2016-17 Luxembourg National Division Season

182 games

Final

Champion

F91 Dudelange

65 points

Relegated

No relegation

Biggest Overachiever

Differdange 03

12.57 points above expected

65 points · 52.43 expected points

Biggest Disappointment

Jeunesse Esch

13.65 points below expected

29 points · 42.65 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	F91 Dudelange	26	20	5	1	65	68	14	+54	58.06	+6.94
2	Differdange 03	26	20	5	1	65	65	21	+44	52.43	+12.57
3	Fola Esch	26	16	8	2	56	69	34	+35	54.44	+1.56
4	Progres Niedercorn	26	13	5	8	44	57	38	+19	41.66	+2.34
5	UNA Strassen	26	11	4	11	37	39	47	-8	29.20	+7.80
6	Union Titus Petange	26	10	5	11	35	38	33	+5	29.16	+5.84
7	Mondorf-les-Bains	26	9	3	14	30	29	45	-16	32.67	-2.67
8	Jeunesse Esch	26	7	8	11	29	38	49	-11	42.65	-13.65
9	Victoria Rosport	26	8	4	14	28	38	54	-16	28.70	-0.70
10	Racing FC Union Luxembourg	26	8	3	15	27	38	52	-14	30.73	-3.73
11	RM Hamm Benfica	26	7	5	14	26	29	47	-18	30.51	-4.51
12	Jeunesse Canach	26	5	8	13	23	30	54	-24	23.38	-0.38
13	Rumelange	26	5	8	13	23	29	53	-24	26.81	-3.81
14	UN Kaerjeng	26	7	1	18	22	37	63	-26	29.84	-7.84

Top Overachievers & Disappointments

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

Biggest Overachievers

#	Team	Actual	Sim	vsSim
1	Differdange 03	65	52.43	+12.57
2	UNA Strassen	37	29.20	+7.80
3	F91 Dudelange	65	58.06	+6.94
4	Union Titus Petange	35	29.16	+5.84
5	Progres Niedercorn	44	41.66	+2.34

Biggest Disappointments

#	Team	Actual	Sim	vsSim
1	Jeunesse Esch	29	42.65	-13.65
2	UN Kaerjeng	22	29.84	-7.84
3	RM Hamm Benfica	26	30.51	-4.51
4	Rumelange	23	26.81	-3.81
5	Racing FC Union Luxembourg	27	30.73	-3.73

Top Streaks

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

Most Unlikely Winning Streaks

#	Team	Games	Dates	Probability
1	Victoria Rosport	4	Apr 2 – Apr 30	1 in 107
2	Union Titus Petange	3	Nov 5 – Nov 27	1 in 35
3	UNA Strassen	3	Sep 25 – Oct 16	1 in 31
4	Racing FC Union Luxembourg	3	Aug 14 – Aug 28	1 in 21
5	Differdange 03	6	Mar 5 – Apr 23	1 in 17

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Racing FC Union Luxembourg	6	Dec 4 – Mar 5	1 in 355
2	RM Hamm Benfica	6	Aug 15 – Oct 1	1 in 256
3	Mondorf-les-Bains	5	Apr 23 – May 21	1 in 93
4	UN Kaerjeng	5	Mar 5 – Apr 9	1 in 52
5	Jeunesse Esch	3	Apr 2 – Apr 23	1 in 44

Most Unlikely Unbeaten Streaks

#	Team	Games	Dates	Probability
1	Differdange 03	15	Aug 7 – Feb 19	1 in 47
2	Victoria Rosport	5	Mar 18 – Apr 30	1 in 32
3	F91 Dudelange	20	Aug 6 – Apr 2	1 in 30
4	Rumelange	5	Sep 25 – Nov 5	1 in 26
5	Union Titus Petange	4	Aug 15 – Sep 11	1 in 21

Most Unlikely Winless Streaks

#	Team	Games	Dates	Probability
1	Jeunesse Esch	7	Oct 16 – Feb 12	1 in 172
2	RM Hamm Benfica	9	Aug 15 – Nov 6	1 in 60
3	Victoria Rosport	8	Sep 11 – Dec 4	1 in 26
4	Racing FC Union Luxembourg	6	Dec 4 – Mar 5	1 in 24
5	Fola Esch	2	Mar 18 – Apr 2	1 in 15

Position Race

Each team’s league position across the whole season. Colored teams are the season’s headline finishers — champion, promoted, and relegated; everyone else is gray as context.

Recent Form

Each team’s last 5 games, hottest first. Form shows the results (navy win, gray draw, red loss, newest on the right); the bars show Elo change over the window, points taken, points expected from the odds, and actual minus expected. Beside each team: current Elo and season points.

Team	Elo	Season Pts	Elo Δ (5)	Points (5)	Expected (5)	Actual − Exp
F91 Dudelange	1468	65	+37	15	11.2	+3.8
Differdange 03	1422	65	+23	13	10.9	+2.1
Fola Esch	1401	56	-5	10	10.0	+0.0
Progres Niedercorn	1283	44	+49	13	9.4	+3.6
UNA Strassen	1140	37	+18	8	6.4	+1.6
Union Titus Petange	1148	35	-19	6	6.9	-0.9
Mondorf-les-Bains	1082	30	-63	0	6.6	-6.6
Jeunesse Esch	1146	29	-53	2	7.1	-5.1
Victoria Rosport	1117	28	+23	9	6.3	+2.7
Racing FC Union Luxembourg	1082	27	+27	6	5.0	+1.0
RM Hamm Benfica	1088	26	-1	7	6.1	+0.9
Rumelange	1045	23	+5	3	3.6	-0.6
Jeunesse Canach	1005	23	-26	2	3.9	-1.9
UN Kaerjeng	1028	22	-16	6	4.8	+1.2

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	D0	FD	FE	JC	JE	MON	PN	RHB	RFUL	RUM	UK	US	UTP	VR
Differdange 03	—	1-1-0 2.33	1-1-0 2.55	2-0-0 4.62	1-0-1 3.60	2-0-0 4.46	2-0-0 3.68	2-0-0 4.37	2-0-0 4.48	1-1-0 4.64	2-0-0 4.61	1-1-0 4.43	2-0-0 4.39	1-1-0 4.24
F91 Dudelange	0-1-1 3.26	—	1-1-0 3.14	2-0-0 4.89	2-0-0 4.26	1-1-0 4.43	2-0-0 4.20	2-0-0 4.43	2-0-0 4.61	2-0-0 4.85	1-1-0 4.52	2-0-0 4.65	1-1-0 4.62	2-0-0 4.68
Fola Esch	0-1-1 3.03	0-1-1 2.44	—	1-1-0 4.80	1-1-0 3.87	2-0-0 4.31	0-2-0 3.92	1-1-0 4.59	2-0-0 4.64	2-0-0 4.78	2-0-0 4.49	2-0-0 4.52	1-1-0 4.61	2-0-0 4.48
Jeunesse Canach	0-0-2 1.04	0-0-2 0.80	0-1-1 0.87	—	0-2-0 1.55	0-1-1 1.96	0-1-1 1.51	1-0-1 1.98	1-0-1 2.21	1-1-0 2.58	1-0-1 2.40	1-0-1 2.10	0-1-1 2.53	0-1-1 2.38
Jeunesse Esch	1-0-1 1.99	0-0-2 1.36	0-1-1 1.73	0-2-0 4.06	—	0-0-2 3.60	0-1-1 2.85	1-1-0 3.48	1-0-1 3.79	1-0-1 4.07	2-0-0 3.76	0-2-0 3.60	1-0-1 3.61	0-1-1 3.86
Mondorf-les-Bains	0-0-2 1.18	0-1-1 1.21	0-0-2 1.31	1-1-0 3.63	2-0-0 2.00	—	2-0-0 2.25	0-0-2 3.37	1-0-1 2.96	0-1-1 3.30	1-0-1 2.97	0-0-2 3.17	0-0-2 3.17	2-0-0 3.08
Progres Niedercorn	0-0-2 1.91	0-0-2 1.42	0-2-0 1.69	1-1-0 4.11	1-1-0 2.73	0-0-2 3.34	—	2-0-0 3.86	2-0-0 3.89	2-0-0 3.66	1-0-1 3.63	2-0-0 3.34	1-0-1 3.73	1-1-0 3.74
RM Hamm Benfica	0-0-2 1.27	0-0-2 1.21	0-1-1 1.06	1-0-1 3.61	0-1-1 2.11	2-0-0 2.22	0-0-2 1.74	—	0-0-2 2.98	0-2-0 3.15	0-0-2 2.99	1-1-0 2.85	1-0-1 3.08	2-0-0 2.74
Racing FC Union Luxembourg	0-0-2 1.16	0-0-2 1.05	0-0-2 1.01	1-0-1 3.37	1-0-1 1.81	1-0-1 2.62	0-0-2 1.71	2-0-0 2.60	—	0-2-0 3.06	2-0-0 2.70	1-0-1 3.05	0-1-1 2.95	0-0-2 3.00
Rumelange	0-1-1 1.02	0-0-2 0.84	0-0-2 0.90	0-1-1 3.00	1-0-1 1.54	1-1-0 2.28	0-0-2 1.93	0-2-0 2.43	0-2-0 2.52	—	1-0-1 2.63	0-0-2 2.71	1-1-0 2.39	1-0-1 2.68
UN Kaerjeng	0-0-2 1.05	0-1-1 1.12	0-0-2 1.16	1-0-1 3.19	0-0-2 1.84	1-0-1 2.62	1-0-1 1.96	2-0-0 2.60	0-0-2 2.88	1-0-1 2.95	—	0-0-2 2.99	0-0-2 2.80	1-0-1 2.93
UNA Strassen	0-1-1 1.21	0-0-2 1.00	0-0-2 1.12	1-0-1 3.49	0-2-0 2.00	2-0-0 2.42	0-0-2 2.25	0-1-1 2.73	1-0-1 2.53	2-0-0 2.87	2-0-0 2.59	—	2-0-0 2.63	1-0-1 3.25
Union Titus Petange	0-0-2 1.24	0-1-1 1.03	0-1-1 1.05	1-1-0 3.05	1-0-1 1.99	2-0-0 2.42	1-0-1 1.87	1-0-1 2.51	1-1-0 2.63	0-1-1 3.20	2-0-0 2.78	0-0-2 2.96	—	1-0-1 3.09
Victoria Rosport	0-1-1 1.39	0-0-2 0.98	0-0-2 1.16	1-1-0 3.21	1-1-0 1.74	0-0-2 2.50	0-1-1 1.86	0-0-2 2.85	2-0-0 2.59	1-0-1 2.90	1-0-1 2.65	1-0-1 2.34	1-0-1 2.49	—

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	0.88	+9.6
Allowed	0.86	-10.3
Differential	0.97	+5.5

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	4.40%	4.12%	6.04%	5.49%	1.92%	1.37%	23.35%
1	4.12%	10.44%	6.32%	6.59%	1.37%	1.37%	30.22%
2	6.04%	6.32%	4.40%	1.92%	0.82%	1.37%	20.88%
3	5.49%	6.59%	1.92%	—	0.82%	0.27%	15.11%
4	1.92%	1.37%	0.82%	0.82%	0.55%	0.27%	5.77%
5+	1.37%	1.37%	1.37%	0.27%	0.27%	—	4.67%
Total	23.35%	30.22%	20.88%	15.11%	5.77%	4.67%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.66	1.66	+0.00
SD	1.44	1.44	2.24
CV	0.87	0.87	—
Max	7	7	+6
Min	0	0	-6

Games Played: 182

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.69%	3.85%	—	—	—	—	11.54%
1	19.23%	7.69%	—	—	—	—	26.92%
2	15.38%	3.85%	—	—	—	—	19.23%
3	3.85%	7.69%	3.85%	—	—	—	15.38%
4	—	3.85%	—	—	3.85%	—	7.69%
5+	3.85%	3.85%	7.69%	3.85%	—	—	19.23%
Total	50.00%	30.77%	11.54%	3.85%	3.85%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.50	0.81	+1.69
SD	1.90	1.06	1.59
CV	0.76	1.31	—
Max	6	4	+6
Min	0	0	-1

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.85%	3.85%	—	—	—	—	7.69%
1	7.69%	11.54%	—	—	—	—	19.23%
2	3.85%	7.69%	3.85%	—	—	—	15.38%
3	30.77%	—	3.85%	—	—	—	34.62%
4	11.54%	—	—	—	—	—	11.54%
5+	—	7.69%	3.85%	—	—	—	11.54%
Total	57.69%	30.77%	11.54%	—	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.62	0.54	+2.08
SD	1.53	0.71	1.65
CV	0.58	1.31	—
Max	6	2	+5
Min	0	0	-1

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	—	3.85%	—	—	—	3.85%
1	3.85%	15.38%	—	—	—	—	19.23%
2	3.85%	—	15.38%	—	—	3.85%	23.08%
3	3.85%	23.08%	3.85%	—	—	—	30.77%
4	3.85%	3.85%	3.85%	3.85%	—	—	15.38%
5+	3.85%	3.85%	—	—	—	—	7.69%
Total	19.23%	46.15%	26.92%	3.85%	—	3.85%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.65	1.31	+1.35
SD	1.50	1.09	1.96
CV	0.56	0.83	—
Max	7	5	+6
Min	0	0	-3

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.69%	7.69%	11.54%	3.85%	3.85%	3.85%	38.46%
1	—	11.54%	—	7.69%	—	7.69%	26.92%
2	7.69%	—	11.54%	—	—	—	19.23%
3	—	3.85%	3.85%	—	3.85%	—	11.54%
4	—	3.85%	—	—	—	—	3.85%
5+	—	—	—	—	—	—	—
Total	15.38%	26.92%	26.92%	11.54%	7.69%	11.54%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.15	2.08	-0.92
SD	1.19	1.65	2.13
CV	1.03	0.79	—
Max	4	6	+3
Min	0	0	-5

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	3.85%	3.85%	7.69%	—	—	15.38%
1	3.85%	19.23%	7.69%	7.69%	—	3.85%	42.31%
2	—	7.69%	11.54%	3.85%	—	3.85%	26.92%
3	3.85%	7.69%	—	—	—	—	11.54%
4	—	3.85%	—	—	—	—	3.85%
5+	—	—	—	—	—	—	—
Total	7.69%	42.31%	23.08%	19.23%	—	7.69%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.46	1.88	-0.42
SD	1.03	1.40	1.90
CV	0.70	0.74	—
Max	4	6	+3
Min	0	0	-4

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.85%	11.54%	7.69%	7.69%	—	3.85%	34.62%
1	3.85%	7.69%	7.69%	11.54%	—	—	30.77%
2	3.85%	15.38%	—	—	—	3.85%	23.08%
3	3.85%	7.69%	—	—	—	—	11.54%
4	—	—	—	—	—	—	—
5+	—	—	—	—	—	—	—
Total	15.38%	42.31%	15.38%	19.23%	—	7.69%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.12	1.73	-0.62
SD	1.03	1.48	2.04
CV	0.93	0.86	—
Max	3	6	+3
Min	0	0	-6

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	—	15.38%	—	3.85%	—	19.23%
1	—	7.69%	11.54%	—	—	—	19.23%
2	3.85%	3.85%	11.54%	—	—	—	19.23%
3	7.69%	11.54%	—	—	—	—	19.23%
4	3.85%	3.85%	3.85%	—	—	—	11.54%
5+	3.85%	3.85%	—	—	3.85%	—	11.54%
Total	19.23%	30.77%	42.31%	—	7.69%	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	2.19	1.46	+0.73
SD	1.65	1.07	2.25
CV	0.75	0.73	—
Max	5	4	+5
Min	0	0	-4

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.69%	7.69%	—	11.54%	—	3.85%	30.77%
1	3.85%	11.54%	7.69%	7.69%	7.69%	—	38.46%
2	7.69%	11.54%	—	7.69%	—	—	26.92%
3	—	—	—	—	—	—	—
4	—	—	—	—	—	—	—
5+	3.85%	—	—	—	—	—	3.85%
Total	23.08%	30.77%	7.69%	26.92%	7.69%	3.85%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.12	1.81	-0.69
SD	1.11	1.58	2.19
CV	0.99	0.87	—
Max	5	6	+5
Min	0	0	-6

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	—	7.69%	3.85%	7.69%	—	19.23%
1	7.69%	11.54%	19.23%	—	3.85%	—	42.31%
2	—	7.69%	—	7.69%	—	—	15.38%
3	7.69%	3.85%	3.85%	—	3.85%	—	19.23%
4	—	—	—	—	—	3.85%	3.85%
5+	—	—	—	—	—	—	—
Total	15.38%	23.08%	30.77%	11.54%	15.38%	3.85%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.46	2.00	-0.54
SD	1.14	1.41	1.86
CV	0.78	0.71	—
Max	4	5	+3
Min	0	0	-4

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	19.23%	—	11.54%	7.69%	3.85%	—	42.31%
1	—	11.54%	—	11.54%	—	3.85%	26.92%
2	—	7.69%	—	3.85%	3.85%	—	15.38%
3	—	3.85%	3.85%	—	3.85%	—	11.54%
4	—	—	—	—	—	—	—
5+	—	—	3.85%	—	—	—	3.85%
Total	19.23%	23.08%	19.23%	23.08%	11.54%	3.85%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.12	2.04	-0.92
SD	1.31	1.66	1.94
CV	1.17	0.81	—
Max	5	7	+3
Min	0	0	-6

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	3.85%	11.54%	11.54%	3.85%	—	30.77%
1	3.85%	3.85%	7.69%	7.69%	3.85%	—	26.92%
2	3.85%	7.69%	—	3.85%	7.69%	3.85%	26.92%
3	—	3.85%	—	—	—	3.85%	7.69%
4	—	—	—	3.85%	—	—	3.85%
5+	3.85%	—	—	—	—	—	3.85%
Total	11.54%	19.23%	19.23%	26.92%	15.38%	7.69%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.42	2.42	-1.00
SD	1.45	1.55	2.24
CV	1.02	0.64	—
Max	6	6	+6
Min	0	0	-4

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	—	3.85%	7.69%	7.69%	—	7.69%	26.92%
1	—	11.54%	—	7.69%	3.85%	3.85%	26.92%
2	15.38%	3.85%	—	—	—	—	19.23%
3	11.54%	11.54%	—	—	—	—	23.08%
4	—	—	—	—	3.85%	—	3.85%
5+	—	—	—	—	—	—	—
Total	26.92%	30.77%	7.69%	15.38%	7.69%	11.54%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.50	1.81	-0.31
SD	1.24	1.72	2.56
CV	0.83	0.95	—
Max	4	5	+3
Min	0	0	-5

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	7.69%	7.69%	—	11.54%	—	—	26.92%
1	3.85%	11.54%	11.54%	11.54%	—	—	38.46%
2	11.54%	3.85%	—	—	—	—	15.38%
3	3.85%	3.85%	—	—	—	—	7.69%
4	7.69%	—	—	—	—	—	7.69%
5+	—	—	3.85%	—	—	—	3.85%
Total	34.62%	26.92%	15.38%	23.08%	—	—	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.46	1.27	+0.19
SD	1.50	1.19	2.17
CV	1.03	0.93	—
Max	6	3	+4
Min	0	0	-3

Games Played: 26

↓ Scored \| Allowed →	0	1	2	3	4	5+	Total
0	3.85%	3.85%	3.85%	3.85%	3.85%	—	19.23%
1	—	3.85%	15.38%	19.23%	—	—	38.46%
2	7.69%	7.69%	7.69%	—	—	3.85%	26.92%
3	—	3.85%	3.85%	—	—	—	7.69%
4	—	—	3.85%	3.85%	—	—	7.69%
5+	—	—	—	—	—	—	—
Total	11.54%	19.23%	34.62%	26.92%	3.85%	3.85%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	1.46	2.08	-0.62
SD	1.14	1.32	1.79
CV	0.78	0.64	—
Max	4	6	+2
Min	0	0	-4

Games Played: 26

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
F91 Dudelange	1468	65	58.06	+6.94	91.0%	37	48	54	59	62	67	70
Differdange 03	1422	65	52.43	+12.57	98.0%	37	41	47	53	56	63	67
Fola Esch	1401	56	54.44	+1.56	62.0%	35	44	51	55	58	63	66
Progres Niedercorn	1283	44	41.66	+2.34	61.0%	19	30	38	42	46	53	58
Union Titus Petange	1148	35	29.16	+5.84	81.0%	11	19	25	28	33	40	44
Jeunesse Esch	1146	29	42.65	-13.65	0.0%	31	33	38	42	47	55	60
UNA Strassen	1140	37	29.20	+7.80	90.0%	12	18	24	29	34	40	47
Victoria Rosport	1117	28	28.70	-0.70	40.0%	11	19	25	30	33	36	40
RM Hamm Benfica	1088	26	30.51	-4.51	25.0%	11	20	26	31	35	43	44
Racing FC Union Luxembourg	1082	27	30.73	-3.73	31.0%	19	22	26	30	34	42	45
Mondorf-les-Bains	1082	30	32.67	-2.67	36.0%	17	21	28	33	37	44	50
Rumelange	1045	23	26.81	-3.81	27.0%	15	18	22	27	30	35	41
UN Kaerjeng	1028	22	29.84	-7.84	5.0%	18	22	26	29	33	40	44
Jeunesse Canach	1005	23	23.38	-0.38	54.0%	9	13	20	23	27	34	42

Point Totals in Context

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

Home-Field Advantage Edge

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

Season Trends

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

Edges & Scoring

How these are measured

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

Home Edge: Share of matches won by the home team minus the share won by the away team.
No Edge: under 7% * Slight Edge: 7% to 11.5% * Clear Edge: 11.5% to 16.5% * Strong Edge: 16.5% and up.
Elo Value: Number of Elo rating points one goal is worth. A team this many Elo points better than another is expected to win by one goal on a neutral field.
Scoring Tilt: Average home goals minus average away goals per match. The gold line is the home goals edge implied by the scoring value of an Elo point and the home-field Elo bonus.
Road-Tilted: under -0.2 * Neutral: -0.2 to 0.5 * Home-Tilted: 0.5 to 1.2 * Strong Home: 1.2 and up.

Home Edge

HomeDrawAway

+7.69%

Slight Edge

43.96%19.78%36.26%

Elo Value

Home Edge: 26.78 Elo pts.

149 Elo

0.007 goals per Elo point

0400

Scoring Tilt

Expected

+0.25 goals

Neutral

-2+0.18+2

Title Race

How these are measured

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

Title-Race Openness: Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 3 * Open: 3 to 4 * Wide Open: 4 and up.
Champion Preseason Odds: Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd to 3rd * Middle of the Pack: 4th to 7th * Longshot: 8th 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 0.05 * Tight Race: 0.05 to 0.17 * Comfortable: 0.17 to 0.27 * Runaway: 0.27 and up.

Title-Race Openness

2.3

Top-Heavy

123410

Champion Preseason Odds

59%

F91 Dudelange, 1st of 14

LongshotFavorite

Title Margin

Expected

0.00/gm

Photo Finish

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 5.01 * Some Luck: 5.01 to 7.51 * Lucky: 7.51 to 10.01 * Wild Swing: 10.01 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 1.55 * Close: 1.55 to 2.32 * Off: 2.32 to 3.1 * Way Off: 3.1 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 14 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 14 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 14 * As Expected: 14 to 22.4 * Several Outliers: 22.4 to 30.8 * Many Outliers: 30.8 and up.

Luck Spread

Expected

6.62 points

Some Luck

06.2616

Average Finish Error

Expected

2.43

Off

01.944

Biggest Overachiever

Expected 96.43%

98.00%

Differdange 03

50100

Biggest Underachiever

Expected 3.57%

0.00%

Jeunesse Esch

050

Season Outliers

Expected

2 of 14

Minimal Outliers

01.47

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 0.17 * Even: 0.17 to 0.19 * Top-Heavy: 0.19 to 0.21 * Lopsided: 0.21 and up.
Noll-Scully: Take a league where every match is a coin flip and nobody is better than anybody. You would still get a table, with a leader and a bottom club, purely by luck, and you can work out how far apart that table would be. This is the real table measured against it. At 1.00 the season was no more spread out than pure chance; at 2.00 it was twice as spread out, which takes genuine differences in quality. Dividing by the luck figure is what makes seasons of different lengths comparable, because a short season spreads a table by luck alone far more than a long one does. Elo SD in the corner is the same question in rating points: how far apart the teams finished on the ratings.
Coin-Flip Parity: under 1.65 * Moderate Separation: 1.65 to 1.85 * Strong Separation: 1.85 to 2.05 * Wide Separation: 2.05 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 68% * Slight Edge: 68% to 72.5% * Clear Edge: 72.5% to 78% * Wide Edge: 78% 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 89.5% * Clear Edge: 89.5% to 92% * Strong Edge: 92% to 95% * Dominant: 95% and up.
Close Games: Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 49% * Some Drama: 49% to 53% * Frequent: 53% to 56% * Very Frequent: 56% 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 23% * Occasional: 23% to 26% * Frequent: 26% to 28% * Very Frequent: 28% and up.

Gini Index

0.21

Lopsided

00.170.5

Noll-Scully

Elo SD: 154.06

2.20

Wide Separation

11.651.852.052.5

Interquartile Edge

72%

Slight Edge

50%68%78%100%

Best vs. Worst

Baseline 96%

94%

Strong Edge

50%100%

Close Games

Expected

47%

Few

0%50%100%

Blowouts

Expected

26%

Occasional

0%26%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 0.35 * Slight Separation: 0.35 to 0.39 * Notable Separation: 0.39 to 0.44 * Lopsided: 0.44 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 0.43 * Some Carryover: 0.43 to 0.62 * Strong Carryover: 0.62 to 0.73 * Near-Lock: 0.73 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 21.5% * As Expected: 21.5% to 24% * Upset-Prone: 24% to 26.5% * Very Upset-Prone: 26.5% 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 18% * As Expected: 18% to 20.5% * Shaky Favorites: 20.5% to 23.5% * Very Shaky: 23.5% and up.

Brier Score

Expected

0.55

Highly Predictable

00.572

Matchup Imbalance

0.39

Slight Separation

00.350.5

Strangeness

Expected

1.10

Wilder Than Modeled

01.002

Repeatability

0.55

Some Carryover

00.430.621

Upset Rate

Expected

24%

As Expected

0%24%50%

Clear Favorite Upset Rate

Expected

18%

As Expected

0%19%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 0.18 * Above Noise: 0.18 to 0.25 * Well Above Noise: 0.25 and up.

Probability calibration

0.29

Well Calibrated

0.010.050.10.51

Calibration slope

Ideal

1.28

Underconfident

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.107

Well Within Noise

00.1230.3

Final Table Odds

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

Team	1	2	3	4	5	6	7	8	9	10	11	12	13	14
F91 Dudelange	59.00%	28.00%	9.00%	2.00%	1.00%	—	1.00%	—	—	—	—	—	—	—
Differdange 03	17.00%	28.00%	34.00%	17.00%	3.00%	1.00%	—	—	—	—	—	—	—	—
Fola Esch	24.00%	38.00%	26.00%	10.00%	1.00%	—	1.00%	—	—	—	—	—	—	—
Progres Niedercorn	—	2.00%	15.00%	26.00%	23.00%	13.00%	10.00%	4.00%	5.00%	—	—	1.00%	1.00%	—
UNA Strassen	—	—	1.00%	2.00%	4.00%	9.00%	16.00%	10.00%	10.00%	8.00%	7.00%	9.00%	16.00%	8.00%
Union Titus Petange	—	—	—	4.00%	3.00%	11.00%	7.00%	14.00%	9.00%	11.00%	9.00%	13.00%	9.00%	10.00%
Mondorf-les-Bains	—	—	1.00%	5.00%	11.00%	17.00%	14.00%	6.00%	14.00%	6.00%	10.00%	9.00%	3.00%	4.00%
Jeunesse Esch	—	4.00%	13.00%	25.00%	32.00%	13.00%	7.00%	3.00%	3.00%	—	—	—	—	—
Victoria Rosport	—	—	—	1.00%	1.00%	6.00%	6.00%	17.00%	14.00%	15.00%	15.00%	6.00%	8.00%	11.00%
Racing FC Union Luxembourg	—	—	—	2.00%	7.00%	8.00%	14.00%	7.00%	11.00%	14.00%	15.00%	7.00%	10.00%	5.00%
RM Hamm Benfica	—	—	—	5.00%	4.00%	11.00%	10.00%	15.00%	7.00%	12.00%	11.00%	12.00%	9.00%	4.00%
Jeunesse Canach	—	—	—	—	1.00%	3.00%	1.00%	5.00%	5.00%	5.00%	8.00%	19.00%	18.00%	35.00%
Rumelange	—	—	—	—	2.00%	3.00%	3.00%	13.00%	7.00%	15.00%	9.00%	17.00%	17.00%	14.00%
UN Kaerjeng	—	—	1.00%	1.00%	7.00%	5.00%	10.00%	6.00%	15.00%	14.00%	16.00%	7.00%	9.00%	9.00%

Points Required Per Position

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

Next-Season Status

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

Team	Same level	Qualified for relegation playoff	Direct relegation
Differdange 03	100%	—	—
F91 Dudelange	100%	—	—
Fola Esch	100%	—	—
Jeunesse Esch	100%	—	—
Progres Niedercorn	98.00%	1.00%	1.00%
Mondorf-les-Bains	84.00%	9.00%	7.00%
RM Hamm Benfica	75.00%	12.00%	13.00%
Racing FC Union Luxembourg	78.00%	7.00%	15.00%
UN Kaerjeng	75.00%	7.00%	18.00%
Union Titus Petange	68.00%	13.00%	19.00%
Victoria Rosport	75.00%	6.00%	19.00%
UNA Strassen	67.00%	9.00%	24.00%
Rumelange	52.00%	17.00%	31.00%
Jeunesse Canach	28.00%	19.00%	53.00%

Filter by Team:

Overall Game Log

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

Date	Opponent	Score	Excitement	Pre Elo	Opp Elo	Win %	Tie %	Loss %	Proj. Margin	Elo Δ	Points
2016-08-06	Jeunesse Canach	W 6-1	28.7	1333	1057	72.38%	17.07%	10.55%	+2.03	+9.8	3
2016-08-06	@ F91 Dudelange	L 1-6	28.7	1057	1333	10.55%	17.07%	72.38%	-2.03	-9.8	0
2016-08-07	Differdange 03	D 1-1	54.2	1140	1289	24.10%	20.26%	55.63%	-0.82	+1.6	1
2016-08-07	@ Victoria Rosport	D 1-1	54.2	1289	1140	55.63%	20.26%	24.10%	+0.82	-1.6	1
2016-08-07	RM Hamm Benfica	L 0-5	33.4	1098	1165	33.92%	20.90%	45.19%	-0.27	-35.1	0
2016-08-07	@ UNA Strassen	W 5-0	33.4	1165	1098	45.19%	20.90%	33.92%	+0.27	+35.1	3
2016-08-07	Fola Esch	L 0-4	29.2	1147	1334	20.40%	19.77%	59.83%	-1.07	-18.3	0
2016-08-07	@ UN Kaerjeng	W 4-0	29.2	1334	1147	59.83%	19.77%	20.40%	+1.07	+18.3	3
2016-08-07	Racing FC Union Luxembourg	W 2-1	41.5	1210	1111	55.94%	20.23%	23.83%	+0.84	+5.6	3
2016-08-07	@ Progres Niedercorn	L 1-2	41.5	1111	1210	23.83%	20.23%	55.94%	-0.84	-5.6	0
2016-08-07	Rumelange	D 0-0	50.1	1160	1114	49.56%	20.72%	29.73%	+0.49	-1.1	1
2016-08-07	@ Mondorf-les-Bains	D 0-0	50.1	1114	1160	29.73%	20.72%	49.56%	-0.49	+1.1	1
2016-08-08	Union Titus Petange	W 2-1	38.8	1239	1055	64.82%	18.96%	16.22%	+1.41	+3.9	3
2016-08-08	@ Jeunesse Esch	L 1-2	38.8	1055	1239	16.22%	18.96%	64.82%	-1.41	-3.9	0
2016-08-12	Progres Niedercorn	W 2-0	34.8	1288	1215	52.84%	20.50%	26.66%	+0.66	+12.3	4
2016-08-12	@ Differdange 03	L 0-2	34.8	1215	1288	26.66%	20.50%	52.84%	-0.66	-12.3	3
2016-08-13	Victoria Rosport	W 3-1	43.7	1115	1141	39.59%	20.97%	39.44%	+0.00	+14.7	4
2016-08-13	@ Rumelange	L 1-3	43.7	1141	1115	39.44%	20.97%	39.59%	+0.00	-14.7	1
2016-08-14	UN Kaerjeng	W 1-0	33.5	1343	1129	67.47%	18.39%	14.14%	+1.61	+3.6	6
2016-08-14	@ F91 Dudelange	L 0-1	33.5	1129	1343	14.14%	18.39%	67.47%	-1.61	-3.6	0
2016-08-14	UNA Strassen	W 1-0	38.7	1106	1063	49.18%	20.74%	30.09%	+0.47	+7.2	3
2016-08-14	@ Racing FC Union Luxembourg	L 0-1	38.7	1063	1106	30.09%	20.74%	49.18%	-0.47	-7.2	0
2016-08-15	Jeunesse Canach	D 0-0	50.0	1052	1047	43.97%	20.93%	35.11%	+0.21	-0.5	1
2016-08-15	@ Union Titus Petange	D 0-0	50.0	1047	1052	35.11%	20.93%	43.97%	-0.21	+0.5	1
2016-08-15	Jeunesse Esch	L 1-3	43.3	1200	1243	37.16%	20.96%	41.88%	-0.11	-14.0	3
2016-08-15	@ RM Hamm Benfica	W 3-1	43.3	1243	1200	41.88%	20.96%	37.16%	+0.11	+14.0	6
2016-08-15	Mondorf-les-Bains	W 1-0	34.2	1353	1159	65.69%	18.78%	15.53%	+1.48	+4.0	6
2016-08-15	@ Fola Esch	L 0-1	34.2	1159	1353	15.53%	18.78%	65.69%	-1.48	-4.0	1
2016-08-19	Rumelange	W 4-0	31.0	1203	1130	52.94%	20.50%	26.56%	+0.67	+23.2	6
2016-08-19	@ Progres Niedercorn	L 0-4	31.0	1130	1203	26.56%	20.50%	52.94%	-0.67	-23.2	4
2016-08-21	Differdange 03	D 4-4	66.5	1055	1300	15.71%	18.83%	65.47%	-1.46	+1.4	1
2016-08-21	@ UNA Strassen	D 4-4	66.5	1300	1055	65.47%	18.83%	15.71%	+1.46	-1.4	5
2016-08-21	F91 Dudelange	D 1-1	54.9	1051	1346	12.41%	17.83%	69.76%	-1.80	+3.0	2
2016-08-21	@ Union Titus Petange	D 1-1	54.9	1346	1051	69.76%	17.83%	12.41%	+1.80	-3.0	7
2016-08-21	RM Hamm Benfica	W 4-1	45.5	1047	1186	25.25%	20.38%	54.37%	-0.75	+27.3	4
2016-08-21	@ Jeunesse Canach	L 1-4	45.5	1186	1047	54.37%	20.38%	25.25%	+0.75	-27.3	3
2016-08-21	Fola Esch	L 1-3	36.7	1127	1357	16.80%	19.09%	64.12%	-1.36	-7.0	1
2016-08-21	@ Victoria Rosport	W 3-1	36.7	1357	1127	64.12%	19.09%	16.80%	+1.36	+7.0	9
2016-08-21	Racing FC Union Luxembourg	L 1-2	52.5	1257	1113	60.95%	19.61%	19.44%	+1.15	-12.4	6
2016-08-21	@ Jeunesse Esch	W 2-1	52.5	1113	1257	19.44%	19.61%	60.95%	-1.15	+12.4	6
2016-08-21	UN Kaerjeng	W 2-1	44.0	1155	1125	47.41%	20.82%	31.77%	+0.38	+7.1	4
2016-08-21	@ Mondorf-les-Bains	L 1-2	44.0	1125	1155	31.77%	20.82%	47.41%	-0.38	-7.1	0
2016-08-26	Progres Niedercorn	D 1-1	55.0	1364	1226	60.25%	19.72%	20.04%	+1.10	-2.0	10
2016-08-26	@ Fola Esch	D 1-1	55.0	1226	1364	20.04%	19.72%	60.25%	-1.10	+2.0	7
2016-08-27	UNA Strassen	L 0-2	41.5	1107	1057	50.04%	20.69%	29.27%	+0.51	-20.7	4
2016-08-27	@ Rumelange	W 2-0	41.5	1057	1107	29.27%	20.69%	50.04%	-0.51	+20.7	4
2016-08-28	Jeunesse Canach	W 1-0	38.4	1125	1075	50.14%	20.68%	29.17%	+0.52	+7.0	9
2016-08-28	@ Racing FC Union Luxembourg	L 0-1	38.4	1075	1125	29.17%	20.68%	50.14%	-0.52	-7.0	4
2016-08-28	Jeunesse Esch	W 3-1	41.0	1298	1245	50.49%	20.66%	28.85%	+0.54	+11.4	8
2016-08-28	@ Differdange 03	L 1-3	41.0	1245	1298	28.85%	20.66%	50.49%	-0.54	-11.4	6
2016-08-28	Mondorf-les-Bains	W 1-0	34.5	1343	1162	64.54%	19.01%	16.45%	+1.39	+4.2	10
2016-08-28	@ F91 Dudelange	L 0-1	34.5	1162	1343	16.45%	19.01%	64.54%	-1.39	-4.2	4
2016-08-28	Union Titus Petange	L 0-1	46.5	1159	1054	56.65%	20.16%	23.19%	+0.88	-12.3	3
2016-08-28	@ RM Hamm Benfica	W 1-0	46.5	1054	1159	23.19%	20.16%	56.65%	-0.88	+12.3	5
2016-08-28	Victoria Rosport	L 2-3	52.6	1118	1120	43.10%	20.94%	35.95%	+0.17	-8.6	0
2016-08-28	@ UN Kaerjeng	W 3-2	52.6	1120	1118	35.95%	20.94%	43.10%	-0.17	+8.6	4
2016-09-11	Differdange 03	L 0-1	34.0	1068	1310	15.87%	18.87%	65.26%	-1.44	-4.0	4
2016-09-11	@ Jeunesse Canach	W 1-0	34.0	1310	1068	65.26%	18.87%	15.87%	+1.44	+4.0	11
2016-09-11	F91 Dudelange	L 0-3	29.8	1146	1348	19.14%	19.56%	61.30%	-1.17	-13.2	3
2016-09-11	@ RM Hamm Benfica	W 3-0	29.8	1348	1146	61.30%	19.56%	19.14%	+1.17	+13.2	13
2016-09-11	Fola Esch	L 1-3	35.2	1077	1362	13.07%	18.05%	68.88%	-1.73	-5.4	4
2016-09-11	@ UNA Strassen	W 3-1	35.2	1362	1077	68.88%	18.05%	13.07%	+1.73	+5.4	13
2016-09-11	Mondorf-les-Bains	L 1-3	43.6	1128	1158	39.08%	20.97%	39.95%	-0.02	-14.6	4
2016-09-11	@ Victoria Rosport	W 3-1	43.6	1158	1128	39.95%	20.97%	39.08%	+0.02	+14.6	7
2016-09-11	Racing FC Union Luxembourg	D 1-1	53.8	1066	1132	34.05%	20.90%	45.05%	-0.26	+0.5	6
2016-09-11	@ Union Titus Petange	D 1-1	53.8	1132	1066	45.05%	20.90%	34.05%	+0.26	-0.5	10
2016-09-12	Rumelange	W 3-0	29.5	1234	1086	61.29%	19.56%	19.15%	+1.17	+13.2	9
2016-09-12	@ Jeunesse Esch	L 0-3	29.5	1086	1234	19.15%	19.56%	61.29%	-1.17	-13.2	4
2016-09-12	UN Kaerjeng	L 0-2	43.8	1228	1110	58.23%	19.98%	21.79%	+0.97	-23.7	7
2016-09-12	@ Progres Niedercorn	W 2-0	43.8	1110	1228	21.79%	19.98%	58.23%	-0.97	+23.7	3
2016-09-24	Union Titus Petange	W 1-0	32.6	1314	1067	70.18%	17.71%	12.11%	+1.83	+3.1	14
2016-09-24	@ Differdange 03	L 0-1	32.6	1067	1314	12.11%	17.71%	70.18%	-1.83	-3.1	6
2016-09-25	RM Hamm Benfica	W 2-1	45.3	1132	1133	43.15%	20.94%	35.90%	+0.17	+7.9	13
2016-09-25	@ Racing FC Union Luxembourg	L 1-2	45.3	1133	1132	35.90%	20.94%	43.15%	-0.17	-7.9	3
2016-09-25	Jeunesse Canach	D 1-1	53.8	1073	1064	44.60%	20.91%	34.49%	+0.24	-0.5	5
2016-09-25	@ Rumelange	D 1-1	53.8	1064	1073	34.49%	20.91%	44.60%	-0.24	+0.5	5
2016-09-25	Jeunesse Esch	D 2-2	60.4	1367	1247	58.41%	19.96%	21.63%	+0.99	-1.4	14
2016-09-25	@ Fola Esch	D 2-2	60.4	1247	1367	21.63%	19.96%	58.41%	-0.99	+1.4	10
2016-09-25	Progres Niedercorn	W 2-0	38.8	1173	1205	38.81%	20.97%	40.22%	-0.03	+17.2	10
2016-09-25	@ Mondorf-les-Bains	L 0-2	38.8	1205	1173	40.22%	20.97%	38.81%	+0.03	-17.2	7
2016-09-25	UNA Strassen	L 0-2	41.9	1133	1072	51.49%	20.60%	27.91%	+0.59	-21.2	3
2016-09-25	@ UN Kaerjeng	W 2-0	41.9	1072	1133	27.91%	20.60%	51.49%	-0.59	+21.2	7
2016-09-25	Victoria Rosport	W 3-0	27.1	1361	1114	70.17%	17.72%	12.11%	+1.83	+8.5	16
2016-09-25	@ F91 Dudelange	L 0-3	27.1	1114	1361	12.11%	17.72%	70.17%	-1.83	-8.5	4
2016-09-29	Mondorf-les-Bains	W 3-1	46.6	1093	1190	30.08%	20.74%	49.18%	-0.47	+17.6	10
2016-09-29	@ UNA Strassen	L 1-3	46.6	1190	1093	49.18%	20.74%	30.08%	+0.47	-17.6	10
2016-09-29	Rumelange	L 1-2	47.1	1064	1072	42.12%	20.96%	36.92%	+0.12	-8.9	6
2016-09-29	@ Union Titus Petange	W 2-1	47.1	1072	1064	36.92%	20.96%	42.12%	-0.12	+8.9	8
2016-09-29	Victoria Rosport	W 3-1	39.4	1187	1105	54.01%	20.41%	25.58%	+0.73	+10.2	10
2016-09-29	@ Progres Niedercorn	L 1-3	39.4	1105	1187	25.58%	20.41%	54.01%	-0.73	-10.2	4
2016-10-01	Differdange 03	L 1-3	37.7	1125	1317	19.98%	19.71%	60.32%	-1.10	-8.2	3
2016-10-01	@ RM Hamm Benfica	W 3-1	37.7	1317	1125	60.32%	19.71%	19.98%	+1.10	+8.2	17
2016-10-01	F91 Dudelange	L 1-2	39.4	1140	1369	16.84%	19.10%	64.07%	-1.36	-4.0	13
2016-10-01	@ Racing FC Union Luxembourg	W 2-1	39.4	1369	1140	64.07%	19.10%	16.84%	+1.36	+4.0	19
2016-10-01	Fola Esch	L 3-4	45.9	1064	1366	12.04%	17.69%	70.27%	-1.84	-2.7	5
2016-10-01	@ Jeunesse Canach	W 4-3	45.9	1366	1064	70.27%	17.69%	12.04%	+1.84	+2.7	17
2016-10-01	UN Kaerjeng	W 3-1	37.7	1248	1112	60.10%	19.74%	20.17%	+1.09	+8.3	13
2016-10-01	@ Jeunesse Esch	L 1-3	37.7	1112	1248	20.17%	19.74%	60.10%	-1.09	-8.3	3
2016-10-16	RM Hamm Benfica	D 0-0	50.0	1081	1117	38.22%	20.97%	40.81%	-0.06	+0.1	9
2016-10-16	@ Rumelange	D 0-0	50.0	1117	1081	40.81%	20.97%	38.22%	+0.06	-0.1	4
2016-10-16	Jeunesse Canach	W 3-1	40.8	1104	1061	49.07%	20.74%	30.19%	+0.46	+11.8	6
2016-10-16	@ UN Kaerjeng	L 1-3	40.8	1061	1104	30.19%	20.74%	49.07%	-0.46	-11.8	5
2016-10-16	Jeunesse Esch	W 1-0	44.2	1172	1256	31.71%	20.82%	47.47%	-0.38	+10.5	13
2016-10-16	@ Mondorf-les-Bains	L 0-1	44.2	1256	1172	47.47%	20.82%	31.71%	+0.38	-10.5	13
2016-10-16	Progres Niedercorn	W 4-0	28.3	1373	1198	64.05%	19.10%	16.85%	+1.36	+15.3	22
2016-10-16	@ F91 Dudelange	L 0-4	28.3	1198	1373	16.85%	19.10%	64.05%	-1.36	-15.3	10
2016-10-16	Racing FC Union Luxembourg	W 3-2	44.1	1325	1136	65.32%	18.86%	15.82%	+1.45	+3.6	20
2016-10-16	@ Differdange 03	L 2-3	44.1	1136	1325	15.82%	18.86%	65.32%	-1.45	-3.6	13
2016-10-16	UNA Strassen	L 1-2	46.8	1095	1111	41.11%	20.97%	37.92%	+0.07	-8.8	4
2016-10-16	@ Victoria Rosport	W 2-1	46.8	1111	1095	37.92%	20.97%	41.11%	-0.07	+8.8	13
2016-10-16	Union Titus Petange	W 3-1	33.3	1368	1055	74.94%	16.22%	8.85%	+2.28	+3.6	20
2016-10-16	@ Fola Esch	L 1-3	33.3	1055	1368	8.85%	16.22%	74.94%	-2.28	-3.6	6
2016-10-23	F91 Dudelange	D 0-0	52.1	1329	1389	34.89%	20.92%	44.18%	-0.22	+0.5	21
2016-10-23	@ Differdange 03	D 0-0	52.1	1389	1329	44.18%	20.92%	34.89%	+0.22	-0.5	23
2016-10-23	Fola Esch	D 1-1	54.8	1117	1372	14.96%	18.63%	66.41%	-1.53	+2.7	5
2016-10-23	@ RM Hamm Benfica	D 1-1	54.8	1372	1117	66.41%	18.63%	14.96%	+1.53	-2.7	21
2016-10-23	Mondorf-les-Bains	D 1-1	53.9	1050	1183	25.81%	20.43%	53.76%	-0.71	+1.4	6
2016-10-23	@ Jeunesse Canach	D 1-1	53.9	1183	1050	53.76%	20.43%	25.81%	+0.71	-1.4	14
2016-10-23	Progres Niedercorn	L 1-3	42.3	1120	1182	34.50%	20.91%	44.59%	-0.24	-13.2	13
2016-10-23	@ UNA Strassen	W 3-1	42.3	1182	1120	44.59%	20.91%	34.50%	+0.24	+13.2	13
2016-10-23	Rumelange	D 1-1	53.8	1132	1081	50.14%	20.68%	29.17%	+0.52	-1.0	14
2016-10-23	@ Racing FC Union Luxembourg	D 1-1	53.8	1081	1132	29.17%	20.68%	50.14%	-0.52	+1.0	10
2016-10-23	Victoria Rosport	D 2-2	59.6	1246	1086	62.50%	19.37%	18.13%	+1.25	-1.7	14
2016-10-23	@ Jeunesse Esch	D 2-2	59.6	1086	1246	18.13%	19.37%	62.50%	-1.25	+1.7	5
2016-11-05	Differdange 03	D 0-0	50.9	1082	1329	15.54%	18.78%	65.68%	-1.47	+2.9	11
2016-11-05	@ Rumelange	D 0-0	50.9	1329	1082	65.68%	18.78%	15.54%	+1.47	-2.9	22
2016-11-05	Jeunesse Esch	D 1-1	54.0	1195	1244	36.40%	20.95%	42.65%	-0.15	+0.3	14
2016-11-05	@ Progres Niedercorn	D 1-1	54.0	1244	1195	42.65%	20.95%	36.40%	+0.15	-0.3	15
2016-11-05	Racing FC Union Luxembourg	W 4-1	32.6	1369	1131	69.48%	17.90%	12.62%	+1.78	+7.4	24
2016-11-05	@ Fola Esch	L 1-4	32.6	1131	1369	12.62%	17.90%	69.48%	-1.78	-7.4	14
2016-11-05	UNA Strassen	W 3-0	26.4	1388	1106	72.77%	16.95%	10.28%	+2.07	+7.1	26
2016-11-05	@ F91 Dudelange	L 0-3	26.4	1106	1388	10.28%	16.95%	72.77%	-2.07	-7.2	13
2016-11-05	Union Titus Petange	L 0-2	44.1	1182	1051	59.49%	19.82%	20.69%	+1.05	-24.2	14
2016-11-05	@ Mondorf-les-Bains	W 2-0	44.1	1051	1182	20.69%	19.82%	59.49%	-1.05	+24.2	9
2016-11-06	RM Hamm Benfica	W 6-0	34.8	1116	1120	42.77%	20.95%	36.28%	+0.15	+44.1	9
2016-11-06	@ UN Kaerjeng	L 0-6	34.8	1120	1116	36.28%	20.95%	42.77%	-0.15	-44.1	5
2016-11-06	Jeunesse Canach	D 0-0	50.0	1088	1051	48.37%	20.78%	30.85%	+0.43	-0.9	6
2016-11-06	@ Victoria Rosport	D 0-0	50.0	1051	1088	30.85%	20.78%	48.37%	-0.43	+1.0	7
2016-11-20	UN Kaerjeng	W 3-1	46.1	1075	1160	31.66%	20.81%	47.52%	-0.39	+17.1	12
2016-11-20	@ Union Titus Petange	L 1-3	46.1	1160	1075	47.52%	20.81%	31.66%	+0.39	-17.1	9
2016-11-27	F91 Dudelange	L 0-3	26.9	1085	1395	11.59%	17.51%	70.90%	-1.90	-8.1	11
2016-11-27	@ Rumelange	W 3-0	26.9	1395	1085	70.90%	17.51%	11.59%	+1.90	+8.1	29
2016-11-27	Fola Esch	W 2-0	41.3	1326	1377	36.18%	20.95%	42.88%	-0.16	+18.1	25
2016-11-27	@ Differdange 03	L 0-2	41.3	1377	1326	42.88%	20.95%	36.18%	+0.16	-18.1	24
2016-11-27	Mondorf-les-Bains	W 2-0	40.7	1076	1157	31.98%	20.83%	47.19%	-0.37	+19.7	8
2016-11-27	@ RM Hamm Benfica	L 0-2	40.7	1157	1076	47.19%	20.83%	31.98%	+0.37	-19.7	14
2016-11-27	Progres Niedercorn	L 0-5	30.5	1052	1196	24.67%	20.32%	55.01%	-0.78	-26.8	7
2016-11-27	@ Jeunesse Canach	W 5-0	30.5	1196	1052	55.01%	20.32%	24.67%	+0.78	+26.8	17
2016-11-27	UN Kaerjeng	W 3-0	35.7	1124	1143	40.64%	20.97%	38.39%	+0.05	+24.1	17
2016-11-27	@ Racing FC Union Luxembourg	L 0-3	35.7	1143	1124	38.39%	20.97%	40.64%	-0.05	-24.1	9
2016-11-27	UNA Strassen	D 1-1	54.3	1244	1099	61.01%	19.61%	19.39%	+1.15	-2.1	16
2016-11-27	@ Jeunesse Esch	D 1-1	54.3	1099	1244	19.39%	19.61%	61.01%	-1.15	+2.1	14
2016-11-27	Victoria Rosport	W 2-0	37.1	1093	1087	44.06%	20.92%	35.01%	+0.22	+15.4	15
2016-11-27	@ Union Titus Petange	L 0-2	37.1	1087	1093	35.01%	20.92%	44.06%	-0.22	-15.4	6
2016-12-04	Differdange 03	L 3-5	43.5	1119	1344	17.10%	19.16%	63.74%	-1.33	-6.0	9
2016-12-04	@ UN Kaerjeng	W 5-3	43.5	1344	1119	63.74%	19.16%	17.10%	+1.33	+6.0	28
2016-12-04	RM Hamm Benfica	L 0-1	41.7	1072	1095	39.99%	20.97%	39.03%	+0.02	-9.1	6
2016-12-04	@ Victoria Rosport	W 1-0	41.7	1095	1072	39.03%	20.97%	39.99%	-0.02	+9.1	11
2016-12-04	Jeunesse Canach	L 0-2	42.4	1101	1025	53.33%	20.47%	26.20%	+0.69	-21.9	14
2016-12-04	@ UNA Strassen	W 2-0	42.4	1025	1101	26.20%	20.47%	53.33%	-0.69	+21.9	10
2016-12-04	Jeunesse Esch	W 5-1	33.7	1403	1242	62.68%	19.34%	17.98%	+1.26	+13.6	32
2016-12-04	@ F91 Dudelange	L 1-5	33.7	1242	1403	17.98%	19.34%	62.68%	-1.26	-13.6	16
2016-12-04	Racing FC Union Luxembourg	W 2-1	45.7	1138	1148	41.89%	20.96%	37.15%	+0.11	+8.1	17
2016-12-04	@ Mondorf-les-Bains	L 1-2	45.7	1148	1138	37.15%	20.96%	41.89%	-0.11	-8.1	17
2016-12-04	Rumelange	W 7-1	28.4	1359	1077	72.74%	16.96%	10.30%	+2.06	+11.3	27
2016-12-04	@ Fola Esch	L 1-7	28.4	1077	1359	10.30%	16.96%	72.74%	-2.06	-11.3	11
2016-12-10	F91 Dudelange	D 2-2	62.4	1370	1417	36.66%	20.96%	42.39%	-0.14	+0.2	28
2016-12-10	@ Fola Esch	D 2-2	62.4	1417	1370	42.39%	20.96%	36.66%	+0.14	-0.2	33
2016-12-11	Jeunesse Esch	D 1-1	54.1	1047	1228	20.92%	19.85%	59.22%	-1.04	+2.0	11
2016-12-11	@ Jeunesse Canach	D 1-1	54.1	1228	1047	59.22%	19.85%	20.92%	+1.04	-1.9	17
2016-12-11	Mondorf-les-Bains	W 6-0	28.0	1350	1146	66.69%	18.57%	14.74%	+1.55	+19.7	31
2016-12-11	@ Differdange 03	L 0-6	28.0	1146	1350	14.74%	18.57%	66.69%	-1.55	-19.7	17
2016-12-11	Progres Niedercorn	L 0-3	32.3	1104	1223	27.52%	20.57%	51.91%	-0.61	-18.3	11
2016-12-11	@ RM Hamm Benfica	W 3-0	32.3	1223	1104	51.91%	20.57%	27.52%	+0.61	+18.3	20
2016-12-11	UN Kaerjeng	W 2-1	47.2	1066	1113	36.71%	20.96%	42.34%	-0.13	+9.0	14
2016-12-11	@ Rumelange	L 1-2	47.2	1113	1066	42.34%	20.96%	36.71%	+0.13	-9.0	9
2016-12-11	UNA Strassen	L 0-3	38.2	1108	1079	47.22%	20.83%	31.96%	+0.37	-28.6	15
2016-12-11	@ Union Titus Petange	W 3-0	38.2	1079	1108	31.96%	20.83%	47.22%	-0.37	+28.6	17
2016-12-11	Victoria Rosport	L 1-2	50.4	1140	1063	53.43%	20.46%	26.11%	+0.70	-11.0	17
2016-12-11	@ Racing FC Union Luxembourg	W 2-1	50.4	1063	1140	26.11%	20.46%	53.43%	-0.70	+10.9	9
2016-12-14	Union Titus Petange	L 0-2	45.0	1241	1079	62.69%	19.34%	17.97%	+1.26	-25.4	20
2016-12-14	@ Progres Niedercorn	W 2-0	45.0	1079	1241	17.97%	19.34%	62.69%	-1.26	+25.4	18
2017-02-11	Differdange 03	L 1-2	42.1	1216	1370	23.54%	20.20%	56.26%	-0.86	-5.5	20
2017-02-11	@ Progres Niedercorn	W 2-1	42.1	1370	1216	56.26%	20.20%	23.54%	+0.86	+5.5	34
2017-02-12	F91 Dudelange	D 1-1	55.3	1104	1417	11.41%	17.44%	71.14%	-1.92	+3.2	10
2017-02-12	@ UN Kaerjeng	D 1-1	55.3	1417	1104	71.14%	17.44%	11.41%	+1.92	-3.2	34
2017-02-12	RM Hamm Benfica	D 1-1	54.2	1226	1086	60.55%	19.67%	19.77%	+1.12	-2.1	18
2017-02-12	@ Jeunesse Esch	D 1-1	54.2	1086	1226	19.77%	19.67%	60.55%	-1.12	+2.1	12
2017-02-12	Fola Esch	L 1-3	36.4	1126	1370	15.74%	18.84%	65.42%	-1.46	-6.5	17
2017-02-12	@ Mondorf-les-Bains	W 3-1	36.4	1370	1126	65.42%	18.84%	15.74%	+1.46	+6.6	31
2017-02-12	Racing FC Union Luxembourg	W 3-0	35.7	1108	1129	40.38%	20.97%	38.65%	+0.04	+24.2	20
2017-02-12	@ UNA Strassen	L 0-3	35.7	1129	1108	38.65%	20.97%	40.38%	-0.04	-24.2	17
2017-02-12	Rumelange	W 4-2	47.0	1074	1075	43.13%	20.94%	35.92%	+0.17	+12.2	12
2017-02-12	@ Victoria Rosport	L 2-4	47.0	1075	1074	35.92%	20.94%	43.13%	-0.17	-12.2	14
2017-02-12	Union Titus Petange	L 0-4	33.7	1049	1105	35.42%	20.93%	43.64%	-0.20	-29.5	11
2017-02-12	@ Jeunesse Canach	W 4-0	33.7	1105	1049	43.64%	20.93%	35.42%	+0.20	+29.5	21
2017-02-19	Jeunesse Canach	W 2-0	34.5	1088	1019	52.40%	20.54%	27.07%	+0.64	+12.4	15
2017-02-19	@ RM Hamm Benfica	L 0-2	34.5	1019	1088	27.07%	20.54%	52.40%	-0.64	-12.4	11
2017-02-19	Jeunesse Esch	L 1-2	42.7	1105	1224	27.36%	20.56%	52.08%	-0.62	-6.3	17
2017-02-19	@ Racing FC Union Luxembourg	W 2-1	42.7	1224	1105	52.08%	20.56%	27.36%	+0.62	+6.3	21
2017-02-19	Mondorf-les-Bains	W 1-0	41.0	1107	1120	41.51%	20.97%	37.53%	+0.09	+8.6	13
2017-02-19	@ UN Kaerjeng	L 0-1	41.0	1120	1107	37.53%	20.97%	41.51%	-0.09	-8.6	17
2017-02-19	Progres Niedercorn	L 1-3	39.0	1063	1210	24.31%	20.28%	55.41%	-0.81	-9.8	14
2017-02-19	@ Rumelange	W 3-1	39.0	1210	1063	55.41%	20.28%	24.31%	+0.81	+9.8	23
2017-02-19	UNA Strassen	W 4-1	32.5	1376	1132	69.90%	17.79%	12.31%	+1.81	+7.2	37
2017-02-19	@ Differdange 03	L 1-4	32.5	1132	1376	12.31%	17.79%	69.90%	-1.81	-7.2	20
2017-02-19	Union Titus Petange	W 3-0	26.7	1414	1134	72.59%	17.01%	10.41%	+2.05	+7.2	37
2017-02-19	@ F91 Dudelange	L 0-3	26.7	1134	1414	10.41%	17.01%	72.59%	-2.05	-7.2	21
2017-02-19	Victoria Rosport	W 3-1	33.9	1377	1086	73.41%	16.74%	9.85%	+2.13	+4.1	34
2017-02-19	@ Fola Esch	L 1-3	33.9	1086	1377	9.85%	16.74%	73.41%	-2.13	-4.1	12
2017-02-25	F91 Dudelange	D 1-1	55.3	1111	1421	11.59%	17.51%	70.90%	-1.90	+3.1	18
2017-02-25	@ Mondorf-les-Bains	D 1-1	55.3	1421	1111	70.90%	17.51%	11.59%	+1.90	-3.1	38
2017-02-25	RM Hamm Benfica	L 1-2	48.6	1127	1100	46.96%	20.84%	32.20%	+0.36	-9.8	21
2017-02-25	@ Union Titus Petange	W 2-1	48.6	1100	1127	32.20%	20.84%	46.96%	-0.36	+9.8	18
2017-02-25	Fola Esch	D 2-2	60.2	1220	1381	22.90%	20.12%	56.97%	-0.90	+1.3	24
2017-02-25	@ Progres Niedercorn	D 2-2	60.2	1381	1220	56.97%	20.12%	22.90%	+0.90	-1.3	35
2017-02-25	Racing FC Union Luxembourg	W 3-2	54.1	1007	1098	30.78%	20.77%	48.45%	-0.43	+9.5	14
2017-02-25	@ Jeunesse Canach	L 2-3	54.1	1098	1007	48.45%	20.77%	30.78%	+0.43	-9.5	17
2017-02-25	Rumelange	W 2-0	34.4	1125	1053	52.82%	20.51%	26.68%	+0.66	+12.3	23
2017-02-25	@ UNA Strassen	L 0-2	34.4	1053	1125	26.68%	20.51%	52.82%	-0.66	-12.3	14
2017-02-25	UN Kaerjeng	L 1-2	46.1	1082	1115	38.53%	20.97%	40.50%	-0.05	-8.3	12
2017-02-25	@ Victoria Rosport	W 2-1	46.1	1115	1082	40.50%	20.97%	38.53%	+0.05	+8.3	16
2017-02-26	Differdange 03	W 1-0	47.3	1231	1383	23.77%	20.23%	56.00%	-0.84	+12.1	24
2017-02-26	@ Jeunesse Esch	L 0-1	47.3	1383	1231	56.00%	20.23%	23.77%	+0.84	-12.1	37
2017-03-05	RM Hamm Benfica	W 3-0	26.0	1418	1110	74.53%	16.36%	9.11%	+2.24	+6.3	41
2017-03-05	@ F91 Dudelange	L 0-3	26.0	1110	1418	9.11%	16.36%	74.53%	-2.24	-6.3	18
2017-03-05	Jeunesse Canach	W 5-1	28.1	1371	1016	77.48%	15.24%	7.28%	+2.55	+5.4	40
2017-03-05	@ Differdange 03	L 1-5	28.1	1016	1371	7.28%	15.24%	77.48%	-2.55	-5.4	14
2017-03-05	Jeunesse Esch	W 3-2	57.7	1041	1243	19.07%	19.55%	61.38%	-1.17	+11.8	17
2017-03-05	@ Rumelange	L 2-3	57.7	1243	1041	61.38%	19.55%	19.07%	+1.17	-11.8	24
2017-03-05	Progres Niedercorn	L 2-4	45.3	1124	1221	30.02%	20.73%	49.24%	-0.47	-10.5	16
2017-03-05	@ UN Kaerjeng	W 4-2	45.3	1221	1124	49.24%	20.73%	30.02%	+0.47	+10.5	27
2017-03-05	UNA Strassen	W 5-0	26.5	1379	1137	69.80%	17.81%	12.38%	+1.80	+13.9	38
2017-03-05	@ Fola Esch	L 0-5	26.5	1137	1379	12.38%	17.81%	69.80%	-1.80	-13.9	23
2017-03-05	Union Titus Petange	L 0-4	34.9	1089	1117	39.26%	20.97%	39.77%	-0.01	-32.1	17
2017-03-05	@ Racing FC Union Luxembourg	W 4-0	34.9	1117	1089	39.77%	20.97%	39.26%	+0.01	+32.1	24
2017-03-05	Victoria Rosport	W 2-1	43.6	1114	1073	48.82%	20.76%	30.42%	+0.45	+6.9	21
2017-03-05	@ Mondorf-les-Bains	L 1-2	43.6	1073	1114	30.42%	20.76%	48.82%	-0.45	-6.9	12
2017-03-12	Differdange 03	L 0-1	34.8	1149	1376	17.03%	19.14%	63.82%	-1.34	-4.3	24
2017-03-12	@ Union Titus Petange	W 1-0	34.8	1376	1149	63.82%	19.14%	17.03%	+1.34	+4.3	43
2017-03-12	F91 Dudelange	L 0-4	24.9	1067	1424	9.26%	16.44%	74.30%	-2.22	-8.4	12
2017-03-12	@ Victoria Rosport	W 4-0	24.9	1424	1067	74.30%	16.44%	9.26%	+2.22	+8.4	44
2017-03-12	Fola Esch	L 0-3	31.8	1231	1393	22.74%	20.10%	57.16%	-0.91	-15.5	24
2017-03-12	@ Jeunesse Esch	W 3-0	31.8	1393	1231	57.16%	20.10%	22.74%	+0.91	+15.5	41
2017-03-12	Mondorf-les-Bains	L 1-2	51.5	1232	1121	57.35%	20.08%	22.57%	+0.92	-11.7	27
2017-03-12	@ Progres Niedercorn	W 2-1	51.5	1121	1232	22.57%	20.08%	57.35%	-0.92	+11.7	24
2017-03-12	Racing FC Union Luxembourg	L 2-3	54.5	1104	1057	49.69%	20.71%	29.60%	+0.50	-9.8	18
2017-03-12	@ RM Hamm Benfica	W 3-2	54.5	1057	1104	29.60%	20.71%	49.69%	-0.50	+9.8	20
2017-03-12	Rumelange	W 3-1	44.3	1011	1052	37.44%	20.96%	41.60%	-0.10	+15.3	17
2017-03-12	@ Jeunesse Canach	L 1-3	44.3	1052	1011	41.60%	20.96%	37.44%	+0.10	-15.3	17
2017-03-12	UN Kaerjeng	W 2-0	36.9	1123	1113	44.73%	20.91%	34.36%	+0.25	+15.2	26
2017-03-12	@ UNA Strassen	L 0-2	36.9	1113	1123	34.36%	20.91%	44.73%	-0.25	-15.2	16
2017-03-18	RM Hamm Benfica	W 1-0	31.9	1381	1094	73.09%	16.85%	10.06%	+2.10	+2.5	46
2017-03-18	@ Differdange 03	L 0-1	31.9	1094	1381	10.06%	16.85%	73.09%	-2.10	-2.5	18
2017-03-18	Jeunesse Canach	D 2-2	61.2	1409	1026	79.09%	14.55%	6.36%	+2.74	-2.9	42
2017-03-18	@ Fola Esch	D 2-2	61.2	1026	1409	6.36%	14.55%	79.09%	-2.74	+2.9	18
2017-03-18	Progres Niedercorn	D 2-2	59.4	1058	1220	22.82%	20.11%	57.07%	-0.90	+1.3	13
2017-03-18	@ Victoria Rosport	D 2-2	59.4	1220	1058	57.07%	20.11%	22.82%	+0.90	-1.3	28
2017-03-18	Racing FC Union Luxembourg	W 4-0	23.8	1432	1066	78.15%	14.96%	6.89%	+2.63	+6.1	47
2017-03-18	@ F91 Dudelange	L 0-4	23.8	1066	1432	6.89%	14.96%	78.15%	-2.63	-6.1	20
2017-03-18	UNA Strassen	L 0-3	36.9	1133	1139	42.48%	20.95%	36.57%	+0.14	-26.1	24
2017-03-18	@ Mondorf-les-Bains	W 3-0	36.9	1139	1133	36.57%	20.95%	42.48%	-0.14	+26.1	29
2017-03-18	Union Titus Petange	D 0-0	50.1	1037	1145	28.75%	20.66%	50.60%	-0.54	+1.2	18
2017-03-18	@ Rumelange	D 0-0	50.1	1145	1037	50.60%	20.66%	28.75%	+0.54	-1.2	25
2017-03-19	Jeunesse Esch	L 1-4	37.5	1098	1215	27.63%	20.58%	51.79%	-0.61	-15.5	16
2017-03-19	@ UN Kaerjeng	W 4-1	37.5	1215	1098	51.79%	20.58%	27.63%	+0.61	+15.5	27
2017-04-02	Differdange 03	L 0-2	29.0	1060	1383	10.91%	17.23%	71.86%	-1.98	-5.2	20
2017-04-02	@ Racing FC Union Luxembourg	W 2-0	29.0	1383	1060	71.86%	17.23%	10.91%	+1.98	+5.2	49
2017-04-02	F91 Dudelange	L 1-2	40.6	1219	1438	17.59%	19.26%	63.14%	-1.29	-4.2	28
2017-04-02	@ Progres Niedercorn	W 2-1	40.6	1438	1219	63.14%	19.26%	17.59%	+1.29	+4.2	50
2017-04-02	Fola Esch	D 1-1	55.1	1144	1406	14.48%	18.49%	67.03%	-1.58	+2.7	26
2017-04-02	@ Union Titus Petange	D 1-1	55.1	1406	1144	67.03%	18.49%	14.48%	+1.58	-2.7	43
2017-04-02	Mondorf-les-Bains	L 1-3	49.3	1231	1106	58.86%	19.90%	21.24%	+1.01	-20.7	27
2017-04-02	@ Jeunesse Esch	W 3-1	49.3	1106	1231	21.24%	19.90%	58.86%	-1.01	+20.7	27
2017-04-02	Rumelange	D 0-0	50.1	1092	1038	50.47%	20.67%	28.87%	+0.54	-1.2	19
2017-04-02	@ RM Hamm Benfica	D 0-0	50.1	1038	1092	28.87%	20.67%	50.47%	-0.54	+1.2	19
2017-04-02	UN Kaerjeng	W 2-0	39.5	1029	1082	35.79%	20.94%	43.27%	-0.18	+18.3	21
2017-04-02	@ Jeunesse Canach	L 0-2	39.5	1082	1029	43.27%	20.94%	35.79%	+0.18	-18.3	16
2017-04-02	Victoria Rosport	L 0-2	43.4	1165	1059	56.73%	20.15%	23.12%	+0.88	-23.1	29
2017-04-02	@ UNA Strassen	W 2-0	43.4	1059	1165	23.12%	20.15%	56.73%	-0.88	+23.1	16
2017-04-09	Differdange 03	L 0-1	49.2	1443	1388	50.59%	20.66%	28.75%	+0.54	-11.1	50
2017-04-09	@ F91 Dudelange	W 1-0	49.2	1388	1443	28.75%	20.66%	50.59%	-0.54	+11.1	52
2017-04-09	RM Hamm Benfica	W 3-2	41.3	1403	1090	74.89%	16.23%	8.88%	+2.28	+2.0	46
2017-04-09	@ Fola Esch	L 2-3	41.3	1090	1403	8.88%	16.23%	74.89%	-2.28	-2.0	19
2017-04-09	Jeunesse Canach	W 3-0	31.7	1127	1048	53.73%	20.43%	25.83%	+0.71	+17.3	30
2017-04-09	@ Mondorf-les-Bains	L 0-3	31.7	1048	1127	25.83%	20.43%	53.73%	-0.71	-17.3	21
2017-04-09	Jeunesse Esch	W 2-1	50.3	1083	1210	26.47%	20.49%	53.04%	-0.67	+10.9	19
2017-04-09	@ Victoria Rosport	L 1-2	50.3	1210	1083	53.04%	20.49%	26.47%	+0.67	-10.9	27
2017-04-09	Racing FC Union Luxembourg	D 1-1	53.7	1039	1055	41.11%	20.97%	37.92%	+0.07	-0.1	20
2017-04-09	@ Rumelange	D 1-1	53.7	1055	1039	37.92%	20.97%	41.11%	-0.07	+0.2	21
2017-04-09	UNA Strassen	W 5-1	35.5	1214	1142	52.91%	20.50%	26.59%	+0.67	+19.4	31
2017-04-09	@ Progres Niedercorn	L 1-5	35.5	1142	1214	26.59%	20.50%	52.91%	-0.67	-19.4	29
2017-04-09	Union Titus Petange	L 0-3	33.7	1064	1147	31.92%	20.83%	47.26%	-0.37	-20.8	16
2017-04-09	@ UN Kaerjeng	W 3-0	33.7	1147	1064	47.26%	20.83%	31.92%	+0.37	+20.8	29
2017-04-23	F91 Dudelange	L 0-3	27.2	1122	1432	11.62%	17.52%	70.86%	-1.89	-8.1	29
2017-04-23	@ UNA Strassen	W 3-0	27.2	1432	1122	70.86%	17.52%	11.62%	+1.89	+8.1	53
2017-04-23	Fola Esch	L 0-2	28.4	1055	1405	9.59%	16.61%	73.80%	-2.17	-4.6	21
2017-04-23	@ Racing FC Union Luxembourg	W 2-0	28.4	1405	1055	73.80%	16.61%	9.59%	+2.17	+4.6	49
2017-04-23	Mondorf-les-Bains	W 2-1	44.3	1167	1145	46.45%	20.86%	32.69%	+0.33	+7.3	32
2017-04-23	@ Union Titus Petange	L 1-2	44.3	1145	1167	32.69%	20.86%	46.45%	-0.33	-7.3	30
2017-04-23	Progres Niedercorn	L 0-2	38.3	1199	1234	38.40%	20.97%	40.63%	-0.05	-16.6	27
2017-04-23	@ Jeunesse Esch	W 2-0	38.3	1234	1199	40.63%	20.97%	38.40%	+0.05	+16.6	34
2017-04-23	Rumelange	W 2-0	27.2	1399	1039	77.82%	15.10%	7.08%	+2.59	+3.3	55
2017-04-23	@ Differdange 03	L 0-2	27.2	1039	1399	7.08%	15.10%	77.82%	-2.59	-3.3	20
2017-04-23	UN Kaerjeng	L 1-2	49.2	1088	1043	49.40%	20.73%	29.88%	+0.48	-10.2	19
2017-04-23	@ RM Hamm Benfica	W 2-1	49.2	1043	1088	29.88%	20.73%	49.40%	-0.48	+10.2	19
2017-04-23	Victoria Rosport	L 0-2	36.9	1030	1094	34.42%	20.91%	44.67%	-0.24	-15.2	21
2017-04-23	@ Jeunesse Canach	W 2-0	36.9	1094	1030	44.67%	20.91%	34.42%	+0.24	+15.2	22
2017-04-28	Jeunesse Canach	D 2-2	60.0	1250	1015	69.26%	17.96%	12.78%	+1.76	-2.2	35
2017-04-28	@ Progres Niedercorn	D 2-2	60.0	1015	1250	12.78%	17.96%	69.26%	-1.76	+2.2	22
2017-04-30	Differdange 03	D 1-1	57.7	1410	1403	44.31%	20.92%	34.77%	+0.23	-0.4	50
2017-04-30	@ Fola Esch	D 1-1	57.7	1403	1410	34.77%	20.92%	44.31%	-0.23	+0.4	56
2017-04-30	RM Hamm Benfica	L 1-2	49.8	1137	1078	51.18%	20.62%	28.20%	+0.57	-10.5	30
2017-04-30	@ Mondorf-les-Bains	W 2-1	49.8	1078	1137	28.20%	20.62%	51.18%	-0.57	+10.5	22
2017-04-30	Racing FC Union Luxembourg	L 0-3	37.2	1054	1051	43.73%	20.93%	35.34%	+0.20	-26.8	19
2017-04-30	@ UN Kaerjeng	W 3-0	37.2	1051	1054	35.34%	20.93%	43.73%	-0.20	+26.8	24
2017-04-30	Rumelange	W 3-2	39.6	1440	1036	80.23%	14.03%	5.74%	+2.88	+1.2	56
2017-04-30	@ F91 Dudelange	L 2-3	39.6	1036	1440	5.74%	14.03%	80.23%	-2.88	-1.2	20
2017-04-30	Union Titus Petange	W 3-1	45.4	1109	1175	34.07%	20.90%	45.03%	-0.26	+16.4	25
2017-04-30	@ Victoria Rosport	L 1-3	45.4	1175	1109	45.03%	20.90%	34.07%	+0.26	-16.4	32
2017-05-01	Jeunesse Esch	D 1-1	53.8	1114	1183	33.72%	20.89%	45.39%	-0.28	+0.6	30
2017-05-01	@ UNA Strassen	D 1-1	53.8	1183	1114	45.39%	20.89%	33.72%	+0.28	-0.5	28
2017-05-06	Mondorf-les-Bains	W 3-1	44.7	1077	1127	36.34%	20.95%	42.71%	-0.15	+15.7	27
2017-05-06	@ Racing FC Union Luxembourg	L 1-3	44.7	1127	1077	42.71%	20.95%	36.34%	+0.15	-15.7	30
2017-05-07	F91 Dudelange	L 0-3	28.9	1182	1441	14.70%	18.56%	66.74%	-1.55	-10.3	28
2017-05-07	@ Jeunesse Esch	W 3-0	28.9	1441	1182	66.74%	18.56%	14.70%	+1.55	+10.3	59
2017-05-07	Fola Esch	L 1-3	33.2	1035	1409	8.54%	16.04%	75.43%	-2.33	-3.5	20
2017-05-07	@ Rumelange	W 3-1	33.2	1409	1035	75.43%	16.04%	8.54%	+2.33	+3.5	53
2017-05-07	Progres Niedercorn	L 0-3	33.5	1158	1248	30.96%	20.78%	48.26%	-0.42	-20.2	32
2017-05-07	@ Union Titus Petange	W 3-0	33.5	1248	1158	48.26%	20.78%	30.96%	+0.42	+20.2	38
2017-05-07	UN Kaerjeng	W 6-2	30.1	1403	1027	78.74%	14.70%	6.55%	+2.70	+4.1	59
2017-05-07	@ Differdange 03	L 2-6	30.1	1027	1403	6.55%	14.70%	78.74%	-2.70	-4.1	19
2017-05-07	UNA Strassen	L 1-3	40.8	1017	1115	30.02%	20.73%	49.25%	-0.47	-11.8	22
2017-05-07	@ Jeunesse Canach	W 3-1	40.8	1115	1017	49.25%	20.73%	30.02%	+0.47	+11.8	33
2017-05-07	Victoria Rosport	W 2-1	46.8	1089	1125	38.16%	20.97%	40.87%	-0.06	+8.7	25
2017-05-07	@ RM Hamm Benfica	L 1-2	46.8	1125	1089	40.87%	20.97%	38.16%	+0.06	-8.7	25
2017-05-14	Differdange 03	L 0-3	27.4	1111	1407	12.36%	17.81%	69.84%	-1.81	-8.6	30
2017-05-14	@ Mondorf-les-Bains	W 3-0	27.4	1407	1111	69.84%	17.81%	12.36%	+1.81	+8.6	62
2017-05-14	RM Hamm Benfica	W 4-1	34.1	1268	1098	63.60%	19.18%	17.22%	+1.32	+10.1	41
2017-05-14	@ Progres Niedercorn	L 1-4	34.1	1098	1268	17.22%	19.18%	63.60%	-1.32	-10.1	25
2017-05-14	Fola Esch	W 5-2	47.1	1451	1413	48.51%	20.77%	30.72%	+0.44	+14.7	62
2017-05-14	@ F91 Dudelange	L 2-5	47.1	1413	1451	30.72%	20.77%	48.51%	-0.44	-14.7	53
2017-05-14	Jeunesse Canach	D 2-2	59.6	1172	1005	63.16%	19.26%	17.58%	+1.29	-1.8	29
2017-05-14	@ Jeunesse Esch	D 2-2	59.6	1005	1172	17.58%	19.26%	63.16%	-1.29	+1.8	23
2017-05-14	Racing FC Union Luxembourg	W 4-3	52.8	1116	1093	46.51%	20.85%	32.64%	+0.33	+6.7	28
2017-05-14	@ Victoria Rosport	L 3-4	52.8	1093	1116	32.64%	20.85%	46.51%	-0.33	-6.7	27
2017-05-14	Rumelange	W 4-3	54.1	1023	1031	42.13%	20.96%	36.92%	+0.12	+7.4	22
2017-05-14	@ UN Kaerjeng	L 3-4	54.1	1031	1023	36.92%	20.96%	42.13%	-0.12	-7.4	20
2017-05-14	Union Titus Petange	W 3-1	43.1	1126	1138	41.68%	20.96%	37.36%	+0.10	+14.1	36
2017-05-14	@ UNA Strassen	L 1-3	43.1	1138	1126	37.36%	20.96%	41.68%	-0.10	-14.1	32
2017-05-21	F91 Dudelange	L 0-2	26.5	1007	1466	5.70%	13.99%	80.31%	-2.89	-2.6	23
2017-05-21	@ Jeunesse Canach	W 2-0	26.5	1466	1007	80.31%	13.99%	5.70%	+2.89	+2.6	65
2017-05-21	Jeunesse Esch	W 6-2	42.6	1124	1170	36.78%	20.96%	42.26%	-0.13	+24.0	35
2017-05-21	@ Union Titus Petange	L 2-6	42.6	1170	1124	42.26%	20.96%	36.78%	+0.13	-24.0	29
2017-05-21	Mondorf-les-Bains	W 5-2	46.6	1024	1102	32.41%	20.84%	46.75%	-0.35	+20.7	23
2017-05-21	@ Rumelange	L 2-5	46.6	1102	1024	46.75%	20.84%	32.41%	+0.35	-20.7	30
2017-05-21	Progres Niedercorn	L 4-5	50.2	1086	1279	19.93%	19.70%	60.37%	-1.11	-4.3	27
2017-05-21	@ Racing FC Union Luxembourg	W 5-4	50.2	1279	1086	60.37%	19.70%	19.93%	+1.11	+4.3	44
2017-05-21	UN Kaerjeng	W 4-2	36.7	1398	1030	78.27%	14.91%	6.82%	+2.64	+2.5	56
2017-05-21	@ Fola Esch	L 2-4	36.7	1030	1398	6.82%	14.91%	78.27%	-2.64	-2.5	22
2017-05-21	UNA Strassen	D 1-1	53.8	1087	1140	35.82%	20.94%	43.24%	-0.18	+0.3	26
2017-05-21	@ RM Hamm Benfica	D 1-1	53.8	1140	1087	43.24%	20.94%	35.82%	+0.18	-0.4	37
2017-05-21	Victoria Rosport	W 6-2	32.0	1416	1123	73.54%	16.70%	9.76%	+2.14	+6.2	65
2017-05-21	@ Differdange 03	L 2-6	32.0	1123	1416	9.76%	16.70%	73.54%	-2.14	-6.2	28

Biggest Upsets

The 25 games where the underdog won despite the lowest pregame win probability. Underdog Win % is the winner's pregame chance of winning the game (lower = bigger upset). @ before a team name indicates the away side. An asterisk (*) after the date marks a playoff game.

#	Date	Underdog Win %	Winning Team			Losing Team
#	Date	Underdog Win %	Team	Elo	Score	Team	Elo	Score
1	2016-12-14	17.97%	Union Titus Petange	1079	2	@ Progres Niedercorn	1241	0
2	2017-03-05	19.07%	@ Rumelange	1041	3	Jeunesse Esch	1243	2
3	2016-08-21	19.44%	Racing FC Union Luxembourg	1113	2	@ Jeunesse Esch	1257	1
4	2016-11-05	20.69%	Union Titus Petange	1051	2	@ Mondorf-les-Bains	1182	0
5	2017-04-02	21.24%	Mondorf-les-Bains	1106	3	@ Jeunesse Esch	1231	1
6	2016-09-12	21.79%	UN Kaerjeng	1110	2	@ Progres Niedercorn	1228	0
7	2017-03-12	22.57%	Mondorf-les-Bains	1121	2	@ Progres Niedercorn	1232	1
8	2017-04-02	23.12%	Victoria Rosport	1059	2	@ UNA Strassen	1165	0
9	2016-08-28	23.19%	Union Titus Petange	1054	1	@ RM Hamm Benfica	1159	0
10	2017-02-26	23.77%	@ Jeunesse Esch	1231	1	Differdange 03	1383	0
11	2016-08-21	25.25%	@ Jeunesse Canach	1047	4	RM Hamm Benfica	1186	1
12	2016-12-11	26.11%	Victoria Rosport	1063	2	@ Racing FC Union Luxembourg	1140	1
13	2016-12-04	26.20%	Jeunesse Canach	1025	2	@ UNA Strassen	1101	0
14	2017-04-09	26.47%	@ Victoria Rosport	1083	2	Jeunesse Esch	1210	1
15	2016-09-25	27.91%	UNA Strassen	1072	2	@ UN Kaerjeng	1133	0
16	2017-04-30	28.20%	RM Hamm Benfica	1078	2	@ Mondorf-les-Bains	1137	1
17	2017-04-09	28.75%	Differdange 03	1388	1	@ F91 Dudelange	1443	0
18	2016-08-27	29.27%	UNA Strassen	1057	2	@ Rumelange	1107	0
19	2017-03-12	29.60%	Racing FC Union Luxembourg	1057	3	@ RM Hamm Benfica	1104	2
20	2017-04-23	29.88%	UN Kaerjeng	1043	2	@ RM Hamm Benfica	1088	1
21	2016-09-29	30.08%	@ UNA Strassen	1093	3	Mondorf-les-Bains	1190	1
22	2017-02-25	30.78%	@ Jeunesse Canach	1007	3	Racing FC Union Luxembourg	1098	2
23	2016-11-20	31.66%	@ Union Titus Petange	1075	3	UN Kaerjeng	1160	1
24	2016-10-16	31.71%	@ Mondorf-les-Bains	1172	1	Jeunesse Esch	1256	0
25	2016-12-11	31.96%	UNA Strassen	1079	3	@ Union Titus Petange	1108	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	2016-11-06	44.08	@ UN Kaerjeng	6	1116	42.77%	RM Hamm Benfica	0	1120	36.28%	20.95%
2	2016-08-07	35.14	RM Hamm Benfica	5	1165	45.19%	@ UNA Strassen	0	1098	33.92%	20.90%
3	2017-03-05	32.07	Union Titus Petange	4	1117	39.77%	@ Racing FC Union Luxembourg	0	1089	39.26%	20.97%
4	2017-02-12	29.53	Union Titus Petange	4	1105	43.64%	@ Jeunesse Canach	0	1049	35.42%	20.93%
5	2016-12-11	28.57	UNA Strassen	3	1079	31.96%	@ Union Titus Petange	0	1108	47.22%	20.83%
6	2016-08-21	27.27	@ Jeunesse Canach	4	1047	25.25%	RM Hamm Benfica	1	1186	54.37%	20.38%
7	2016-11-27	26.82	Progres Niedercorn	5	1196	55.01%	@ Jeunesse Canach	0	1052	24.67%	20.32%
8	2017-04-30	26.78	Racing FC Union Luxembourg	3	1051	35.34%	@ UN Kaerjeng	0	1054	43.73%	20.93%
9	2017-03-18	26.14	UNA Strassen	3	1139	36.57%	@ Mondorf-les-Bains	0	1133	42.48%	20.95%
10	2016-12-14	25.39	Union Titus Petange	2	1079	17.97%	@ Progres Niedercorn	0	1241	62.69%	19.34%
11	2017-02-12	24.24	@ UNA Strassen	3	1108	40.38%	Racing FC Union Luxembourg	0	1129	38.65%	20.97%
12	2016-11-05	24.18	Union Titus Petange	2	1051	20.69%	@ Mondorf-les-Bains	0	1182	59.49%	19.82%
13	2016-11-27	24.11	@ Racing FC Union Luxembourg	3	1124	40.64%	UN Kaerjeng	0	1143	38.39%	20.97%
14	2017-05-21	24.05	@ Union Titus Petange	6	1124	36.78%	Jeunesse Esch	2	1170	42.26%	20.96%
15	2016-09-12	23.71	UN Kaerjeng	2	1110	21.79%	@ Progres Niedercorn	0	1228	58.23%	19.98%
16	2016-08-19	23.21	@ Progres Niedercorn	4	1203	52.94%	Rumelange	0	1130	26.56%	20.50%
17	2017-04-02	23.15	Victoria Rosport	2	1059	23.12%	@ UNA Strassen	0	1165	56.73%	20.15%
18	2016-12-04	21.89	Jeunesse Canach	2	1025	26.20%	@ UNA Strassen	0	1101	53.33%	20.47%
19	2016-09-25	21.21	UNA Strassen	2	1072	27.91%	@ UN Kaerjeng	0	1133	51.49%	20.60%
20	2017-04-09	20.76	Union Titus Petange	3	1147	47.26%	@ UN Kaerjeng	0	1064	31.92%	20.83%
21	2017-04-02	20.73	Mondorf-les-Bains	3	1106	21.24%	@ Jeunesse Esch	1	1231	58.86%	19.90%
22	2016-08-27	20.68	UNA Strassen	2	1057	29.27%	@ Rumelange	0	1107	50.04%	20.69%
23	2017-05-21	20.68	@ Rumelange	5	1024	32.41%	Mondorf-les-Bains	2	1102	46.75%	20.84%
24	2017-05-07	20.24	Progres Niedercorn	3	1248	48.26%	@ Union Titus Petange	0	1158	30.96%	20.78%
25	2016-12-11	19.70	@ Differdange 03	6	1350	66.69%	Mondorf-les-Bains	0	1146	14.74%	18.57%

Most & Least Exciting Games

The season’s games ranked by excitement rating (0–100) — a blend of closeness, upset, team quality, and scoring. An asterisk (*) after the date indicates a playoff game.

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2016-08-21	66.5	@ UNA Strassen	4	1055	15.71%	Differdange 03	4	1300	65.47%	18.83%
2	2016-12-10	62.4	@ Fola Esch	2	1370	36.66%	F91 Dudelange	2	1417	42.39%	20.96%
3	2017-03-18	61.2	@ Fola Esch	2	1409	79.09%	Jeunesse Canach	2	1026	6.36%	14.55%
4	2016-09-25	60.4	@ Fola Esch	2	1367	58.41%	Jeunesse Esch	2	1247	21.63%	19.96%
5	2017-02-25	60.2	@ Progres Niedercorn	2	1220	22.90%	Fola Esch	2	1381	56.97%	20.12%
6	2017-04-28	60.0	@ Progres Niedercorn	2	1250	69.26%	Jeunesse Canach	2	1015	12.78%	17.96%
7	2016-10-23	59.6	@ Jeunesse Esch	2	1246	62.50%	Victoria Rosport	2	1086	18.13%	19.37%
8	2017-05-14	59.6	@ Jeunesse Esch	2	1172	63.16%	Jeunesse Canach	2	1005	17.58%	19.26%
9	2017-03-18	59.4	@ Victoria Rosport	2	1058	22.82%	Progres Niedercorn	2	1220	57.07%	20.11%
10	2017-03-05	57.7	@ Rumelange	3	1041	19.07%	Jeunesse Esch	2	1243	61.38%	19.55%
11	2017-04-30	57.7	@ Fola Esch	1	1410	44.31%	Differdange 03	1	1403	34.77%	20.92%
12	2017-02-12	55.3	@ UN Kaerjeng	1	1104	11.41%	F91 Dudelange	1	1417	71.14%	17.44%
13	2017-02-25	55.3	@ Mondorf-les-Bains	1	1111	11.59%	F91 Dudelange	1	1421	70.90%	17.51%
14	2017-04-02	55.1	@ Union Titus Petange	1	1144	14.48%	Fola Esch	1	1406	67.03%	18.49%
15	2016-08-26	55.0	@ Fola Esch	1	1364	60.25%	Progres Niedercorn	1	1226	20.04%	19.72%
16	2016-08-21	54.9	@ Union Titus Petange	1	1051	12.41%	F91 Dudelange	1	1346	69.76%	17.83%
17	2016-10-23	54.8	@ RM Hamm Benfica	1	1117	14.96%	Fola Esch	1	1372	66.41%	18.63%
18	2017-03-12	54.5	Racing FC Union Luxembourg	3	1057	29.60%	@ RM Hamm Benfica	2	1104	49.69%	20.71%
19	2016-11-27	54.3	@ Jeunesse Esch	1	1244	61.01%	UNA Strassen	1	1099	19.39%	19.61%
20	2016-08-07	54.2	@ Victoria Rosport	1	1140	24.10%	Differdange 03	1	1289	55.63%	20.26%
21	2017-02-12	54.2	@ Jeunesse Esch	1	1226	60.55%	RM Hamm Benfica	1	1086	19.77%	19.67%
22	2016-12-11	54.1	@ Jeunesse Canach	1	1047	20.92%	Jeunesse Esch	1	1228	59.22%	19.85%
23	2017-02-25	54.1	@ Jeunesse Canach	3	1007	30.78%	Racing FC Union Luxembourg	2	1098	48.45%	20.77%
24	2017-05-14	54.1	@ UN Kaerjeng	4	1023	42.13%	Rumelange	3	1031	36.92%	20.96%
25	2016-11-05	54.0	@ Progres Niedercorn	1	1195	36.40%	Jeunesse Esch	1	1244	42.65%	20.95%

#	Date	Excitement	Winning Team				Losing Team				Tie %
#	Date	Excitement	Team	Score	Elo	Win %	Team	Score	Elo	Win %	Tie %
1	2017-03-18	23.8	@ F91 Dudelange	4	1432	78.15%	Racing FC Union Luxembourg	0	1066	6.89%	14.96%
2	2017-03-12	24.9	F91 Dudelange	4	1424	74.30%	@ Victoria Rosport	0	1067	9.26%	16.44%
3	2017-03-05	26.0	@ F91 Dudelange	3	1418	74.53%	RM Hamm Benfica	0	1110	9.11%	16.36%
4	2016-11-05	26.4	@ F91 Dudelange	3	1388	72.77%	UNA Strassen	0	1106	10.28%	16.95%
5	2017-03-05	26.5	@ Fola Esch	5	1379	69.80%	UNA Strassen	0	1137	12.38%	17.81%
6	2017-05-21	26.5	F91 Dudelange	2	1466	80.31%	@ Jeunesse Canach	0	1007	5.70%	13.99%
7	2017-02-19	26.7	@ F91 Dudelange	3	1414	72.59%	Union Titus Petange	0	1134	10.41%	17.01%
8	2016-11-27	26.9	F91 Dudelange	3	1395	70.90%	@ Rumelange	0	1085	11.59%	17.51%
9	2016-09-25	27.1	@ F91 Dudelange	3	1361	70.17%	Victoria Rosport	0	1114	12.11%	17.72%
10	2017-04-23	27.2	F91 Dudelange	3	1432	70.86%	@ UNA Strassen	0	1122	11.62%	17.52%
11	2017-04-23	27.2	@ Differdange 03	2	1399	77.82%	Rumelange	0	1039	7.08%	15.10%
12	2017-05-14	27.4	Differdange 03	3	1407	69.84%	@ Mondorf-les-Bains	0	1111	12.36%	17.81%
13	2016-12-11	28.0	@ Differdange 03	6	1350	66.69%	Mondorf-les-Bains	0	1146	14.74%	18.57%
14	2017-03-05	28.1	@ Differdange 03	5	1371	77.48%	Jeunesse Canach	1	1016	7.28%	15.24%
15	2016-10-16	28.3	@ F91 Dudelange	4	1373	64.05%	Progres Niedercorn	0	1198	16.85%	19.10%
16	2016-12-04	28.4	@ Fola Esch	7	1359	72.74%	Rumelange	1	1077	10.30%	16.96%
17	2017-04-23	28.4	Fola Esch	2	1405	73.80%	@ Racing FC Union Luxembourg	0	1055	9.59%	16.61%
18	2016-08-06	28.7	@ F91 Dudelange	6	1333	72.38%	Jeunesse Canach	1	1057	10.55%	17.07%
19	2017-05-07	28.9	F91 Dudelange	3	1441	66.74%	@ Jeunesse Esch	0	1182	14.70%	18.56%
20	2017-04-02	29.0	Differdange 03	2	1383	71.86%	@ Racing FC Union Luxembourg	0	1060	10.91%	17.23%
21	2016-08-07	29.2	Fola Esch	4	1334	59.83%	@ UN Kaerjeng	0	1147	20.40%	19.77%
22	2016-09-12	29.5	@ Jeunesse Esch	3	1234	61.29%	Rumelange	0	1086	19.15%	19.56%
23	2016-09-11	29.8	F91 Dudelange	3	1348	61.30%	@ RM Hamm Benfica	0	1146	19.14%	19.56%
24	2017-05-07	30.1	@ Differdange 03	6	1403	78.74%	UN Kaerjeng	2	1027	6.55%	14.70%
25	2016-11-27	30.5	Progres Niedercorn	5	1196	55.01%	@ Jeunesse Canach	0	1052	24.67%	20.32%