2002-03 Superliga Season

198 games

Final

Champion

FC Copenhagen

61 points · 3rd Title

Last Title: 2000-01

Relegated

Koge BK

27 pts

Silkeborg · 36 pts

Biggest Overachiever

Nordsjaelland

13.58 points above expected

51 points · 37.42 expected points

Biggest Disappointment

Midtjylland

10.63 points below expected

44 points · 54.63 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	17	10	6	61	51	32	+19	63.83	-2.83
2	Brondby	33	15	11	7	56	61	35	+26	65.76	-9.76
3	Nordsjaelland	33	16	3	14	51	49	58	-9	37.42	+13.58
4	Odense	33	12	12	9	48	55	50	+5	47.31	+0.69
5	Esbjerg	33	12	11	10	47	65	57	+8	39.67	+7.33
6	Aalborg	33	14	4	15	46	42	45	-3	44.48	+1.52
7	Midtjylland	33	11	11	11	44	49	45	+4	54.63	-10.63
8	Viborg	33	11	10	12	43	58	55	+3	41.42	+1.58
9	AB Copenhagen	33	10	12	11	42	44	48	-4	45.91	-3.91
10	Aarhus GF	33	10	10	13	40	49	59	-10	37.94	+2.06
11	Silkeborg Relegated	33	9	9	15	36	52	54	-2	39.17	-3.17
12	Koge BK Relegated	33	8	3	22	27	45	82	-37	27.05	-0.05

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
Brondby	1770	56	65.76	-9.76	9.0%	37	54	61	66	70	77	91
FC Copenhagen	1746	61	63.83	-2.83	36.5%	37	52	59	64	69	75	88
Midtjylland	1659	44	54.63	-10.63	8.0%	28	43	50	55	59	67	80
Odense	1620	48	47.31	+0.69	56.8%	18	36	43	47	52	59	78
Aalborg	1590	46	44.48	+1.52	61.3%	16	33	40	44	49	56	76
Viborg	1590	43	41.42	+1.58	62.1%	18	30	37	41	46	53	69
AB Copenhagen	1590	42	45.91	-3.91	32.3%	18	34	41	46	51	58	74
Esbjerg	1581	47	39.67	+7.33	86.4%	15	28	35	40	44	51	68
Silkeborg	1569	36	39.17	-3.17	35.2%	14	28	34	39	44	51	64
Nordsjaelland	1549	51	37.42	+13.58	97.7%	13	26	33	37	42	49	70
Aarhus GF	1544	40	37.94	+2.06	64.8%	15	26	33	38	43	50	64
Koge BK	1417	27	27.05	-0.05	54.4%	6	17	23	27	31	38	54

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	AC	AAL	AG	BRO	ESB	FC	KB	MID	NOR	ODE	SIL	VIB
AB Copenhagen	—	2-0-1 3.82	2-1-0 5.00	1-2-0 2.23	0-1-2 4.87	0-2-1 2.40	2-1-0 5.98	0-2-1 3.18	1-0-2 5.01	0-2-1 4.25	2-0-1 4.92	0-1-2 4.19
Aalborg	1-0-2 4.35	—	1-0-2 4.95	1-0-2 2.48	2-0-1 4.16	2-1-0 2.62	2-1-0 5.43	1-0-2 2.95	1-0-2 4.85	1-0-2 3.68	1-1-1 4.77	1-1-1 4.18
Aarhus GF	0-1-2 3.21	2-0-1 3.25	—	1-2-0 2.14	0-2-1 4.19	0-1-2 2.01	1-0-2 5.08	2-1-0 2.50	1-1-1 4.33	2-1-0 3.43	1-0-2 3.69	0-1-2 4.05
Brondby	0-2-1 6.12	2-0-1 5.81	0-2-1 6.22	—	1-2-0 6.44	0-1-2 4.05	2-0-1 7.22	2-1-0 5.34	2-1-0 6.21	2-1-0 5.87	2-0-1 6.16	2-1-0 6.30
Esbjerg	2-1-0 3.31	1-0-2 4.01	1-2-0 3.98	0-2-1 1.96	—	1-1-1 2.46	2-0-1 5.43	2-0-1 3.04	2-0-1 4.08	1-2-0 3.64	0-3-0 3.89	0-0-3 3.90
FC Copenhagen	1-2-0 5.90	0-1-2 5.65	2-1-0 6.38	2-1-0 4.14	1-1-1 5.84	—	3-0-0 6.82	1-2-0 4.71	3-0-0 6.44	1-1-1 5.40	2-0-1 6.44	1-1-1 6.14
Koge BK	0-1-2 2.34	0-1-2 2.81	2-0-1 3.13	1-0-2 1.35	1-0-2 2.82	0-0-3 1.66	—	0-1-2 2.13	1-0-2 2.87	0-0-3 2.12	1-0-2 3.23	2-0-1 2.51
Midtjylland	1-2-0 5.03	2-0-1 5.28	0-1-2 5.79	0-1-2 2.90	1-0-2 5.17	0-2-1 3.48	2-1-0 6.22	—	2-0-1 5.68	0-1-2 4.59	2-1-0 5.53	1-2-0 5.07
Nordsjaelland	2-0-1 3.19	2-0-1 3.35	1-1-1 3.86	0-1-2 2.15	1-0-2 4.10	0-0-3 1.97	2-0-1 5.37	1-0-2 2.59	—	2-1-0 3.39	2-0-1 3.60	3-0-0 3.79
Odense	1-2-0 3.93	2-0-1 4.50	0-1-2 4.75	0-1-2 2.43	0-2-1 4.54	1-1-1 2.83	3-0-0 6.24	2-1-0 3.59	0-1-2 4.79	—	1-2-0 5.05	2-1-0 4.66
Silkeborg	1-0-2 3.26	1-1-1 3.44	2-0-1 4.47	1-0-2 2.19	0-3-0 4.29	1-0-2 1.96	2-0-1 4.96	0-1-2 2.73	1-0-2 4.58	0-2-1 3.16	—	0-2-1 4.20
Viborg	2-1-0 3.98	1-1-1 3.98	2-1-0 4.13	0-1-2 2.07	3-0-0 4.29	1-1-1 2.21	1-0-2 5.80	0-2-1 3.13	0-0-3 4.38	0-1-2 3.51	1-2-0 3.97	—

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	0.13	+4.6
Allowed	0.70	-5.8
Differential	0.71	+4.8

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	4.55%	5.81%	4.80%	2.78%	1.77%	1.01%	20.71%
1	5.81%	14.14%	7.32%	4.80%	2.27%	1.26%	35.61%
2	4.80%	7.32%	7.07%	2.78%	0.51%	—	22.47%
3	2.78%	4.80%	2.78%	0.51%	1.52%	—	12.37%
4	1.77%	2.27%	0.51%	1.52%	0.51%	—	6.57%
5+	1.01%	1.26%	—	—	—	—	2.27%
Total	20.71%	35.61%	22.47%	12.37%	6.57%	2.27%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.57	1.57	+0.00
SD	1.30	1.30	1.95
CV	0.83	0.83	—
Max	7	7	+6
Min	0	0	-6

Games Played: 198

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	9.09%	6.06%	3.03%	9.09%	3.03%	—	30.30%
1	3.03%	18.18%	9.09%	—	3.03%	—	33.33%
2	3.03%	3.03%	6.06%	—	—	—	12.12%
3	—	15.15%	3.03%	3.03%	—	—	21.21%
4	3.03%	—	—	—	—	—	3.03%
5+	—	—	—	—	—	—	—
Total	18.18%	42.42%	21.21%	12.12%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.33	1.45	-0.12
SD	1.22	1.12	1.80
CV	0.91	0.77	—
Max	4	4	+4
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	9.09%	3.03%	3.03%	3.03%	—	21.21%
1	18.18%	6.06%	12.12%	9.09%	—	—	45.45%
2	6.06%	6.06%	3.03%	3.03%	—	—	18.18%
3	3.03%	9.09%	—	—	3.03%	—	15.15%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	30.30%	30.30%	18.18%	15.15%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.27	1.36	-0.09
SD	0.98	1.25	1.65
CV	0.77	0.91	—
Max	3	4	+3
Min	0	0	-4

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	12.12%	—	—	—	18.18%
1	3.03%	9.09%	6.06%	9.09%	6.06%	—	33.33%
2	3.03%	12.12%	18.18%	—	3.03%	—	36.36%
3	—	—	6.06%	—	—	—	6.06%
4	—	6.06%	—	—	—	—	6.06%
5+	—	—	—	—	—	—	—
Total	9.09%	30.30%	42.42%	9.09%	9.09%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.48	1.79	-0.30
SD	1.06	1.05	1.57
CV	0.72	0.59	—
Max	4	4	+3
Min	0	0	-3

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	3.03%	—	—	—	—	6.06%
1	3.03%	27.27%	9.09%	6.06%	—	—	45.45%
2	9.09%	15.15%	3.03%	—	—	—	27.27%
3	3.03%	3.03%	—	—	3.03%	—	9.09%
4	9.09%	—	—	—	—	—	9.09%
5+	—	3.03%	—	—	—	—	3.03%
Total	27.27%	51.52%	12.12%	6.06%	3.03%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.85	1.06	+0.79
SD	1.39	0.97	1.83
CV	0.75	0.91	—
Max	7	4	+6
Min	0	0	-2

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	6.06%	6.06%	—	—	3.03%	18.18%
1	3.03%	21.21%	6.06%	—	3.03%	3.03%	36.36%
2	—	3.03%	6.06%	—	—	—	9.09%
3	3.03%	—	6.06%	—	3.03%	—	12.12%
4	—	12.12%	—	3.03%	3.03%	—	18.18%
5+	3.03%	3.03%	—	—	—	—	6.06%
Total	12.12%	45.45%	24.24%	3.03%	9.09%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.97	1.73	+0.24
SD	1.67	1.44	2.32
CV	0.85	0.83	—
Max	6	6	+5
Min	0	0	-6

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	6.06%	3.03%	3.03%	9.09%	—	—	21.21%
1	18.18%	15.15%	—	—	—	—	33.33%
2	3.03%	12.12%	9.09%	3.03%	—	—	27.27%
3	6.06%	3.03%	—	—	—	—	9.09%
4	3.03%	3.03%	—	—	—	—	6.06%
5+	3.03%	—	—	—	—	—	3.03%
Total	39.39%	36.36%	12.12%	12.12%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.55	0.97	+0.58
SD	1.28	1.02	1.84
CV	0.83	1.05	—
Max	5	3	+5
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.36	2.48	-1.12
SD	1.25	1.56	2.19
CV	0.91	0.63	—
Max	4	6	+3
Min	0	0	-5

Games Played: 33

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.03%	9.09%	3.03%	—	3.03%	—	18.18%
1	3.03%	21.21%	6.06%	3.03%	3.03%	—	36.36%
2	12.12%	6.06%	6.06%	6.06%	—	—	30.30%
3	3.03%	3.03%	3.03%	3.03%	—	—	12.12%
4	—	—	—	—	—	—	—
5+	3.03%	—	—	—	—	—	3.03%
Total	24.24%	39.39%	18.18%	12.12%	6.06%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.48	1.36	+0.12
SD	1.12	1.17	1.75
CV	0.76	0.86	—
Max	5	4	+5
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	12.12%	3.03%	6.06%	3.03%	—	6.06%	30.30%
2	9.09%	15.15%	6.06%	3.03%	3.03%	—	36.36%
3	—	6.06%	6.06%	—	3.03%	—	15.15%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	21.21%	30.30%	27.27%	6.06%	9.09%	6.06%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.48	1.76	-0.27
SD	0.97	1.62	1.96
CV	0.65	0.92	—
Max	3	7	+2
Min	0	0	-6

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.67	1.52	+0.15
SD	1.22	1.35	1.91
CV	0.73	0.89	—
Max	4	5	+4
Min	0	0	-5

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.58	1.64	-0.06
SD	1.44	1.19	1.75
CV	0.91	0.73	—
Max	5	4	+4
Min	0	0	-3

Games Played: 33

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

Summary Statistics

	Scored	Allowed	Difference
Mean	1.76	1.67	+0.09
SD	1.75	1.19	2.32
CV	1.00	0.71	—
Max	6	4	+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	Nordsjaelland	51	37.42	+13.58
2	Esbjerg	47	39.67	+7.33
3	Aarhus GF	40	37.94	+2.06
4	Viborg	43	41.42	+1.58
5	Aalborg	46	44.48	+1.52

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Midtjylland	44	54.63	-10.63
2	Brondby	56	65.76	-9.76
3	AB Copenhagen	42	45.91	-3.91
4	Silkeborg	36	39.17	-3.17
5	FC Copenhagen	61	63.83	-2.83

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	Nordsjaelland	4	Dec 1 – Apr 13	1 in 134
2	Koge BK	2	Oct 6 – Oct 20	1 in 65
3	Viborg	3	May 4 – May 18	1 in 62
4	Aalborg	4	Jun 1 – Jun 22	1 in 57
5	Silkeborg	3	Apr 17 – Apr 27	1 in 26

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Koge BK	6	May 18 – Jun 22	1 in 37
2	Viborg	4	Dec 1 – Apr 6	1 in 35
3	Aalborg	4	Apr 27 – May 18	1 in 32
4	Brondby	2	Aug 3 – Aug 10	1 in 28
5	AB Copenhagen	3	Mar 16 – Apr 6	1 in 24

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Aarhus GF	8	Apr 27 – Jun 18	1 in 145
2	Nordsjaelland	7	Dec 1 – Apr 24	1 in 60
3	Viborg	7	Apr 13 – May 18	1 in 49
4	Brondby	17	Nov 10 – Jun 15	1 in 35
5	AB Copenhagen	7	Oct 20 – Dec 1	1 in 34

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Aalborg	7	Nov 17 – Apr 13	1 in 32
2	Midtjylland	5	May 24 – Jun 22	1 in 24
3	Odense	6	Apr 6 – May 4	1 in 21
4	Silkeborg	7	Aug 25 – Oct 6	1 in 14
5	Koge BK	12	Apr 13 – Jun 22	1 in 13

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	38.29%	41.18%	13.45%	4.42%	1.64%	0.67%	0.21%	0.10%	0.02%	0.02%	—	—
Brondby	53.84%	32.85%	9.18%	2.64%	0.92%	0.32%	0.16%	0.05%	0.03%	0.01%	—	—
Nordsjaelland	0.04%	0.21%	1.01%	2.99%	5.16%	7.32%	9.84%	12.22%	14.88%	18.26%	19.57%	8.50%
Odense	0.79%	3.72%	13.12%	20.43%	17.10%	14.23%	11.18%	7.16%	5.89%	3.57%	2.26%	0.55%
Esbjerg	0.04%	0.46%	2.56%	6.05%	8.74%	11.00%	12.58%	13.73%	13.85%	13.78%	12.39%	4.82%
Aalborg	0.34%	1.79%	7.38%	13.10%	14.89%	14.93%	13.34%	11.33%	9.41%	7.30%	4.73%	1.46%
Midtjylland	5.96%	15.82%	36.81%	18.35%	10.11%	5.89%	3.17%	2.00%	1.20%	0.50%	0.14%	0.05%
Viborg	0.06%	0.79%	3.86%	8.06%	10.54%	12.95%	13.35%	14.15%	12.96%	11.57%	8.92%	2.79%
AB Copenhagen	0.61%	2.63%	9.65%	15.68%	16.90%	14.75%	12.21%	10.10%	7.90%	5.63%	3.13%	0.81%
Aarhus GF	—	0.18%	1.28%	3.31%	6.00%	7.78%	10.39%	13.26%	15.02%	17.24%	18.07%	7.47%
Silkeborg	0.03%	0.37%	1.68%	4.85%	7.72%	9.72%	12.40%	13.89%	15.16%	14.69%	13.52%	5.97%
Koge BK	—	—	0.02%	0.12%	0.28%	0.44%	1.17%	2.01%	3.68%	7.43%	17.27%	67.58%

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

+17.68%

Clear Edge

45.45%26.77%27.78%

Elo Value

Home Edge

232 Elo

0.004 goals per Elo point

062.07600

Scoring Tilt

Expected

+0.43 goals

Neutral

-2+0.27+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

2.3

Top-Heavy

124610

Champion Preseason Odds

38%

FC Copenhagen, 2nd of 12

LongshotFavorite

Title Margin

Expected

0.15/gm

Tight Race

00.210.5/gm

Simulation-Based Surprises

How these are measured

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

Luck Spread: Standard deviation of the gap between each team's actual points and their simulated average points. The gold line is the spread the model expected from chance alone.
As Expected: under 5.61 * Some Luck: 5.61 to 8.42 * Lucky: 8.42 to 11.22 * Wild Swing: 11.22 and up.
Average Finish Error: Average gap between where each team was projected to finish and where they actually finished in the table.
Pinpoint: under 1.28 * Close: 1.28 to 1.93 * Off: 1.93 to 2.57 * Way Off: 2.57 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 0.87 * A Surprise: 0.87 to 1.39 * Several Surprises: 1.39 to 1.92 * Many Surprises: 1.92 and up.

Luck Spread

Expected

6.38 points

Some Luck

07.0118

Average Finish Error

Expected

2.00

Off

01.614

Biggest Overachiever

Expected 95.83%

97.74%

Nordsjaelland

50100

Biggest Underachiever

Expected 4.17%

7.99%

Midtjylland

050

Season Outliers

Expected

1 of 12

Minimal Outliers

01.26

Unexpected Relegations

Expected

1 of 2

A Surprise

00.92

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

0.10

Balanced

00.120.180.260.5

Noll-Scully

Coin-flip

1.03

Moderate Separation

01.003

Interquartile Edge

59%

Even

50%60%70%80%100%

Best vs. Worst

Baseline

88%

Strong Edge

50%86%100%

Close Games

Expected

62%

Very Frequent

0%56%100%

Blowouts

Expected

18%

Frequent

0%20%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

0.64

Hard to Predict

00.602

Matchup Imbalance

0.37

Lopsided

00.10.180.280.5

Strangeness

Expected

0.83

As Expected

01.002

Repeatability

0.50

Some Carryover

00.30.60.851

Upset Rate

Expected

30%

As Expected

0%23%50%

Clear Favorite Upset Rate

Expected

25%

Shaky Favorites

0%20%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 0.19 * Above Noise: 0.19 to 0.25 * Well Above Noise: 0.25 and up.

Probability calibration

0.21

Well Calibrated

0.010.050.10.51

Calibration slope

Ideal

0.57

Overconfident

0.4416841.001.55832

Calibration error (ECE)

Noise ceiling

0.101

Well Within Noise

00.1230.3

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
Brondby	100%	—
FC Copenhagen	100%	—
Midtjylland	99.81%	0.19%
Odense	97.19%	2.81%
AB Copenhagen	96.06%	3.94%
Aalborg	93.81%	6.19%
Viborg	88.29%	11.71%
Esbjerg	82.79%	17.21%
Silkeborg	80.51%	19.49%
Aarhus GF	74.46%	25.54%
Nordsjaelland	71.93%	28.07%
Koge BK	15.15%	84.85%

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
2002-07-27	Brondby	L 0-3	1550	1765	19.35%	24.05%	56.60%	-6.8	0
2002-07-27	@ Silkeborg	W 3-0	1765	1550	56.60%	24.05%	19.35%	+6.8	3
2002-07-28	Aalborg	L 1-2	1544	1596	37.14%	28.38%	34.48%	-4.1	0
2002-07-28	@ Esbjerg	W 2-1	1596	1544	34.48%	28.38%	37.14%	+4.1	3
2002-07-28	Koge BK	D 2-2	1617	1450	65.62%	19.83%	14.55%	-0.9	1
2002-07-28	@ AB Copenhagen	D 2-2	1450	1617	14.55%	19.83%	65.62%	+0.9	1
2002-07-28	Midtjylland	W 2-0	1602	1679	33.72%	28.35%	37.93%	+8.3	3
2002-07-28	@ Odense	L 0-2	1679	1602	37.93%	28.35%	33.72%	-8.3	0
2002-07-28	Nordsjaelland	W 2-0	1556	1528	48.35%	26.80%	24.85%	+5.9	3
2002-07-28	@ Aarhus GF	L 0-2	1528	1556	24.85%	26.80%	48.35%	-5.9	0
2002-07-28	Viborg	D 2-2	1761	1579	67.37%	18.91%	13.72%	-1.0	1
2002-07-28	@ FC Copenhagen	D 2-2	1579	1761	13.72%	18.91%	67.37%	+1.0	1
2002-08-03	AB Copenhagen	L 1-3	1772	1616	64.48%	20.42%	15.11%	-10.7	3
2002-08-03	@ Brondby	W 3-1	1616	1772	15.11%	20.42%	64.48%	+10.7	4
2002-08-04	Aalborg	W 2-0	1670	1600	53.93%	25.07%	21.00%	+5.1	3
2002-08-04	@ Midtjylland	L 0-2	1600	1670	21.00%	25.07%	53.93%	-5.1	3
2002-08-04	Esbjerg	D 2-2	1562	1540	47.61%	26.98%	25.41%	-0.4	4
2002-08-04	@ Aarhus GF	D 2-2	1540	1562	25.41%	26.98%	47.61%	+0.4	1
2002-08-04	FC Copenhagen	L 1-3	1451	1760	13.62%	18.78%	67.60%	-2.7	1
2002-08-04	@ Koge BK	W 3-1	1760	1451	67.60%	18.78%	13.62%	+2.7	4
2002-08-04	Silkeborg	D 2-2	1610	1544	53.49%	25.23%	21.28%	-0.6	4
2002-08-04	@ Odense	D 2-2	1544	1610	21.28%	25.23%	53.49%	+0.6	1
2002-08-04	Viborg	W 3-2	1522	1580	36.48%	28.39%	35.13%	+3.7	3
2002-08-04	@ Nordsjaelland	L 2-3	1580	1522	35.13%	28.39%	36.48%	-3.7	1
2002-08-10	Brondby	W 3-1	1595	1761	23.46%	26.27%	50.27%	+8.9	6
2002-08-10	@ Aalborg	L 1-3	1761	1595	50.27%	26.27%	23.46%	-8.9	3
2002-08-11	Aarhus GF	W 1-0	1544	1561	42.23%	27.98%	29.79%	+3.7	4
2002-08-11	@ Silkeborg	L 0-1	1561	1544	29.79%	27.98%	42.23%	-3.7	4
2002-08-11	Koge BK	L 3-4	1540	1449	56.66%	24.02%	19.31%	-5.2	1
2002-08-11	@ Esbjerg	W 4-3	1449	1540	19.31%	24.02%	56.66%	+5.2	4
2002-08-11	Midtjylland	D 1-1	1576	1675	30.74%	28.11%	41.15%	+0.2	2
2002-08-11	@ Viborg	D 1-1	1675	1576	41.15%	28.11%	30.74%	-0.2	4
2002-08-11	Nordsjaelland	W 2-1	1762	1526	73.11%	15.74%	11.16%	+1.2	7
2002-08-11	@ FC Copenhagen	L 1-2	1526	1762	11.16%	15.74%	73.11%	-1.2	3
2002-08-11	Odense	L 0-4	1626	1609	46.95%	27.13%	25.92%	-18.5	4
2002-08-11	@ AB Copenhagen	W 4-0	1609	1626	25.92%	27.13%	46.95%	+18.5	7
2002-08-17	Esbjerg	L 3-4	1525	1535	43.20%	27.84%	28.96%	-4.2	3
2002-08-17	@ Nordsjaelland	W 4-3	1535	1525	28.96%	27.84%	43.20%	+4.2	4
2002-08-18	AB Copenhagen	W 1-0	1604	1608	44.09%	27.70%	28.21%	+3.5	9
2002-08-18	@ Aalborg	L 0-1	1608	1604	28.21%	27.70%	44.09%	-3.5	4
2002-08-18	FC Copenhagen	D 2-2	1675	1763	32.19%	28.25%	39.56%	+0.1	5
2002-08-18	@ Midtjylland	D 2-2	1763	1675	39.56%	28.25%	32.19%	-0.1	8
2002-08-18	Odense	W 3-2	1557	1628	34.62%	28.38%	37.00%	+3.9	7
2002-08-18	@ Aarhus GF	L 2-3	1628	1557	37.00%	28.38%	34.62%	-3.8	7
2002-08-18	Silkeborg	L 0-4	1454	1548	31.45%	28.18%	40.37%	-13.7	4
2002-08-18	@ Koge BK	W 4-0	1548	1454	40.37%	28.18%	31.45%	+13.7	7
2002-08-18	Viborg	W 4-0	1752	1576	66.75%	19.23%	14.01%	+6.1	6
2002-08-18	@ Brondby	L 0-4	1576	1752	14.01%	19.23%	66.75%	-6.1	2
2002-08-24	Brondby	W 2-1	1763	1759	45.26%	27.49%	27.25%	+3.2	11
2002-08-24	@ FC Copenhagen	L 1-2	1759	1763	27.25%	27.49%	45.26%	-3.2	6
2002-08-25	Aalborg	D 2-2	1570	1608	39.27%	28.27%	32.45%	-0.1	3
2002-08-25	@ Viborg	D 2-2	1608	1570	32.45%	28.27%	39.27%	+0.1	10
2002-08-25	Aarhus GF	D 2-2	1604	1561	50.46%	26.21%	23.32%	-0.5	5
2002-08-25	@ AB Copenhagen	D 2-2	1561	1604	23.32%	26.21%	50.46%	+0.5	8
2002-08-25	Koge BK	W 2-1	1624	1440	67.58%	18.80%	13.63%	+1.5	10
2002-08-25	@ Odense	L 1-2	1440	1624	13.63%	18.80%	67.58%	-1.6	4
2002-08-25	Midtjylland	W 3-2	1539	1675	26.45%	27.28%	46.27%	+4.6	7
2002-08-25	@ Esbjerg	L 2-3	1675	1539	46.27%	27.28%	26.45%	-4.6	5
2002-08-25	Nordsjaelland	L 0-1	1562	1520	50.18%	26.30%	23.52%	-5.4	7
2002-08-25	@ Silkeborg	W 1-0	1520	1562	23.52%	26.30%	50.18%	+5.4	6
2002-08-31	Aarhus GF	W 2-0	1439	1562	27.90%	27.63%	44.47%	+9.3	7
2002-08-31	@ Koge BK	L 0-2	1562	1439	44.47%	27.63%	27.90%	-9.3	8
2002-09-01	AB Copenhagen	W 2-1	1570	1604	39.80%	28.23%	31.97%	+3.7	6
2002-09-01	@ Viborg	L 1-2	1604	1570	31.97%	28.23%	39.80%	-3.7	5
2002-09-01	Esbjerg	D 1-1	1755	1544	70.59%	17.15%	12.26%	-1.4	7
2002-09-01	@ Brondby	D 1-1	1544	1755	12.26%	17.15%	70.59%	+1.4	8
2002-09-01	FC Copenhagen	W 3-0	1608	1767	24.16%	26.55%	49.29%	+14.7	13
2002-09-01	@ Aalborg	L 0-3	1767	1608	49.29%	26.55%	24.16%	-14.7	11
2002-09-01	Odense	W 2-1	1526	1626	30.73%	28.10%	41.17%	+4.4	9
2002-09-01	@ Nordsjaelland	L 1-2	1626	1526	41.17%	28.10%	30.73%	-4.4	10
2002-09-01	Silkeborg	W 2-0	1671	1556	59.54%	22.79%	17.67%	+4.2	8
2002-09-01	@ Midtjylland	L 0-2	1556	1671	17.67%	22.79%	59.54%	-4.2	7
2002-09-08	Aalborg	W 3-0	1621	1623	44.40%	27.65%	27.96%	+9.5	13
2002-09-08	@ Odense	L 0-3	1623	1621	27.96%	27.65%	44.40%	-9.5	13
2002-09-08	Brondby	D 2-2	1552	1754	20.39%	24.72%	54.90%	+0.6	9
2002-09-08	@ Aarhus GF	D 2-2	1754	1552	54.90%	24.72%	20.39%	-0.6	8
2002-09-08	FC Copenhagen	W 3-0	1545	1752	19.96%	24.45%	55.58%	+16.1	11
2002-09-08	@ Esbjerg	L 0-3	1752	1545	55.58%	24.45%	19.96%	-16.1	11
2002-09-08	Midtjylland	L 2-3	1448	1675	18.48%	23.43%	58.10%	-2.1	7
2002-09-08	@ Koge BK	W 3-2	1675	1448	58.10%	23.43%	18.48%	+2.1	11
2002-09-08	Nordsjaelland	W 2-0	1600	1530	53.97%	25.06%	20.97%	+5.1	8
2002-09-08	@ AB Copenhagen	L 0-2	1530	1600	20.97%	25.06%	53.97%	-5.1	9
2002-09-08	Viborg	D 1-1	1552	1574	41.57%	28.06%	30.37%	-0.2	8
2002-09-08	@ Silkeborg	D 1-1	1574	1552	30.37%	28.06%	41.57%	+0.2	7
2002-09-14	Koge BK	W 1-0	1525	1446	55.16%	24.62%	20.22%	+2.6	12
2002-09-14	@ Nordsjaelland	L 0-1	1446	1525	20.22%	24.62%	55.16%	-2.6	7
2002-09-15	Aarhus GF	L 1-2	1677	1553	60.67%	22.27%	17.06%	-5.9	11
2002-09-15	@ Midtjylland	W 2-1	1553	1677	17.06%	22.27%	60.67%	+5.9	12
2002-09-15	AB Copenhagen	W 1-0	1736	1605	61.43%	21.91%	16.65%	+2.1	14
2002-09-15	@ FC Copenhagen	L 0-1	1605	1736	16.65%	21.91%	61.43%	-2.1	8
2002-09-15	Esbjerg	W 6-0	1574	1561	46.35%	27.27%	26.38%	+17.4	10
2002-09-15	@ Viborg	L 0-6	1561	1574	26.38%	27.27%	46.35%	-17.4	11
2002-09-15	Odense	W 2-0	1753	1631	60.51%	22.35%	17.14%	+4.1	11
2002-09-15	@ Brondby	L 0-2	1631	1753	17.14%	22.35%	60.51%	-4.1	13
2002-09-15	Silkeborg	W 1-0	1613	1552	52.85%	25.45%	21.69%	+2.8	16
2002-09-15	@ Aalborg	L 0-1	1552	1613	21.69%	25.45%	52.85%	-2.8	8
2002-09-21	Nordsjaelland	L 1-3	1616	1528	56.25%	24.19%	19.56%	-9.7	16
2002-09-21	@ Aalborg	W 3-1	1528	1616	19.56%	24.19%	56.25%	+9.7	15
2002-09-22	Aarhus GF	W 2-0	1738	1559	67.03%	19.09%	13.88%	+3.2	17
2002-09-22	@ FC Copenhagen	L 0-2	1559	1738	13.88%	19.09%	67.03%	-3.2	12
2002-09-22	Koge BK	L 1-4	1591	1443	63.51%	20.91%	15.59%	-15.0	10
2002-09-22	@ Viborg	W 4-1	1443	1591	15.59%	20.91%	63.51%	+15.0	10
2002-09-22	Midtjylland	W 4-0	1757	1671	56.03%	24.28%	19.69%	+9.0	14
2002-09-22	@ Brondby	L 0-4	1671	1757	19.69%	24.28%	56.03%	-9.0	11
2002-09-22	Odense	W 5-0	1544	1627	32.90%	28.30%	38.79%	+19.7	14
2002-09-22	@ Esbjerg	L 0-5	1627	1544	38.79%	28.30%	32.90%	-19.7	13
2002-09-22	Silkeborg	W 1-0	1603	1549	51.95%	25.75%	22.30%	+2.9	11
2002-09-22	@ AB Copenhagen	L 0-1	1549	1603	22.30%	25.75%	51.95%	-2.8	8
2002-09-28	Viborg	L 1-3	1556	1576	41.76%	28.04%	30.21%	-7.7	12
2002-09-28	@ Aarhus GF	W 3-1	1576	1556	30.21%	28.04%	41.76%	+7.7	13
2002-09-29	Aalborg	L 0-2	1458	1606	25.22%	26.92%	47.86%	-6.0	10
2002-09-29	@ Koge BK	W 2-0	1606	1458	47.86%	26.92%	25.22%	+6.0	19
2002-09-29	AB Copenhagen	D 1-1	1662	1606	52.13%	25.69%	22.17%	-0.7	12
2002-09-29	@ Midtjylland	D 1-1	1606	1662	22.17%	25.69%	52.13%	+0.7	12
2002-09-29	Brondby	L 1-2	1538	1766	18.34%	23.32%	58.33%	-2.2	15
2002-09-29	@ Nordsjaelland	W 2-1	1766	1538	58.33%	23.32%	18.34%	+2.2	17
2002-09-29	Esbjerg	D 1-1	1546	1563	42.18%	27.98%	29.84%	-0.3	9
2002-09-29	@ Silkeborg	D 1-1	1563	1546	29.84%	27.98%	42.18%	+0.3	15
2002-09-29	FC Copenhagen	L 0-1	1607	1741	26.67%	27.34%	45.98%	-3.4	13
2002-09-29	@ Odense	W 1-0	1741	1607	45.98%	27.34%	26.67%	+3.4	20
2002-10-04	Aarhus GF	L 1-2	1612	1548	53.19%	25.33%	21.47%	-5.4	19
2002-10-04	@ Aalborg	W 2-1	1548	1612	21.47%	25.33%	53.19%	+5.4	15
2002-10-06	Esbjerg	L 1-2	1607	1564	50.47%	26.21%	23.32%	-5.1	12
2002-10-06	@ AB Copenhagen	W 2-1	1564	1607	23.32%	26.21%	50.47%	+5.1	18
2002-10-06	Koge BK	L 1-2	1769	1452	80.42%	11.51%	8.07%	-7.1	17
2002-10-06	@ Brondby	W 2-1	1452	1769	8.07%	11.51%	80.42%	+7.1	13
2002-10-06	Nordsjaelland	W 1-0	1661	1535	60.92%	22.15%	16.92%	+2.1	15
2002-10-06	@ Midtjylland	L 0-1	1535	1661	16.92%	22.15%	60.92%	-2.1	15
2002-10-06	Silkeborg	W 2-1	1744	1546	69.19%	17.92%	12.89%	+1.4	23
2002-10-06	@ FC Copenhagen	L 1-2	1546	1744	12.89%	17.92%	69.19%	-1.5	9
2002-10-06	Viborg	W 3-0	1604	1584	47.30%	27.05%	25.64%	+8.9	16
2002-10-06	@ Odense	L 0-3	1584	1604	25.64%	27.05%	47.30%	-8.9	13
2002-10-19	Midtjylland	D 1-1	1746	1664	55.53%	24.47%	19.99%	-0.9	24
2002-10-19	@ FC Copenhagen	D 1-1	1664	1746	19.99%	24.47%	55.53%	+0.9	16
2002-10-20	Brondby	D 1-1	1602	1761	24.05%	26.51%	49.44%	+0.6	13
2002-10-20	@ AB Copenhagen	D 1-1	1761	1602	49.44%	26.51%	24.05%	-0.6	18
2002-10-20	Koge BK	L 1-3	1553	1459	57.02%	23.88%	19.10%	-9.8	15
2002-10-20	@ Aarhus GF	W 3-1	1459	1553	19.10%	23.88%	57.02%	+9.8	16
2002-10-20	Nordsjaelland	L 0-2	1569	1533	49.45%	26.50%	24.04%	-10.1	18
2002-10-20	@ Esbjerg	W 2-0	1533	1569	24.04%	26.50%	49.45%	+10.1	18
2002-10-20	Odense	D 0-0	1575	1612	39.34%	28.27%	32.39%	-0.2	14
2002-10-20	@ Viborg	D 0-0	1612	1575	32.39%	28.27%	39.34%	+0.2	17
2002-10-20	Silkeborg	L 3-4	1607	1544	53.00%	25.40%	21.60%	-4.9	19
2002-10-20	@ Aalborg	W 4-3	1544	1607	21.60%	25.40%	53.00%	+4.9	12
2002-10-26	FC Copenhagen	L 0-3	1575	1745	23.06%	26.10%	50.83%	-8.1	14
2002-10-26	@ Viborg	W 3-0	1745	1575	50.83%	26.10%	23.06%	+8.1	27
2002-10-27	Aalborg	W 1-0	1761	1602	64.78%	20.26%	14.96%	+1.9	21
2002-10-27	@ Brondby	L 0-1	1602	1761	14.96%	20.26%	64.78%	-1.9	19
2002-10-27	Aarhus GF	W 2-1	1549	1544	45.37%	27.47%	27.17%	+3.2	15
2002-10-27	@ Silkeborg	L 1-2	1544	1549	27.17%	27.47%	45.37%	-3.2	15
2002-10-27	AB Copenhagen	D 0-0	1613	1602	46.01%	27.34%	26.65%	-0.5	18
2002-10-27	@ Odense	D 0-0	1602	1613	26.65%	27.34%	46.01%	+0.5	14
2002-10-27	Esbjerg	L 1-4	1469	1559	32.02%	28.24%	39.74%	-9.0	16
2002-10-27	@ Koge BK	W 4-1	1559	1469	39.74%	28.24%	32.02%	+9.0	21
2002-10-27	Midtjylland	W 1-0	1543	1664	28.14%	27.68%	44.18%	+4.9	21
2002-10-27	@ Nordsjaelland	L 0-1	1664	1543	44.18%	27.68%	28.14%	-4.9	16
2002-11-02	Brondby	W 2-1	1540	1763	18.82%	23.67%	57.51%	+5.7	18
2002-11-02	@ Aarhus GF	L 1-2	1763	1540	57.51%	23.67%	18.82%	-5.7	21
2002-11-03	Koge BK	W 5-0	1659	1460	69.26%	17.88%	12.86%	+6.8	19
2002-11-03	@ Midtjylland	L 0-5	1460	1659	12.86%	17.88%	69.26%	-6.8	16
2002-11-03	Nordsjaelland	W 4-0	1753	1548	69.85%	17.56%	12.59%	+5.3	30
2002-11-03	@ FC Copenhagen	L 0-4	1548	1753	12.59%	17.56%	69.85%	-5.3	21
2002-11-03	Odense	W 2-1	1600	1612	42.92%	27.88%	29.20%	+3.4	22
2002-11-03	@ Aalborg	L 1-2	1612	1600	29.20%	27.88%	42.92%	-3.4	18
2002-11-03	Silkeborg	D 1-1	1568	1552	46.69%	27.19%	26.11%	-0.5	22
2002-11-03	@ Esbjerg	D 1-1	1552	1568	26.11%	27.19%	46.69%	+0.5	16
2002-11-03	Viborg	D 1-1	1603	1567	49.52%	26.49%	24.00%	-0.6	15
2002-11-03	@ AB Copenhagen	D 1-1	1567	1603	24.00%	26.49%	49.52%	+0.6	15
2002-11-09	Aalborg	L 1-3	1567	1603	39.53%	28.25%	32.22%	-7.4	15
2002-11-09	@ Viborg	W 3-1	1603	1567	32.22%	28.25%	39.53%	+7.4	25
2002-11-10	Aarhus GF	D 2-2	1609	1546	53.00%	25.40%	21.60%	-0.5	19
2002-11-10	@ Odense	D 2-2	1546	1609	21.60%	25.40%	53.00%	+0.6	19
2002-11-10	Esbjerg	D 1-1	1757	1567	68.24%	18.44%	13.32%	-1.3	22
2002-11-10	@ Brondby	D 1-1	1567	1757	13.32%	18.44%	68.24%	+1.3	23
2002-11-10	FC Copenhagen	D 0-0	1602	1758	24.40%	26.64%	48.97%	+0.7	16
2002-11-10	@ AB Copenhagen	D 0-0	1758	1602	48.97%	26.64%	24.40%	-0.6	31
2002-11-10	Midtjylland	D 1-1	1553	1666	29.05%	27.86%	43.09%	+0.3	17
2002-11-10	@ Silkeborg	D 1-1	1666	1553	43.09%	27.86%	29.05%	-0.3	20
2002-11-10	Nordsjaelland	W 4-2	1453	1543	32.03%	28.24%	39.73%	+6.6	19
2002-11-10	@ Koge BK	L 2-4	1543	1453	39.73%	28.24%	32.03%	-6.6	21
2002-11-16	Odense	D 4-4	1568	1608	39.02%	28.29%	32.69%	-0.1	24
2002-11-16	@ Esbjerg	D 4-4	1608	1568	32.69%	28.29%	39.02%	+0.1	20
2002-11-17	AB Copenhagen	L 0-4	1611	1603	45.70%	27.40%	26.90%	-18.1	25
2002-11-17	@ Aalborg	W 4-0	1603	1611	26.90%	27.40%	45.70%	+18.1	19
2002-11-17	Brondby	D 1-1	1666	1756	31.99%	28.24%	39.77%	+0.2	21
2002-11-17	@ Midtjylland	D 1-1	1756	1666	39.77%	28.24%	31.99%	-0.2	23
2002-11-17	Koge BK	W 1-0	1758	1460	78.84%	12.43%	8.72%	+0.9	34
2002-11-17	@ FC Copenhagen	L 0-1	1460	1758	8.72%	12.43%	78.84%	-0.9	19
2002-11-17	Silkeborg	W 3-2	1536	1553	42.23%	27.98%	29.79%	+3.3	24
2002-11-17	@ Nordsjaelland	L 2-3	1553	1536	29.79%	27.98%	42.23%	-3.3	17
2002-11-17	Viborg	L 2-4	1547	1560	42.75%	27.91%	29.34%	-7.0	19
2002-11-17	@ Aarhus GF	W 4-2	1560	1547	29.34%	27.91%	42.75%	+7.0	18
2002-11-23	Nordsjaelland	W 7-1	1755	1540	71.03%	16.91%	12.07%	+6.1	26
2002-11-23	@ Brondby	L 1-7	1540	1755	12.07%	16.91%	71.03%	-6.1	24
2002-11-24	Aarhus GF	W 3-1	1621	1540	55.40%	24.53%	20.08%	+4.2	22
2002-11-24	@ AB Copenhagen	L 1-3	1540	1621	20.08%	24.53%	55.40%	-4.2	19
2002-11-24	Esbjerg	W 4-1	1567	1568	44.40%	27.65%	27.95%	+8.0	21
2002-11-24	@ Viborg	L 1-4	1568	1567	27.95%	27.65%	44.40%	-8.1	24
2002-11-24	FC Copenhagen	D 1-1	1593	1759	23.46%	26.27%	50.27%	+0.6	26
2002-11-24	@ Aalborg	D 1-1	1759	1593	50.27%	26.27%	23.46%	-0.6	35
2002-11-24	Koge BK	L 3-4	1550	1459	56.60%	24.05%	19.35%	-5.2	17
2002-11-24	@ Silkeborg	W 4-3	1459	1550	19.35%	24.05%	56.60%	+5.2	22
2002-11-24	Midtjylland	W 1-0	1608	1666	36.41%	28.39%	35.20%	+4.2	23
2002-11-24	@ Odense	L 0-1	1666	1608	35.20%	28.39%	36.41%	-4.2	21
2002-11-30	Brondby	L 0-2	1464	1762	14.18%	19.43%	66.39%	-3.3	22
2002-11-30	@ Koge BK	W 2-0	1762	1464	66.39%	19.43%	14.18%	+3.3	29
2002-12-01	Aalborg	W 1-0	1536	1593	36.41%	28.39%	35.20%	+4.2	22
2002-12-01	@ Aarhus GF	L 0-1	1593	1536	35.20%	28.39%	36.41%	-4.2	26
2002-12-01	AB Copenhagen	D 1-1	1560	1625	35.41%	28.39%	36.19%	+0.0	25
2002-12-01	@ Esbjerg	D 1-1	1625	1560	36.19%	28.39%	35.41%	-0.0	23
2002-12-01	Odense	W 2-1	1533	1612	33.44%	28.34%	38.23%	+4.2	27
2002-12-01	@ Nordsjaelland	L 1-2	1612	1533	38.23%	28.34%	33.44%	-4.2	23
2002-12-01	Silkeborg	W 3-0	1758	1545	70.75%	17.06%	12.19%	+3.9	38
2002-12-01	@ FC Copenhagen	L 0-3	1545	1758	12.19%	17.06%	70.75%	-3.9	17
2002-12-01	Viborg	W 3-1	1662	1575	56.10%	24.25%	19.65%	+4.1	24
2002-12-01	@ Midtjylland	L 1-3	1575	1662	19.65%	24.25%	56.10%	-4.1	21
2003-03-15	Viborg	W 2-1	1765	1571	68.68%	18.20%	13.12%	+1.5	32
2003-03-15	@ Brondby	L 1-2	1571	1765	13.12%	18.20%	68.68%	-1.5	21
2003-03-16	Aalborg	D 1-1	1461	1589	27.33%	27.51%	45.16%	+0.4	23
2003-03-16	@ Koge BK	D 1-1	1589	1461	45.16%	27.51%	27.33%	-0.4	27
2003-03-16	AB Copenhagen	W 3-0	1541	1625	32.71%	28.29%	39.00%	+12.3	20
2003-03-16	@ Silkeborg	L 0-3	1625	1541	39.00%	28.29%	32.71%	-12.3	23
2003-03-16	Esbjerg	W 2-0	1666	1560	58.44%	23.28%	18.28%	+4.4	27
2003-03-16	@ Midtjylland	L 0-2	1560	1666	18.28%	23.28%	58.44%	-4.4	25
2003-03-16	FC Copenhagen	W 2-0	1608	1762	24.63%	26.72%	48.65%	+10.0	26
2003-03-16	@ Odense	L 0-2	1762	1608	48.65%	26.72%	24.63%	-10.0	38
2003-03-22	Silkeborg	W 2-0	1766	1553	70.74%	17.07%	12.19%	+2.7	35
2003-03-22	@ Brondby	L 0-2	1553	1766	12.19%	17.07%	70.74%	-2.7	20
2003-03-23	Esbjerg	L 0-1	1589	1556	49.08%	26.61%	24.32%	-5.3	27
2003-03-23	@ Aalborg	W 1-0	1556	1589	24.32%	26.61%	49.08%	+5.3	28
2003-03-23	FC Copenhagen	D 2-2	1540	1752	19.55%	24.18%	56.27%	+0.7	23
2003-03-23	@ Aarhus GF	D 2-2	1752	1540	56.27%	24.18%	19.55%	-0.7	39
2003-03-23	Koge BK	W 3-1	1618	1461	64.53%	20.39%	15.08%	+3.0	29
2003-03-23	@ Odense	L 1-3	1461	1618	15.08%	20.39%	64.53%	-3.0	23
2003-03-23	Midtjylland	L 0-3	1613	1670	36.46%	28.39%	35.15%	-11.7	23
2003-03-23	@ AB Copenhagen	W 3-0	1670	1613	35.15%	28.39%	36.46%	+11.7	30
2003-03-24	Nordsjaelland	L 1-3	1569	1538	48.95%	26.64%	24.41%	-8.7	21
2003-03-24	@ Viborg	W 3-1	1538	1569	24.41%	26.64%	48.95%	+8.7	30
2003-04-05	Aalborg	W 2-1	1682	1583	57.57%	23.65%	18.78%	+2.2	33
2003-04-05	@ Midtjylland	L 1-2	1583	1682	18.78%	23.65%	57.57%	-2.2	27
2003-04-06	Aarhus GF	W 4-1	1561	1540	47.48%	27.01%	25.51%	+7.5	31
2003-04-06	@ Esbjerg	L 1-4	1540	1561	25.51%	27.01%	47.48%	-7.4	23
2003-04-06	AB Copenhagen	W 2-0	1546	1601	36.83%	28.38%	34.78%	+7.8	33
2003-04-06	@ Nordsjaelland	L 0-2	1601	1546	34.78%	28.38%	36.83%	-7.8	23
2003-04-06	Brondby	D 1-1	1751	1769	42.13%	27.99%	29.88%	-0.3	40
2003-04-06	@ FC Copenhagen	D 1-1	1769	1751	29.88%	27.99%	42.13%	+0.3	36
2003-04-06	Odense	D 1-1	1550	1621	34.56%	28.38%	37.07%	+0.1	21
2003-04-06	@ Silkeborg	D 1-1	1621	1550	37.07%	28.38%	34.56%	-0.0	30
2003-04-06	Viborg	W 2-0	1458	1561	30.39%	28.06%	41.55%	+8.9	26
2003-04-06	@ Koge BK	L 0-2	1561	1458	41.55%	28.06%	30.39%	-8.9	21
2003-04-12	Brondby	D 1-1	1621	1769	25.20%	26.91%	47.89%	+0.5	31
2003-04-12	@ Odense	D 1-1	1769	1621	47.89%	26.91%	25.20%	-0.5	37
2003-04-13	Esbjerg	W 1-0	1751	1569	67.40%	18.89%	13.71%	+1.7	43
2003-04-13	@ FC Copenhagen	L 0-1	1569	1751	13.71%	18.89%	67.40%	-1.7	31
2003-04-13	Koge BK	W 3-1	1593	1467	60.93%	22.15%	16.92%	+3.5	26
2003-04-13	@ AB Copenhagen	L 1-3	1467	1593	16.92%	22.15%	60.93%	-3.5	26
2003-04-13	Midtjylland	W 3-2	1533	1684	24.87%	26.80%	48.33%	+4.7	26
2003-04-13	@ Aarhus GF	L 2-3	1684	1533	48.33%	26.80%	24.87%	-4.7	33
2003-04-13	Nordsjaelland	L 1-2	1581	1554	48.32%	26.80%	24.88%	-5.0	27
2003-04-13	@ Aalborg	W 2-1	1554	1581	24.88%	26.80%	48.32%	+5.0	36
2003-04-13	Silkeborg	D 0-0	1552	1550	44.80%	27.57%	27.62%	-0.4	22
2003-04-13	@ Viborg	D 0-0	1550	1552	27.62%	27.57%	44.80%	+0.4	22
2003-04-16	Aarhus GF	W 2-0	1576	1538	49.86%	26.39%	23.75%	+5.7	30
2003-04-16	@ Aalborg	L 0-2	1538	1576	23.75%	26.39%	49.86%	-5.7	26
2003-04-17	Esbjerg	L 1-4	1597	1567	48.67%	26.72%	24.62%	-12.2	26
2003-04-17	@ AB Copenhagen	W 4-1	1567	1597	24.62%	26.72%	48.67%	+12.2	34
2003-04-17	FC Copenhagen	W 3-0	1551	1753	20.36%	24.70%	54.94%	+15.9	25
2003-04-17	@ Silkeborg	L 0-3	1753	1551	54.94%	24.70%	20.36%	-15.9	43
2003-04-17	Koge BK	W 2-1	1769	1464	79.47%	12.07%	8.46%	+0.9	40
2003-04-17	@ Brondby	L 1-2	1464	1769	8.46%	12.07%	79.47%	-0.9	26
2003-04-17	Midtjylland	D 0-0	1551	1680	27.34%	27.51%	45.16%	+0.5	23
2003-04-17	@ Viborg	D 0-0	1680	1551	45.16%	27.51%	27.34%	-0.5	34
2003-04-17	Nordsjaelland	D 2-2	1622	1559	53.02%	25.40%	21.59%	-0.6	32
2003-04-17	@ Odense	D 2-2	1559	1622	21.59%	25.40%	53.02%	+0.6	37
2003-04-20	Brondby	D 1-1	1560	1770	19.72%	24.30%	55.99%	+0.9	38
2003-04-20	@ Nordsjaelland	D 1-1	1770	1560	55.99%	24.30%	19.72%	-0.9	41
2003-04-21	Aalborg	L 0-1	1737	1582	64.30%	20.51%	15.19%	-6.5	43
2003-04-21	@ FC Copenhagen	W 1-0	1582	1737	15.19%	20.51%	64.30%	+6.5	33
2003-04-21	AB Copenhagen	L 1-2	1532	1585	37.15%	28.38%	34.48%	-4.1	26
2003-04-21	@ Aarhus GF	W 2-1	1585	1532	34.48%	28.38%	37.15%	+4.1	29
2003-04-21	Odense	D 2-2	1679	1621	52.41%	25.60%	21.99%	-0.5	35
2003-04-21	@ Midtjylland	D 2-2	1621	1679	21.99%	25.60%	52.41%	+0.5	33
2003-04-21	Silkeborg	L 1-3	1463	1567	30.19%	28.03%	41.77%	-6.1	26
2003-04-21	@ Koge BK	W 3-1	1567	1463	41.77%	28.03%	30.19%	+6.1	28
2003-04-21	Viborg	L 1-5	1579	1552	48.36%	26.79%	24.85%	-15.7	34
2003-04-21	@ Esbjerg	W 5-1	1552	1579	24.85%	26.79%	48.36%	+15.7	26
2003-04-24	Aarhus GF	W 2-0	1560	1528	49.05%	26.61%	24.33%	+5.8	41
2003-04-24	@ Nordsjaelland	L 0-2	1528	1560	24.33%	26.61%	49.05%	-5.8	26
2003-04-26	FC Copenhagen	L 0-5	1457	1730	15.51%	20.83%	63.65%	-8.5	26
2003-04-26	@ Koge BK	W 5-0	1730	1457	63.65%	20.83%	15.51%	+8.5	46
2003-04-27	Aalborg	W 3-1	1589	1589	44.63%	27.61%	27.76%	+5.7	32
2003-04-27	@ AB Copenhagen	L 1-3	1589	1589	27.76%	27.61%	44.63%	-5.7	33
2003-04-27	Aarhus GF	D 0-0	1568	1522	50.79%	26.12%	23.10%	-0.7	27
2003-04-27	@ Viborg	D 0-0	1522	1568	23.10%	26.12%	50.79%	+0.7	27
2003-04-27	Esbjerg	D 1-1	1622	1564	52.41%	25.60%	21.99%	-0.7	34
2003-04-27	@ Odense	D 1-1	1564	1622	21.99%	25.60%	52.41%	+0.7	35
2003-04-27	Midtjylland	W 3-1	1769	1679	56.52%	24.08%	19.40%	+4.0	44
2003-04-27	@ Brondby	L 1-3	1679	1769	19.40%	24.08%	56.52%	-4.0	35
2003-04-27	Nordsjaelland	W 5-1	1573	1566	45.51%	27.44%	27.05%	+10.1	31
2003-04-27	@ Silkeborg	L 1-5	1566	1573	27.05%	27.44%	45.51%	-10.1	41
2003-05-03	Brondby	L 1-2	1564	1773	19.84%	24.38%	55.78%	-2.4	35
2003-05-03	@ Esbjerg	W 2-1	1773	1564	55.78%	24.38%	19.84%	+2.4	47
2003-05-04	AB Copenhagen	D 1-1	1739	1594	63.09%	21.11%	15.80%	-1.2	47
2003-05-04	@ FC Copenhagen	D 1-1	1594	1739	15.80%	21.11%	63.09%	+1.2	33
2003-05-04	Koge BK	W 2-1	1556	1448	58.71%	23.16%	18.13%	+2.2	44
2003-05-04	@ Nordsjaelland	L 1-2	1448	1556	18.13%	23.16%	58.71%	-2.2	26
2003-05-04	Odense	W 4-1	1523	1621	30.90%	28.12%	40.97%	+10.7	30
2003-05-04	@ Aarhus GF	L 1-4	1621	1523	40.97%	28.12%	30.90%	-10.7	34
2003-05-04	Silkeborg	W 2-1	1675	1583	56.70%	24.01%	19.29%	+2.3	38
2003-05-04	@ Midtjylland	L 1-2	1583	1675	19.29%	24.01%	56.70%	-2.3	31
2003-05-04	Viborg	L 2-3	1583	1567	46.79%	27.17%	26.04%	-4.6	33
2003-05-04	@ Aalborg	W 3-2	1567	1583	26.04%	27.17%	46.79%	+4.6	30
2003-05-10	FC Copenhagen	L 0-1	1558	1738	22.25%	25.73%	52.02%	-2.8	44
2003-05-10	@ Nordsjaelland	W 1-0	1738	1558	52.02%	25.73%	22.25%	+2.9	50
2003-05-11	Aalborg	W 3-1	1610	1578	48.97%	26.64%	24.40%	+5.1	37
2003-05-11	@ Odense	L 1-3	1578	1610	24.40%	26.64%	48.97%	-5.1	33
2003-05-11	Aarhus GF	D 1-1	1775	1533	73.65%	15.43%	10.92%	-1.5	48
2003-05-11	@ Brondby	D 1-1	1533	1775	10.92%	15.43%	73.65%	+1.5	31
2003-05-11	AB Copenhagen	W 3-0	1572	1596	41.24%	28.10%	30.66%	+10.3	33
2003-05-11	@ Viborg	L 0-3	1596	1572	30.66%	28.10%	41.24%	-10.3	33
2003-05-11	Esbjerg	D 2-2	1581	1562	47.17%	27.08%	25.75%	-0.4	32
2003-05-11	@ Silkeborg	D 2-2	1562	1581	25.75%	27.08%	47.17%	+0.4	36
2003-05-11	Midtjylland	D 1-1	1446	1677	18.22%	23.23%	58.55%	+1.0	27
2003-05-11	@ Koge BK	D 1-1	1677	1446	58.55%	23.23%	18.22%	-1.0	39
2003-05-17	Odense	D 1-1	1585	1615	40.39%	28.18%	31.43%	-0.2	34
2003-05-17	@ AB Copenhagen	D 1-1	1615	1585	31.43%	28.18%	40.39%	+0.2	38
2003-05-18	Brondby	L 1-2	1573	1774	20.46%	24.76%	54.77%	-2.5	33
2003-05-18	@ Aalborg	W 2-1	1774	1573	54.77%	24.76%	20.46%	+2.5	51
2003-05-18	Koge BK	W 6-1	1562	1447	59.61%	22.76%	17.63%	+8.2	39
2003-05-18	@ Esbjerg	L 1-6	1447	1562	17.63%	22.76%	59.61%	-8.2	27
2003-05-18	Nordsjaelland	W 2-0	1676	1556	60.24%	22.47%	17.29%	+4.1	42
2003-05-18	@ Midtjylland	L 0-2	1556	1676	17.29%	22.47%	60.24%	-4.1	44
2003-05-18	Silkeborg	W 2-1	1535	1580	38.21%	28.34%	33.45%	+3.8	34
2003-05-18	@ Aarhus GF	L 1-2	1580	1535	33.45%	28.34%	38.21%	-3.8	32
2003-05-18	Viborg	L 2-3	1740	1582	64.74%	20.28%	14.98%	-5.9	50
2003-05-18	@ FC Copenhagen	W 3-2	1582	1740	14.98%	20.28%	64.74%	+5.9	36
2003-05-24	FC Copenhagen	L 1-2	1680	1734	36.89%	28.38%	34.72%	-4.0	42
2003-05-24	@ Midtjylland	W 2-1	1734	1680	34.72%	28.38%	36.89%	+4.1	53
2003-05-25	Aalborg	D 0-0	1577	1571	45.40%	27.46%	27.14%	-0.5	33
2003-05-25	@ Silkeborg	D 0-0	1571	1577	27.14%	27.46%	45.40%	+0.5	34
2003-05-25	Aarhus GF	L 1-4	1439	1539	30.71%	28.10%	41.18%	-8.7	27
2003-05-25	@ Koge BK	W 4-1	1539	1439	41.18%	28.10%	30.71%	+8.7	37
2003-05-25	AB Copenhagen	D 0-0	1776	1585	68.37%	18.37%	13.26%	-1.5	52
2003-05-25	@ Brondby	D 0-0	1585	1776	13.26%	18.37%	68.37%	+1.5	35
2003-05-25	Esbjerg	L 2-3	1551	1570	41.93%	28.02%	30.05%	-4.2	44
2003-05-25	@ Nordsjaelland	W 3-2	1570	1551	30.05%	28.02%	41.93%	+4.2	42
2003-05-25	Viborg	W 3-1	1615	1588	48.41%	26.78%	24.81%	+5.1	41
2003-05-25	@ Odense	L 1-3	1588	1615	24.81%	26.78%	48.41%	-5.1	36
2003-05-31	Nordsjaelland	D 2-2	1547	1547	44.64%	27.60%	27.75%	-0.3	38
2003-05-31	@ Aarhus GF	D 2-2	1547	1547	27.75%	27.60%	44.64%	+0.3	45
2003-06-01	Brondby	D 1-1	1583	1775	21.15%	25.16%	53.70%	+0.8	37
2003-06-01	@ Viborg	D 1-1	1775	1583	53.70%	25.16%	21.15%	-0.8	53
2003-06-01	Koge BK	W 1-0	1571	1430	62.68%	21.32%	16.01%	+2.0	37
2003-06-01	@ Aalborg	L 0-1	1430	1571	16.01%	21.32%	62.68%	-2.0	27
2003-06-01	Midtjylland	W 4-1	1575	1676	30.53%	28.08%	41.39%	+10.8	45
2003-06-01	@ Esbjerg	L 1-4	1676	1575	41.39%	28.08%	30.53%	-10.8	42
2003-06-01	Odense	D 1-1	1739	1621	59.94%	22.61%	17.45%	-1.0	54
2003-06-01	@ FC Copenhagen	D 1-1	1621	1739	17.45%	22.61%	59.94%	+1.0	42
2003-06-01	Silkeborg	W 3-1	1587	1576	46.05%	27.33%	26.62%	+5.5	38
2003-06-01	@ AB Copenhagen	L 1-3	1576	1587	26.62%	27.33%	46.05%	-5.5	33
2003-06-14	FC Copenhagen	D 0-0	1586	1738	24.81%	26.78%	48.41%	+0.6	46
2003-06-14	@ Esbjerg	D 0-0	1738	1586	48.41%	26.78%	24.81%	-0.6	55
2003-06-15	Aalborg	L 1-3	1547	1573	40.99%	28.12%	30.88%	-7.6	45
2003-06-15	@ Nordsjaelland	W 3-1	1573	1547	30.88%	28.12%	40.99%	+7.6	40
2003-06-15	Aarhus GF	D 1-1	1665	1547	59.95%	22.61%	17.45%	-1.0	43
2003-06-15	@ Midtjylland	D 1-1	1547	1665	17.45%	22.61%	59.95%	+1.0	39
2003-06-15	AB Copenhagen	L 2-3	1428	1592	23.67%	26.36%	49.97%	-2.7	27
2003-06-15	@ Koge BK	W 3-2	1592	1428	49.97%	26.36%	23.67%	+2.7	41
2003-06-15	Odense	W 4-0	1774	1622	64.00%	20.66%	15.34%	+6.8	56
2003-06-15	@ Brondby	L 0-4	1622	1774	15.34%	20.66%	64.00%	-6.8	42
2003-06-15	Viborg	L 2-3	1571	1583	42.83%	27.90%	29.28%	-4.3	33
2003-06-15	@ Silkeborg	W 3-2	1583	1571	29.28%	27.90%	42.83%	+4.3	40
2003-06-18	Esbjerg	D 1-1	1548	1586	39.26%	28.27%	32.47%	-0.2	40
2003-06-18	@ Aarhus GF	D 1-1	1586	1548	32.47%	28.27%	39.26%	+0.1	47
2003-06-18	FC Copenhagen	L 0-1	1781	1737	50.53%	26.19%	23.27%	-5.5	56
2003-06-18	@ Brondby	W 1-0	1737	1781	23.27%	26.19%	50.53%	+5.5	58
2003-06-18	Koge BK	W 6-1	1588	1426	65.12%	20.09%	14.79%	+6.7	43
2003-06-18	@ Viborg	L 1-6	1426	1588	14.79%	20.09%	65.12%	-6.6	27
2003-06-18	Midtjylland	W 1-0	1581	1664	32.85%	28.30%	38.85%	+4.5	43
2003-06-18	@ Aalborg	L 0-1	1664	1581	38.85%	28.30%	32.85%	-4.5	43
2003-06-18	Nordsjaelland	L 1-2	1595	1540	52.00%	25.74%	22.26%	-5.3	41
2003-06-18	@ AB Copenhagen	W 2-1	1540	1595	22.26%	25.74%	52.00%	+5.3	48
2003-06-18	Silkeborg	W 4-3	1615	1566	51.17%	26.00%	22.83%	+2.6	45
2003-06-18	@ Odense	L 3-4	1566	1615	22.83%	26.00%	51.17%	-2.5	33
2003-06-22	Aalborg	L 0-1	1586	1585	44.75%	27.58%	27.67%	-5.0	47
2003-06-22	@ Esbjerg	W 1-0	1585	1586	27.67%	27.58%	44.75%	+5.0	46
2003-06-22	Aarhus GF	W 4-1	1742	1548	68.72%	18.18%	13.10%	+3.6	61
2003-06-22	@ FC Copenhagen	L 1-4	1548	1742	13.10%	18.18%	68.72%	-3.6	40
2003-06-22	AB Copenhagen	D 3-3	1660	1589	53.98%	25.06%	20.96%	-0.5	44
2003-06-22	@ Midtjylland	D 3-3	1589	1660	20.96%	25.06%	53.98%	+0.5	42
2003-06-22	Brondby	W 4-3	1564	1775	19.61%	24.23%	56.16%	+5.2	36
2003-06-22	@ Silkeborg	L 3-4	1775	1564	56.16%	24.23%	19.61%	-5.2	56
2003-06-22	Odense	L 1-2	1419	1617	20.63%	24.86%	54.50%	-2.5	27
2003-06-22	@ Koge BK	W 2-1	1617	1419	54.50%	24.86%	20.63%	+2.5	48
2003-06-22	Viborg	W 1-0	1545	1594	37.66%	28.36%	33.98%	+4.1	51
2003-06-22	@ Nordsjaelland	L 0-1	1594	1545	33.98%	28.36%	37.66%	-4.1	43

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	2002-10-06	8.07%	Koge BK	1452	2	@ Brondby	1769	1
2	2003-05-18	14.98%	Viborg	1582	3	@ FC Copenhagen	1740	2
3	2002-08-03	15.11%	AB Copenhagen	1616	3	@ Brondby	1772	1
4	2003-04-21	15.19%	Aalborg	1582	1	@ FC Copenhagen	1737	0
5	2002-09-22	15.59%	Koge BK	1443	4	@ Viborg	1591	1
6	2002-09-15	17.06%	Aarhus GF	1553	2	@ Midtjylland	1677	1
7	2002-11-02	18.82%	@ Aarhus GF	1540	2	Brondby	1763	1
8	2002-10-20	19.10%	Koge BK	1459	3	@ Aarhus GF	1553	1
9	2002-08-11	19.31%	Koge BK	1449	4	@ Esbjerg	1540	3
10	2002-11-24	19.35%	Koge BK	1459	4	@ Silkeborg	1550	3
11	2002-09-21	19.56%	Nordsjaelland	1528	3	@ Aalborg	1616	1
12	2003-06-22	19.61%	@ Silkeborg	1564	4	Brondby	1775	3
13	2002-09-08	19.96%	@ Esbjerg	1545	3	FC Copenhagen	1752	0
14	2003-04-17	20.36%	@ Silkeborg	1551	3	FC Copenhagen	1753	0
15	2002-10-04	21.47%	Aarhus GF	1548	2	@ Aalborg	1612	1
16	2002-10-20	21.60%	Silkeborg	1544	4	@ Aalborg	1607	3
17	2003-06-18	22.26%	Nordsjaelland	1540	2	@ AB Copenhagen	1595	1
18	2003-06-18	23.27%	FC Copenhagen	1737	1	@ Brondby	1781	0
19	2002-10-06	23.32%	Esbjerg	1564	2	@ AB Copenhagen	1607	1
20	2002-08-10	23.46%	@ Aalborg	1595	3	Brondby	1761	1
21	2002-08-25	23.52%	Nordsjaelland	1520	1	@ Silkeborg	1562	0
22	2002-10-20	24.04%	Nordsjaelland	1533	2	@ Esbjerg	1569	0
23	2002-09-01	24.16%	@ Aalborg	1608	3	FC Copenhagen	1767	0
24	2003-03-23	24.32%	Esbjerg	1556	1	@ Aalborg	1589	0
25	2003-03-24	24.41%	Nordsjaelland	1538	3	@ Viborg	1569	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	2002-09-22	19.70	@ Esbjerg	5	1544	32.90%	Odense	0	1627	38.79%	28.30%
2	2002-08-11	18.45	Odense	4	1609	25.92%	@ AB Copenhagen	0	1626	46.95%	27.13%
3	2002-11-17	18.07	AB Copenhagen	4	1603	26.90%	@ Aalborg	0	1611	45.70%	27.40%
4	2002-09-15	17.39	@ Viborg	6	1574	46.35%	Esbjerg	0	1561	26.38%	27.27%
5	2002-09-08	16.09	@ Esbjerg	3	1545	19.96%	FC Copenhagen	0	1752	55.58%	24.45%
6	2003-04-17	15.94	@ Silkeborg	3	1551	20.36%	FC Copenhagen	0	1753	54.94%	24.70%
7	2003-04-21	15.73	Viborg	5	1552	24.85%	@ Esbjerg	1	1579	48.36%	26.79%
8	2002-09-22	14.99	Koge BK	4	1443	15.59%	@ Viborg	1	1591	63.51%	20.91%
9	2002-09-01	14.66	@ Aalborg	3	1608	24.16%	FC Copenhagen	0	1767	49.29%	26.55%
10	2002-08-18	13.69	Silkeborg	4	1548	40.37%	@ Koge BK	0	1454	31.45%	28.18%
11	2003-03-16	12.27	@ Silkeborg	3	1541	32.71%	AB Copenhagen	0	1625	39.00%	28.29%
12	2003-04-17	12.24	Esbjerg	4	1567	24.62%	@ AB Copenhagen	1	1597	48.67%	26.72%
13	2003-03-23	11.69	Midtjylland	3	1670	35.15%	@ AB Copenhagen	0	1613	36.46%	28.39%
14	2003-06-01	10.83	@ Esbjerg	4	1575	30.53%	Midtjylland	1	1676	41.39%	28.08%
15	2003-05-04	10.74	@ Aarhus GF	4	1523	30.90%	Odense	1	1621	40.97%	28.12%
16	2002-08-03	10.72	AB Copenhagen	3	1616	15.11%	@ Brondby	1	1772	64.48%	20.42%
17	2003-05-11	10.28	@ Viborg	3	1572	41.24%	AB Copenhagen	0	1596	30.66%	28.10%
18	2002-10-20	10.12	Nordsjaelland	2	1533	24.04%	@ Esbjerg	0	1569	49.45%	26.50%
19	2003-04-27	10.11	@ Silkeborg	5	1573	45.51%	Nordsjaelland	1	1566	27.05%	27.44%
20	2003-03-16	9.99	@ Odense	2	1608	24.63%	FC Copenhagen	0	1762	48.65%	26.72%
21	2002-10-20	9.78	Koge BK	3	1459	19.10%	@ Aarhus GF	1	1553	57.02%	23.88%
22	2002-09-21	9.68	Nordsjaelland	3	1528	19.56%	@ Aalborg	1	1616	56.25%	24.19%
23	2002-09-08	9.54	@ Odense	3	1621	44.40%	Aalborg	0	1623	27.96%	27.65%
24	2002-08-31	9.33	@ Koge BK	2	1439	27.90%	Aarhus GF	0	1562	44.47%	27.63%
25	2002-09-22	9.01	@ Brondby	4	1757	56.03%	Midtjylland	0	1671	19.69%	24.28%