 3.98	—	1-2-0 4.14	1-2-0 4.38	0-1-2 4.83	1-2-0 4.68
Randers	2-0-1 3.43	1-1-1 3.97	0-2-1 3.66	3-0-0 3.40	1-2-0 2.93	0-1-2 3.12	0-1-2 3.59	0-2-1 3.93	—	1-1-1 4.48	0-2-1 4.52	1-2-0 4.17
Sonderjyske	1-0-2 3.39	1-0-2 3.86	1-1-1 3.55	1-0-2 3.07	0-1-2 2.75	1-0-2 2.88	2-0-1 3.43	0-2-1 3.70	1-1-1 3.60	—	1-2-0 4.45	1-1-1 4.30
Vestsjaelland	1-2-0 2.82	1-1-1 3.62	0-2-1 3.19	1-1-1 2.98	0-1-2 2.52	0-1-2 2.53	2-1-0 2.94	2-1-0 3.27	1-2-0 3.56	0-2-1 3.64	—	0-0-3 3.64
Viborg	0-0-3 3.14	1-0-2 3.69	0-2-1 3.72	1-1-1 3.05	0-0-3 2.95	0-1-2 2.80	0-1-2 3.04	0-2-1 3.41	0-2-1 3.90	1-1-1 3.79	3-0-0 4.44	—

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	0.69	+9.2
Allowed	0.76	-10.1
Differential	0.92	+6.1

Scoreline Distribution

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

View:

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.58%	8.08%	4.80%	2.78%	1.01%	0.25%	24.49%
1	8.08%	14.65%	6.82%	5.30%	1.77%	0.76%	37.37%
2	4.80%	6.82%	7.07%	2.27%	0.51%	0.76%	22.22%
3	2.78%	5.30%	2.27%	—	—	0.25%	10.61%
4	1.01%	1.77%	0.51%	—	—	—	3.28%
5+	0.25%	0.76%	0.76%	0.25%	—	—	2.02%
Total	24.49%	37.37%	22.22%	10.61%	3.28%	2.02%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.37	1.37	+0.00
SD	1.18	1.18	1.70
CV	0.86	0.86	—
Max	6	6	+5
Min	0	0	-5

Games Played: 198

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.82	1.15	+0.67
SD	1.38	1.00	1.57
CV	0.76	0.87	—
Max	5	3	+5
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.15	1.82	-0.67
SD	1.35	1.38	1.98
CV	1.17	0.76	—
Max	6	5	+3
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	3.03%	6.06%	—	—	—	21.21%
1	12.12%	15.15%	6.06%	3.03%	—	—	36.36%
2	3.03%	6.06%	12.12%	—	—	3.03%	24.24%
3	3.03%	9.09%	3.03%	—	—	—	15.15%
4	—	3.03%	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	30.30%	36.36%	27.27%	3.03%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.15	+0.27
SD	1.09	1.09	1.40
CV	0.77	0.95	—
Max	4	5	+3
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.15	+0.27
SD	1.35	1.03	1.81
CV	0.95	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%	6.06%	—	—	—	—	9.09%
1	12.12%	24.24%	6.06%	3.03%	—	3.03%	48.48%
2	6.06%	6.06%	6.06%	3.03%	—	—	21.21%
3	3.03%	3.03%	6.06%	—	—	—	12.12%
4	3.03%	6.06%	—	—	—	—	9.09%
5+	—	—	—	—	—	—	—
Total	27.27%	45.45%	18.18%	6.06%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.64	1.15	+0.48
SD	1.11	1.09	1.58
CV	0.68	0.95	—
Max	4	5	+4
Min	0	0	-4

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.85	1.15	+0.70
SD	1.48	1.00	1.78
CV	0.80	0.87	—
Max	5	3	+4
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	6.06%	3.03%	—	6.06%	—	18.18%
1	21.21%	12.12%	15.15%	3.03%	3.03%	—	54.55%
2	6.06%	6.06%	6.06%	—	3.03%	—	21.21%
3	3.03%	3.03%	—	—	—	—	6.06%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	33.33%	27.27%	24.24%	3.03%	12.12%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.15	1.33	-0.18
SD	0.80	1.31	1.67
CV	0.69	0.99	—
Max	3	4	+3
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	15.15%	3.03%	—	—	—	24.24%
1	6.06%	18.18%	9.09%	3.03%	—	—	36.36%
2	3.03%	9.09%	6.06%	6.06%	—	—	24.24%
3	—	3.03%	—	—	—	3.03%	6.06%
4	—	3.03%	3.03%	—	—	—	6.06%
5+	—	3.03%	—	—	—	—	3.03%
Total	15.15%	51.52%	21.21%	9.09%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.39	+0.03
SD	1.28	1.17	1.47
CV	0.90	0.84	—
Max	5	6	+4
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	9.09%	6.06%	3.03%	—	—	21.21%
1	6.06%	33.33%	3.03%	6.06%	3.03%	—	51.52%
2	—	3.03%	6.06%	—	—	—	9.09%
3	3.03%	9.09%	6.06%	—	—	—	18.18%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	12.12%	54.55%	21.21%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.24	1.36	-0.12
SD	1.00	0.93	1.41
CV	0.81	0.68	—
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%	—	—	21.21%
1	9.09%	12.12%	12.12%	12.12%	3.03%	3.03%	51.52%
2	6.06%	—	6.06%	—	—	—	12.12%
3	3.03%	6.06%	3.03%	—	—	—	12.12%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	27.27%	18.18%	30.30%	18.18%	3.03%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.24	1.61	-0.36
SD	1.03	1.32	1.90
CV	0.83	0.82	—
Max	4	5	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	15.15%	12.12%	9.09%	—	3.03%	—	39.39%
1	3.03%	18.18%	—	6.06%	3.03%	—	30.30%
2	3.03%	15.15%	9.09%	—	—	—	27.27%
3	—	3.03%	—	—	—	—	3.03%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	21.21%	48.48%	18.18%	6.06%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.94	1.27	-0.33
SD	0.90	1.07	1.36
CV	0.96	0.84	—
Max	3	4	+2
Min	0	0	-4

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.15	1.91	-0.76
SD	1.03	1.49	1.82
CV	0.90	0.78	—
Max	4	5	+3
Min	0	0	-5

Games Played: 33

Home-Field Advantage Edge

The simulation applies the same home-field boost to every game across the league, so the per-game home win probabilities bake in the model's idea of HFA. For each team, we sum expected points at home and compare to actual home points, and the same on the road. The bar shows (home points above expected) minus (away points above expected). A tall positive bar means the team's home/road split exceeded what the model predicted — a real fortress effect. A tall negative bar means the reverse: they played worse at home or better on the road than expected.

Top Overachievers & Disappointments

Teams that most beat — or most fell short of — their simulated point projections. A positive vsSim means the team accumulated more points than the model expected on average; a negative one means fewer.

Biggest Overachievers

#	Team	Actual	Sim	vsSim
1	Aalborg	62	49.25	+12.75
2	Brondby	52	44.28	+7.72
3	Vestsjaelland	38	34.62	+3.38
4	FC Copenhagen	56	54.33	+1.67
5	Midtjylland	55	53.94	+1.06

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Viborg	28	37.92	-9.92
2	Aarhus GF	32	41.45	-9.45
3	Odense	40	43.68	-3.68
4	Sonderjyske	38	38.97	-0.97
5	Nordsjaelland	46	46.73	-0.73

Top Streaks

Ranked by model unlikelihood — the product of pregame W/D/L probabilities over the games in each team's streak. A short streak by a poor team can outrank a longer one by a strong team since the poor team's per-game probabilities were lower going in. Unbeaten counts W or D consecutively; Winless counts L or D consecutively.

Most Unlikely Winning Streaks

#	Team	Games	Dates	Probability
1	Randers	4	Apr 4 – Apr 20	1 in 170
2	Midtjylland	5	Jul 19 – Aug 16	1 in 108
3	Aalborg	4	Mar 30 – Apr 16	1 in 50
4	Brondby	3	Sep 15 – Sep 28	1 in 40
5	Esbjerg	3	Feb 24 – Mar 9	1 in 18

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Viborg	7	Apr 13 – May 11	1 in 217
2	Sonderjyske	6	Sep 29 – Nov 9	1 in 184
3	Esbjerg	4	Oct 6 – Nov 3	1 in 169
4	Aarhus GF	6	Mar 24 – Apr 21	1 in 165
5	Nordsjaelland	4	Aug 25 – Sep 22	1 in 93

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Brondby	9	Sep 15 – Nov 24	1 in 77
2	Midtjylland	12	Jul 19 – Oct 19	1 in 49
3	Aalborg	10	Oct 27 – Mar 16	1 in 33
4	Vestsjaelland	6	Aug 5 – Sep 15	1 in 32
5	FC Copenhagen	9	Oct 6 – Feb 23	1 in 13

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Esbjerg	8	Oct 6 – Dec 8	1 in 55
2	FC Copenhagen	6	Jul 21 – Aug 25	1 in 25
3	Midtjylland	5	Sep 21 – Oct 26	1 in 24
4	Viborg	10	Mar 30 – May 18	1 in 17
5	Brondby	7	Jul 21 – Sep 1	1 in 15

Finish Position Heatmap

Each cell is the probability — across 100,000 simulations — that the team (row) finished at that position (column). Rows are sorted by actual finish (champion at top, bottom of the table at the bottom).

Team	1	2	3	4	5	6	7	8	9	10	11	12
Aalborg	12.34%	14.45%	14.35%	13.62%	11.28%	10.14%	8.01%	6.07%	4.17%	3.20%	1.54%	0.83%
FC Copenhagen	31.41%	22.49%	15.12%	10.59%	6.86%	4.96%	3.58%	2.18%	1.31%	0.78%	0.57%	0.15%
Midtjylland	30.75%	21.52%	15.24%	10.35%	7.97%	4.84%	3.75%	2.57%	1.43%	0.96%	0.45%	0.17%
Brondby	3.25%	6.18%	8.43%	9.90%	11.13%	11.51%	11.19%	10.84%	10.09%	7.99%	5.82%	3.67%
Esbjerg	9.37%	12.18%	14.25%	13.37%	12.48%	10.48%	8.22%	6.89%	5.11%	3.79%	2.74%	1.12%
Nordsjaelland	6.13%	9.45%	10.90%	11.79%	12.36%	11.22%	9.97%	8.95%	7.27%	6.00%	3.85%	2.11%
Randers	1.33%	2.81%	4.24%	6.43%	7.82%	9.02%	10.61%	11.82%	12.59%	12.54%	12.19%	8.60%
Odense	2.87%	5.28%	7.21%	9.10%	10.77%	10.58%	11.30%	11.79%	9.93%	9.21%	7.49%	4.47%
Vestsjaelland	0.07%	0.39%	0.85%	1.48%	2.13%	3.58%	5.22%	7.17%	9.78%	13.56%	20.68%	35.09%
Sonderjyske	0.75%	1.44%	2.63%	4.09%	5.16%	7.71%	9.59%	10.08%	13.50%	14.68%	15.82%	14.55%
Aarhus GF	1.37%	2.84%	4.99%	5.77%	7.73%	9.34%	10.76%	11.91%	12.58%	12.04%	11.13%	9.54%
Viborg	0.36%	0.97%	1.79%	3.51%	4.31%	6.62%	7.80%	9.73%	12.24%	15.25%	17.72%	19.70%

Points Required Per Position

The empirical CDF of simulated point totals per finishing position. Each curve shows, for one position (1st, 2nd, ..., last), the spread of point totals teams accumulated across simulations. Reading the curve at the 50% mark gives the median points typically needed to finish at that position. Steep curves mean the position is tightly clustered around a particular point range; shallow curves mean the position came with a wide variety of point totals.

Points Totals in Context

How did each team's actual results compare to their simulated points, Elo rating, average opponent Elo, and percentile within simulated outcomes? Use the buttons to switch between views. In each chart, dashed crosshairs at the league means split the plot into four quadrants: pastel green (team did well, model agreed), pastel red (team did poorly, model agreed), and pastel yellow (model and reality disagreed).

Season Trends

How each metric evolved across the season - Elo rating, actual and projected points, title/promotion probability, and relegation probability - day by day.

Edges & Scoring

How these are measured

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

Home Edge: Share of matches won by the home team minus the share won by the away team.
No Edge: under 5% * Slight Edge: 5% to 15% * Clear Edge: 15% to 25% * Strong Edge: 25% and up.
Elo Value: Number of Elo rating points one goal is worth. A team this many Elo points better than another is expected to win by one goal on a neutral field.
Scoring Tilt: Average home goals minus average away goals per match. The gold line is the home goals edge implied by the scoring value of an Elo point and the home-field Elo bonus.
Road-Tilted: under -0.2 * Neutral: -0.2 to 0.5 * Home-Tilted: 0.5 to 1.2 * Strong Home: 1.2 and up.

Home Edge

HomeDrawAway

+6.06%

Slight Edge

38.38%29.29%32.32%

Elo Value

Home Edge: 21.08 Elo pts.

185 Elo

0.005 goals per Elo point

0500

Scoring Tilt

Expected

+0.07 goals

Neutral

-2+0.11+2

Title Race

How these are measured

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

Title-Race Openness: Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 4 * Open: 4 to 6 * Wide Open: 6 and up.
Champion Preseason Odds: Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd * Middle of the Pack: 3rd to 6th * Longshot: 7th or lower.
Title Margin: Points-per-game gap between the champion and the runner-up. Shown per game so it reads the same across long and short seasons. The gold line is the winning margin the model expected, so a dot to the right means a more one-sided race than projected. A title won on goal difference shows 0.00.
Photo Finish: under 0.15 * Tight Race: 0.15 to 0.4 * Comfortable: 0.4 to 0.75 * Runaway: 0.75 and up.

Title-Race Openness

4.5

Open

124610

Champion Preseason Odds

12%

Aalborg, 3rd of 12

LongshotFavorite

Title Margin

Expected

0.18/gm

Tight Race

00.150.5/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 5.73 * Some Luck: 5.73 to 8.59 * Lucky: 8.59 to 11.46 * Wild Swing: 11.46 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 1.8 * Close: 1.8 to 2.69 * Off: 2.69 to 3.59 * Way Off: 3.59 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 1.07 * A Surprise: 1.07 to 1.71 * Several Surprises: 1.71 to 2.35 * Many Surprises: 2.35 and up.

Luck Spread

Expected

6.06 points

Some Luck

07.1618

Average Finish Error

Expected

1.50

Pinpoint

02.245

Biggest Overachiever

Expected 95.83%

96.25%

Aalborg

50100

Biggest Underachiever

Expected 4.17%

8.98%

Viborg

050

Season Outliers

Expected

1 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

1 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 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
Noll-Scully: How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.
Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
Interquartile Edge: Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.
Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
Best vs. Worst: Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.
Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
Close Games: Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
Blowouts: Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.
Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.

Gini Index

0.13

Even

00.120.180.260.5

Noll-Scully

Coin-flip

1.19

Moderate Separation

01.003

Interquartile Edge

62%

Slight Edge

50%60%70%80%100%

Best vs. Worst

Baseline

76%

Clear Edge

50%79%100%

Close Games

Expected

64%

Very Frequent

0%62%100%

Blowouts

Expected

15%

Frequent

0%14%100%

Predictability

How these are measured

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

Brier Score: How close the pregame probabilities landed to the actual result, averaged over the season. Confident, correct calls are rewarded most; confident misses are punished most. Lower is better; since draws are possible, a score under 0.66 beats guessing the base rate.
Highly Predictable: under 0.56 * Predictable: 0.56 to 0.62 * Hard to Predict: 0.62 to 0.66 * Coin-Flip: 0.66 and up.
Matchup Imbalance: How lopsided the matchups were on paper, averaging the gap between the two win probabilities over their sum. 0 means every match was a toss-up; 1 means every match was a heavy favorite against a big underdog.
Very Even: under 0.1 * Slight Separation: 0.1 to 0.18 * Notable Separation: 0.18 to 0.28 * Lopsided: 0.28 and up.
Strangeness: How wild the final table was versus what the model expected. A value of 1 means teams landed about one standard deviation from their projections on average. Above 1 is a stranger season; below 1 hugged the projections.
Very Predictable: under 0.8 * As Expected: 0.8 to 1.1 * Wilder Than Modeled: 1.1 to 1.4 * Chaotic: 1.4 and up.
Repeatability: How closely the final table order matched the preseason Elo order, by Spearman rank correlation. Higher means last season's ratings strongly predicted this season's finish. Shows N/A for an inaugural season.
Weak Carryover: under 0.3 * Some Carryover: 0.3 to 0.6 * Strong Carryover: 0.6 to 0.85 * Near-Lock: 0.85 and up.
Upset Rate: Share of matches the underdog won. The gold line is how often the model expected underdogs to win; a dot to the right means upsets ran hotter than expected.
Chalky: under 25% * As Expected: 25% to 33% * Upset-Prone: 33% to 42% * Very Upset-Prone: 42% and up.
Clear Favorite Upset Rate: Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 15% * As Expected: 15% to 25% * Shaky Favorites: 25% to 35% * Very Shaky: 35% and up.

Brier Score

Expected

0.65

Hard to Predict

00.652

Matchup Imbalance

0.21

Notable Separation

00.10.180.280.5

Strangeness

Expected

0.72

Very Predictable

01.002

Repeatability

0.58

Some Carryover

00.30.60.851

Upset Rate

Expected

30%

As Expected

0%28%50%

Clear Favorite Upset Rate

Expected

27%

Shaky Favorites

0%24%50%

Calibration

How these are measured

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

Probability calibration: An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope: Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE): The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.12 * Near Noise Ceiling: 0.12 to 0.17 * Above Noise: 0.17 to 0.23 * Well Above Noise: 0.23 and up.

Probability calibration

0.66

Excellent

0.010.050.10.51

Calibration slope

Ideal

0.85

Calibrated

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.050

Well Within Noise

00.1160.3

Next-Season Status

Across 100,000 regular-season simulations, the probability of each team's next-season status. Columns appear in best-to-worst outcome order: promotion-positive on the left, relegation-positive on the right. Cells with darker shading indicate higher likelihood.

Team	Same level	Direct relegation
Midtjylland	99.38%	0.62%
FC Copenhagen	99.28%	0.72%
Aalborg	97.63%	2.37%
Esbjerg	96.14%	3.86%
Nordsjaelland	94.04%	5.96%
Brondby	90.51%	9.49%
Odense	88.04%	11.96%
Aarhus GF	79.33%	20.67%
Randers	79.21%	20.79%
Sonderjyske	69.63%	30.37%
Viborg	62.58%	37.42%
Vestsjaelland	44.23%	55.77%

Filter by Team:

Overall Game Log

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

Date	Opponent	Score	Pre Elo	Opp Elo	Win %	Tie %	Loss %	Elo Δ	Points
2013-07-19	Midtjylland	L 0-2	1580	1597	34.94%	31.07%	34.00%	-10.5	0
2013-07-19	@ Aarhus GF	W 2-0	1597	1580	34.00%	31.07%	34.94%	+10.5	3
2013-07-20	Randers	D 2-2	1537	1558	34.52%	31.07%	34.41%	+0.0	1
2013-07-20	@ Viborg	D 2-2	1558	1537	34.41%	31.07%	34.52%	+0.0	1
2013-07-21	FC Copenhagen	W 2-1	1574	1634	29.24%	30.73%	40.03%	+5.8	3
2013-07-21	@ Aalborg	L 1-2	1634	1574	40.03%	30.73%	29.24%	-5.8	0
2013-07-21	Vestsjaelland	D 1-1	1566	1518	44.21%	30.02%	25.77%	-0.6	1
2013-07-21	@ Brondby	D 1-1	1518	1566	25.77%	30.02%	44.21%	+0.6	1
2013-07-21	Sonderjyske	D 1-1	1564	1572	36.38%	31.03%	32.59%	-0.1	1
2013-07-21	@ Odense	D 1-1	1572	1564	32.59%	31.03%	36.38%	+0.1	1
2013-07-22	Nordsjaelland	W 4-0	1595	1623	33.49%	31.06%	35.45%	+20.2	3
2013-07-22	@ Esbjerg	L 0-4	1623	1595	35.45%	31.06%	33.49%	-20.2	0
2013-07-26	Viborg	D 1-1	1602	1537	46.56%	29.45%	24.00%	-0.7	1
2013-07-26	@ Nordsjaelland	D 1-1	1537	1602	24.00%	29.45%	46.56%	+0.7	2
2013-07-27	Aarhus GF	L 0-2	1519	1569	30.51%	30.88%	38.61%	-9.6	1
2013-07-27	@ Vestsjaelland	W 2-0	1569	1519	38.61%	30.88%	30.51%	+9.6	3
2013-07-28	Brondby	W 1-0	1572	1566	38.33%	30.91%	30.76%	+5.1	4
2013-07-28	@ Sonderjyske	L 0-1	1566	1572	30.76%	30.91%	38.33%	-5.1	1
2013-07-28	FC Copenhagen	W 1-0	1608	1628	34.64%	31.07%	34.29%	+5.5	6
2013-07-28	@ Midtjylland	L 0-1	1628	1608	34.29%	31.07%	34.64%	-5.5	0
2013-07-28	Odense	D 1-1	1558	1564	36.69%	31.02%	32.29%	-0.1	2
2013-07-28	@ Randers	D 1-1	1564	1558	32.29%	31.02%	36.69%	+0.1	2
2013-07-29	Aalborg	L 1-2	1615	1579	42.51%	30.35%	27.14%	-6.0	3
2013-07-29	@ Esbjerg	W 2-1	1579	1615	27.14%	30.35%	42.51%	+6.1	6
2013-08-02	Sonderjyske	W 2-1	1613	1577	42.66%	30.33%	27.02%	+4.4	9
2013-08-02	@ Midtjylland	L 1-2	1577	1613	27.02%	30.33%	42.66%	-4.4	4
2013-08-03	Nordsjaelland	W 2-1	1579	1602	34.16%	31.07%	34.77%	+5.2	6
2013-08-03	@ Aarhus GF	L 1-2	1602	1579	34.77%	31.07%	34.16%	-5.2	1
2013-08-04	Esbjerg	L 0-2	1561	1609	30.75%	30.90%	38.35%	-9.6	1
2013-08-04	@ Brondby	W 2-0	1609	1561	38.35%	30.90%	30.75%	+9.6	6
2013-08-04	Randers	L 1-3	1622	1558	46.45%	29.47%	24.08%	-11.2	0
2013-08-04	@ FC Copenhagen	W 3-1	1558	1622	24.08%	29.47%	46.45%	+11.2	5
2013-08-04	Viborg	W 4-2	1564	1538	41.13%	30.58%	28.29%	+7.0	5
2013-08-04	@ Odense	L 2-4	1538	1564	28.29%	30.58%	41.13%	-7.0	2
2013-08-05	Aalborg	W 2-1	1509	1585	27.34%	30.40%	42.26%	+6.0	4
2013-08-05	@ Vestsjaelland	L 1-2	1585	1509	42.26%	30.40%	27.34%	-6.0	6
2013-08-09	Brondby	D 2-2	1531	1551	34.63%	31.07%	34.30%	-0.0	3
2013-08-09	@ Viborg	D 2-2	1551	1531	34.30%	31.07%	34.63%	+0.0	2
2013-08-10	Aarhus GF	W 5-1	1618	1584	42.38%	30.38%	27.25%	+13.9	9
2013-08-10	@ Esbjerg	L 1-5	1584	1618	27.25%	30.38%	42.38%	-13.9	6
2013-08-11	FC Copenhagen	D 2-2	1597	1611	35.41%	31.06%	33.53%	-0.0	2
2013-08-11	@ Nordsjaelland	D 2-2	1611	1597	33.53%	31.06%	35.41%	+0.0	1
2013-08-11	Midtjylland	L 1-3	1569	1618	30.70%	30.90%	38.40%	-8.3	5
2013-08-11	@ Randers	W 3-1	1618	1569	38.40%	30.90%	30.70%	+8.3	12
2013-08-11	Odense	D 0-0	1579	1571	38.70%	30.87%	30.42%	-0.3	7
2013-08-11	@ Aalborg	D 0-0	1571	1579	30.42%	30.87%	38.70%	+0.3	6
2013-08-12	Vestsjaelland	D 0-0	1572	1516	45.45%	29.73%	24.82%	-0.7	5
2013-08-12	@ Sonderjyske	D 0-0	1516	1572	24.82%	29.73%	45.45%	+0.7	5
2013-08-16	Brondby	W 5-2	1626	1551	47.90%	29.06%	23.04%	+8.1	15
2013-08-16	@ Midtjylland	L 2-5	1551	1626	23.04%	29.06%	47.90%	-8.1	2
2013-08-17	Aalborg	W 2-1	1597	1579	39.96%	30.74%	29.30%	+4.6	5
2013-08-17	@ Nordsjaelland	L 1-2	1579	1597	29.30%	30.74%	39.96%	-4.6	7
2013-08-18	Aarhus GF	D 1-1	1611	1570	43.28%	30.21%	26.51%	-0.5	2
2013-08-18	@ FC Copenhagen	D 1-1	1570	1611	26.51%	30.21%	43.28%	+0.5	7
2013-08-18	Odense	D 1-1	1516	1571	29.88%	30.81%	39.30%	+0.3	6
2013-08-18	@ Vestsjaelland	D 1-1	1571	1516	39.30%	30.81%	29.88%	-0.3	7
2013-08-18	Viborg	L 0-3	1572	1531	43.20%	30.22%	26.57%	-17.8	5
2013-08-18	@ Sonderjyske	W 3-0	1531	1572	26.57%	30.22%	43.20%	+17.8	6
2013-08-19	Esbjerg	W 3-2	1561	1632	27.87%	30.50%	41.63%	+5.7	8
2013-08-19	@ Randers	L 2-3	1632	1561	41.63%	30.50%	27.87%	-5.7	9
2013-08-23	Sonderjyske	W 3-1	1570	1554	39.84%	30.75%	29.41%	+8.0	10
2013-08-23	@ Aarhus GF	L 1-3	1554	1570	29.41%	30.75%	39.84%	-8.1	5
2013-08-25	Esbjerg	W 3-1	1549	1627	27.14%	30.35%	42.51%	+10.5	9
2013-08-25	@ Viborg	L 1-3	1627	1549	42.51%	30.35%	27.14%	-10.5	9
2013-08-25	Nordsjaelland	W 1-0	1571	1601	33.16%	31.05%	35.79%	+5.7	10
2013-08-25	@ Odense	L 0-1	1601	1571	35.79%	31.05%	33.16%	-5.7	5
2013-08-25	Randers	D 0-0	1543	1567	34.11%	31.07%	34.82%	+0.0	3
2013-08-25	@ Brondby	D 0-0	1567	1543	34.82%	31.07%	34.11%	-0.0	9
2013-08-25	Vestsjaelland	D 1-1	1611	1516	50.43%	28.24%	21.33%	-0.9	3
2013-08-25	@ FC Copenhagen	D 1-1	1516	1611	21.33%	28.24%	50.43%	+0.9	7
2013-08-26	Midtjylland	D 1-1	1574	1634	29.29%	30.73%	39.98%	+0.3	8
2013-08-26	@ Aalborg	D 1-1	1634	1574	39.98%	30.73%	29.29%	-0.3	16
2013-08-30	Aarhus GF	L 3-6	1577	1579	37.20%	30.99%	31.81%	-10.8	10
2013-08-30	@ Odense	W 6-3	1579	1577	31.81%	30.99%	37.20%	+10.8	13
2013-09-01	Brondby	W 2-1	1575	1543	41.98%	30.44%	27.58%	+4.4	11
2013-09-01	@ Aalborg	L 1-2	1543	1575	27.58%	30.44%	41.98%	-4.4	3
2013-09-01	FC Copenhagen	L 1-4	1559	1610	30.48%	30.88%	38.64%	-11.7	9
2013-09-01	@ Viborg	W 4-1	1610	1559	38.64%	30.88%	30.48%	+11.7	6
2013-09-01	Midtjylland	D 1-1	1616	1634	34.96%	31.07%	33.97%	-0.0	10
2013-09-01	@ Esbjerg	D 1-1	1634	1616	33.97%	31.07%	34.96%	+0.0	17
2013-09-01	Vestsjaelland	L 1-2	1595	1517	48.31%	28.94%	22.75%	-6.7	5
2013-09-01	@ Nordsjaelland	W 2-1	1517	1595	22.75%	28.94%	48.31%	+6.7	10
2013-09-02	Sonderjyske	L 0-2	1567	1546	40.42%	30.68%	28.90%	-11.7	9
2013-09-02	@ Randers	W 2-0	1546	1567	28.90%	30.68%	40.42%	+11.7	8
2013-09-13	Aalborg	L 1-3	1558	1579	34.38%	31.07%	34.55%	-9.0	8
2013-09-13	@ Sonderjyske	W 3-1	1579	1558	34.55%	31.07%	34.38%	+9.0	14
2013-09-14	Esbjerg	D 1-1	1621	1616	38.23%	30.91%	30.85%	-0.2	7
2013-09-14	@ FC Copenhagen	D 1-1	1616	1621	30.85%	30.91%	38.23%	+0.2	11
2013-09-15	Odense	W 2-1	1539	1566	33.60%	31.06%	35.34%	+5.3	6
2013-09-15	@ Brondby	L 1-2	1566	1539	35.34%	31.06%	33.60%	-5.3	10
2013-09-15	Randers	W 2-0	1524	1555	33.09%	31.05%	35.86%	+10.7	13
2013-09-15	@ Vestsjaelland	L 0-2	1555	1524	35.86%	31.05%	33.09%	-10.7	9
2013-09-15	Viborg	L 0-1	1589	1548	43.35%	30.19%	26.46%	-6.5	13
2013-09-15	@ Aarhus GF	W 1-0	1548	1589	26.46%	30.19%	43.35%	+6.5	12
2013-09-16	Nordsjaelland	W 2-1	1634	1589	43.82%	30.10%	26.08%	+4.2	20
2013-09-16	@ Midtjylland	L 1-2	1589	1634	26.08%	30.10%	43.82%	-4.2	5
2013-09-20	Aalborg	W 3-2	1544	1588	31.29%	30.95%	37.76%	+5.3	12
2013-09-20	@ Randers	L 2-3	1588	1544	37.76%	30.95%	31.29%	-5.3	14
2013-09-21	Viborg	D 0-0	1638	1554	49.08%	28.70%	22.22%	-0.9	21
2013-09-21	@ Midtjylland	D 0-0	1554	1638	22.22%	28.70%	49.08%	+0.9	13
2013-09-22	Brondby	L 1-3	1583	1544	42.98%	30.27%	26.76%	-10.6	13
2013-09-22	@ Aarhus GF	W 3-1	1544	1583	26.76%	30.27%	42.98%	+10.6	9
2013-09-22	Nordsjaelland	W 2-0	1549	1585	32.36%	31.02%	36.62%	+10.9	11
2013-09-22	@ Sonderjyske	L 0-2	1585	1549	36.62%	31.02%	32.36%	-10.9	5
2013-09-22	Odense	W 2-1	1621	1560	45.98%	29.60%	24.43%	+4.0	10
2013-09-22	@ FC Copenhagen	L 1-2	1560	1621	24.43%	29.60%	45.98%	-4.0	10
2013-09-23	Esbjerg	L 1-3	1535	1616	26.70%	30.25%	43.05%	-7.5	13
2013-09-23	@ Vestsjaelland	W 3-1	1616	1535	43.05%	30.25%	26.70%	+7.5	14
2013-09-27	Vestsjaelland	W 2-0	1555	1527	41.44%	30.53%	28.03%	+9.0	16
2013-09-27	@ Viborg	L 0-2	1527	1555	28.03%	30.53%	41.44%	-9.0	13
2013-09-28	FC Copenhagen	W 3-2	1554	1625	27.95%	30.52%	41.53%	+5.6	12
2013-09-28	@ Brondby	L 2-3	1625	1554	41.53%	30.52%	27.95%	-5.6	10
2013-09-29	Aarhus GF	D 0-0	1583	1572	39.01%	30.84%	30.15%	-0.3	15
2013-09-29	@ Aalborg	D 0-0	1572	1583	30.15%	30.84%	39.01%	+0.3	14
2013-09-29	Midtjylland	D 1-1	1556	1637	26.79%	30.28%	42.93%	+0.5	11
2013-09-29	@ Odense	D 1-1	1637	1556	42.93%	30.28%	26.79%	-0.5	22
2013-09-29	Sonderjyske	W 4-1	1624	1559	46.48%	29.47%	24.06%	+9.7	17
2013-09-29	@ Esbjerg	L 1-4	1559	1624	24.06%	29.47%	46.48%	-9.7	11
2013-09-30	Randers	W 1-0	1574	1549	40.93%	30.61%	28.46%	+4.8	8
2013-09-30	@ Nordsjaelland	L 0-1	1549	1574	28.46%	30.61%	40.93%	-4.8	12
2013-10-05	Aarhus GF	D 2-2	1545	1573	33.49%	31.06%	35.45%	+0.0	13
2013-10-05	@ Randers	D 2-2	1573	1545	35.45%	31.06%	33.49%	-0.0	15
2013-10-06	Brondby	D 1-1	1579	1560	40.10%	30.72%	29.18%	-0.3	9
2013-10-06	@ Nordsjaelland	D 1-1	1560	1579	29.18%	30.72%	40.10%	+0.3	13
2013-10-06	Odense	L 1-3	1634	1557	48.12%	29.00%	22.88%	-11.5	17
2013-10-06	@ Esbjerg	W 3-1	1557	1634	22.88%	29.00%	48.12%	+11.5	14
2013-10-06	Sonderjyske	W 2-1	1620	1550	47.20%	29.27%	23.53%	+3.9	13
2013-10-06	@ FC Copenhagen	L 1-2	1550	1620	23.53%	29.27%	47.20%	-3.9	11
2013-10-06	Viborg	W 3-1	1583	1564	40.12%	30.72%	29.17%	+8.0	18
2013-10-06	@ Aalborg	L 1-3	1564	1583	29.17%	30.72%	40.12%	-8.0	16
2013-10-07	Vestsjaelland	D 2-2	1637	1518	53.57%	27.04%	19.39%	-0.8	23
2013-10-07	@ Midtjylland	D 2-2	1518	1637	19.39%	27.04%	53.57%	+0.8	14
2013-10-18	Nordsjaelland	L 0-1	1573	1578	36.67%	31.02%	32.31%	-5.8	15
2013-10-18	@ Aarhus GF	W 1-0	1578	1573	32.31%	31.02%	36.67%	+5.8	12
2013-10-19	Randers	D 1-1	1636	1545	50.05%	28.37%	21.58%	-0.9	24
2013-10-19	@ Midtjylland	D 1-1	1545	1636	21.58%	28.37%	50.05%	+0.9	14
2013-10-20	Aalborg	W 3-0	1623	1591	42.12%	30.42%	27.46%	+12.8	16
2013-10-20	@ FC Copenhagen	L 0-3	1591	1623	27.46%	30.42%	42.12%	-12.8	18
2013-10-20	Esbjerg	W 2-1	1519	1622	24.43%	29.60%	45.97%	+6.4	17
2013-10-20	@ Vestsjaelland	L 1-2	1622	1519	45.97%	29.60%	24.43%	-6.4	17
2013-10-20	Viborg	D 0-0	1560	1556	38.10%	30.92%	30.98%	-0.2	14
2013-10-20	@ Brondby	D 0-0	1556	1560	30.98%	30.92%	38.10%	+0.2	17
2013-10-21	Odense	L 1-5	1546	1568	34.25%	31.07%	34.68%	-16.4	11
2013-10-21	@ Sonderjyske	W 5-1	1568	1546	34.68%	31.07%	34.25%	+16.4	17
2013-10-25	Vestsjaelland	W 4-1	1556	1526	41.85%	30.47%	27.69%	+10.9	20
2013-10-25	@ Viborg	L 1-4	1526	1556	27.69%	30.47%	41.85%	-10.9	17
2013-10-26	Midtjylland	W 2-1	1584	1635	30.38%	30.87%	38.75%	+5.7	15
2013-10-26	@ Nordsjaelland	L 1-2	1635	1584	38.75%	30.87%	30.38%	-5.7	24
2013-10-27	Brondby	D 0-0	1585	1560	40.98%	30.60%	28.42%	-0.4	18
2013-10-27	@ Odense	D 0-0	1560	1585	28.42%	30.60%	40.98%	+0.4	15
2013-10-27	FC Copenhagen	D 1-1	1546	1636	25.70%	30.00%	44.30%	+0.6	15
2013-10-27	@ Randers	D 1-1	1636	1546	44.30%	30.00%	25.70%	-0.6	17
2013-10-27	Sonderjyske	W 2-0	1578	1529	44.29%	30.00%	25.71%	+8.4	21
2013-10-27	@ Aalborg	L 0-2	1529	1578	25.71%	30.00%	44.29%	-8.4	11
2013-10-28	Aarhus GF	L 0-2	1616	1567	44.35%	29.98%	25.66%	-12.5	17
2013-10-28	@ Esbjerg	W 2-0	1567	1616	25.66%	29.98%	44.35%	+12.5	18
2013-11-01	Randers	L 1-3	1521	1546	33.90%	31.07%	35.04%	-8.9	11
2013-11-01	@ Sonderjyske	W 3-1	1546	1521	35.04%	31.07%	33.90%	+8.9	18
2013-11-02	Nordsjaelland	W 4-0	1636	1590	43.96%	30.07%	25.97%	+16.0	20
2013-11-02	@ FC Copenhagen	L 0-4	1590	1636	25.97%	30.07%	43.96%	-16.0	15
2013-11-02	Odense	W 1-0	1586	1584	37.75%	30.95%	31.30%	+5.2	24
2013-11-02	@ Aalborg	L 0-1	1584	1586	31.30%	30.95%	37.75%	-5.2	18
2013-11-03	Esbjerg	W 3-0	1629	1603	41.20%	30.57%	28.23%	+13.1	27
2013-11-03	@ Midtjylland	L 0-3	1603	1629	28.23%	30.57%	41.20%	-13.1	17
2013-11-03	Viborg	W 2-1	1579	1567	39.19%	30.82%	29.98%	+4.7	21
2013-11-03	@ Aarhus GF	L 1-2	1567	1579	29.98%	30.82%	39.19%	-4.7	20
2013-11-04	Brondby	L 0-2	1515	1561	31.04%	30.93%	38.03%	-9.7	17
2013-11-04	@ Vestsjaelland	W 2-0	1561	1515	38.03%	30.93%	31.04%	+9.7	18
2013-11-08	Midtjylland	L 2-3	1563	1642	26.89%	30.30%	42.81%	-4.1	20
2013-11-08	@ Viborg	W 3-2	1642	1563	42.81%	30.30%	26.89%	+4.1	30
2013-11-09	Sonderjyske	W 3-0	1574	1512	46.07%	29.57%	24.35%	+11.6	18
2013-11-09	@ Nordsjaelland	L 0-3	1512	1574	24.35%	29.57%	46.07%	-11.6	11
2013-11-10	Aarhus GF	W 3-0	1570	1584	35.53%	31.06%	33.41%	+14.8	21
2013-11-10	@ Brondby	L 0-3	1584	1570	33.41%	31.06%	35.53%	-14.8	21
2013-11-10	FC Copenhagen	D 1-1	1590	1652	29.04%	30.70%	40.26%	+0.3	18
2013-11-10	@ Esbjerg	D 1-1	1652	1590	40.26%	30.70%	29.04%	-0.3	21
2013-11-10	Vestsjaelland	L 1-3	1579	1505	47.79%	29.10%	23.11%	-11.5	18
2013-11-10	@ Odense	W 3-1	1505	1579	23.11%	29.10%	47.79%	+11.5	20
2013-11-11	Aalborg	L 1-4	1555	1591	32.32%	31.02%	36.66%	-12.2	18
2013-11-11	@ Randers	W 4-1	1591	1555	36.66%	31.02%	32.32%	+12.2	27
2013-11-22	Esbjerg	W 1-0	1501	1590	25.79%	30.02%	44.19%	+6.6	14
2013-11-22	@ Sonderjyske	L 0-1	1590	1501	44.19%	30.02%	25.79%	-6.6	18
2013-11-23	Odense	D 1-1	1543	1568	33.91%	31.07%	35.02%	+0.0	19
2013-11-23	@ Randers	D 1-1	1568	1543	35.02%	31.07%	33.91%	-0.0	19
2013-11-24	Brondby	L 0-1	1647	1585	46.06%	29.58%	24.36%	-6.8	30
2013-11-24	@ Midtjylland	W 1-0	1585	1647	24.36%	29.58%	46.06%	+6.8	24
2013-11-24	Vestsjaelland	D 2-2	1569	1516	44.87%	29.87%	25.26%	-0.4	22
2013-11-24	@ Aarhus GF	D 2-2	1516	1569	25.26%	29.87%	44.87%	+0.4	21
2013-11-24	Viborg	W 4-1	1651	1558	50.27%	28.30%	21.43%	+8.7	24
2013-11-24	@ FC Copenhagen	L 1-4	1558	1651	21.43%	28.30%	50.27%	-8.7	20
2013-11-25	Nordsjaelland	D 1-1	1604	1585	40.10%	30.72%	29.18%	-0.3	28
2013-11-25	@ Aalborg	D 1-1	1585	1604	29.18%	30.72%	40.10%	+0.3	19
2013-11-29	Midtjylland	L 0-1	1517	1640	22.51%	28.83%	48.65%	-4.0	21
2013-11-29	@ Vestsjaelland	W 1-0	1640	1517	48.65%	28.83%	22.51%	+4.0	33
2013-11-30	Sonderjyske	D 2-2	1550	1507	43.48%	30.17%	26.35%	-0.4	21
2013-11-30	@ Viborg	D 2-2	1507	1550	26.35%	30.17%	43.48%	+0.4	15
2013-12-01	Aarhus GF	W 4-1	1568	1569	37.36%	30.98%	31.67%	+12.0	22
2013-12-01	@ Odense	L 1-4	1569	1568	31.67%	30.98%	37.36%	-12.0	22
2013-12-01	FC Copenhagen	L 1-3	1592	1660	28.26%	30.57%	41.17%	-7.8	24
2013-12-01	@ Brondby	W 3-1	1660	1592	41.17%	30.57%	28.26%	+7.8	27
2013-12-01	Randers	D 1-1	1586	1543	43.50%	30.16%	26.34%	-0.5	20
2013-12-01	@ Nordsjaelland	D 1-1	1543	1586	26.34%	30.16%	43.50%	+0.5	20
2013-12-02	Aalborg	D 2-2	1584	1603	34.69%	31.07%	34.24%	-0.0	19
2013-12-02	@ Esbjerg	D 2-2	1603	1584	34.24%	31.07%	34.69%	+0.0	29
2013-12-06	Odense	W 2-0	1585	1580	38.24%	30.91%	30.85%	+9.6	23
2013-12-06	@ Nordsjaelland	L 0-2	1580	1585	30.85%	30.91%	38.24%	-9.6	22
2013-12-07	Vestsjaelland	W 1-0	1668	1513	58.15%	24.98%	16.87%	+2.9	30
2013-12-07	@ FC Copenhagen	L 0-1	1513	1668	16.87%	24.98%	58.15%	-3.0	21
2013-12-08	Aarhus GF	W 3-0	1644	1557	49.49%	28.56%	21.94%	+10.6	36
2013-12-08	@ Midtjylland	L 0-3	1557	1644	21.94%	28.56%	49.49%	-10.6	22
2013-12-08	Brondby	D 1-1	1508	1584	27.27%	30.38%	42.35%	+0.5	16
2013-12-08	@ Sonderjyske	D 1-1	1584	1508	42.35%	30.38%	27.27%	-0.5	25
2013-12-08	Esbjerg	W 1-0	1543	1584	31.78%	30.99%	37.23%	+5.8	23
2013-12-08	@ Randers	L 0-1	1584	1543	37.23%	30.99%	31.78%	-5.8	19
2013-12-09	Viborg	W 5-0	1603	1549	45.05%	29.83%	25.13%	+19.2	32
2013-12-09	@ Aalborg	L 0-5	1549	1603	25.13%	29.83%	45.05%	-19.2	21
2014-02-21	Sonderjyske	L 0-4	1510	1508	37.78%	30.95%	31.27%	-21.1	21
2014-02-21	@ Vestsjaelland	W 4-0	1508	1510	31.27%	30.95%	37.78%	+21.1	19
2014-02-22	Midtjylland	W 2-1	1570	1654	26.42%	30.19%	43.39%	+6.1	25
2014-02-22	@ Odense	L 1-2	1654	1570	43.39%	30.19%	26.42%	-6.2	36
2014-02-23	Aalborg	D 2-2	1584	1622	31.99%	31.00%	37.01%	+0.1	26
2014-02-23	@ Brondby	D 2-2	1622	1584	37.01%	31.00%	31.99%	-0.1	33
2014-02-23	FC Copenhagen	D 1-1	1546	1671	22.34%	28.75%	48.91%	+0.8	23
2014-02-23	@ Aarhus GF	D 1-1	1671	1546	48.91%	28.75%	22.34%	-0.8	31
2014-02-23	Randers	D 1-1	1530	1549	34.75%	31.07%	34.18%	-0.0	22
2014-02-23	@ Viborg	D 1-1	1549	1530	34.18%	31.07%	34.75%	+0.0	24
2014-02-24	Nordsjaelland	W 2-1	1578	1595	35.08%	31.07%	33.85%	+5.1	22
2014-02-24	@ Esbjerg	L 1-2	1595	1578	33.85%	31.07%	35.08%	-5.2	23
2014-02-28	Viborg	W 2-0	1590	1530	45.79%	29.64%	24.56%	+8.1	26
2014-02-28	@ Nordsjaelland	L 0-2	1530	1590	24.56%	29.64%	45.79%	-8.0	22
2014-03-01	Aarhus GF	L 1-2	1529	1547	34.93%	31.07%	34.00%	-5.3	19
2014-03-01	@ Sonderjyske	W 2-1	1547	1529	34.00%	31.07%	34.93%	+5.3	26
2014-03-02	Brondby	L 0-1	1549	1584	32.57%	31.03%	36.40%	-5.3	24
2014-03-02	@ Randers	W 1-0	1584	1549	36.40%	31.03%	32.57%	+5.3	29
2014-03-02	Midtjylland	L 1-5	1670	1648	40.60%	30.65%	28.75%	-18.5	31
2014-03-02	@ FC Copenhagen	W 5-1	1648	1670	28.75%	30.65%	40.60%	+18.5	39
2014-03-02	Odense	W 1-0	1583	1576	38.45%	30.90%	30.65%	+5.1	25
2014-03-02	@ Esbjerg	L 0-1	1576	1583	30.65%	30.90%	38.45%	-5.1	25
2014-03-02	Vestsjaelland	D 0-0	1622	1489	55.48%	26.22%	18.29%	-1.3	34
2014-03-02	@ Aalborg	D 0-0	1489	1622	18.29%	26.22%	55.48%	+1.3	22
2014-03-07	Randers	D 1-1	1490	1544	30.04%	30.83%	39.13%	+0.3	23
2014-03-07	@ Vestsjaelland	D 1-1	1544	1490	39.13%	30.83%	30.04%	-0.3	25
2014-03-08	Aalborg	L 2-5	1552	1621	28.17%	30.56%	41.27%	-9.6	26
2014-03-08	@ Aarhus GF	W 5-2	1621	1552	41.27%	30.56%	28.17%	+9.5	37
2014-03-09	Esbjerg	L 1-3	1522	1588	28.50%	30.61%	40.88%	-7.9	22
2014-03-09	@ Viborg	W 3-1	1588	1522	40.88%	30.61%	28.50%	+7.9	28
2014-03-09	FC Copenhagen	L 0-1	1571	1652	26.85%	30.29%	42.86%	-4.6	25
2014-03-09	@ Odense	W 1-0	1652	1571	42.86%	30.29%	26.85%	+4.6	34
2014-03-09	Nordsjaelland	W 4-1	1589	1598	36.27%	31.03%	32.69%	+12.3	32
2014-03-09	@ Brondby	L 1-4	1598	1589	32.69%	31.03%	36.27%	-12.3	26
2014-03-10	Sonderjyske	W 2-0	1667	1524	56.65%	25.69%	17.66%	+5.9	42
2014-03-10	@ Midtjylland	L 0-2	1524	1667	17.66%	25.69%	56.65%	-5.8	19
2014-03-14	FC Copenhagen	D 0-0	1518	1656	21.17%	28.16%	50.67%	+1.0	20
2014-03-14	@ Sonderjyske	D 0-0	1656	1518	50.67%	28.16%	21.17%	-1.0	35
2014-03-15	Vestsjaelland	L 1-2	1585	1490	50.52%	28.21%	21.27%	-6.9	26
2014-03-15	@ Nordsjaelland	W 2-1	1490	1585	21.27%	28.21%	50.52%	+6.9	26
2014-03-16	Brondby	D 0-0	1596	1601	36.72%	31.01%	32.27%	-0.2	29
2014-03-16	@ Esbjerg	D 0-0	1601	1596	32.27%	31.01%	36.72%	+0.1	33
2014-03-16	Midtjylland	W 1-0	1631	1672	31.58%	30.97%	37.45%	+5.9	40
2014-03-16	@ Aalborg	L 0-1	1672	1631	37.45%	30.97%	31.58%	-5.9	42
2014-03-16	Viborg	D 1-1	1567	1514	44.84%	29.88%	25.29%	-0.6	26
2014-03-16	@ Odense	D 1-1	1514	1567	25.29%	29.88%	44.84%	+0.6	23
2014-03-17	Aarhus GF	L 1-3	1544	1543	37.63%	30.96%	31.41%	-9.6	25
2014-03-17	@ Randers	W 3-1	1543	1544	31.41%	30.96%	37.63%	+9.6	29
2014-03-21	Viborg	L 0-1	1497	1515	35.00%	31.07%	33.94%	-5.6	26
2014-03-21	@ Vestsjaelland	W 1-0	1515	1497	33.94%	31.07%	35.00%	+5.6	26
2014-03-22	Nordsjaelland	L 0-1	1667	1578	49.65%	28.51%	21.84%	-7.2	42
2014-03-22	@ Midtjylland	W 1-0	1578	1667	21.84%	28.51%	49.65%	+7.2	29
2014-03-23	Aalborg	W 3-2	1519	1636	23.01%	29.05%	47.94%	+6.3	23
2014-03-23	@ Sonderjyske	L 2-3	1636	1519	47.94%	29.05%	23.01%	-6.3	40
2014-03-23	Odense	L 1-2	1602	1566	42.50%	30.35%	27.14%	-6.0	33
2014-03-23	@ Brondby	W 2-1	1566	1602	27.14%	30.35%	42.50%	+6.1	29
2014-03-23	Randers	D 1-1	1655	1534	53.91%	26.90%	19.19%	-1.1	36
2014-03-23	@ FC Copenhagen	D 1-1	1534	1655	19.19%	26.90%	53.91%	+1.1	26
2014-03-24	Esbjerg	L 0-3	1552	1596	31.34%	30.95%	37.70%	-14.2	29
2014-03-24	@ Aarhus GF	W 3-0	1596	1552	37.70%	30.95%	31.34%	+14.2	32
2014-03-28	Sonderjyske	D 2-2	1572	1525	44.06%	30.05%	25.89%	-0.4	30
2014-03-28	@ Odense	D 2-2	1525	1572	25.89%	30.05%	44.06%	+0.4	24
2014-03-29	Vestsjaelland	D 0-0	1610	1492	53.55%	27.05%	19.40%	-1.2	33
2014-03-29	@ Esbjerg	D 0-0	1492	1610	19.40%	27.05%	53.55%	+1.2	27
2014-03-30	Brondby	L 0-1	1520	1596	27.44%	30.42%	42.15%	-4.7	26
2014-03-30	@ Viborg	W 1-0	1596	1520	42.15%	30.42%	27.44%	+4.7	36
2014-03-30	FC Copenhagen	W 2-1	1630	1654	34.08%	31.07%	34.85%	+5.3	43
2014-03-30	@ Aalborg	L 1-2	1654	1630	34.85%	31.07%	34.08%	-5.2	36
2014-03-30	Midtjylland	L 0-3	1535	1659	22.39%	28.77%	48.84%	-10.8	26
2014-03-30	@ Randers	W 3-0	1659	1535	48.84%	28.77%	22.39%	+10.8	45
2014-03-31	Aarhus GF	W 1-0	1586	1538	44.17%	30.03%	25.81%	+4.5	32
2014-03-31	@ Nordsjaelland	L 0-1	1538	1586	25.81%	30.03%	44.17%	-4.5	29
2014-04-04	Randers	L 0-1	1534	1524	38.80%	30.86%	30.33%	-6.0	29
2014-04-04	@ Aarhus GF	W 1-0	1524	1534	30.33%	30.86%	38.80%	+6.0	29
2014-04-05	Aalborg	L 2-3	1670	1635	42.39%	30.37%	27.23%	-5.7	45
2014-04-05	@ Midtjylland	W 3-2	1635	1670	27.23%	30.37%	42.39%	+5.7	46
2014-04-06	Esbjerg	W 1-0	1600	1609	36.25%	31.04%	32.71%	+5.3	39
2014-04-06	@ Brondby	L 0-1	1609	1600	32.71%	31.04%	36.25%	-5.3	33
2014-04-06	Odense	D 2-2	1516	1572	29.75%	30.80%	39.45%	+0.2	27
2014-04-06	@ Viborg	D 2-2	1572	1516	39.45%	30.80%	29.75%	-0.2	31
2014-04-06	Sonderjyske	W 2-0	1649	1526	54.16%	26.80%	19.04%	+6.3	39
2014-04-06	@ FC Copenhagen	L 0-2	1526	1649	19.04%	26.80%	54.16%	-6.3	24
2014-04-07	Nordsjaelland	D 0-0	1493	1590	25.03%	29.80%	45.17%	+0.7	28
2014-04-07	@ Vestsjaelland	D 0-0	1590	1493	45.17%	29.80%	25.03%	-0.7	33
2014-04-11	Vestsjaelland	D 1-1	1519	1494	41.12%	30.58%	28.30%	-0.4	25
2014-04-11	@ Sonderjyske	D 1-1	1494	1519	28.30%	30.58%	41.12%	+0.4	29
2014-04-12	Odense	L 0-2	1664	1571	50.28%	28.30%	21.42%	-13.7	45
2014-04-12	@ Midtjylland	W 2-0	1571	1664	21.42%	28.30%	50.28%	+13.7	34
2014-04-13	Aarhus GF	W 1-0	1655	1528	54.72%	26.56%	18.72%	+3.3	42
2014-04-13	@ FC Copenhagen	L 0-1	1528	1655	18.72%	26.56%	54.72%	-3.3	29
2014-04-13	Brondby	W 2-0	1641	1606	42.52%	30.35%	27.13%	+8.7	49
2014-04-13	@ Aalborg	L 0-2	1606	1641	27.13%	30.35%	42.52%	-8.7	39
2014-04-13	Viborg	W 3-1	1530	1516	39.55%	30.78%	29.67%	+8.1	32
2014-04-13	@ Randers	L 1-3	1516	1530	29.67%	30.78%	39.55%	-8.1	27
2014-04-14	Esbjerg	L 0-1	1589	1603	35.47%	31.06%	33.47%	-5.6	33
2014-04-14	@ Nordsjaelland	W 1-0	1603	1589	33.47%	31.06%	35.47%	+5.6	36
2014-04-16	Aalborg	L 0-2	1508	1650	20.84%	27.97%	51.19%	-6.9	27
2014-04-16	@ Viborg	W 2-0	1650	1508	51.19%	27.97%	20.84%	+6.9	52
2014-04-17	FC Copenhagen	L 0-1	1494	1658	19.11%	26.85%	54.04%	-3.4	29
2014-04-17	@ Vestsjaelland	W 1-0	1658	1494	54.04%	26.85%	19.11%	+3.4	45
2014-04-17	Nordsjaelland	L 0-1	1585	1584	37.70%	30.96%	31.35%	-5.9	34
2014-04-17	@ Odense	W 1-0	1584	1585	31.35%	30.96%	37.70%	+5.9	36
2014-04-17	Randers	L 0-3	1609	1538	47.31%	29.24%	23.45%	-19.1	36
2014-04-17	@ Esbjerg	W 3-0	1538	1609	23.45%	29.24%	47.31%	+19.0	35
2014-04-18	Midtjylland	L 0-4	1524	1651	22.19%	28.68%	49.13%	-14.0	29
2014-04-18	@ Aarhus GF	W 4-0	1651	1524	49.13%	28.68%	22.19%	+14.0	48
2014-04-18	Sonderjyske	W 3-1	1597	1519	48.27%	28.95%	22.78%	+6.5	42
2014-04-18	@ Brondby	L 1-3	1519	1597	22.78%	28.95%	48.27%	-6.5	25
2014-04-20	Odense	W 1-0	1491	1579	25.93%	30.06%	44.01%	+6.6	32
2014-04-20	@ Vestsjaelland	L 0-1	1579	1491	44.01%	30.06%	25.93%	-6.6	34
2014-04-20	Randers	L 1-2	1657	1558	51.11%	28.00%	20.89%	-6.9	52
2014-04-20	@ Aalborg	W 2-1	1558	1657	20.89%	28.00%	51.11%	+7.0	38
2014-04-21	Brondby	L 1-2	1510	1603	25.46%	29.93%	44.61%	-4.1	29
2014-04-21	@ Aarhus GF	W 2-1	1603	1510	44.61%	29.93%	25.46%	+4.2	45
2014-04-21	Esbjerg	D 2-2	1662	1590	47.44%	29.20%	23.36%	-0.6	46
2014-04-21	@ FC Copenhagen	D 2-2	1590	1662	23.36%	29.20%	47.44%	+0.6	37
2014-04-21	Nordsjaelland	W 3-1	1512	1590	27.20%	30.37%	42.43%	+10.5	28
2014-04-21	@ Sonderjyske	L 1-3	1590	1512	42.43%	30.37%	27.20%	-10.5	36
2014-04-21	Viborg	W 5-2	1665	1501	59.23%	24.44%	16.33%	+5.7	51
2014-04-21	@ Midtjylland	L 2-5	1501	1665	16.33%	24.44%	59.23%	-5.7	27
2014-04-25	Sonderjyske	D 1-1	1564	1523	43.34%	30.20%	26.46%	-0.5	39
2014-04-25	@ Randers	D 1-1	1523	1564	26.46%	30.20%	43.34%	+0.5	29
2014-04-26	Aalborg	L 2-3	1573	1650	27.20%	30.37%	42.43%	-4.2	34
2014-04-26	@ Odense	W 3-2	1650	1573	42.43%	30.37%	27.20%	+4.2	55
2014-04-27	Aarhus GF	L 0-3	1495	1506	35.91%	31.05%	33.04%	-15.6	27
2014-04-27	@ Viborg	W 3-0	1506	1495	33.04%	31.05%	35.91%	+15.6	32
2014-04-27	FC Copenhagen	W 1-0	1579	1661	26.65%	30.24%	43.10%	+6.5	39
2014-04-27	@ Nordsjaelland	L 0-1	1661	1579	43.10%	30.24%	26.65%	-6.5	46
2014-04-27	Vestsjaelland	D 2-2	1607	1497	52.51%	27.47%	20.02%	-0.8	46
2014-04-27	@ Brondby	D 2-2	1497	1607	20.02%	27.47%	52.51%	+0.8	33
2014-04-28	Midtjylland	D 0-0	1591	1670	26.91%	30.30%	42.78%	+0.5	38
2014-04-28	@ Esbjerg	D 0-0	1670	1591	42.78%	30.30%	26.91%	-0.5	52
2014-05-02	Nordsjaelland	L 0-1	1564	1586	34.38%	31.07%	34.55%	-5.5	39
2014-05-02	@ Randers	W 1-0	1586	1564	34.55%	31.07%	34.38%	+5.5	42
2014-05-03	Esbjerg	L 0-2	1654	1591	46.26%	29.52%	24.22%	-12.9	55
2014-05-03	@ Aalborg	W 2-0	1591	1654	24.22%	29.52%	46.26%	+12.9	41
2014-05-04	Brondby	D 1-1	1655	1607	44.23%	30.01%	25.76%	-0.6	47
2014-05-04	@ FC Copenhagen	D 1-1	1607	1655	25.76%	30.01%	44.23%	+0.6	47
2014-05-04	Vestsjaelland	W 3-1	1670	1498	60.19%	23.95%	15.86%	+4.5	55
2014-05-04	@ Midtjylland	L 1-3	1498	1670	15.86%	23.95%	60.19%	-4.5	33
2014-05-04	Viborg	W 1-0	1523	1480	43.65%	30.13%	26.21%	+4.5	32
2014-05-04	@ Sonderjyske	L 0-1	1480	1523	26.21%	30.13%	43.65%	-4.5	27
2014-05-05	Odense	L 0-1	1522	1569	30.93%	30.92%	38.15%	-5.1	32
2014-05-05	@ Aarhus GF	W 1-0	1569	1522	38.15%	30.92%	30.93%	+5.1	37
2014-05-07	Aalborg	L 2-4	1591	1641	30.52%	30.88%	38.60%	-7.4	42
2014-05-07	@ Nordsjaelland	W 4-2	1641	1591	38.60%	30.88%	30.52%	+7.4	58
2014-05-07	Sonderjyske	W 2-1	1604	1528	48.05%	29.02%	22.93%	+3.8	44
2014-05-07	@ Esbjerg	L 1-2	1528	1604	22.93%	29.02%	48.05%	-3.8	32
2014-05-08	Aarhus GF	W 2-1	1494	1517	34.18%	31.07%	34.75%	+5.2	36
2014-05-08	@ Vestsjaelland	L 1-2	1517	1494	34.75%	31.07%	34.18%	-5.2	32
2014-05-08	FC Copenhagen	L 0-2	1475	1654	18.06%	26.03%	55.91%	-6.0	27
2014-05-08	@ Viborg	W 2-0	1654	1475	55.91%	26.03%	18.06%	+6.0	50
2014-05-08	Midtjylland	W 3-1	1607	1674	28.39%	30.60%	41.01%	+10.2	50
2014-05-08	@ Brondby	L 1-3	1674	1607	41.01%	30.60%	28.39%	-10.2	55
2014-05-08	Randers	W 2-1	1574	1558	39.65%	30.77%	29.58%	+4.7	40
2014-05-08	@ Odense	L 1-2	1558	1574	29.58%	30.77%	39.65%	-4.7	39
2014-05-11	Aalborg	D 0-0	1499	1649	20.22%	27.60%	52.18%	+1.1	37
2014-05-11	@ Vestsjaelland	D 0-0	1649	1499	52.18%	27.60%	20.22%	-1.1	59
2014-05-11	Esbjerg	L 1-2	1578	1608	33.27%	31.05%	35.68%	-5.1	40
2014-05-11	@ Odense	W 2-1	1608	1578	35.68%	31.05%	33.27%	+5.1	47
2014-05-11	FC Copenhagen	L 2-3	1664	1660	38.05%	30.93%	31.02%	-5.3	55
2014-05-11	@ Midtjylland	W 3-2	1660	1664	31.02%	30.93%	38.05%	+5.3	53
2014-05-11	Nordsjaelland	L 1-3	1469	1584	23.28%	29.17%	47.56%	-6.7	27
2014-05-11	@ Viborg	W 3-1	1584	1469	47.56%	29.17%	23.28%	+6.7	45
2014-05-11	Randers	D 1-1	1617	1554	46.37%	29.50%	24.14%	-0.7	51
2014-05-11	@ Brondby	D 1-1	1554	1617	24.14%	29.50%	46.37%	+0.7	40
2014-05-11	Sonderjyske	L 0-3	1511	1524	35.66%	31.05%	33.28%	-15.5	32
2014-05-11	@ Aarhus GF	W 3-0	1524	1511	33.28%	31.05%	35.66%	+15.5	35
2014-05-18	Aarhus GF	W 1-0	1647	1496	57.73%	25.18%	17.09%	+3.0	62
2014-05-18	@ Aalborg	L 0-1	1496	1647	17.09%	25.18%	57.73%	-3.0	32
2014-05-18	Brondby	D 2-2	1590	1617	33.71%	31.06%	35.23%	+0.0	46
2014-05-18	@ Nordsjaelland	D 2-2	1617	1590	35.23%	31.06%	33.71%	-0.0	52
2014-05-18	Midtjylland	W 3-1	1540	1659	22.86%	28.99%	48.16%	+11.5	38
2014-05-18	@ Sonderjyske	L 1-3	1659	1540	48.16%	28.99%	22.86%	-11.5	55
2014-05-18	Odense	W 3-2	1665	1573	50.17%	28.33%	21.50%	+3.4	56
2014-05-18	@ FC Copenhagen	L 2-3	1573	1665	21.50%	28.33%	50.17%	-3.4	40
2014-05-18	Vestsjaelland	D 1-1	1554	1500	45.12%	29.81%	25.07%	-0.6	41
2014-05-18	@ Randers	D 1-1	1500	1554	25.07%	29.81%	45.12%	+0.6	38
2014-05-18	Viborg	D 0-0	1613	1462	57.60%	25.24%	17.16%	-1.5	48
2014-05-18	@ Esbjerg	D 0-0	1462	1613	17.16%	25.24%	57.60%	+1.5	28

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	2014-04-20	20.89%	Randers	1558	2	@ Aalborg	1657	1
2	2014-03-15	21.27%	Vestsjaelland	1490	2	@ Nordsjaelland	1585	1
3	2014-04-12	21.42%	Odense	1571	2	@ Midtjylland	1664	0
4	2014-03-22	21.84%	Nordsjaelland	1578	1	@ Midtjylland	1667	0
5	2013-09-01	22.75%	Vestsjaelland	1517	2	@ Nordsjaelland	1595	1
6	2014-05-18	22.86%	@ Sonderjyske	1540	3	Midtjylland	1659	1
7	2013-10-06	22.88%	Odense	1557	3	@ Esbjerg	1634	1
8	2014-03-23	23.01%	@ Sonderjyske	1519	3	Aalborg	1636	2
9	2013-11-10	23.11%	Vestsjaelland	1505	3	@ Odense	1579	1
10	2014-04-17	23.45%	Randers	1538	3	@ Esbjerg	1609	0
11	2013-08-04	24.08%	Randers	1558	3	@ FC Copenhagen	1622	1
12	2014-05-03	24.22%	Esbjerg	1591	2	@ Aalborg	1654	0
13	2013-11-24	24.36%	Brondby	1585	1	@ Midtjylland	1647	0
14	2013-10-20	24.43%	@ Vestsjaelland	1519	2	Esbjerg	1622	1
15	2013-10-28	25.66%	Aarhus GF	1567	2	@ Esbjerg	1616	0
16	2013-11-22	25.79%	@ Sonderjyske	1501	1	Esbjerg	1590	0
17	2014-04-20	25.93%	@ Vestsjaelland	1491	1	Odense	1579	0
18	2014-02-22	26.42%	@ Odense	1570	2	Midtjylland	1654	1
19	2013-09-15	26.46%	Viborg	1548	1	@ Aarhus GF	1589	0
20	2013-08-18	26.57%	Viborg	1531	3	@ Sonderjyske	1572	0
21	2014-04-27	26.65%	@ Nordsjaelland	1579	1	FC Copenhagen	1661	0
22	2013-09-22	26.76%	Brondby	1544	3	@ Aarhus GF	1583	1
23	2013-07-29	27.14%	Aalborg	1579	2	@ Esbjerg	1615	1
24	2013-08-25	27.14%	@ Viborg	1549	3	Esbjerg	1627	1
25	2014-03-23	27.14%	Odense	1566	2	@ Brondby	1602	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	2014-02-21	21.10	Sonderjyske	4	1508	31.27%	@ Vestsjaelland	0	1510	37.78%	30.95%
2	2013-07-22	20.18	@ Esbjerg	4	1595	33.49%	Nordsjaelland	0	1623	35.45%	31.06%
3	2013-12-09	19.20	@ Aalborg	5	1603	45.05%	Viborg	0	1549	25.13%	29.83%
4	2014-04-17	19.05	Randers	3	1538	23.45%	@ Esbjerg	0	1609	47.31%	29.24%
5	2014-03-02	18.52	Midtjylland	5	1648	28.75%	@ FC Copenhagen	1	1670	40.60%	30.65%
6	2013-08-18	17.81	Viborg	3	1531	26.57%	@ Sonderjyske	0	1572	43.20%	30.22%
7	2013-10-21	16.42	Odense	5	1568	34.68%	@ Sonderjyske	1	1546	34.25%	31.07%
8	2013-11-02	16.01	@ FC Copenhagen	4	1636	43.96%	Nordsjaelland	0	1590	25.97%	30.07%
9	2014-04-27	15.59	Aarhus GF	3	1506	33.04%	@ Viborg	0	1495	35.91%	31.05%
10	2014-05-11	15.51	Sonderjyske	3	1524	33.28%	@ Aarhus GF	0	1511	35.66%	31.05%
11	2013-11-10	14.82	@ Brondby	3	1570	35.53%	Aarhus GF	0	1584	33.41%	31.06%
12	2014-03-24	14.16	Esbjerg	3	1596	37.70%	@ Aarhus GF	0	1552	31.34%	30.95%
13	2014-04-18	13.97	Midtjylland	4	1651	49.13%	@ Aarhus GF	0	1524	22.19%	28.68%
14	2013-08-10	13.87	@ Esbjerg	5	1618	42.38%	Aarhus GF	1	1584	27.25%	30.38%
15	2014-04-12	13.73	Odense	2	1571	21.42%	@ Midtjylland	0	1664	50.28%	28.30%
16	2013-11-03	13.09	@ Midtjylland	3	1629	41.20%	Esbjerg	0	1603	28.23%	30.57%
17	2014-05-03	12.90	Esbjerg	2	1591	24.22%	@ Aalborg	0	1654	46.26%	29.52%
18	2013-10-20	12.82	@ FC Copenhagen	3	1623	42.12%	Aalborg	0	1591	27.46%	30.42%
19	2013-10-28	12.50	Aarhus GF	2	1567	25.66%	@ Esbjerg	0	1616	44.35%	29.98%
20	2014-03-09	12.31	@ Brondby	4	1589	36.27%	Nordsjaelland	1	1598	32.69%	31.03%
21	2013-11-11	12.21	Aalborg	4	1591	36.66%	@ Randers	1	1555	32.32%	31.02%
22	2013-12-01	12.03	@ Odense	4	1568	37.36%	Aarhus GF	1	1569	31.67%	30.98%
23	2013-09-01	11.70	FC Copenhagen	4	1610	38.64%	@ Viborg	1	1559	30.48%	30.88%
24	2013-09-02	11.67	Sonderjyske	2	1546	28.90%	@ Randers	0	1567	40.42%	30.68%
25	2013-11-09	11.61	@ Nordsjaelland	3	1574	46.07%	Sonderjyske	0	1512	24.35%	29.57%