2015-16 Superliga Season

198 games

Final

Champion

FC Copenhagen

71 points · 11th Title

Last Title: 2012-13

Relegated

Hobro

18 pts

Biggest Overachiever

Sonderjyske

14.31 points above expected

62 points · 47.69 expected points

Biggest Disappointment

Hobro

11.67 points below expected

18 points · 29.67 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	FC Copenhagen Champion	33	21	8	4	71	62	28	+34	60.40	+10.60
2	Sonderjyske	33	19	5	9	62	56	36	+20	47.69	+14.31
3	Midtjylland	33	17	8	8	59	57	33	+24	58.37	+0.63
4	Brondby	33	16	6	11	54	43	37	+6	51.60	+2.40
5	Aalborg	33	15	5	13	50	56	44	+12	52.27	-2.27
6	Randers	33	13	8	12	47	45	43	+2	49.36	-2.36
7	Odense	33	14	4	15	46	50	52	-2	43.95	+2.05
8	Viborg	33	11	7	15	40	34	42	-8	39.07	+0.93
9	Nordsjaelland	33	11	5	17	38	35	51	-16	39.60	-1.60
10	Aarhus GF	33	8	13	12	37	47	49	-2	40.26	-3.26
11	Esbjerg	33	7	9	17	30	38	64	-26	38.84	-8.84
12	Hobro Relegated	33	4	6	23	18	26	70	-44	29.67	-11.67

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	1737	71	60.40	+10.60	93.3%	35	48	55	60	65	73	89
Midtjylland	1697	59	58.37	+0.63	55.8%	31	46	53	58	63	70	83
Sonderjyske	1653	62	47.69	+14.31	97.6%	20	35	43	48	53	60	75
Brondby	1618	54	51.60	+2.40	65.4%	22	39	46	52	57	64	81
Aalborg	1618	50	52.27	-2.27	41.1%	23	40	47	52	57	65	82
Randers	1592	47	49.36	-2.36	40.0%	16	37	44	49	54	62	76
Odense	1569	46	43.95	+2.05	63.3%	19	32	39	44	49	56	73
Aarhus GF	1544	37	40.26	-3.26	36.1%	16	28	35	40	45	53	66
Viborg	1528	40	39.07	+0.93	58.4%	13	27	34	39	44	51	67
Nordsjaelland	1508	38	39.60	-1.60	44.5%	16	28	35	40	44	52	67
Esbjerg	1466	30	38.84	-8.84	12.7%	12	27	34	39	44	51	68
Hobro	1387	18	29.67	-11.67	4.5%	8	19	25	30	34	41	58

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	HOB	MID	NOR	ODE	RAN	SON	VIB
Aalborg	—	1-1-1 5.02	3-0-0 4.26	1-1-1 5.35	0-0-3 3.33	3-0-0 5.64	0-2-1 3.78	1-0-2 5.14	1-0-2 5.10	1-1-1 4.66	2-0-1 4.64	2-0-1 5.30
Aarhus GF	1-1-1 3.32	—	1-1-1 3.24	1-1-1 4.52	0-2-1 2.36	1-1-1 5.03	1-1-1 2.37	1-1-1 4.17	1-2-0 3.69	1-0-2 3.64	0-2-1 3.85	0-1-2 3.96
Brondby	0-0-3 4.07	1-1-1 5.10	—	1-2-0 5.65	1-1-1 3.59	2-0-1 6.09	1-1-1 3.72	3-0-0 4.95	2-0-1 4.94	2-1-0 4.01	1-0-2 4.52	2-0-1 4.94
Esbjerg	1-1-1 3.01	1-1-1 3.81	0-2-1 2.72	—	0-0-3 2.66	0-3-0 5.03	0-1-2 2.80	2-1-0 3.87	1-0-2 3.88	1-0-2 3.30	0-0-3 3.71	1-0-2 4.10
FC Copenhagen	3-0-0 5.00	1-2-0 6.03	1-1-1 4.74	3-0-0 5.73	—	2-0-1 6.76	2-1-0 4.12	1-1-1 6.26	2-0-1 5.37	2-1-0 5.19	3-0-0 5.02	1-2-0 6.15
Hobro	0-0-3 2.73	1-1-1 3.32	1-0-2 2.30	0-3-0 3.31	1-0-2 1.70	—	0-0-3 1.76	0-0-3 3.53	1-0-2 2.59	0-1-2 2.27	0-0-3 2.53	0-1-2 3.59
Midtjylland	1-2-0 4.55	1-1-1 6.02	1-1-1 4.61	2-1-0 5.56	0-1-2 4.21	3-0-0 6.69	—	1-0-2 6.01	2-1-0 5.49	3-0-0 4.82	2-0-1 4.73	1-1-1 5.76
Nordsjaelland	2-0-1 3.21	1-1-1 4.15	0-0-3 3.39	0-1-2 4.46	1-1-1 2.15	3-0-0 4.82	2-0-1 2.38	—	0-0-3 4.04	0-1-2 3.21	0-0-3 3.99	2-1-0 3.93
Odense	2-0-1 3.24	0-2-1 4.64	1-0-2 3.39	2-0-1 4.45	1-0-2 2.98	2-0-1 5.79	0-1-2 2.87	3-0-0 4.29	—	0-1-2 4.05	0-0-3 3.60	3-0-0 4.64
Randers	1-1-1 3.67	2-0-1 4.69	0-1-2 4.33	2-0-1 5.04	0-1-2 3.15	2-1-0 6.13	0-0-3 3.52	2-1-0 5.14	2-1-0 4.29	—	1-2-0 4.30	1-0-2 5.12
Sonderjyske	1-0-2 3.70	1-2-0 4.49	2-0-1 3.81	3-0-0 4.64	0-0-3 3.32	3-0-0 5.84	1-0-2 3.61	3-0-0 4.35	3-0-0 4.74	0-2-1 4.04	—	2-1-0 5.17
Viborg	1-0-2 3.05	2-1-0 4.37	1-0-2 3.41	2-0-1 4.22	0-2-1 2.25	2-1-0 4.76	1-1-1 2.62	0-1-2 4.40	0-0-3 3.69	2-0-1 3.23	0-1-2 3.17	—

Points vs. Goals Scored, Allowed, and Differential

Points plotted against goals scored, allowed, and differential. Use the buttons to switch views; hover a team for exact values. The table gives each fit's R² and slope (the change in points per 10 goals).

Fit Metrics

	R²	Slope
Scored	0.77	+11.7
Allowed	0.88	-11.2
Differential	0.95	+6.5

Scoreline Distribution

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

View:

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.07%	8.33%	8.84%	2.27%	1.01%	0.76%	28.28%
1	8.33%	8.59%	8.59%	2.53%	1.52%	1.26%	30.81%
2	8.84%	8.59%	4.04%	2.27%	1.26%	0.51%	25.51%
3	2.27%	2.53%	2.27%	1.01%	—	0.25%	8.33%
4	1.01%	1.52%	1.26%	—	0.51%	—	4.29%
5+	0.76%	1.26%	0.51%	0.25%	—	—	2.78%
Total	28.28%	30.81%	25.51%	8.33%	4.29%	2.78%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.39	1.39	+0.00
SD	1.27	1.27	1.86
CV	0.92	0.92	—
Max	6	6	+6
Min	0	0	-6

Games Played: 198

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.70	1.33	+0.36
SD	1.59	1.36	2.26
CV	0.94	1.02	—
Max	6	6	+6
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	3.03%	9.09%	—	—	—	24.24%
1	—	9.09%	15.15%	3.03%	3.03%	—	30.30%
2	3.03%	9.09%	15.15%	3.03%	—	—	30.30%
3	6.06%	—	3.03%	3.03%	—	—	12.12%
4	—	—	—	—	—	—	—
5+	—	3.03%	—	—	—	—	3.03%
Total	21.21%	24.24%	42.42%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	1.48	-0.06
SD	1.17	1.03	1.52
CV	0.82	0.70	—
Max	5	4	+4
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	3.03%	12.12%	3.03%	—	—	27.27%
1	15.15%	6.06%	9.09%	3.03%	3.03%	—	36.36%
2	15.15%	9.09%	—	—	—	—	24.24%
3	—	—	3.03%	3.03%	—	—	6.06%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	3.03%	—	—	—	3.03%
Total	42.42%	18.18%	27.27%	9.09%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.30	1.12	+0.18
SD	1.21	1.17	1.72
CV	0.93	1.04	—
Max	5	4	+4
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	3.03%	12.12%	—	3.03%	—	27.27%
1	6.06%	9.09%	15.15%	3.03%	3.03%	6.06%	42.42%
2	—	12.12%	6.06%	3.03%	3.03%	—	24.24%
3	—	—	—	—	—	—	—
4	—	—	3.03%	—	3.03%	—	6.06%
5+	—	—	—	—	—	—	—
Total	15.15%	24.24%	36.36%	6.06%	12.12%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.15	1.94	-0.79
SD	1.03	1.41	1.56
CV	0.90	0.73	—
Max	4	5	+2
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	12.12%	6.06%	3.03%	—	—	—	21.21%
1	15.15%	9.09%	—	—	—	—	24.24%
2	9.09%	12.12%	3.03%	—	3.03%	—	27.27%
3	3.03%	6.06%	—	—	—	—	9.09%
4	3.03%	6.06%	3.03%	—	—	—	12.12%
5+	—	—	3.03%	3.03%	—	—	6.06%
Total	42.42%	39.39%	12.12%	3.03%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.88	0.85	+1.03
SD	1.58	0.97	1.49
CV	0.84	1.15	—
Max	6	4	+4
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	15.15%	18.18%	12.12%	—	6.06%	54.55%
1	3.03%	6.06%	9.09%	6.06%	3.03%	—	27.27%
2	3.03%	—	6.06%	—	—	—	9.09%
3	—	3.03%	—	—	—	—	3.03%
4	—	—	3.03%	—	3.03%	—	6.06%
5+	—	—	—	—	—	—	—
Total	9.09%	24.24%	36.36%	18.18%	6.06%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	0.79	2.12	-1.33
SD	1.14	1.43	1.87
CV	1.45	0.67	—
Max	4	6	+2
Min	0	0	-6

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.73	1.00	+0.73
SD	1.21	1.20	1.55
CV	0.70	1.20	—
Max	5	5	+4
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	9.09%	12.12%	6.06%	—	—	30.30%
1	12.12%	6.06%	12.12%	6.06%	3.03%	3.03%	42.42%
2	6.06%	9.09%	3.03%	—	—	—	18.18%
3	3.03%	3.03%	—	3.03%	—	—	9.09%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	24.24%	27.27%	27.27%	15.15%	3.03%	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.06	1.55	-0.48
SD	0.93	1.28	1.72
CV	0.88	0.83	—
Max	3	5	+3
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	15.15%	3.03%	—	3.03%	—	21.21%
1	12.12%	6.06%	6.06%	3.03%	3.03%	3.03%	33.33%
2	9.09%	6.06%	6.06%	3.03%	3.03%	3.03%	30.30%
3	3.03%	3.03%	3.03%	—	—	—	9.09%
4	—	—	—	—	—	—	—
5+	—	6.06%	—	—	—	—	6.06%
Total	24.24%	36.36%	18.18%	6.06%	9.09%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.52	1.58	-0.06
SD	1.28	1.48	2.05
CV	0.84	0.94	—
Max	5	5	+4
Min	0	0	-4

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.36	1.30	+0.06
SD	1.14	1.16	1.66
CV	0.84	0.89	—
Max	4	4	+3
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	3.03%	6.06%	9.09%	3.03%	—	—	21.21%
2	12.12%	21.21%	3.03%	3.03%	—	—	39.39%
3	3.03%	9.09%	3.03%	—	—	—	15.15%
4	6.06%	—	—	—	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	30.30%	45.45%	15.15%	6.06%	—	3.03%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.70	1.09	+0.61
SD	1.13	1.10	1.78
CV	0.67	1.01	—
Max	4	5	+4
Min	0	0	-5

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.03	1.27	-0.24
SD	1.42	1.18	1.90
CV	1.38	0.93	—
Max	6	5	+6
Min	0	0	-4

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	Sonderjyske	62	47.69	+14.31
2	FC Copenhagen	71	60.40	+10.60
3	Brondby	54	51.60	+2.40
4	Odense	46	43.95	+2.05
5	Viborg	40	39.07	+0.93

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Hobro	18	29.67	-11.67
2	Esbjerg	30	38.84	-8.84
3	Aarhus GF	37	40.26	-3.26
4	Randers	47	49.36	-2.36
5	Aalborg	50	52.27	-2.27

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	Hobro	2	May 15 – May 22	1 in 81
2	Aalborg	5	Nov 1 – Dec 7	1 in 45
3	Nordsjaelland	3	Sep 12 – Sep 27	1 in 39
4	Sonderjyske	5	Apr 17 – May 11	1 in 30
5	Odense	3	Mar 4 – Mar 19	1 in 18

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Aalborg	3	May 12 – May 22	1 in 55
2	Brondby	3	Jul 19 – Aug 2	1 in 41
3	Odense	3	May 15 – May 26	1 in 37
4	Hobro	5	Aug 17 – Sep 20	1 in 35
5	Randers	3	Mar 6 – Mar 20	1 in 23

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Sonderjyske	7	Nov 21 – Mar 20	1 in 25
2	FC Copenhagen	11	Oct 4 – Mar 13	1 in 22
3	Aarhus GF	5	May 8 – May 26	1 in 22
4	Esbjerg	5	Mar 6 – Apr 11	1 in 22
5	Brondby	7	Sep 27 – Nov 22	1 in 20

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Aarhus GF	10	Feb 26 – May 8	1 in 50
2	Hobro	16	Nov 1 – May 11	1 in 42
3	Midtjylland	5	Nov 20 – Mar 7	1 in 28
4	Aalborg	5	May 12 – May 29	1 in 24
5	Randers	5	Dec 5 – Mar 20	1 in 21

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
FC Copenhagen	43.91%	24.76%	13.52%	8.03%	4.78%	2.50%	1.53%	0.56%	0.22%	0.15%	0.04%	—
Sonderjyske	3.23%	7.07%	10.65%	12.47%	14.63%	14.11%	12.01%	9.69%	6.96%	5.17%	3.03%	0.98%
Midtjylland	30.01%	26.57%	17.05%	11.19%	6.80%	3.81%	2.21%	1.29%	0.63%	0.27%	0.14%	0.03%
Brondby	7.58%	12.83%	16.30%	16.19%	14.18%	11.46%	8.18%	6.41%	3.66%	2.11%	0.82%	0.28%
Aalborg	9.05%	14.42%	17.28%	16.94%	12.89%	10.42%	7.61%	5.05%	3.08%	2.06%	0.94%	0.26%
Randers	4.41%	8.44%	12.47%	14.67%	15.49%	13.14%	10.83%	8.32%	5.98%	3.67%	2.04%	0.54%
Odense	0.81%	2.95%	5.21%	7.67%	10.39%	12.75%	14.41%	13.32%	12.55%	10.10%	6.74%	3.10%
Viborg	0.21%	0.67%	1.52%	3.00%	4.93%	7.38%	10.00%	13.20%	15.43%	17.32%	17.30%	9.04%
Nordsjaelland	0.29%	0.74%	1.87%	3.38%	5.06%	7.47%	10.33%	13.41%	15.94%	16.90%	16.09%	8.52%
Aarhus GF	0.26%	0.94%	2.54%	3.90%	6.16%	9.00%	11.80%	13.90%	15.19%	14.74%	13.91%	7.66%
Esbjerg	0.24%	0.59%	1.57%	2.43%	4.33%	7.25%	9.48%	12.07%	15.21%	17.42%	18.83%	10.58%
Hobro	—	0.02%	0.02%	0.13%	0.36%	0.71%	1.61%	2.78%	5.15%	10.09%	20.12%	59.01%

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

+13.13%

Slight Edge

45.96%21.21%32.83%

Elo Value

Home Edge: 45.89 Elo pts.

166 Elo

0.006 goals per Elo point

0500

Scoring Tilt

Expected

+0.32 goals

Neutral

-2+0.28+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

3.3

Top-Heavy

124610

Champion Preseason Odds

44%

FC Copenhagen, 1st of 12

LongshotFavorite

Title Margin

Expected

0.27/gm

Tight Race

00.170.5/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 5.88 * Some Luck: 5.88 to 8.82 * Lucky: 8.82 to 11.76 * Wild Swing: 11.76 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 1.45 * Close: 1.45 to 2.18 * Off: 2.18 to 2.9 * Way Off: 2.9 and up.
Biggest Overachiever: The team that finished highest inside its own range of simulated outcomes. The gold line is where the top team in a league of 12 typically lands.
Biggest Underachiever: The team that finished lowest inside its own range of simulated outcomes. The gold line is where the bottom team in a league of 12 typically lands.
Season Outliers: Number of teams that finished above the 95th or below the 5th percentile of their own simulated range. Even a well-calibrated model expects about 10% of teams in the extremes.
Minimal Outliers: under 12 * As Expected: 12 to 19.2 * Several Outliers: 19.2 to 26.4 * Many Outliers: 26.4 and up.
Unexpected Relegations: Number of teams that were actually relegated but were not in the model's projected bottom field of the same size. The gold line is how many the model expected to miss on average.
As Expected: under 0.5 * A Surprise: 0.5 to 0.8 * Several Surprises: 0.8 to 1.1 * Many Surprises: 1.1 and up.

Luck Spread

Expected

6.87 points

Some Luck

07.3518

Average Finish Error

Expected

1.00

Pinpoint

01.814

Biggest Overachiever

Expected 95.83%

97.60%

Sonderjyske

50100

Biggest Underachiever

Expected 4.17%

4.46%

Hobro

050

Season Outliers

Expected

2 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

0 of 1

As Expected

00.41

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

0.17

Even

00.120.180.260.5

Noll-Scully

Coin-flip

1.70

Strong Separation

01.003

Interquartile Edge

65%

Slight Edge

50%60%70%80%100%

Best vs. Worst

Baseline

88%

Strong Edge

50%88%100%

Close Games

Expected

60%

Very Frequent

0%58%100%

Blowouts

Expected

15%

Frequent

0%18%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

0.59

Predictable

00.612

Matchup Imbalance

0.28

Lopsided

00.10.180.280.5

Strangeness

Expected

0.90

As Expected

01.002

Repeatability

0.63

Strong Carryover

00.30.60.851

Upset Rate

Expected

26%

As Expected

0%28%50%

Clear Favorite Upset Rate

Expected

17%

As Expected

0%23%50%

Calibration

How these are measured

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

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

Probability calibration

0.24

Well Calibrated

0.010.050.10.51

Calibration slope

Ideal

1.14

Calibrated

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.111

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
FC Copenhagen	100%	—
Midtjylland	99.97%	0.03%
Aalborg	99.74%	0.26%
Brondby	99.72%	0.28%
Randers	99.46%	0.54%
Sonderjyske	99.02%	0.98%
Odense	96.90%	3.10%
Aarhus GF	92.34%	7.66%
Nordsjaelland	91.48%	8.52%
Viborg	90.96%	9.04%
Esbjerg	89.42%	10.58%
Hobro	40.99%	59.01%

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
2015-07-17	Sonderjyske	L 0-2	1555	1539	47.39%	22.22%	30.39%	-16.4	0
2015-07-17	@ Nordsjaelland	W 2-0	1539	1555	30.39%	22.22%	47.39%	+16.4	3
2015-07-18	Viborg	W 2-0	1642	1540	57.81%	20.99%	21.20%	+8.4	3
2015-07-18	@ Midtjylland	L 0-2	1540	1642	21.20%	20.99%	57.81%	-8.4	0
2015-07-19	Brondby	W 2-1	1536	1606	35.31%	22.46%	42.23%	+7.5	3
2015-07-19	@ Aarhus GF	L 1-2	1606	1536	42.23%	22.46%	35.31%	-7.5	0
2015-07-19	Hobro	W 3-0	1556	1536	47.88%	22.19%	29.93%	+16.5	3
2015-07-19	@ Odense	L 0-3	1536	1556	29.93%	22.19%	47.88%	-16.5	0
2015-07-20	Esbjerg	D 1-1	1598	1575	48.24%	22.16%	29.59%	-0.7	1
2015-07-20	@ Aalborg	D 1-1	1575	1598	29.59%	22.16%	48.24%	+0.8	1
2015-07-24	Aalborg	L 0-1	1520	1597	34.37%	22.43%	43.20%	-6.7	0
2015-07-24	@ Hobro	W 1-0	1597	1520	43.20%	22.43%	34.37%	+6.7	4
2015-07-24	Midtjylland	L 1-2	1555	1650	32.04%	22.33%	45.63%	-6.0	3
2015-07-24	@ Sonderjyske	W 2-1	1650	1555	45.63%	22.33%	32.04%	+6.0	6
2015-07-26	FC Copenhagen	L 1-2	1576	1632	37.24%	22.49%	40.27%	-6.8	1
2015-07-26	@ Esbjerg	W 2-1	1632	1576	40.27%	22.49%	37.24%	+6.8	3
2015-07-26	Nordsjaelland	W 3-0	1603	1538	53.60%	21.62%	24.78%	+14.0	3
2015-07-26	@ Randers	L 0-3	1538	1603	24.78%	21.62%	53.60%	-14.0	0
2015-07-26	Odense	L 1-2	1599	1573	48.67%	22.13%	29.20%	-8.4	0
2015-07-26	@ Brondby	W 2-1	1573	1599	29.20%	22.13%	48.67%	+8.4	6
2015-07-27	Aarhus GF	D 0-0	1532	1543	43.66%	22.41%	33.93%	-0.4	1
2015-07-27	@ Viborg	D 0-0	1543	1532	33.93%	22.41%	43.66%	+0.4	4
2015-07-31	Esbjerg	W 2-1	1532	1569	39.95%	22.50%	37.55%	+6.8	4
2015-07-31	@ Viborg	L 1-2	1569	1532	37.55%	22.50%	39.95%	-6.8	1
2015-07-31	Odense	W 1-0	1656	1581	54.78%	21.47%	23.75%	+4.9	9
2015-07-31	@ Midtjylland	L 0-1	1581	1656	23.75%	21.47%	54.78%	-4.9	6
2015-08-02	FC Copenhagen	L 1-3	1549	1639	32.66%	22.36%	44.98%	-10.5	3
2015-08-02	@ Sonderjyske	W 3-1	1639	1549	44.98%	22.36%	32.66%	+10.5	6
2015-08-02	Hobro	L 0-2	1590	1513	55.05%	21.43%	23.52%	-18.7	0
2015-08-02	@ Brondby	W 2-0	1513	1590	23.52%	21.43%	55.05%	+18.7	3
2015-08-02	Randers	W 3-2	1544	1617	34.85%	22.44%	42.71%	+7.1	7
2015-08-02	@ Aarhus GF	L 2-3	1617	1544	42.71%	22.44%	34.85%	-7.2	3
2015-08-03	Aalborg	W 2-1	1524	1604	34.08%	22.42%	43.50%	+7.6	3
2015-08-03	@ Nordsjaelland	L 1-2	1604	1524	43.50%	22.42%	34.08%	-7.6	4
2015-08-07	Aarhus GF	D 2-2	1576	1551	48.59%	22.13%	29.28%	-0.6	7
2015-08-07	@ Odense	D 2-2	1551	1576	29.28%	22.13%	48.59%	+0.6	8
2015-08-08	Viborg	D 1-1	1532	1538	44.28%	22.39%	33.33%	-0.4	4
2015-08-08	@ Hobro	D 1-1	1538	1532	33.33%	22.39%	44.28%	+0.4	5
2015-08-09	Brondby	D 3-3	1610	1572	50.32%	21.99%	27.69%	-0.6	4
2015-08-09	@ Randers	D 3-3	1572	1610	27.69%	21.99%	50.32%	+0.6	1
2015-08-09	Nordsjaelland	D 1-1	1650	1532	59.63%	20.65%	19.72%	-1.7	7
2015-08-09	@ FC Copenhagen	D 1-1	1532	1650	19.72%	20.65%	59.63%	+1.7	4
2015-08-09	Sonderjyske	L 0-4	1562	1538	48.40%	22.15%	29.45%	-31.7	1
2015-08-09	@ Esbjerg	W 4-0	1538	1562	29.45%	22.15%	48.40%	+31.7	6
2015-08-10	Midtjylland	L 0-2	1596	1661	36.09%	22.48%	41.43%	-13.2	4
2015-08-10	@ Aalborg	W 2-0	1661	1596	41.43%	22.48%	36.09%	+13.2	12
2015-08-14	FC Copenhagen	D 0-0	1674	1648	48.68%	22.13%	29.19%	-0.9	13
2015-08-14	@ Midtjylland	D 0-0	1648	1674	29.19%	22.13%	48.68%	+0.9	8
2015-08-15	Aalborg	L 2-3	1551	1583	40.79%	22.49%	36.72%	-6.9	8
2015-08-15	@ Aarhus GF	W 3-2	1583	1551	36.72%	22.49%	40.79%	+6.9	7
2015-08-16	Brondby	L 0-4	1539	1572	40.56%	22.49%	36.95%	-27.4	5
2015-08-16	@ Viborg	W 4-0	1572	1539	36.95%	22.49%	40.56%	+27.4	4
2015-08-16	Esbjerg	L 1-2	1534	1531	45.62%	22.33%	32.05%	-8.0	4
2015-08-16	@ Nordsjaelland	W 2-1	1531	1534	32.05%	22.33%	45.62%	+7.9	4
2015-08-16	Randers	L 2-3	1576	1610	40.43%	22.49%	37.08%	-6.8	7
2015-08-16	@ Odense	W 3-2	1610	1576	37.08%	22.49%	40.43%	+6.8	7
2015-08-17	Hobro	W 3-0	1570	1531	50.34%	21.98%	27.68%	+15.4	9
2015-08-17	@ Sonderjyske	L 0-3	1531	1570	27.68%	21.98%	50.34%	-15.4	4
2015-08-21	Nordsjaelland	L 1-3	1516	1526	43.85%	22.41%	33.75%	-13.3	4
2015-08-21	@ Hobro	W 3-1	1526	1516	33.75%	22.41%	43.85%	+13.3	7
2015-08-23	Aarhus GF	D 2-2	1649	1545	58.18%	20.93%	20.90%	-1.2	9
2015-08-23	@ FC Copenhagen	D 2-2	1545	1649	20.90%	20.93%	58.18%	+1.2	9
2015-08-23	Midtjylland	D 1-1	1539	1673	27.22%	21.93%	50.85%	+1.0	5
2015-08-23	@ Esbjerg	D 1-1	1673	1539	50.85%	21.93%	27.22%	-1.0	14
2015-08-23	Sonderjyske	W 1-0	1600	1586	47.09%	22.24%	30.67%	+6.1	7
2015-08-23	@ Brondby	L 0-1	1586	1600	30.67%	22.24%	47.09%	-6.1	9
2015-08-23	Viborg	L 0-1	1617	1511	58.25%	20.91%	20.84%	-10.4	7
2015-08-23	@ Randers	W 1-0	1511	1617	20.84%	20.91%	58.25%	+10.4	8
2015-08-24	Odense	W 5-1	1590	1569	48.04%	22.18%	29.78%	+17.8	10
2015-08-24	@ Aalborg	L 1-5	1569	1590	29.78%	22.18%	48.04%	-17.8	7
2015-08-28	Esbjerg	D 0-0	1546	1540	46.03%	22.30%	31.66%	-0.6	10
2015-08-28	@ Aarhus GF	D 0-0	1540	1546	31.66%	22.30%	46.03%	+0.6	6
2015-08-29	Viborg	W 2-1	1579	1522	52.69%	21.74%	25.58%	+5.0	12
2015-08-29	@ Sonderjyske	L 1-2	1522	1579	25.58%	21.74%	52.69%	-5.0	8
2015-08-30	Brondby	L 0-2	1539	1606	35.83%	22.47%	41.70%	-13.1	7
2015-08-30	@ Nordsjaelland	W 2-0	1606	1539	41.70%	22.47%	35.83%	+13.1	10
2015-08-30	FC Copenhagen	W 1-0	1551	1648	31.79%	22.31%	45.89%	+8.5	10
2015-08-30	@ Odense	L 0-1	1648	1551	45.89%	22.31%	31.79%	-8.5	9
2015-08-30	Hobro	W 2-0	1672	1503	64.91%	19.42%	15.67%	+6.3	17
2015-08-30	@ Midtjylland	L 0-2	1503	1672	15.67%	19.42%	64.91%	-6.3	4
2015-08-30	Randers	L 0-2	1608	1606	45.42%	22.34%	32.24%	-15.8	10
2015-08-30	@ Aalborg	W 2-0	1606	1608	32.24%	22.34%	45.42%	+15.8	10
2015-09-11	Aarhus GF	L 0-3	1496	1545	38.35%	22.50%	39.15%	-20.1	4
2015-09-11	@ Hobro	W 3-0	1545	1496	39.15%	22.50%	38.35%	+20.1	13
2015-09-12	Nordsjaelland	L 0-1	1517	1526	43.95%	22.40%	33.64%	-8.2	8
2015-09-12	@ Viborg	W 1-0	1526	1517	33.64%	22.40%	43.95%	+8.2	10
2015-09-13	Aalborg	W 4-2	1639	1592	51.42%	21.88%	26.70%	+8.0	12
2015-09-13	@ FC Copenhagen	L 2-4	1592	1639	26.70%	21.88%	51.42%	-8.0	10
2015-09-13	Midtjylland	D 0-0	1619	1679	36.79%	22.49%	40.73%	+0.2	11
2015-09-13	@ Brondby	D 0-0	1679	1619	40.73%	22.49%	36.79%	-0.2	18
2015-09-13	Sonderjyske	W 1-0	1622	1584	50.17%	22.00%	27.83%	+5.7	13
2015-09-13	@ Randers	L 0-1	1584	1622	27.83%	22.00%	50.17%	-5.7	12
2015-09-14	Odense	W 4-2	1540	1559	42.55%	22.45%	35.01%	+10.0	9
2015-09-14	@ Esbjerg	L 2-4	1559	1540	35.01%	22.45%	42.55%	-10.0	10
2015-09-16	Randers	W 3-0	1647	1628	47.84%	22.19%	29.97%	+16.5	15
2015-09-16	@ FC Copenhagen	L 0-3	1628	1647	29.97%	22.19%	47.84%	-16.5	13
2015-09-18	Sonderjyske	L 1-2	1565	1579	43.32%	22.43%	34.26%	-7.6	13
2015-09-18	@ Aarhus GF	W 2-1	1579	1565	34.26%	22.43%	43.32%	+7.6	15
2015-09-19	Viborg	W 2-0	1549	1509	50.57%	21.96%	27.47%	+10.5	13
2015-09-19	@ Odense	L 0-2	1509	1549	27.47%	21.96%	50.57%	-10.5	8
2015-09-20	Brondby	W 4-1	1584	1619	40.30%	22.49%	37.21%	+16.5	13
2015-09-20	@ Aalborg	L 1-4	1619	1584	37.21%	22.49%	40.30%	-16.5	11
2015-09-20	Hobro	W 1-0	1664	1476	66.58%	18.94%	14.48%	+3.1	18
2015-09-20	@ FC Copenhagen	L 0-1	1476	1664	14.48%	18.94%	66.58%	-3.1	4
2015-09-20	Nordsjaelland	L 0-1	1678	1534	62.40%	20.05%	17.55%	-11.1	18
2015-09-20	@ Midtjylland	W 1-0	1534	1678	17.55%	20.05%	62.40%	+11.1	13
2015-09-21	Randers	L 0-2	1550	1611	36.61%	22.48%	40.91%	-13.4	9
2015-09-21	@ Esbjerg	W 2-0	1611	1550	40.91%	22.48%	36.61%	+13.3	16
2015-09-25	Aalborg	W 1-0	1498	1600	31.11%	22.27%	46.62%	+8.6	11
2015-09-25	@ Viborg	L 0-1	1600	1498	46.62%	22.27%	31.11%	-8.6	13
2015-09-25	Odense	W 4-0	1586	1560	48.74%	22.12%	29.14%	+21.0	18
2015-09-25	@ Sonderjyske	L 0-4	1560	1586	29.14%	22.12%	48.74%	-21.0	13
2015-09-27	Aarhus GF	W 2-0	1545	1558	43.51%	22.42%	34.07%	+12.6	16
2015-09-27	@ Nordsjaelland	L 0-2	1558	1545	34.07%	22.42%	43.51%	-12.6	13
2015-09-27	FC Copenhagen	W 1-0	1602	1667	36.14%	22.48%	41.39%	+7.8	14
2015-09-27	@ Brondby	L 0-1	1667	1602	41.39%	22.48%	36.14%	-7.8	18
2015-09-27	Midtjylland	L 0-2	1624	1667	39.20%	22.50%	38.30%	-14.1	16
2015-09-27	@ Randers	W 2-0	1667	1624	38.30%	22.50%	39.20%	+14.1	21
2015-09-28	Esbjerg	D 2-2	1473	1537	36.24%	22.48%	41.28%	+0.1	5
2015-09-28	@ Hobro	D 2-2	1537	1473	41.28%	22.48%	36.24%	-0.1	10
2015-10-02	Odense	L 1-5	1558	1539	47.75%	22.20%	30.06%	-26.1	16
2015-10-02	@ Nordsjaelland	W 5-1	1539	1558	30.06%	22.20%	47.75%	+26.1	16
2015-10-03	Hobro	W 2-1	1610	1473	61.67%	20.22%	18.11%	+3.6	19
2015-10-03	@ Randers	L 1-2	1473	1610	18.11%	20.22%	61.67%	-3.6	5
2015-10-04	Aarhus GF	W 2-0	1681	1545	61.61%	20.23%	18.16%	+7.2	24
2015-10-04	@ Midtjylland	L 0-2	1545	1681	18.16%	20.23%	61.61%	-7.2	13
2015-10-04	Esbjerg	D 1-1	1610	1537	54.62%	21.49%	23.89%	-1.3	15
2015-10-04	@ Brondby	D 1-1	1537	1610	23.89%	21.49%	54.62%	+1.3	11
2015-10-04	Sonderjyske	W 5-0	1592	1607	43.06%	22.43%	34.51%	+29.8	16
2015-10-04	@ Aalborg	L 0-5	1607	1592	34.51%	22.43%	43.06%	-29.8	18
2015-10-04	Viborg	W 1-0	1659	1507	63.21%	19.86%	16.93%	+3.6	21
2015-10-04	@ FC Copenhagen	L 0-1	1507	1659	16.93%	19.86%	63.21%	-3.6	11
2015-10-16	Randers	W 2-1	1689	1614	54.74%	21.47%	23.79%	+4.7	27
2015-10-16	@ Midtjylland	L 1-2	1614	1689	23.79%	21.47%	54.74%	-4.6	19
2015-10-17	Sonderjyske	L 1-2	1565	1578	43.46%	22.42%	34.12%	-7.6	16
2015-10-17	@ Odense	W 2-1	1578	1565	34.12%	22.42%	43.46%	+7.6	21
2015-10-18	Brondby	L 0-2	1503	1609	30.67%	22.24%	47.09%	-11.6	11
2015-10-18	@ Viborg	W 2-0	1609	1503	47.09%	22.24%	30.67%	+11.6	18
2015-10-18	Hobro	W 3-1	1663	1470	67.07%	18.80%	14.13%	+4.9	24
2015-10-18	@ FC Copenhagen	L 1-3	1470	1663	14.13%	18.80%	67.07%	-4.9	5
2015-10-18	Nordsjaelland	W 3-0	1538	1532	46.01%	22.31%	31.69%	+17.3	16
2015-10-18	@ Aarhus GF	L 0-3	1532	1538	31.69%	22.31%	46.01%	-17.3	16
2015-10-19	Aalborg	L 1-2	1538	1622	33.51%	22.40%	44.10%	-6.2	11
2015-10-19	@ Esbjerg	W 2-1	1622	1538	44.10%	22.40%	33.51%	+6.2	19
2015-10-23	Aarhus GF	W 3-1	1465	1555	32.67%	22.36%	44.97%	+13.6	8
2015-10-23	@ Hobro	L 1-3	1555	1465	44.97%	22.36%	32.67%	-13.6	16
2015-10-24	Esbjerg	W 4-2	1492	1532	39.58%	22.50%	37.92%	+10.6	14
2015-10-24	@ Viborg	L 2-4	1532	1492	37.92%	22.50%	39.58%	-10.6	11
2015-10-25	Aalborg	W 3-0	1514	1628	29.72%	22.17%	48.11%	+24.1	19
2015-10-25	@ Nordsjaelland	L 0-3	1628	1514	48.11%	22.17%	29.72%	-24.2	19
2015-10-25	FC Copenhagen	L 1-2	1585	1667	33.71%	22.40%	43.88%	-6.2	21
2015-10-25	@ Sonderjyske	W 2-1	1667	1585	43.88%	22.40%	33.71%	+6.2	27
2015-10-25	Midtjylland	W 2-1	1621	1693	34.99%	22.45%	42.56%	+7.5	21
2015-10-25	@ Brondby	L 1-2	1693	1621	42.56%	22.45%	34.99%	-7.5	27
2015-10-26	Odense	D 1-1	1609	1557	52.00%	21.81%	26.19%	-1.1	20
2015-10-26	@ Randers	D 1-1	1557	1609	26.19%	21.81%	52.00%	+1.0	17
2015-10-30	Nordsjaelland	W 2-1	1521	1539	42.78%	22.44%	34.78%	+6.4	14
2015-10-30	@ Esbjerg	L 1-2	1539	1521	34.78%	22.44%	42.78%	-6.4	19
2015-10-31	Viborg	L 2-4	1686	1502	66.21%	19.05%	14.74%	-17.1	27
2015-10-31	@ Midtjylland	W 4-2	1502	1686	14.74%	19.05%	66.21%	+17.1	17
2015-11-01	Brondby	L 2-5	1558	1628	35.41%	22.46%	42.13%	-13.8	17
2015-11-01	@ Odense	W 5-2	1628	1558	42.13%	22.46%	35.41%	+13.8	24
2015-11-01	Hobro	W 6-0	1604	1478	60.44%	20.49%	19.07%	+21.1	22
2015-11-01	@ Aalborg	L 0-6	1478	1604	19.07%	20.49%	60.44%	-21.1	8
2015-11-01	Randers	W 4-0	1674	1608	53.64%	21.62%	24.74%	+18.3	30
2015-11-01	@ FC Copenhagen	L 0-4	1608	1674	24.74%	21.62%	53.64%	-18.3	20
2015-11-02	Sonderjyske	D 0-0	1541	1579	39.92%	22.50%	37.58%	-0.1	17
2015-11-02	@ Aarhus GF	D 0-0	1579	1541	37.58%	22.50%	39.92%	+0.1	22
2015-11-06	Aalborg	L 1-2	1579	1625	38.78%	22.50%	38.72%	-7.0	22
2015-11-06	@ Sonderjyske	W 2-1	1625	1579	38.72%	22.50%	38.78%	+7.0	25
2015-11-06	Aarhus GF	W 4-1	1590	1541	51.60%	21.86%	26.54%	+12.5	23
2015-11-06	@ Randers	L 1-4	1541	1590	26.54%	21.86%	51.60%	-12.5	17
2015-11-07	Nordsjaelland	L 0-1	1457	1532	34.70%	22.44%	42.86%	-6.8	8
2015-11-07	@ Hobro	W 1-0	1532	1457	42.86%	22.44%	34.70%	+6.8	22
2015-11-08	Esbjerg	W 5-1	1669	1528	62.09%	20.12%	17.78%	+11.2	30
2015-11-08	@ Midtjylland	L 1-5	1528	1669	17.78%	20.12%	62.09%	-11.2	14
2015-11-08	FC Copenhagen	D 0-0	1642	1692	38.14%	22.50%	39.36%	+0.1	25
2015-11-08	@ Brondby	D 0-0	1692	1642	39.36%	22.50%	38.14%	-0.0	31
2015-11-08	Odense	L 0-1	1519	1545	41.68%	22.47%	35.85%	-7.8	17
2015-11-08	@ Viborg	W 1-0	1545	1519	35.85%	22.47%	41.68%	+7.8	20
2015-11-20	Midtjylland	D 1-1	1552	1680	28.05%	22.02%	49.92%	+0.9	21
2015-11-20	@ Odense	D 1-1	1680	1552	49.92%	22.02%	28.05%	-0.9	31
2015-11-21	Sonderjyske	L 1-2	1539	1572	40.57%	22.49%	36.94%	-7.2	22
2015-11-21	@ Nordsjaelland	W 2-1	1572	1539	36.94%	22.49%	40.57%	+7.2	25
2015-11-22	Brondby	D 1-1	1529	1642	29.75%	22.17%	48.08%	+0.7	18
2015-11-22	@ Aarhus GF	D 1-1	1642	1529	48.08%	22.17%	29.75%	-0.7	26
2015-11-22	Hobro	D 4-4	1516	1451	53.68%	21.61%	24.71%	-0.6	15
2015-11-22	@ Esbjerg	D 4-4	1451	1516	24.71%	21.61%	53.68%	+0.6	9
2015-11-22	Viborg	D 0-0	1692	1511	65.93%	19.13%	14.94%	-2.5	32
2015-11-22	@ FC Copenhagen	D 0-0	1511	1692	14.94%	19.13%	65.93%	+2.5	18
2015-11-23	Randers	W 3-2	1632	1603	49.09%	22.09%	28.81%	+5.2	28
2015-11-23	@ Aalborg	L 2-3	1603	1632	28.81%	22.09%	49.09%	-5.2	23
2015-11-27	Aarhus GF	W 1-0	1514	1529	43.06%	22.43%	34.50%	+6.8	21
2015-11-27	@ Viborg	L 0-1	1529	1514	34.50%	22.43%	43.06%	-6.8	18
2015-11-28	Nordsjaelland	W 1-0	1597	1532	53.67%	21.62%	24.71%	+5.1	26
2015-11-28	@ Randers	L 0-1	1532	1597	24.71%	21.62%	53.67%	-5.1	22
2015-11-29	Aalborg	L 0-2	1641	1637	45.77%	22.32%	31.92%	-15.9	26
2015-11-29	@ Brondby	W 2-0	1637	1641	31.92%	22.32%	45.77%	+16.0	31
2015-11-29	Hobro	W 2-0	1579	1451	60.74%	20.42%	18.84%	+7.5	28
2015-11-29	@ Sonderjyske	L 0-2	1451	1579	18.84%	20.42%	60.74%	-7.5	9
2015-11-30	Esbjerg	W 2-1	1553	1516	50.19%	22.00%	27.81%	+5.3	24
2015-11-30	@ Odense	L 1-2	1516	1553	27.81%	22.00%	50.19%	-5.3	15
2015-12-04	Midtjylland	W 2-1	1523	1679	24.83%	21.63%	53.54%	+9.1	21
2015-12-04	@ Aarhus GF	L 1-2	1679	1523	53.54%	21.63%	24.83%	-9.1	31
2015-12-05	Randers	D 0-0	1444	1602	24.58%	21.59%	53.83%	+1.3	10
2015-12-05	@ Hobro	D 0-0	1602	1444	53.83%	21.59%	24.58%	-1.3	27
2015-12-06	Brondby	L 0-2	1527	1625	31.58%	22.30%	46.12%	-11.9	22
2015-12-06	@ Nordsjaelland	W 2-0	1625	1527	46.12%	22.30%	31.58%	+11.8	29
2015-12-06	Odense	W 4-1	1690	1559	61.02%	20.36%	18.61%	+9.1	35
2015-12-06	@ FC Copenhagen	L 1-4	1559	1690	18.61%	20.36%	61.02%	-9.1	24
2015-12-06	Sonderjyske	L 0-1	1510	1587	34.47%	22.43%	43.10%	-6.8	15
2015-12-06	@ Esbjerg	W 1-0	1587	1510	43.10%	22.43%	34.47%	+6.7	31
2015-12-07	Viborg	W 2-0	1653	1521	61.17%	20.33%	18.50%	+7.4	34
2015-12-07	@ Aalborg	L 0-2	1521	1653	18.50%	20.33%	61.17%	-7.4	21
2016-02-26	Aarhus GF	D 2-2	1550	1532	47.60%	22.21%	30.19%	-0.5	25
2016-02-26	@ Odense	D 2-2	1532	1550	30.19%	22.21%	47.60%	+0.5	22
2016-02-27	Sonderjyske	D 1-1	1601	1594	46.22%	22.29%	31.49%	-0.6	28
2016-02-27	@ Randers	D 1-1	1594	1601	31.49%	22.29%	46.22%	+0.6	32
2016-02-28	Esbjerg	W 2-1	1699	1504	67.26%	18.74%	14.00%	+2.8	38
2016-02-28	@ FC Copenhagen	L 1-2	1504	1699	14.00%	18.74%	67.26%	-2.8	15
2016-02-28	Hobro	W 1-0	1637	1445	66.99%	18.82%	14.19%	+3.0	32
2016-02-28	@ Brondby	L 0-1	1445	1637	14.19%	18.82%	66.99%	-3.0	10
2016-02-28	Nordsjaelland	D 1-1	1513	1515	44.99%	22.36%	32.65%	-0.5	22
2016-02-28	@ Viborg	D 1-1	1515	1513	32.65%	22.36%	44.99%	+0.5	23
2016-02-29	Aalborg	D 1-1	1670	1660	46.50%	22.28%	31.23%	-0.6	32
2016-02-29	@ Midtjylland	D 1-1	1660	1670	31.23%	22.28%	46.50%	+0.6	35
2016-03-03	FC Copenhagen	L 0-1	1669	1701	40.72%	22.49%	36.79%	-7.7	32
2016-03-03	@ Midtjylland	W 1-0	1701	1669	36.79%	22.49%	40.72%	+7.7	41
2016-03-04	Odense	L 0-1	1661	1549	58.99%	20.78%	20.23%	-10.6	35
2016-03-04	@ Aalborg	W 1-0	1549	1661	20.23%	20.78%	58.99%	+10.5	28
2016-03-05	Viborg	L 0-6	1442	1513	35.26%	22.46%	42.28%	-36.0	10
2016-03-05	@ Hobro	W 6-0	1513	1442	42.28%	22.46%	35.26%	+36.0	25
2016-03-06	Brondby	W 3-1	1594	1640	38.76%	22.50%	38.74%	+12.1	35
2016-03-06	@ Sonderjyske	L 1-3	1640	1594	38.74%	22.50%	38.76%	-12.1	32
2016-03-06	FC Copenhagen	D 0-0	1532	1709	22.74%	21.29%	55.97%	+1.5	23
2016-03-06	@ Aarhus GF	D 0-0	1709	1532	55.97%	21.29%	22.74%	-1.5	42
2016-03-06	Randers	W 1-0	1501	1601	31.42%	22.29%	46.29%	+8.5	18
2016-03-06	@ Esbjerg	L 0-1	1601	1501	46.29%	22.29%	31.42%	-8.5	28
2016-03-07	Midtjylland	W 2-1	1515	1662	25.91%	21.78%	52.31%	+8.9	26
2016-03-07	@ Nordsjaelland	L 1-2	1662	1515	52.31%	21.78%	25.91%	-8.9	32
2016-03-11	Aarhus GF	W 2-1	1509	1534	41.80%	22.47%	35.74%	+6.5	21
2016-03-11	@ Esbjerg	L 1-2	1534	1509	35.74%	22.47%	41.80%	-6.5	23
2016-03-12	Sonderjyske	D 0-0	1549	1606	37.10%	22.49%	40.41%	+0.1	26
2016-03-12	@ Viborg	D 0-0	1606	1549	40.41%	22.49%	37.10%	-0.1	36
2016-03-13	Aalborg	W 6-2	1708	1650	52.63%	21.74%	25.62%	+13.3	45
2016-03-13	@ FC Copenhagen	L 2-6	1650	1708	25.62%	21.74%	52.63%	-13.3	35
2016-03-13	Nordsjaelland	W 3-1	1560	1524	49.90%	22.02%	28.08%	+9.3	31
2016-03-13	@ Odense	L 1-3	1524	1560	28.08%	22.02%	49.90%	-9.3	26
2016-03-13	Randers	W 1-0	1628	1592	49.97%	22.02%	28.02%	+5.7	35
2016-03-13	@ Brondby	L 0-1	1592	1628	28.02%	22.02%	49.97%	-5.7	28
2016-03-14	Hobro	W 3-0	1653	1406	71.64%	17.25%	11.11%	+6.3	35
2016-03-14	@ Midtjylland	L 0-3	1406	1653	11.11%	17.25%	71.64%	-6.4	10
2016-03-18	Aarhus GF	D 2-2	1637	1527	58.77%	20.82%	20.42%	-1.2	36
2016-03-18	@ Aalborg	D 2-2	1527	1637	20.42%	20.82%	58.77%	+1.2	24
2016-03-19	Odense	L 0-2	1400	1569	23.50%	21.42%	55.08%	-9.2	10
2016-03-19	@ Hobro	W 2-0	1569	1400	55.08%	21.42%	23.50%	+9.2	34
2016-03-20	Esbjerg	D 0-0	1634	1516	59.64%	20.65%	19.71%	-1.9	36
2016-03-20	@ Brondby	D 0-0	1516	1634	19.71%	20.65%	59.64%	+1.9	22
2016-03-20	FC Copenhagen	W 2-0	1515	1721	20.03%	20.73%	59.24%	+20.0	29
2016-03-20	@ Nordsjaelland	L 0-2	1721	1515	59.24%	20.73%	20.03%	-19.9	45
2016-03-20	Midtjylland	W 3-2	1606	1659	37.75%	22.50%	39.75%	+6.8	39
2016-03-20	@ Sonderjyske	L 2-3	1659	1606	39.75%	22.50%	37.75%	-6.8	35
2016-03-20	Viborg	L 1-3	1586	1549	50.15%	22.00%	27.85%	-14.9	28
2016-03-20	@ Randers	W 3-1	1549	1586	27.85%	22.00%	50.15%	+14.9	29
2016-04-01	Nordsjaelland	W 1-0	1636	1535	57.79%	20.99%	21.22%	+4.4	39
2016-04-01	@ Aalborg	L 0-1	1535	1636	21.22%	20.99%	57.79%	-4.5	29
2016-04-02	Hobro	D 1-1	1528	1391	61.76%	20.20%	18.04%	-1.8	25
2016-04-02	@ Aarhus GF	D 1-1	1391	1528	18.04%	20.20%	61.76%	+1.9	11
2016-04-03	Brondby	W 2-0	1652	1632	47.95%	22.18%	29.87%	+11.3	38
2016-04-03	@ Midtjylland	L 0-2	1632	1652	29.87%	22.18%	47.95%	-11.3	36
2016-04-03	Randers	L 0-1	1578	1571	46.11%	22.30%	31.59%	-8.5	34
2016-04-03	@ Odense	W 1-0	1571	1578	31.59%	22.30%	46.11%	+8.5	31
2016-04-03	Sonderjyske	W 1-0	1701	1613	56.31%	21.24%	22.45%	+4.7	48
2016-04-03	@ FC Copenhagen	L 0-1	1613	1701	22.45%	21.24%	56.31%	-4.7	39
2016-04-04	Viborg	W 1-0	1518	1564	38.71%	22.50%	38.78%	+7.4	25
2016-04-04	@ Esbjerg	L 0-1	1564	1518	38.78%	22.50%	38.71%	-7.4	29
2016-04-08	Midtjylland	D 1-1	1556	1664	30.51%	22.23%	47.27%	+0.7	30
2016-04-08	@ Viborg	D 1-1	1664	1556	47.27%	22.23%	30.51%	-0.7	39
2016-04-09	Aarhus GF	D 2-2	1608	1527	55.57%	21.35%	23.08%	-1.0	40
2016-04-09	@ Sonderjyske	D 2-2	1527	1608	23.08%	21.35%	55.57%	+1.0	26
2016-04-10	Aalborg	L 0-2	1392	1640	16.65%	19.76%	63.59%	-6.7	11
2016-04-10	@ Hobro	W 2-0	1640	1392	63.59%	19.76%	16.65%	+6.7	42
2016-04-10	FC Copenhagen	D 1-1	1580	1706	28.26%	22.04%	49.70%	+0.9	32
2016-04-10	@ Randers	D 1-1	1706	1580	49.70%	22.04%	28.26%	-0.9	49
2016-04-10	Odense	W 1-0	1620	1570	51.85%	21.83%	26.32%	+5.4	39
2016-04-10	@ Brondby	L 0-1	1570	1620	26.32%	21.83%	51.85%	-5.4	34
2016-04-11	Esbjerg	D 0-0	1530	1525	45.92%	22.31%	31.77%	-0.6	30
2016-04-11	@ Nordsjaelland	D 0-0	1525	1530	31.77%	22.31%	45.92%	+0.6	26
2016-04-15	Hobro	W 2-1	1530	1386	62.38%	20.06%	17.56%	+3.5	33
2016-04-15	@ Nordsjaelland	L 1-2	1386	1530	17.56%	20.06%	62.38%	-3.5	11
2016-04-16	Randers	L 0-2	1528	1581	37.71%	22.50%	39.79%	-13.7	26
2016-04-16	@ Aarhus GF	W 2-0	1581	1528	39.79%	22.50%	37.71%	+13.7	35
2016-04-17	Brondby	W 2-0	1705	1626	55.25%	21.40%	23.35%	+9.1	52
2016-04-17	@ FC Copenhagen	L 0-2	1626	1705	23.35%	21.40%	55.25%	-9.1	39
2016-04-17	Sonderjyske	L 1-2	1647	1607	50.45%	21.97%	27.58%	-8.7	42
2016-04-17	@ Aalborg	W 2-1	1607	1647	27.58%	21.97%	50.45%	+8.7	43
2016-04-17	Viborg	W 5-1	1564	1557	46.16%	22.30%	31.54%	+18.7	37
2016-04-17	@ Odense	L 1-5	1557	1564	31.54%	22.30%	46.16%	-18.7	30
2016-04-18	Midtjylland	L 0-2	1526	1663	26.93%	21.90%	51.16%	-10.4	26
2016-04-18	@ Esbjerg	W 2-0	1663	1526	51.16%	21.90%	26.93%	+10.4	42
2016-04-22	Odense	W 2-0	1673	1583	56.58%	21.20%	22.22%	+8.7	45
2016-04-22	@ Midtjylland	L 0-2	1583	1673	22.22%	21.20%	56.58%	-8.7	37
2016-04-23	Esbjerg	D 2-2	1382	1515	27.39%	21.95%	50.65%	+0.7	12
2016-04-23	@ Hobro	D 2-2	1515	1382	50.65%	21.95%	27.39%	-0.7	27
2016-04-24	Aarhus GF	W 2-1	1617	1514	57.99%	20.96%	21.05%	+4.2	42
2016-04-24	@ Brondby	L 1-2	1514	1617	21.05%	20.96%	57.99%	-4.2	26
2016-04-24	FC Copenhagen	D 1-1	1538	1714	22.87%	21.32%	55.81%	+1.4	31
2016-04-24	@ Viborg	D 1-1	1714	1538	55.81%	21.32%	22.87%	-1.4	53
2016-04-24	Nordsjaelland	W 3-1	1616	1533	55.68%	21.34%	22.98%	+7.8	46
2016-04-24	@ Sonderjyske	L 1-3	1533	1616	22.98%	21.34%	55.68%	-7.8	33
2016-04-25	Aalborg	D 0-0	1594	1638	39.05%	22.50%	38.45%	-0.0	36
2016-04-25	@ Randers	D 0-0	1638	1594	38.45%	22.50%	39.05%	+0.0	43
2016-04-29	Viborg	L 1-2	1510	1540	41.03%	22.48%	36.49%	-7.3	26
2016-04-29	@ Aarhus GF	W 2-1	1540	1510	36.49%	22.48%	41.03%	+7.3	34
2016-04-30	Sonderjyske	L 1-2	1383	1624	17.18%	19.94%	62.88%	-3.4	12
2016-04-30	@ Hobro	W 2-1	1624	1383	62.88%	19.94%	17.18%	+3.4	49
2016-05-01	Brondby	W 3-0	1638	1621	47.55%	22.21%	30.24%	+16.6	46
2016-05-01	@ Aalborg	L 0-3	1621	1638	30.24%	22.21%	47.55%	-16.6	42
2016-05-01	Midtjylland	W 5-3	1712	1682	49.26%	22.08%	28.66%	+8.0	56
2016-05-01	@ FC Copenhagen	L 3-5	1682	1712	28.66%	22.08%	49.26%	-8.0	45
2016-05-01	Randers	D 2-2	1526	1594	35.51%	22.46%	42.03%	+0.2	34
2016-05-01	@ Nordsjaelland	D 2-2	1594	1526	42.03%	22.46%	35.51%	-0.2	37
2016-05-02	Odense	L 0-2	1515	1574	36.81%	22.49%	40.70%	-13.4	27
2016-05-02	@ Esbjerg	W 2-0	1574	1515	40.70%	22.49%	36.81%	+13.4	40
2016-05-06	Esbjerg	W 2-0	1627	1501	60.50%	20.47%	19.03%	+7.6	52
2016-05-06	@ Sonderjyske	L 0-2	1501	1627	19.03%	20.47%	60.50%	-7.6	27
2016-05-07	Hobro	W 2-0	1594	1380	69.00%	18.18%	12.82%	+5.1	40
2016-05-07	@ Randers	L 0-2	1380	1594	12.82%	18.18%	69.00%	-5.1	12
2016-05-08	Aalborg	L 0-2	1547	1655	30.41%	22.22%	47.37%	-11.5	34
2016-05-08	@ Viborg	W 2-0	1655	1547	47.37%	22.22%	30.41%	+11.5	49
2016-05-08	Aarhus GF	D 1-1	1674	1503	65.08%	19.37%	15.55%	-2.1	46
2016-05-08	@ Midtjylland	D 1-1	1503	1674	15.55%	19.37%	65.08%	+2.1	27
2016-05-08	FC Copenhagen	L 0-1	1588	1720	27.42%	21.96%	50.62%	-5.6	40
2016-05-08	@ Odense	W 1-0	1720	1588	50.62%	21.96%	27.42%	+5.6	59
2016-05-09	Nordsjaelland	W 2-1	1604	1526	55.22%	21.40%	23.38%	+4.6	45
2016-05-09	@ Brondby	L 1-2	1526	1604	23.38%	21.40%	55.22%	-4.6	34
2016-05-11	Esbjerg	W 5-1	1505	1494	46.68%	22.27%	31.06%	+18.5	30
2016-05-11	@ Aarhus GF	L 1-5	1494	1505	31.06%	22.27%	46.68%	-18.5	27
2016-05-11	Midtjylland	L 1-4	1374	1672	13.35%	18.44%	68.21%	-6.5	12
2016-05-11	@ Hobro	W 4-1	1672	1374	68.21%	18.44%	13.35%	+6.5	49
2016-05-11	Viborg	W 2-0	1635	1536	57.58%	21.03%	21.39%	+8.5	55
2016-05-11	@ Sonderjyske	L 0-2	1536	1635	21.39%	21.03%	57.58%	-8.4	34
2016-05-12	Brondby	L 0-2	1599	1609	43.89%	22.40%	33.71%	-15.4	40
2016-05-12	@ Randers	W 2-0	1609	1599	33.71%	22.40%	43.89%	+15.4	48
2016-05-12	FC Copenhagen	L 0-2	1666	1726	36.79%	22.49%	40.72%	-13.4	49
2016-05-12	@ Aalborg	W 2-0	1726	1666	40.72%	22.49%	36.79%	+13.4	62
2016-05-12	Odense	L 0-1	1521	1582	36.62%	22.48%	40.90%	-7.1	34
2016-05-12	@ Nordsjaelland	W 1-0	1582	1521	40.90%	22.48%	36.62%	+7.1	43
2016-05-14	Sonderjyske	W 3-2	1678	1643	49.88%	22.03%	28.09%	+5.1	52
2016-05-14	@ Midtjylland	L 2-3	1643	1678	28.09%	22.03%	49.88%	-5.1	55
2016-05-15	Hobro	L 0-1	1589	1368	69.55%	18.00%	12.45%	-12.2	43
2016-05-15	@ Odense	W 1-0	1368	1589	12.45%	18.00%	69.55%	+12.2	15
2016-05-16	Brondby	L 2-3	1475	1624	25.61%	21.74%	52.64%	-4.7	27
2016-05-16	@ Esbjerg	W 3-2	1624	1475	52.64%	21.74%	25.61%	+4.7	51
2016-05-16	Nordsjaelland	W 2-0	1739	1514	69.91%	17.87%	12.22%	+4.8	65
2016-05-16	@ FC Copenhagen	L 0-2	1514	1739	12.22%	17.87%	69.91%	-4.8	34
2016-05-16	Randers	L 2-3	1527	1584	37.20%	22.49%	40.31%	-6.4	34
2016-05-16	@ Viborg	W 3-2	1584	1527	40.31%	22.49%	37.20%	+6.4	43
2016-05-17	Aalborg	W 2-0	1523	1653	27.76%	21.99%	50.24%	+17.2	33
2016-05-17	@ Aarhus GF	L 0-2	1653	1523	50.24%	21.99%	27.76%	-17.3	49
2016-05-20	Odense	W 3-1	1638	1577	53.12%	21.68%	25.20%	+8.5	58
2016-05-20	@ Sonderjyske	L 1-3	1577	1638	25.20%	21.68%	53.12%	-8.5	43
2016-05-21	Aarhus GF	D 3-3	1509	1540	40.85%	22.49%	36.66%	-0.1	35
2016-05-21	@ Nordsjaelland	D 3-3	1540	1509	36.66%	22.49%	40.85%	+0.1	34
2016-05-22	Esbjerg	L 1-2	1636	1471	64.48%	19.53%	15.99%	-10.8	49
2016-05-22	@ Aalborg	W 2-1	1471	1636	15.99%	19.53%	64.48%	+10.8	30
2016-05-22	FC Copenhagen	W 4-2	1380	1744	9.88%	16.46%	73.66%	+18.6	18
2016-05-22	@ Hobro	L 2-4	1744	1380	73.66%	16.46%	9.88%	-18.6	65
2016-05-22	Midtjylland	L 1-2	1590	1683	32.27%	22.34%	45.39%	-6.0	43
2016-05-22	@ Randers	W 2-1	1683	1590	45.39%	22.34%	32.27%	+6.0	55
2016-05-23	Viborg	L 0-1	1629	1521	58.60%	20.85%	20.55%	-10.5	51
2016-05-23	@ Brondby	W 1-0	1521	1629	20.55%	20.85%	58.60%	+10.5	37
2016-05-26	Brondby	L 0-2	1399	1618	18.85%	20.43%	60.72%	-7.5	18
2016-05-26	@ Hobro	W 2-0	1618	1399	60.72%	20.43%	18.85%	+7.5	54
2016-05-26	FC Copenhagen	L 1-4	1481	1726	16.91%	19.85%	63.25%	-8.3	30
2016-05-26	@ Esbjerg	W 4-1	1726	1481	63.25%	19.85%	16.91%	+8.3	68
2016-05-26	Midtjylland	D 0-0	1625	1690	36.11%	22.48%	41.41%	+0.2	50
2016-05-26	@ Aalborg	D 0-0	1690	1625	41.41%	22.48%	36.11%	-0.2	56
2016-05-26	Odense	W 2-1	1540	1568	41.31%	22.48%	36.22%	+6.6	37
2016-05-26	@ Aarhus GF	L 1-2	1568	1540	36.22%	22.48%	41.31%	-6.6	43
2016-05-26	Randers	D 1-1	1646	1584	53.25%	21.67%	25.08%	-1.2	59
2016-05-26	@ Sonderjyske	D 1-1	1584	1646	25.08%	21.67%	53.25%	+1.2	44
2016-05-26	Viborg	W 1-0	1509	1531	42.14%	22.46%	35.41%	+6.9	38
2016-05-26	@ Nordsjaelland	L 0-1	1531	1509	35.41%	22.46%	42.14%	-6.9	37
2016-05-29	Aalborg	W 3-2	1562	1625	36.27%	22.48%	41.25%	+7.0	46
2016-05-29	@ Odense	L 2-3	1625	1562	41.25%	22.48%	36.27%	-6.9	50
2016-05-29	Aarhus GF	W 2-1	1734	1547	66.52%	18.96%	14.52%	+2.9	71
2016-05-29	@ FC Copenhagen	L 1-2	1547	1734	14.52%	18.96%	66.52%	-2.9	37
2016-05-29	Esbjerg	W 3-1	1585	1473	59.06%	20.76%	20.18%	+6.9	47
2016-05-29	@ Randers	L 1-3	1473	1585	20.18%	20.76%	59.06%	-6.9	30
2016-05-29	Hobro	W 1-0	1524	1391	61.26%	20.31%	18.43%	+3.9	40
2016-05-29	@ Viborg	L 0-1	1391	1524	18.43%	20.31%	61.26%	-3.9	18
2016-05-29	Nordsjaelland	W 4-1	1689	1516	65.26%	19.32%	15.42%	+7.5	59
2016-05-29	@ Midtjylland	L 1-4	1516	1689	15.42%	19.32%	65.26%	-7.5	38
2016-05-29	Sonderjyske	L 1-2	1626	1645	42.52%	22.45%	35.03%	-7.5	54
2016-05-29	@ Brondby	W 2-1	1645	1626	35.03%	22.45%	42.52%	+7.5	62

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	2016-05-22	9.88%	@ Hobro	1380	4	FC Copenhagen	1744	2
2	2016-05-15	12.45%	Hobro	1368	1	@ Odense	1589	0
3	2015-10-31	14.74%	Viborg	1502	4	@ Midtjylland	1686	2
4	2016-05-22	15.99%	Esbjerg	1471	2	@ Aalborg	1636	1
5	2015-09-20	17.55%	Nordsjaelland	1534	1	@ Midtjylland	1678	0
6	2016-03-20	20.03%	@ Nordsjaelland	1515	2	FC Copenhagen	1721	0
7	2016-03-04	20.23%	Odense	1549	1	@ Aalborg	1661	0
8	2016-05-23	20.55%	Viborg	1521	1	@ Brondby	1629	0
9	2015-08-23	20.84%	Viborg	1511	1	@ Randers	1617	0
10	2015-08-02	23.52%	Hobro	1513	2	@ Brondby	1590	0
11	2015-12-04	24.83%	@ Aarhus GF	1523	2	Midtjylland	1679	1
12	2016-03-07	25.91%	@ Nordsjaelland	1515	2	Midtjylland	1662	1
13	2016-04-17	27.58%	Sonderjyske	1607	2	@ Aalborg	1647	1
14	2016-05-17	27.76%	@ Aarhus GF	1523	2	Aalborg	1653	0
15	2016-03-20	27.85%	Viborg	1549	3	@ Randers	1586	1
16	2015-07-26	29.20%	Odense	1573	2	@ Brondby	1599	1
17	2015-08-09	29.45%	Sonderjyske	1538	4	@ Esbjerg	1562	0
18	2015-10-25	29.72%	@ Nordsjaelland	1514	3	Aalborg	1628	0
19	2015-10-02	30.06%	Odense	1539	5	@ Nordsjaelland	1558	1
20	2015-07-17	30.39%	Sonderjyske	1539	2	@ Nordsjaelland	1555	0
21	2015-09-25	31.11%	@ Viborg	1498	1	Aalborg	1600	0
22	2016-03-06	31.42%	@ Esbjerg	1501	1	Randers	1601	0
23	2016-04-03	31.59%	Randers	1571	1	@ Odense	1578	0
24	2015-08-30	31.79%	@ Odense	1551	1	FC Copenhagen	1648	0
25	2015-11-29	31.92%	Aalborg	1637	2	@ Brondby	1641	0

Biggest Elo Changes

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

#	Date	Elo Δ	Winning Team				Losing Team				Tie %
#	Date	Elo Δ	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2016-03-05	35.98	Viborg	6	1513	42.28%	@ Hobro	0	1442	35.26%	22.46%
2	2015-08-09	31.71	Sonderjyske	4	1538	29.45%	@ Esbjerg	0	1562	48.40%	22.15%
3	2015-10-04	29.78	@ Aalborg	5	1592	43.06%	Sonderjyske	0	1607	34.51%	22.43%
4	2015-08-16	27.42	Brondby	4	1572	36.95%	@ Viborg	0	1539	40.56%	22.49%
5	2015-10-02	26.13	Odense	5	1539	30.06%	@ Nordsjaelland	1	1558	47.75%	22.20%
6	2015-10-25	24.15	@ Nordsjaelland	3	1514	29.72%	Aalborg	0	1628	48.11%	22.17%
7	2015-11-01	21.07	@ Aalborg	6	1604	60.44%	Hobro	0	1478	19.07%	20.49%
8	2015-09-25	21.04	@ Sonderjyske	4	1586	48.74%	Odense	0	1560	29.14%	22.12%
9	2015-09-11	20.10	Aarhus GF	3	1545	39.15%	@ Hobro	0	1496	38.35%	22.50%
10	2016-03-20	19.96	@ Nordsjaelland	2	1515	20.03%	FC Copenhagen	0	1721	59.24%	20.73%
11	2016-04-17	18.72	@ Odense	5	1564	46.16%	Viborg	1	1557	31.54%	22.30%
12	2015-08-02	18.69	Hobro	2	1513	23.52%	@ Brondby	0	1590	55.05%	21.43%
13	2016-05-22	18.63	@ Hobro	4	1380	9.88%	FC Copenhagen	2	1744	73.66%	16.46%
14	2016-05-11	18.48	@ Aarhus GF	5	1505	46.68%	Esbjerg	1	1494	31.06%	22.27%
15	2015-11-01	18.27	@ FC Copenhagen	4	1674	53.64%	Randers	0	1608	24.74%	21.62%
16	2015-08-24	17.85	@ Aalborg	5	1590	48.04%	Odense	1	1569	29.78%	22.18%
17	2015-10-18	17.26	@ Aarhus GF	3	1538	46.01%	Nordsjaelland	0	1532	31.69%	22.31%
18	2016-05-17	17.26	@ Aarhus GF	2	1523	27.76%	Aalborg	0	1653	50.24%	21.99%
19	2015-10-31	17.06	Viborg	4	1502	14.74%	@ Midtjylland	2	1686	66.21%	19.05%
20	2016-05-01	16.61	@ Aalborg	3	1638	47.55%	Brondby	0	1621	30.24%	22.21%
21	2015-09-20	16.55	@ Aalborg	4	1584	40.30%	Brondby	1	1619	37.21%	22.49%
22	2015-09-16	16.49	@ FC Copenhagen	3	1647	47.84%	Randers	0	1628	29.97%	22.19%
23	2015-07-19	16.46	@ Odense	3	1556	47.88%	Hobro	0	1536	29.93%	22.19%
24	2015-07-17	16.42	Sonderjyske	2	1539	30.39%	@ Nordsjaelland	0	1555	47.39%	22.22%
25	2015-11-29	15.95	Aalborg	2	1637	31.92%	@ Brondby	0	1641	45.77%	22.32%