2015-16 1st Division Season
198 games
Promoted
Lyngby
64 pts
Silkeborg · 63 pts
Horsens · 60 pts
Relegated
Vestsjaelland
withdrew
Biggest Overachiever
Silkeborg
11.36 points above expected
63 points · 51.64 expected points
Biggest Disappointment
Skive
8.93 points below expected
31 points · 39.93 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 | Lyngby Promoted | 33 | 19 | 7 | 7 | 64 | 56 | 37 | +19 | 55.15 | +8.85 |
| 2 | Silkeborg Promoted | 33 | 18 | 9 | 6 | 63 | 53 | 29 | +24 | 51.64 | +11.36 |
| 3 | Horsens Promoted | 33 | 18 | 6 | 9 | 60 | 46 | 34 | +12 | 53.09 | +6.91 |
| 4 | Vendsyssel | 33 | 16 | 8 | 9 | 56 | 38 | 33 | +5 | 48.37 | +7.63 |
| 5 | Vejle BK | 33 | 16 | 5 | 12 | 53 | 50 | 46 | +4 | 51.80 | +1.20 |
| 6 | Fredericia | 33 | 12 | 11 | 10 | 47 | 42 | 45 | -3 | 44.82 | +2.18 |
| 7 | Helsingor | 33 | 14 | 5 | 14 | 47 | 34 | 42 | -8 | 52.77 | -5.77 |
| 8 | HB Koge | 33 | 13 | 6 | 14 | 45 | 31 | 35 | -4 | 44.89 | +0.11 |
| 9 | FC Roskilde | 33 | 10 | 9 | 14 | 39 | 48 | 58 | -10 | 44.13 | -5.13 |
| 10 | Naestved | 33 | 10 | 4 | 19 | 34 | 34 | 48 | -14 | 40.93 | -6.93 |
| 11 | Skive | 33 | 8 | 7 | 18 | 31 | 34 | 50 | -16 | 39.93 | -8.93 |
| 12 | Vestsjaelland Withdrew | 33 | 2 | 7 | 24 | 13 | 19 | 28 | -9 | 20.11 | -7.11 |
* Point deductions: FC Vestsjaelland (-6 pts)
Notes
- FC Vestsjaelland went bankrupt in the middle of the season, causing their 15 remaining matches to be forfeit losses. Their license was subsequently used as an amateur club in the Zealand Series.
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Silkeborg | 1494 | 63 | 51.64 | +11.36 | 95.1% | 22 | 40 | 47 | 52 | 57 | 63 | 80 |
| Lyngby | 1463 | 64 | 55.15 | +8.85 | 89.5% | 29 | 43 | 50 | 55 | 60 | 67 | 80 |
| Horsens | 1429 | 60 | 53.09 | +6.91 | 84.2% | 27 | 41 | 48 | 53 | 58 | 65 | 77 |
| Vendsyssel | 1391 | 56 | 48.37 | +7.63 | 85.5% | 20 | 36 | 43 | 48 | 54 | 61 | 78 |
| Vejle BK | 1382 | 53 | 51.80 | +1.20 | 59.4% | 28 | 40 | 47 | 52 | 57 | 64 | 81 |
| Helsingor | 1368 | 47 | 52.77 | -5.77 | 23.9% | 26 | 41 | 48 | 53 | 58 | 65 | 85 |
| HB Koge | 1363 | 45 | 44.89 | +0.11 | 53.4% | 19 | 33 | 40 | 45 | 50 | 57 | 73 |
| Vestsjaelland | 1352 | 13 | 20.11 | -7.11 | 1.2% | 1 | 11 | 16 | 20 | 24 | 29 | 40 |
| FC Roskilde | 1336 | 39 | 44.13 | -5.13 | 26.9% | 16 | 32 | 39 | 44 | 49 | 56 | 72 |
| Fredericia | 1335 | 47 | 44.82 | +2.18 | 63.9% | 18 | 33 | 40 | 45 | 50 | 57 | 73 |
| Naestved | 1321 | 34 | 40.93 | -6.93 | 18.8% | 15 | 29 | 36 | 41 | 46 | 53 | 69 |
| Skive | 1285 | 31 | 39.93 | -8.93 | 12.0% | 16 | 28 | 35 | 40 | 45 | 52 | 69 |
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 | FR | FRE | HK | HEL | HOR | LYN | NAE | SIL | SKI | VB | VEN | VES |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FC Roskilde | — |
0-2-1
4.12
|
2-1-0
4.11
|
1-0-2
3.81
|
0-0-3
3.45
|
1-1-1
3.41
|
1-1-1
4.18
|
0-1-2
4.09
|
2-1-0
4.35
|
1-0-2
3.67
|
1-0-2
3.40
|
1-2-0
3.63
|
| Fredericia |
1-2-0
4.20
|
— |
0-1-2
4.74
|
2-1-0
3.86
|
0-1-2
3.30
|
2-0-1
3.44
|
2-1-0
4.43
|
1-1-1
3.84
|
1-1-1
4.58
|
0-2-1
3.57
|
1-0-2
3.75
|
2-1-0
3.84
|
| HB Koge |
0-1-2
4.22
|
2-1-0
3.59
|
— |
1-0-2
4.01
|
0-0-3
3.68
|
0-1-2
3.31
|
2-0-1
4.65
|
0-1-2
3.71
|
1-2-0
4.72
|
1-0-2
3.41
|
3-0-0
3.90
|
3-0-0
4.28
|
| Helsingor |
2-0-1
4.52
|
0-1-2
4.47
|
2-0-1
4.32
|
— |
0-2-1
4.38
|
0-0-3
3.85
|
2-0-1
5.17
|
0-1-2
4.39
|
3-0-0
5.31
|
2-0-1
4.41
|
1-1-1
4.35
|
2-0-1
4.53
|
| Horsens |
3-0-0
4.89
|
2-1-0
5.03
|
3-0-0
4.65
|
1-2-0
3.95
|
— |
1-1-1
4.18
|
0-0-3
5.02
|
1-1-1
4.23
|
3-0-0
4.83
|
0-0-3
4.30
|
1-1-1
4.36
|
3-0-0
5.16
|
| Lyngby |
1-1-1
4.93
|
1-0-2
4.91
|
2-1-0
5.03
|
3-0-0
4.49
|
1-1-1
4.15
|
— |
3-0-0
5.43
|
2-0-1
4.80
|
1-2-0
5.76
|
3-0-0
4.74
|
1-0-2
4.68
|
1-2-0
4.85
|
| Naestved |
1-1-1
4.15
|
0-1-2
3.90
|
1-0-2
3.69
|
1-0-2
3.17
|
3-0-0
3.34
|
0-0-3
2.92
|
— |
0-1-2
3.23
|
1-0-2
4.40
|
1-0-2
2.88
|
0-1-2
3.79
|
2-0-1
3.38
|
| Silkeborg |
2-1-0
4.25
|
1-1-1
4.50
|
2-1-0
4.63
|
2-1-0
3.93
|
1-1-1
4.09
|
1-0-2
3.54
|
2-1-0
5.12
|
— |
2-1-0
5.26
|
2-0-1
4.47
|
0-2-1
4.41
|
3-0-0
4.71
|
| Skive |
0-1-2
3.98
|
1-1-1
3.75
|
0-2-1
3.62
|
0-0-3
3.04
|
0-0-3
3.53
|
0-2-1
2.61
|
2-0-1
3.93
|
0-1-2
3.09
|
— |
1-0-2
3.22
|
1-0-2
3.75
|
3-0-0
3.72
|
| Vejle BK |
2-0-1
4.67
|
1-2-0
4.77
|
2-0-1
4.93
|
1-0-2
3.93
|
3-0-0
4.04
|
0-0-3
3.59
|
2-0-1
5.48
|
1-0-2
3.87
|
2-0-1
5.12
|
— |
0-2-1
4.46
|
2-1-0
4.15
|
| Vendsyssel |
2-0-1
4.94
|
2-0-1
4.58
|
0-0-3
4.43
|
1-1-1
3.98
|
1-1-1
3.97
|
2-0-1
3.66
|
2-1-0
4.55
|
1-2-0
3.92
|
2-0-1
4.59
|
1-2-0
3.88
|
— |
2-1-0
4.55
|
| Vestsjaelland |
0-2-1
4.71
|
0-1-2
4.50
|
0-0-3
4.05
|
1-0-2
3.80
|
0-0-3
3.18
|
0-2-1
3.48
|
1-0-2
4.96
|
0-0-3
3.63
|
0-0-3
4.61
|
0-1-2
4.19
|
0-1-2
3.77
|
— |
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 | 0.67 | +11.5 |
| Allowed | 0.04 | -3.4 |
| Differential | 0.68 | +9.6 |
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.
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 7.07% | 10.10% | 5.81% | 3.03% | 0.51% | 0.25% | 26.77% |
| 1 | 10.10% | 9.60% | 6.06% | 4.04% | 0.51% | 0.25% | 30.56% |
| 2 | 5.81% | 6.06% | 3.03% | 2.78% | 1.26% | 0.25% | 19.19% |
| 3 | 3.03% | 4.04% | 2.78% | 0.51% | 0.76% | — | 11.11% |
| 4 | 0.51% | 0.51% | 1.26% | 0.76% | 1.01% | — | 4.04% |
| 5+ | 0.25% | 0.25% | 0.25% | — | — | 7.58% | 8.33% |
| Total | 26.77% | 30.56% | 19.19% | 11.11% | 4.04% | 8.33% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.15 | 1.15 | +0.00 |
| SD | 1.30 | 1.30 | 1.54 |
| CV | 1.13 | 1.13 | — |
| Max | 6 | 6 | +5 |
| Min | -1 | -1 | -5 |
Games Played: 198
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 9.09% | 3.03% | — | 3.03% | — | 21.21% |
| 1 | 6.06% | 9.09% | 9.09% | 6.06% | — | — | 30.30% |
| 2 | 6.06% | 3.03% | 6.06% | 6.06% | 3.03% | 3.03% | 27.27% |
| 3 | 3.03% | 3.03% | 3.03% | 3.03% | — | — | 12.12% |
| 4 | — | — | — | 3.03% | 3.03% | — | 6.06% |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 21.21% | 24.24% | 21.21% | 18.18% | 9.09% | 6.06% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.42 | 1.73 | -0.30 |
| SD | 1.23 | 1.55 | 1.57 |
| CV | 0.86 | 0.90 | — |
| Max | 4 | 6 | +3 |
| Min | -1 | -1 | -4 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 15.15% | 3.03% | 6.06% | 6.06% | — | — | 30.30% |
| 1 | 9.09% | 9.09% | 6.06% | — | 3.03% | — | 27.27% |
| 2 | 3.03% | 12.12% | 3.03% | 3.03% | 3.03% | — | 24.24% |
| 3 | — | 3.03% | 3.03% | 3.03% | — | — | 9.09% |
| 4 | 3.03% | — | — | — | 3.03% | — | 6.06% |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 30.30% | 27.27% | 18.18% | 12.12% | 9.09% | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.24 | 1.33 | -0.09 |
| SD | 1.25 | 1.36 | 1.53 |
| CV | 1.01 | 1.02 | — |
| Max | 4 | 4 | +4 |
| Min | -1 | -1 | -3 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 18.18% | 3.03% | 6.06% | 3.03% | — | 36.36% |
| 1 | 12.12% | 9.09% | 9.09% | 3.03% | — | — | 33.33% |
| 2 | 12.12% | 6.06% | 3.03% | — | — | — | 21.21% |
| 3 | 3.03% | 3.03% | — | — | — | — | 6.06% |
| 4 | — | — | — | — | — | — | — |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 33.33% | 36.36% | 15.15% | 9.09% | 3.03% | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 0.91 | 1.03 | -0.12 |
| SD | 0.98 | 1.13 | 1.63 |
| CV | 1.08 | 1.10 | — |
| Max | 3 | 4 | +3 |
| Min | -1 | -1 | -4 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 18.18% | 3.03% | 12.12% | — | — | 39.39% |
| 1 | 12.12% | 3.03% | 3.03% | 3.03% | 3.03% | — | 24.24% |
| 2 | 3.03% | 6.06% | 6.06% | — | — | — | 15.15% |
| 3 | — | 6.06% | 6.06% | — | — | — | 12.12% |
| 4 | 3.03% | — | — | — | — | — | 3.03% |
| 5+ | — | — | — | — | — | 6.06% | 6.06% |
| Total | 24.24% | 33.33% | 18.18% | 15.15% | 3.03% | 6.06% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 0.97 | 1.21 | -0.24 |
| SD | 1.26 | 1.24 | 1.71 |
| CV | 1.30 | 1.03 | — |
| Max | 4 | 4 | +4 |
| Min | -1 | -1 | -3 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 6.06% | — | 3.03% | — | — | 15.15% |
| 1 | 12.12% | 12.12% | 3.03% | 6.06% | — | 3.03% | 36.36% |
| 2 | 15.15% | 6.06% | — | — | 3.03% | — | 24.24% |
| 3 | 12.12% | — | 3.03% | — | 3.03% | — | 18.18% |
| 4 | — | — | — | — | — | — | — |
| 5+ | — | — | — | — | — | 6.06% | 6.06% |
| Total | 45.45% | 24.24% | 6.06% | 9.09% | 6.06% | 9.09% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.33 | 0.97 | +0.36 |
| SD | 1.14 | 1.49 | 1.76 |
| CV | 0.85 | 1.54 | — |
| Max | 3 | 5 | +3 |
| Min | -1 | -1 | -4 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 3.03% | 6.06% | — | — | — | 15.15% |
| 1 | 18.18% | 9.09% | 6.06% | 3.03% | — | — | 36.36% |
| 2 | 9.09% | 3.03% | 3.03% | 3.03% | — | — | 18.18% |
| 3 | 3.03% | 6.06% | 3.03% | — | — | — | 12.12% |
| 4 | — | 3.03% | 6.06% | 3.03% | 3.03% | — | 15.15% |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 36.36% | 24.24% | 24.24% | 9.09% | 3.03% | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.67 | 1.09 | +0.58 |
| SD | 1.38 | 1.18 | 1.37 |
| CV | 0.83 | 1.08 | — |
| Max | 4 | 4 | +3 |
| Min | -1 | -1 | -2 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 15.15% | 15.15% | 3.03% | — | — | 39.39% |
| 1 | 6.06% | 6.06% | 9.09% | 9.09% | — | — | 30.30% |
| 2 | 3.03% | 9.09% | — | 6.06% | — | — | 18.18% |
| 3 | — | 3.03% | — | — | — | — | 3.03% |
| 4 | — | — | 3.03% | — | — | — | 3.03% |
| 5+ | — | 3.03% | — | — | — | 3.03% | 6.06% |
| Total | 15.15% | 36.36% | 27.27% | 18.18% | — | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.00 | 1.42 | -0.42 |
| SD | 1.27 | 1.06 | 1.56 |
| CV | 1.27 | 0.75 | — |
| Max | 5 | 3 | +4 |
| Min | -1 | -1 | -3 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 9.09% | 6.06% | — | — | — | 21.21% |
| 1 | 9.09% | 18.18% | 3.03% | — | — | — | 30.30% |
| 2 | 3.03% | 9.09% | 3.03% | — | — | — | 15.15% |
| 3 | 3.03% | 12.12% | 3.03% | — | — | — | 18.18% |
| 4 | — | 3.03% | — | — | — | — | 3.03% |
| 5+ | 3.03% | — | 3.03% | — | — | 6.06% | 12.12% |
| Total | 24.24% | 51.52% | 18.18% | — | — | 6.06% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.55 | 0.82 | +0.73 |
| SD | 1.62 | 0.81 | 1.59 |
| CV | 1.05 | 0.99 | — |
| Max | 6 | 2 | +5 |
| Min | -1 | -1 | -2 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 3.03% | 18.18% | 9.09% | 3.03% | — | — | 33.33% |
| 1 | 6.06% | 15.15% | 9.09% | 6.06% | — | — | 36.36% |
| 2 | 3.03% | 3.03% | 3.03% | 3.03% | 3.03% | — | 15.15% |
| 3 | — | 6.06% | 3.03% | — | 3.03% | — | 12.12% |
| 4 | — | — | — | — | — | — | — |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 12.12% | 42.42% | 24.24% | 12.12% | 6.06% | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.00 | 1.48 | -0.48 |
| SD | 1.06 | 1.15 | 1.28 |
| CV | 1.06 | 0.77 | — |
| Max | 3 | 4 | +2 |
| Min | -1 | -1 | -3 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 6.06% | 6.06% | 6.06% | — | — | 3.03% | 21.21% |
| 1 | 9.09% | 6.06% | 3.03% | 6.06% | — | — | 24.24% |
| 2 | 3.03% | 9.09% | 3.03% | 9.09% | — | — | 24.24% |
| 3 | 9.09% | 6.06% | — | — | 3.03% | — | 18.18% |
| 4 | — | — | 3.03% | 3.03% | — | — | 6.06% |
| 5+ | — | — | — | — | — | 6.06% | 6.06% |
| Total | 27.27% | 27.27% | 15.15% | 18.18% | 3.03% | 9.09% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.45 | 1.33 | +0.12 |
| SD | 1.35 | 1.45 | 1.75 |
| CV | 0.93 | 1.09 | — |
| Max | 4 | 5 | +3 |
| Min | -1 | -1 | -5 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 9.09% | 6.06% | 6.06% | 3.03% | — | — | 24.24% |
| 1 | 21.21% | 12.12% | 6.06% | 3.03% | — | — | 42.42% |
| 2 | 9.09% | 6.06% | 3.03% | 3.03% | — | — | 21.21% |
| 3 | — | — | 6.06% | — | — | — | 6.06% |
| 4 | — | — | 3.03% | — | — | — | 3.03% |
| 5+ | — | — | — | — | — | 3.03% | 3.03% |
| Total | 39.39% | 24.24% | 24.24% | 9.09% | — | 3.03% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 1.12 | 0.97 | +0.15 |
| SD | 1.05 | 1.07 | 1.28 |
| CV | 0.94 | 1.11 | — |
| Max | 4 | 3 | +2 |
| Min | -1 | -1 | -3 |
Games Played: 33
| ↓ Scored | Allowed → | 0 | 1 | 2 | 3 | 4 | 5+ | Total |
|---|---|---|---|---|---|---|---|
| 0 | 9.09% | 9.09% | 6.06% | — | — | — | 24.24% |
| 1 | — | 6.06% | 6.06% | 3.03% | — | — | 15.15% |
| 2 | — | — | 3.03% | — | 3.03% | — | 6.06% |
| 3 | 3.03% | — | 3.03% | — | — | — | 6.06% |
| 4 | — | — | — | — | 3.03% | — | 3.03% |
| 5+ | — | — | — | — | — | 45.45% | 45.45% |
| Total | 12.12% | 15.15% | 18.18% | 3.03% | 6.06% | 45.45% | 100% |
Summary Statistics
| Scored | Allowed | Difference | |
|---|---|---|---|
| Mean | 0.12 | 0.39 | -0.27 |
| SD | 1.39 | 1.58 | 0.94 |
| CV | 11.44 | 4.01 | — |
| Max | 4 | 4 | +3 |
| Min | -1 | -1 | -2 |
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 | Silkeborg | 63 | 51.64 | +11.36 |
| 2 | Lyngby | 64 | 55.15 | +8.85 |
| 3 | Vendsyssel | 56 | 48.37 | +7.63 |
| 4 | Horsens | 60 | 53.09 | +6.91 |
| 5 | Fredericia | 47 | 44.82 | +2.18 |
Biggest Disappointments
| # | Team | Actual | Sim | vsSim |
|---|---|---|---|---|
| 1 | Skive | 31 | 39.93 | -8.93 |
| 2 | Vestsjaelland | 13 | 20.11 | -7.11 |
| 3 | Naestved | 34 | 40.93 | -6.93 |
| 4 | Helsingor | 47 | 52.77 | -5.77 |
| 5 | FC Roskilde | 39 | 44.13 | -5.13 |
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 | HB Koge | 5 | Nov 8 – Mar 13 | 1 in 277 |
| 2 | Vendsyssel | 5 | Apr 24 – May 16 | 1 in 159 |
| 3 | Horsens | 5 | Aug 16 – Sep 20 | 1 in 91 |
| 4 | Silkeborg | 5 | Mar 28 – Apr 24 | 1 in 89 |
| 5 | Naestved | 2 | Nov 29 – Mar 13 | 1 in 20 |
Most Unlikely Losing Streaks
| # | Team | Games | Dates | Probability |
|---|---|---|---|---|
| 1 | Vestsjaelland | 16 | Nov 29 – May 28 | 1 in 1,245,719 |
| 2 | FC Roskilde | 6 | Oct 4 – Nov 13 | 1 in 112 |
| 3 | Vendsyssel | 4 | Nov 29 – Mar 17 | 1 in 74 |
| 4 | Naestved | 5 | Aug 2 – Aug 30 | 1 in 72 |
| 5 | HB Koge | 4 | Oct 18 – Nov 1 | 1 in 33 |
Most Unlikely Unbeaten Streaks
| # | Team | Games | Dates | Probability |
|---|---|---|---|---|
| 1 | Vendsyssel | 12 | Aug 30 – Nov 12 | 1 in 212 |
| 2 | Horsens | 9 | Aug 16 – Oct 9 | 1 in 84 |
| 3 | Fredericia | 7 | Jul 26 – Sep 10 | 1 in 42 |
| 4 | Silkeborg | 7 | Mar 20 – Apr 24 | 1 in 22 |
| 5 | Lyngby | 8 | Sep 18 – Nov 5 | 1 in 20 |
Most Unlikely Winless Streaks
| # | Team | Games | Dates | Probability |
|---|---|---|---|---|
| 1 | Vestsjaelland | 16 | Nov 29 – May 28 | 1 in 1,226 |
| 2 | Vendsyssel | 10 | Nov 12 – Apr 20 | 1 in 179 |
| 3 | FC Roskilde | 9 | Sep 18 – Nov 18 | 1 in 52 |
| 4 | Fredericia | 6 | Sep 10 – Oct 14 | 1 in 25 |
| 5 | Naestved | 6 | Aug 2 – Sep 6 | 1 in 15 |
Finish Position Heatmap
Each cell is the probability — across 100,000 simulations — that the team (row) finished at that position (column). Rows are sorted by actual finish (champion at top, bottom of the table at the bottom).
| Team | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Lyngby | 27.27% | 18.01% | 14.69% | 11.12% | 8.91% | 7.27% | 4.98% | 3.35% | 2.43% | 1.42% | 0.55% | — |
| Silkeborg | 13.75% | 14.12% | 13.74% | 12.49% | 11.70% | 9.52% | 8.62% | 6.54% | 4.77% | 3.17% | 1.56% | 0.02% |
| Horsens | 17.07% | 16.54% | 14.01% | 13.00% | 10.37% | 9.02% | 7.41% | 5.13% | 3.93% | 2.41% | 1.10% | 0.01% |
| Vendsyssel | 6.46% | 9.05% | 9.45% | 10.56% | 11.20% | 11.57% | 10.93% | 10.43% | 8.80% | 6.92% | 4.54% | 0.09% |
| Vejle BK | 12.88% | 13.63% | 13.44% | 12.75% | 11.90% | 10.45% | 8.27% | 6.72% | 5.02% | 3.35% | 1.58% | 0.01% |
| Fredericia | 2.18% | 4.03% | 5.89% | 7.27% | 9.04% | 10.53% | 11.53% | 13.01% | 13.22% | 12.62% | 10.32% | 0.36% |
| Helsingor | 15.04% | 15.11% | 14.30% | 12.25% | 11.21% | 9.23% | 8.04% | 5.97% | 4.28% | 3.08% | 1.48% | 0.01% |
| HB Koge | 2.30% | 3.68% | 5.67% | 7.29% | 8.84% | 10.75% | 11.99% | 13.12% | 13.53% | 12.34% | 10.12% | 0.37% |
| FC Roskilde | 1.91% | 3.28% | 4.85% | 6.66% | 7.87% | 9.70% | 11.54% | 12.52% | 13.74% | 14.26% | 13.18% | 0.49% |
| Naestved | 0.67% | 1.59% | 2.08% | 3.76% | 5.08% | 6.14% | 8.67% | 12.27% | 15.31% | 19.40% | 23.69% | 1.34% |
| Skive | 0.47% | 0.96% | 1.88% | 2.85% | 3.88% | 5.82% | 8.02% | 10.94% | 14.90% | 20.53% | 28.18% | 1.57% |
| Vestsjaelland | — | — | — | — | — | — | — | — | 0.07% | 0.50% | 3.70% | 95.73% |
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
+4.04%
No Edge
41.41%21.21%37.37%
Elo Value
Home Edge: 12.29 Elo pts.
354 Elo
0.003 goals per Elo point
01000
Scoring Tilt
Expected
+0.09 goals
Neutral
-2+0.03+2
Title Race
How these are measured
The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.
- Title-Race Openness
- Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.One-Team Race: under 2 * Top-Heavy: 2 to 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
6.0
Open
124610
Champion Preseason Odds
27%
Lyngby, 1st of 12
LongshotFavorite
Title Margin
Expected
0.03/gm
Photo Finish
00.140.5/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 5.77 * Some Luck: 5.77 to 8.66 * Lucky: 8.66 to 11.55 * Wild Swing: 11.55 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 1.68 * Close: 1.68 to 2.52 * Off: 2.52 to 3.36 * Way Off: 3.36 and up.
- Biggest Overachiever
- The team that finished highest inside its own range of simulated outcomes. The gold line is where the top team in a league of 12 typically lands.
- Biggest Underachiever
- The team that finished lowest inside its own range of simulated outcomes. The gold line is where the bottom team in a league of 12 typically lands.
- Season Outliers
- Number of teams that finished above the 95th or below the 5th percentile of their own simulated range. Even a well-calibrated model expects about 10% of teams in the extremes.Minimal Outliers: under 12 * As Expected: 12 to 19.2 * Several Outliers: 19.2 to 26.4 * Many Outliers: 26.4 and up.
- Unexpected Relegations
- Number of teams that were actually relegated but were not in the model's projected bottom field of the same size. The gold line is how many the model expected to miss on average.As Expected: under 0.5 * A Surprise: 0.5 to 0.8 * Several Surprises: 0.8 to 1.1 * Many Surprises: 1.1 and up.
Luck Spread
Expected
7.52 points
Some Luck
07.2218
Average Finish Error
Expected
1.17
Pinpoint
02.105
Biggest Overachiever
Expected 95.83%
95.11%
Silkeborg
50100
Biggest Underachiever
Expected 4.17%
1.19%
Vestsjaelland
050
Season Outliers
Expected
2 of 12
Minimal Outliers
01.26
Unexpected Relegations
Expected 0.0
0 of 1
As Expected
01
Parity
How these are measured
The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.
- Gini Index
- How evenly points were spread across the league. Lower means a tight, balanced table; higher means a few teams ran off with most of the points.Balanced: under 0.12 * Even: 0.12 to 0.18 * Top-Heavy: 0.18 to 0.26 * Lopsided: 0.26 and up.
- Noll-Scully
- How much more spread out the table was than a league where every match is a coin flip. The gold line at 1 is that coin-flip baseline. Above it, real talent gaps stretched the table; below it, the league was tighter than luck alone would produce.Coin-Flip Parity: under 1 * Moderate Separation: 1 to 1.6 * Strong Separation: 1.6 to 2.2 * Wide Separation: 2.2 and up.
- Interquartile Edge
- Chance the team at the 75th percentile of Elo would beat the team at the 25th percentile on a neutral field. Higher means a bigger gap between the upper and lower half of the table.Even: under 60% * Slight Edge: 60% to 70% * Clear Edge: 70% to 80% * Wide Edge: 80% and up.
- Best vs. Worst
- Chance the top-rated team would beat the bottom-rated team on a neutral field. The gold line is how large that gap tends to be in a league of this size; a dot to the right flags an unusually dominant or unusually weak team.Even: under 70% * Clear Edge: 70% to 82% * Strong Edge: 82% to 92% * Dominant: 92% and up.
- Close Games
- Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.Few: under 30% * Some Drama: 30% to 40% * Frequent: 40% to 50% * Very Frequent: 50% and up.
- Blowouts
- Share of matches decided by 3 goals or more. The gold line is how many routs the matchups and the scoring model predict.Rare: under 8% * Occasional: 8% to 14% * Frequent: 14% to 22% * Very Frequent: 22% and up.
Gini Index
0.17
Even
00.120.180.260.5
Noll-Scully
Coin-flip
1.74
Strong Separation
01.003
Interquartile Edge
59%
Even
50%60%70%80%100%
Best vs. Worst
Baseline
77%
Clear Edge
50%77%100%
Close Games
Expected
68%
Very Frequent
0%67%100%
Blowouts
Expected
10%
Occasional
0%11%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
00.632
Matchup Imbalance
0.21
Notable Separation
00.10.180.280.5
Strangeness
Expected
1.24
Wilder Than Modeled
01.002
Repeatability
0.08
Weak Carryover
00.30.60.851
Upset Rate
Expected
37%
Upset-Prone
0%31%50%
Clear Favorite Upset Rate
Expected
30%
Shaky Favorites
0%27%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 0.11 * Near Noise Ceiling: 0.11 to 0.16 * Above Noise: 0.16 to 0.21 * Well Above Noise: 0.21 and up.
Probability calibration
0.80
Excellent
0.010.050.10.51
Calibration slope
Ideal
0.75
Overconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.095
Well Within Noise
00.1070.25
Next-Season Status
Across 100,000 regular-season simulations, the probability of each team's next-season status. Columns appear in best-to-worst outcome order: promotion-positive on the left, relegation-positive on the right. Cells with darker shading indicate higher likelihood.
| Team | Direct promotion | Same level | Direct relegation |
|---|---|---|---|
| Lyngby | 59.97% | 40.03% | — |
| Horsens | 47.62% | 52.37% | 0.01% |
| Helsingor | 44.45% | 55.54% | 0.01% |
| Silkeborg | 41.61% | 58.37% | 0.02% |
| Vejle BK | 39.95% | 60.04% | 0.01% |
| Vendsyssel | 24.96% | 74.95% | 0.09% |
| Fredericia | 12.10% | 87.54% | 0.36% |
| HB Koge | 11.65% | 87.98% | 0.37% |
| FC Roskilde | 10.04% | 89.47% | 0.49% |
| Naestved | 4.34% | 94.32% | 1.34% |
| Skive | 3.31% | 95.12% | 1.57% |
| Vestsjaelland | — | 4.27% | 95.73% |
Overall Game Log
Summary of every completed game this season. Sort any column by clicking its header.
| Date | Opponent | Score | Pre Elo | Opp Elo | Win % | Tie % | Loss % | Elo Δ | Points |
|---|---|---|---|---|---|---|---|---|---|
| 2015-07-23 | HB Koge | W 1-0 | 1383 | 1372 | 46.76% | 22.26% | 30.98% | +6.2 | 3 |
| 2015-07-23 | @ Lyngby | L 0-1 | 1372 | 1383 | 30.98% | 22.26% | 46.76% | -6.2 | 0 |
| 2015-07-25 | Vestsjaelland | W 2-1 | 1381 | 1419 | 39.95% | 22.50% | 37.55% | +6.8 | 3 |
| 2015-07-25 | @ Silkeborg | L 1-2 | 1419 | 1381 | 37.55% | 22.50% | 39.95% | -6.8 | 0 |
| 2015-07-26 | Fredericia | D 1-1 | 1363 | 1334 | 49.04% | 22.10% | 28.87% | -0.8 | 1 |
| 2015-07-26 | @ Vejle BK | D 1-1 | 1334 | 1363 | 28.87% | 22.10% | 49.04% | +0.8 | 1 |
| 2015-07-26 | Helsingor | W 3-0 | 1366 | 1449 | 33.59% | 22.40% | 44.01% | +22.4 | 3 |
| 2015-07-26 | @ FC Roskilde | L 0-3 | 1449 | 1366 | 44.01% | 22.40% | 33.59% | -22.4 | 0 |
| 2015-07-26 | Horsens | W 2-1 | 1369 | 1368 | 45.32% | 22.34% | 32.34% | +6.0 | 3 |
| 2015-07-26 | @ Naestved | L 1-2 | 1368 | 1369 | 32.34% | 22.34% | 45.32% | -6.1 | 0 |
| 2015-07-26 | Vendsyssel | L 0-2 | 1357 | 1358 | 45.00% | 22.36% | 32.64% | -15.7 | 0 |
| 2015-07-26 | @ Skive | W 2-0 | 1358 | 1357 | 32.64% | 22.36% | 45.00% | +15.7 | 3 |
| 2015-08-01 | Vejle BK | D 2-2 | 1412 | 1362 | 51.77% | 21.84% | 26.39% | -0.8 | 1 |
| 2015-08-01 | @ Vestsjaelland | D 2-2 | 1362 | 1412 | 26.39% | 21.84% | 51.77% | +0.8 | 2 |
| 2015-08-02 | FC Roskilde | W 4-0 | 1335 | 1389 | 37.58% | 22.50% | 39.92% | +27.1 | 4 |
| 2015-08-02 | @ Fredericia | L 0-4 | 1389 | 1335 | 39.92% | 22.50% | 37.58% | -27.1 | 3 |
| 2015-08-02 | Lyngby | L 2-4 | 1362 | 1390 | 41.39% | 22.48% | 36.13% | -11.4 | 0 |
| 2015-08-02 | @ Horsens | W 4-2 | 1390 | 1362 | 36.13% | 22.48% | 41.39% | +11.4 | 6 |
| 2015-08-02 | Naestved | W 2-1 | 1427 | 1375 | 51.98% | 21.82% | 26.21% | +5.1 | 3 |
| 2015-08-02 | @ Helsingor | L 1-2 | 1375 | 1427 | 26.21% | 21.82% | 51.98% | -5.1 | 3 |
| 2015-08-02 | Silkeborg | D 1-1 | 1374 | 1388 | 43.25% | 22.43% | 34.32% | -0.4 | 4 |
| 2015-08-02 | @ Vendsyssel | D 1-1 | 1388 | 1374 | 34.32% | 22.43% | 43.25% | +0.3 | 4 |
| 2015-08-02 | Skive | D 1-1 | 1366 | 1341 | 48.49% | 22.14% | 29.36% | -0.8 | 1 |
| 2015-08-02 | @ HB Koge | D 1-1 | 1341 | 1366 | 29.36% | 22.14% | 48.49% | +0.8 | 1 |
| 2015-08-07 | HB Koge | W 1-0 | 1362 | 1365 | 44.76% | 22.37% | 32.88% | +6.5 | 6 |
| 2015-08-07 | @ FC Roskilde | L 0-1 | 1365 | 1362 | 32.88% | 22.37% | 44.76% | -6.5 | 1 |
| 2015-08-07 | Horsens | W 3-0 | 1362 | 1351 | 46.79% | 22.26% | 30.95% | +16.9 | 5 |
| 2015-08-07 | @ Vejle BK | L 0-3 | 1351 | 1362 | 30.95% | 22.26% | 46.79% | -16.9 | 0 |
| 2015-08-07 | Vestsjaelland | W 3-1 | 1342 | 1411 | 35.44% | 22.46% | 42.09% | +12.9 | 4 |
| 2015-08-07 | @ Skive | L 1-3 | 1411 | 1342 | 42.09% | 22.46% | 35.44% | -12.9 | 1 |
| 2015-08-09 | Helsingor | W 1-0 | 1362 | 1432 | 35.32% | 22.46% | 42.22% | +7.9 | 7 |
| 2015-08-09 | @ Fredericia | L 0-1 | 1432 | 1362 | 42.22% | 22.46% | 35.32% | -7.9 | 3 |
| 2015-08-09 | Silkeborg | W 1-0 | 1401 | 1388 | 46.89% | 22.25% | 30.85% | +6.2 | 9 |
| 2015-08-09 | @ Lyngby | L 0-1 | 1388 | 1401 | 30.85% | 22.25% | 46.89% | -6.2 | 4 |
| 2015-08-09 | Vendsyssel | L 0-1 | 1370 | 1374 | 44.72% | 22.37% | 32.91% | -8.3 | 3 |
| 2015-08-09 | @ Naestved | W 1-0 | 1374 | 1370 | 32.91% | 22.37% | 44.72% | +8.3 | 7 |
| 2015-08-15 | Fredericia | D 0-0 | 1398 | 1370 | 49.02% | 22.10% | 28.88% | -0.9 | 2 |
| 2015-08-15 | @ Vestsjaelland | D 0-0 | 1370 | 1398 | 28.88% | 22.10% | 49.02% | +0.9 | 8 |
| 2015-08-16 | FC Roskilde | W 1-0 | 1334 | 1368 | 40.42% | 22.49% | 37.09% | +7.2 | 3 |
| 2015-08-16 | @ Horsens | L 0-1 | 1368 | 1334 | 37.09% | 22.49% | 40.42% | -7.1 | 6 |
| 2015-08-16 | Lyngby | W 2-1 | 1382 | 1407 | 41.70% | 22.47% | 35.83% | +6.6 | 10 |
| 2015-08-16 | @ Vendsyssel | L 1-2 | 1407 | 1382 | 35.83% | 22.47% | 41.70% | -6.6 | 9 |
| 2015-08-16 | Naestved | W 2-0 | 1358 | 1362 | 44.73% | 22.37% | 32.90% | +12.2 | 4 |
| 2015-08-16 | @ HB Koge | L 0-2 | 1362 | 1358 | 32.90% | 22.37% | 44.73% | -12.2 | 3 |
| 2015-08-16 | Skive | W 2-1 | 1382 | 1355 | 48.88% | 22.11% | 29.01% | +5.5 | 7 |
| 2015-08-16 | @ Silkeborg | L 1-2 | 1355 | 1382 | 29.01% | 22.11% | 48.88% | -5.5 | 4 |
| 2015-08-16 | Vejle BK | W 3-1 | 1424 | 1379 | 51.07% | 21.91% | 27.01% | +9.0 | 6 |
| 2015-08-16 | @ Helsingor | L 1-3 | 1379 | 1424 | 27.01% | 21.91% | 51.07% | -9.0 | 5 |
| 2015-08-19 | Silkeborg | W 2-0 | 1341 | 1388 | 38.63% | 22.50% | 38.87% | +14.0 | 6 |
| 2015-08-19 | @ Horsens | L 0-2 | 1388 | 1341 | 38.87% | 22.50% | 38.63% | -14.0 | 7 |
| 2015-08-20 | Naestved | W 1-0 | 1370 | 1349 | 48.01% | 22.18% | 29.81% | +6.0 | 8 |
| 2015-08-20 | @ Vejle BK | L 0-1 | 1349 | 1370 | 29.81% | 22.18% | 48.01% | -6.0 | 3 |
| 2015-08-23 | FC Roskilde | D 0-0 | 1397 | 1361 | 50.03% | 22.01% | 27.96% | -1.0 | 3 |
| 2015-08-23 | @ Vestsjaelland | D 0-0 | 1361 | 1397 | 27.96% | 22.01% | 50.03% | +1.0 | 7 |
| 2015-08-23 | Lyngby | W 3-1 | 1370 | 1400 | 41.02% | 22.48% | 36.50% | +11.5 | 11 |
| 2015-08-23 | @ Fredericia | L 1-3 | 1400 | 1370 | 36.50% | 22.48% | 41.02% | -11.5 | 9 |
| 2015-08-23 | Skive | W 1-0 | 1433 | 1349 | 55.85% | 21.31% | 22.84% | +4.8 | 9 |
| 2015-08-23 | @ Helsingor | L 0-1 | 1349 | 1433 | 22.84% | 21.31% | 55.85% | -4.8 | 4 |
| 2015-08-23 | Vendsyssel | W 2-0 | 1371 | 1388 | 42.74% | 22.44% | 34.82% | +12.8 | 7 |
| 2015-08-23 | @ HB Koge | L 0-2 | 1388 | 1371 | 34.82% | 22.44% | 42.74% | -12.8 | 10 |
| 2015-08-26 | HB Koge | D 0-0 | 1374 | 1383 | 43.87% | 22.41% | 33.73% | -0.4 | 8 |
| 2015-08-26 | @ Silkeborg | D 0-0 | 1383 | 1374 | 33.73% | 22.41% | 43.87% | +0.4 | 8 |
| 2015-08-28 | Helsingor | W 4-1 | 1389 | 1438 | 38.32% | 22.50% | 39.18% | +17.2 | 12 |
| 2015-08-28 | @ Lyngby | L 1-4 | 1438 | 1389 | 39.18% | 22.50% | 38.32% | -17.2 | 9 |
| 2015-08-28 | Horsens | L 0-2 | 1344 | 1355 | 43.74% | 22.41% | 33.85% | -15.4 | 4 |
| 2015-08-28 | @ Skive | W 2-0 | 1355 | 1344 | 33.85% | 22.41% | 43.74% | +15.4 | 9 |
| 2015-08-30 | Fredericia | L 0-2 | 1343 | 1382 | 39.80% | 22.50% | 37.70% | -14.2 | 3 |
| 2015-08-30 | @ Naestved | W 2-0 | 1382 | 1343 | 37.70% | 22.50% | 39.80% | +14.2 | 14 |
| 2015-08-30 | Vestsjaelland | W 4-2 | 1376 | 1396 | 42.32% | 22.45% | 35.22% | +10.0 | 13 |
| 2015-08-30 | @ Vendsyssel | L 2-4 | 1396 | 1376 | 35.22% | 22.45% | 42.32% | -10.0 | 3 |
| 2015-08-30 | Vejle BK | L 1-2 | 1362 | 1376 | 43.20% | 22.43% | 34.37% | -7.6 | 7 |
| 2015-08-30 | @ FC Roskilde | W 2-1 | 1376 | 1362 | 34.37% | 22.43% | 43.20% | +7.6 | 11 |
| 2015-09-06 | FC Roskilde | D 1-1 | 1329 | 1354 | 41.72% | 22.47% | 35.81% | -0.2 | 4 |
| 2015-09-06 | @ Naestved | D 1-1 | 1354 | 1329 | 35.81% | 22.47% | 41.72% | +0.2 | 8 |
| 2015-09-06 | Vestsjaelland | W 2-1 | 1384 | 1386 | 44.86% | 22.36% | 32.77% | +6.1 | 11 |
| 2015-09-06 | @ HB Koge | L 1-2 | 1386 | 1384 | 32.77% | 22.36% | 44.86% | -6.1 | 3 |
| 2015-09-06 | Vejle BK | W 3-2 | 1406 | 1384 | 48.17% | 22.17% | 29.66% | +5.3 | 15 |
| 2015-09-06 | @ Lyngby | L 2-3 | 1384 | 1406 | 29.66% | 22.17% | 48.17% | -5.3 | 11 |
| 2015-09-07 | Helsingor | W 1-0 | 1373 | 1421 | 38.54% | 22.50% | 38.96% | +7.4 | 11 |
| 2015-09-07 | @ Silkeborg | L 0-1 | 1421 | 1373 | 38.96% | 22.50% | 38.54% | -7.4 | 9 |
| 2015-09-10 | Lyngby | W 2-0 | 1355 | 1412 | 37.17% | 22.49% | 40.34% | +14.4 | 11 |
| 2015-09-10 | @ FC Roskilde | L 0-2 | 1412 | 1355 | 40.34% | 22.49% | 37.17% | -14.4 | 15 |
| 2015-09-10 | Silkeborg | D 1-1 | 1396 | 1381 | 47.30% | 22.23% | 30.47% | -0.7 | 15 |
| 2015-09-10 | @ Fredericia | D 1-1 | 1381 | 1396 | 30.47% | 22.23% | 47.30% | +0.7 | 12 |
| 2015-09-13 | HB Koge | W 3-0 | 1370 | 1390 | 42.48% | 22.45% | 35.07% | +18.7 | 12 |
| 2015-09-13 | @ Horsens | L 0-3 | 1390 | 1370 | 35.07% | 22.45% | 42.48% | -18.7 | 11 |
| 2015-09-13 | Naestved | L 0-2 | 1380 | 1329 | 51.90% | 21.83% | 26.28% | -17.8 | 3 |
| 2015-09-13 | @ Vestsjaelland | W 2-0 | 1329 | 1380 | 26.28% | 21.83% | 51.90% | +17.8 | 7 |
| 2015-09-13 | Skive | W 3-1 | 1379 | 1329 | 51.71% | 21.85% | 26.44% | +8.8 | 14 |
| 2015-09-13 | @ Vejle BK | L 1-3 | 1329 | 1379 | 26.44% | 21.85% | 51.71% | -8.8 | 4 |
| 2015-09-13 | Vendsyssel | D 2-2 | 1413 | 1386 | 48.88% | 22.11% | 29.01% | -0.6 | 10 |
| 2015-09-13 | @ Helsingor | D 2-2 | 1386 | 1413 | 29.01% | 22.11% | 48.88% | +0.6 | 14 |
| 2015-09-17 | Vejle BK | L 0-2 | 1381 | 1388 | 44.36% | 22.39% | 33.26% | -15.5 | 12 |
| 2015-09-17 | @ Silkeborg | W 2-0 | 1388 | 1381 | 33.26% | 22.39% | 44.36% | +15.5 | 17 |
| 2015-09-18 | FC Roskilde | D 1-1 | 1320 | 1369 | 38.34% | 22.50% | 39.16% | +0.0 | 5 |
| 2015-09-18 | @ Skive | D 1-1 | 1369 | 1320 | 39.16% | 22.50% | 38.34% | -0.0 | 12 |
| 2015-09-18 | Fredericia | W 3-2 | 1386 | 1396 | 43.90% | 22.40% | 33.69% | +5.9 | 17 |
| 2015-09-18 | @ Vendsyssel | L 2-3 | 1396 | 1386 | 33.69% | 22.40% | 43.90% | -5.9 | 15 |
| 2015-09-18 | Naestved | W 3-1 | 1397 | 1347 | 51.79% | 21.84% | 26.37% | +8.8 | 18 |
| 2015-09-18 | @ Lyngby | L 1-3 | 1347 | 1397 | 26.37% | 21.84% | 51.79% | -8.8 | 7 |
| 2015-09-20 | Helsingor | L 0-4 | 1371 | 1413 | 39.40% | 22.50% | 38.10% | -26.8 | 11 |
| 2015-09-20 | @ HB Koge | W 4-0 | 1413 | 1371 | 38.10% | 22.50% | 39.40% | +26.8 | 13 |
| 2015-09-20 | Vestsjaelland | W 1-0 | 1389 | 1362 | 48.75% | 22.12% | 29.12% | +5.9 | 15 |
| 2015-09-20 | @ Horsens | L 0-1 | 1362 | 1389 | 29.12% | 22.12% | 48.75% | -5.9 | 3 |
| 2015-09-26 | Vendsyssel | D 1-1 | 1403 | 1392 | 46.68% | 22.27% | 31.05% | -0.6 | 18 |
| 2015-09-26 | @ Vejle BK | D 1-1 | 1392 | 1403 | 31.05% | 22.27% | 46.68% | +0.6 | 18 |
| 2015-09-27 | HB Koge | D 0-0 | 1390 | 1344 | 51.15% | 21.90% | 26.94% | -1.1 | 16 |
| 2015-09-27 | @ Fredericia | D 0-0 | 1344 | 1390 | 26.94% | 21.90% | 51.15% | +1.1 | 12 |
| 2015-09-27 | Horsens | D 1-1 | 1439 | 1395 | 51.05% | 21.91% | 27.03% | -1.0 | 14 |
| 2015-09-27 | @ Helsingor | D 1-1 | 1395 | 1439 | 27.03% | 21.91% | 51.05% | +1.0 | 16 |
| 2015-09-27 | Lyngby | D 1-1 | 1357 | 1406 | 38.25% | 22.50% | 39.25% | +0.0 | 4 |
| 2015-09-27 | @ Vestsjaelland | D 1-1 | 1406 | 1357 | 39.25% | 22.50% | 38.25% | -0.0 | 19 |
| 2015-09-27 | Silkeborg | D 2-2 | 1369 | 1366 | 45.62% | 22.33% | 32.06% | -0.4 | 13 |
| 2015-09-27 | @ FC Roskilde | D 2-2 | 1366 | 1369 | 32.06% | 22.33% | 45.62% | +0.4 | 13 |
| 2015-09-27 | Skive | L 0-1 | 1338 | 1320 | 47.59% | 22.21% | 30.20% | -8.7 | 7 |
| 2015-09-27 | @ Naestved | W 1-0 | 1320 | 1338 | 30.20% | 22.21% | 47.59% | +8.7 | 8 |
| 2015-09-30 | Fredericia | W 2-0 | 1329 | 1389 | 36.79% | 22.49% | 40.72% | +14.5 | 11 |
| 2015-09-30 | @ Skive | L 0-2 | 1389 | 1329 | 40.72% | 22.49% | 36.79% | -14.5 | 16 |
| 2015-09-30 | Horsens | D 1-1 | 1393 | 1396 | 44.77% | 22.37% | 32.86% | -0.5 | 19 |
| 2015-09-30 | @ Vendsyssel | D 1-1 | 1396 | 1393 | 32.86% | 22.37% | 44.77% | +0.5 | 17 |
| 2015-10-03 | Fredericia | D 1-1 | 1396 | 1374 | 48.19% | 22.16% | 29.65% | -0.7 | 18 |
| 2015-10-03 | @ Horsens | D 1-1 | 1374 | 1396 | 29.65% | 22.16% | 48.19% | +0.7 | 17 |
| 2015-10-04 | FC Roskilde | W 1-0 | 1392 | 1368 | 48.38% | 22.15% | 29.47% | +5.9 | 22 |
| 2015-10-04 | @ Vendsyssel | L 0-1 | 1368 | 1392 | 29.47% | 22.15% | 48.38% | -5.9 | 13 |
| 2015-10-04 | HB Koge | L 0-1 | 1402 | 1345 | 52.61% | 21.74% | 25.65% | -9.5 | 18 |
| 2015-10-04 | @ Vejle BK | W 1-0 | 1345 | 1402 | 25.65% | 21.74% | 52.61% | +9.5 | 15 |
| 2015-10-04 | Helsingor | W 3-0 | 1357 | 1438 | 33.76% | 22.41% | 43.83% | +22.4 | 7 |
| 2015-10-04 | @ Vestsjaelland | L 0-3 | 1438 | 1357 | 43.83% | 22.41% | 33.76% | -22.4 | 14 |
| 2015-10-04 | Skive | W 1-0 | 1406 | 1343 | 53.29% | 21.66% | 25.05% | +5.2 | 22 |
| 2015-10-04 | @ Lyngby | L 0-1 | 1343 | 1406 | 25.05% | 21.66% | 53.29% | -5.2 | 11 |
| 2015-10-05 | Naestved | D 1-1 | 1366 | 1329 | 50.11% | 22.01% | 27.89% | -0.9 | 14 |
| 2015-10-05 | @ Silkeborg | D 1-1 | 1329 | 1366 | 27.89% | 22.01% | 50.11% | +0.9 | 8 |
| 2015-10-09 | Horsens | L 0-2 | 1338 | 1396 | 37.12% | 22.49% | 40.39% | -13.5 | 11 |
| 2015-10-09 | @ Skive | W 2-0 | 1396 | 1338 | 40.39% | 22.49% | 37.12% | +13.5 | 21 |
| 2015-10-11 | Lyngby | L 0-1 | 1416 | 1411 | 45.88% | 22.31% | 31.81% | -8.5 | 14 |
| 2015-10-11 | @ Helsingor | W 1-0 | 1411 | 1416 | 31.81% | 22.31% | 45.88% | +8.5 | 25 |
| 2015-10-14 | Vejle BK | L 0-1 | 1375 | 1393 | 42.70% | 22.44% | 34.86% | -8.0 | 17 |
| 2015-10-14 | @ Fredericia | W 1-0 | 1393 | 1375 | 34.86% | 22.44% | 42.70% | +8.0 | 21 |
| 2015-10-17 | Helsingor | D 0-0 | 1365 | 1408 | 39.27% | 22.50% | 38.23% | -0.0 | 15 |
| 2015-10-17 | @ Silkeborg | D 0-0 | 1408 | 1365 | 38.23% | 22.50% | 39.27% | +0.0 | 15 |
| 2015-10-18 | FC Roskilde | W 3-1 | 1420 | 1363 | 52.61% | 21.74% | 25.64% | +8.6 | 28 |
| 2015-10-18 | @ Lyngby | L 1-3 | 1363 | 1420 | 25.64% | 21.74% | 52.61% | -8.6 | 13 |
| 2015-10-18 | Fredericia | L 0-1 | 1379 | 1367 | 46.84% | 22.26% | 30.90% | -8.6 | 7 |
| 2015-10-18 | @ Vestsjaelland | W 1-0 | 1367 | 1379 | 30.90% | 22.26% | 46.84% | +8.6 | 20 |
| 2015-10-18 | HB Koge | W 1-0 | 1330 | 1355 | 41.74% | 22.47% | 35.79% | +7.0 | 11 |
| 2015-10-18 | @ Naestved | L 0-1 | 1355 | 1330 | 35.79% | 22.47% | 41.74% | -7.0 | 15 |
| 2015-10-18 | Skive | L 2-3 | 1401 | 1325 | 54.93% | 21.45% | 23.63% | -8.9 | 21 |
| 2015-10-18 | @ Vejle BK | W 3-2 | 1325 | 1401 | 23.63% | 21.45% | 54.93% | +8.8 | 14 |
| 2015-10-18 | Vendsyssel | L 0-1 | 1409 | 1398 | 46.68% | 22.27% | 31.06% | -8.6 | 21 |
| 2015-10-18 | @ Horsens | W 1-0 | 1398 | 1409 | 31.06% | 22.27% | 46.68% | +8.6 | 25 |
| 2015-10-21 | Silkeborg | L 1-2 | 1348 | 1365 | 42.82% | 22.44% | 34.74% | -7.5 | 15 |
| 2015-10-21 | @ HB Koge | W 2-1 | 1365 | 1348 | 34.74% | 22.44% | 42.82% | +7.5 | 18 |
| 2015-10-22 | Vestsjaelland | D 4-4 | 1428 | 1370 | 52.72% | 21.73% | 25.55% | -0.6 | 29 |
| 2015-10-22 | @ Lyngby | D 4-4 | 1370 | 1428 | 25.55% | 21.73% | 52.72% | +0.6 | 8 |
| 2015-10-22 | Vejle BK | W 2-0 | 1407 | 1392 | 47.19% | 22.23% | 30.58% | +11.5 | 28 |
| 2015-10-22 | @ Vendsyssel | L 0-2 | 1392 | 1407 | 30.58% | 22.23% | 47.19% | -11.5 | 21 |
| 2015-10-23 | Fredericia | L 1-2 | 1334 | 1375 | 39.33% | 22.50% | 38.17% | -7.0 | 14 |
| 2015-10-23 | @ Skive | W 2-1 | 1375 | 1334 | 38.17% | 22.50% | 39.33% | +7.0 | 23 |
| 2015-10-25 | Horsens | L 0-1 | 1341 | 1400 | 36.75% | 22.49% | 40.77% | -7.1 | 15 |
| 2015-10-25 | @ HB Koge | W 1-0 | 1400 | 1341 | 40.77% | 22.49% | 36.75% | +7.1 | 24 |
| 2015-10-25 | Naestved | W 1-0 | 1408 | 1337 | 54.27% | 21.54% | 24.19% | +5.0 | 18 |
| 2015-10-25 | @ Helsingor | L 0-1 | 1337 | 1408 | 24.19% | 21.54% | 54.27% | -5.0 | 11 |
| 2015-10-25 | Silkeborg | L 2-3 | 1354 | 1373 | 42.59% | 22.45% | 34.97% | -7.1 | 13 |
| 2015-10-25 | @ FC Roskilde | W 3-2 | 1373 | 1354 | 34.97% | 22.45% | 42.59% | +7.1 | 21 |
| 2015-10-28 | Naestved | D 0-0 | 1418 | 1332 | 56.12% | 21.27% | 22.61% | -1.5 | 29 |
| 2015-10-28 | @ Vendsyssel | D 0-0 | 1332 | 1418 | 22.61% | 21.27% | 56.12% | +1.5 | 12 |
| 2015-10-31 | Lyngby | L 1-2 | 1380 | 1428 | 38.51% | 22.50% | 38.99% | -6.9 | 21 |
| 2015-10-31 | @ Silkeborg | W 2-1 | 1428 | 1380 | 38.99% | 22.50% | 38.51% | +6.9 | 32 |
| 2015-11-01 | FC Roskilde | W 2-1 | 1334 | 1347 | 43.38% | 22.42% | 34.20% | +6.3 | 15 |
| 2015-11-01 | @ Naestved | L 1-2 | 1347 | 1334 | 34.20% | 22.42% | 43.38% | -6.3 | 13 |
| 2015-11-01 | HB Koge | W 3-1 | 1381 | 1333 | 51.38% | 21.88% | 26.74% | +8.9 | 24 |
| 2015-11-01 | @ Vejle BK | L 1-3 | 1333 | 1381 | 26.74% | 21.88% | 51.38% | -8.9 | 15 |
| 2015-11-01 | Helsingor | D 0-0 | 1408 | 1413 | 44.51% | 22.38% | 33.11% | -0.5 | 25 |
| 2015-11-01 | @ Horsens | D 0-0 | 1413 | 1408 | 33.11% | 22.38% | 44.51% | +0.5 | 19 |
| 2015-11-01 | Skive | L 0-1 | 1371 | 1327 | 51.04% | 21.92% | 27.04% | -9.3 | 8 |
| 2015-11-01 | @ Vestsjaelland | W 1-0 | 1327 | 1371 | 27.04% | 21.92% | 51.04% | +9.3 | 17 |
| 2015-11-01 | Vendsyssel | L 1-2 | 1382 | 1417 | 40.41% | 22.49% | 37.10% | -7.2 | 23 |
| 2015-11-01 | @ Fredericia | W 2-1 | 1417 | 1382 | 37.10% | 22.49% | 40.41% | +7.2 | 32 |
| 2015-11-05 | Naestved | W 2-0 | 1434 | 1340 | 57.07% | 21.12% | 21.81% | +8.6 | 35 |
| 2015-11-05 | @ Lyngby | L 0-2 | 1340 | 1434 | 21.81% | 21.12% | 57.07% | -8.6 | 15 |
| 2015-11-06 | Horsens | L 0-1 | 1340 | 1407 | 35.83% | 22.47% | 41.70% | -7.0 | 13 |
| 2015-11-06 | @ FC Roskilde | W 1-0 | 1407 | 1340 | 41.70% | 22.47% | 35.83% | +7.0 | 28 |
| 2015-11-08 | Fredericia | W 2-1 | 1324 | 1375 | 38.05% | 22.50% | 39.45% | +7.1 | 18 |
| 2015-11-08 | @ HB Koge | L 1-2 | 1375 | 1324 | 39.45% | 22.50% | 38.05% | -7.1 | 23 |
| 2015-11-08 | Skive | W 1-0 | 1424 | 1336 | 56.33% | 21.24% | 22.43% | +4.7 | 35 |
| 2015-11-08 | @ Vendsyssel | L 0-1 | 1336 | 1424 | 22.43% | 21.24% | 56.33% | -4.7 | 17 |
| 2015-11-08 | Vejle BK | L 0-3 | 1413 | 1389 | 48.38% | 22.15% | 29.47% | -24.3 | 19 |
| 2015-11-08 | @ Helsingor | W 3-0 | 1389 | 1413 | 29.47% | 22.15% | 48.38% | +24.3 | 27 |
| 2015-11-12 | Vendsyssel | D 0-0 | 1362 | 1429 | 35.77% | 22.47% | 41.76% | +0.3 | 9 |
| 2015-11-12 | @ Vestsjaelland | D 0-0 | 1429 | 1362 | 41.76% | 22.47% | 35.77% | -0.3 | 36 |
| 2015-11-13 | FC Roskilde | W 4-2 | 1414 | 1334 | 55.40% | 21.38% | 23.22% | +7.0 | 30 |
| 2015-11-13 | @ Vejle BK | L 2-4 | 1334 | 1414 | 23.22% | 21.38% | 55.40% | -7.0 | 13 |
| 2015-11-15 | Helsingor | D 2-2 | 1368 | 1389 | 42.34% | 22.45% | 35.21% | -0.2 | 24 |
| 2015-11-15 | @ Fredericia | D 2-2 | 1389 | 1368 | 35.21% | 22.45% | 42.34% | +0.2 | 20 |
| 2015-11-15 | Silkeborg | L 1-3 | 1331 | 1373 | 39.35% | 22.50% | 38.15% | -12.2 | 15 |
| 2015-11-15 | @ Naestved | W 3-1 | 1373 | 1331 | 38.15% | 22.50% | 39.35% | +12.2 | 24 |
| 2015-11-16 | Lyngby | W 2-1 | 1414 | 1443 | 41.16% | 22.48% | 36.36% | +6.6 | 31 |
| 2015-11-16 | @ Horsens | L 1-2 | 1443 | 1414 | 36.36% | 22.48% | 41.16% | -6.6 | 35 |
| 2015-11-18 | Vestsjaelland | D 1-1 | 1326 | 1362 | 40.25% | 22.49% | 37.26% | -0.1 | 14 |
| 2015-11-18 | @ FC Roskilde | D 1-1 | 1362 | 1326 | 37.26% | 22.49% | 40.25% | +0.1 | 10 |
| 2015-11-19 | Vejle BK | W 1-0 | 1436 | 1421 | 47.32% | 22.23% | 30.46% | +6.1 | 38 |
| 2015-11-19 | @ Lyngby | L 0-1 | 1421 | 1436 | 30.46% | 22.23% | 47.32% | -6.1 | 30 |
| 2015-11-22 | Vestsjaelland | L 2-3 | 1319 | 1362 | 39.17% | 22.50% | 38.33% | -6.7 | 15 |
| 2015-11-22 | @ Naestved | W 3-2 | 1362 | 1319 | 38.33% | 22.50% | 39.17% | +6.7 | 13 |
| 2015-11-25 | HB Koge | L 0-1 | 1331 | 1332 | 45.14% | 22.35% | 32.51% | -8.4 | 17 |
| 2015-11-25 | @ Skive | W 1-0 | 1332 | 1331 | 32.51% | 22.35% | 45.14% | +8.4 | 21 |
| 2015-11-28 | Silkeborg | L 1-3 | 1415 | 1385 | 49.12% | 22.09% | 28.79% | -14.7 | 30 |
| 2015-11-28 | @ Vejle BK | W 3-1 | 1385 | 1415 | 28.79% | 22.09% | 49.12% | +14.7 | 27 |
| 2015-11-29 | FC Roskilde | L 0-1 | 1323 | 1326 | 44.71% | 22.37% | 32.92% | -8.3 | 17 |
| 2015-11-29 | @ Skive | W 1-0 | 1326 | 1323 | 32.92% | 22.37% | 44.71% | +8.3 | 17 |
| 2015-11-29 | HB Koge | L 0-2 | 1369 | 1340 | 49.04% | 22.10% | 28.86% | -16.9 | 13 |
| 2015-11-29 | @ Vestsjaelland | W 2-0 | 1340 | 1369 | 28.86% | 22.10% | 49.04% | +16.9 | 24 |
| 2015-11-29 | Helsingor | L 2-3 | 1428 | 1389 | 50.40% | 21.98% | 27.62% | -8.2 | 36 |
| 2015-11-29 | @ Vendsyssel | W 3-2 | 1389 | 1428 | 27.62% | 21.98% | 50.40% | +8.2 | 23 |
| 2015-11-29 | Lyngby | L 2-4 | 1368 | 1443 | 34.74% | 22.44% | 42.82% | -9.9 | 24 |
| 2015-11-29 | @ Fredericia | W 4-2 | 1443 | 1368 | 42.82% | 22.44% | 34.74% | +9.9 | 41 |
| 2015-11-29 | Naestved | L 1-3 | 1421 | 1312 | 58.60% | 20.85% | 20.55% | -17.1 | 31 |
| 2015-11-29 | @ Horsens | W 3-1 | 1312 | 1421 | 20.55% | 20.85% | 58.60% | +17.1 | 18 |
| 2015-12-03 | Fredericia | D 4-4 | 1335 | 1358 | 41.95% | 22.46% | 35.59% | -0.1 | 18 |
| 2015-12-03 | @ FC Roskilde | D 4-4 | 1358 | 1335 | 35.59% | 22.46% | 41.95% | +0.1 | 25 |
| 2015-12-03 | Horsens | D 1-1 | 1400 | 1404 | 44.70% | 22.37% | 32.93% | -0.5 | 28 |
| 2015-12-03 | @ Silkeborg | D 1-1 | 1404 | 1400 | 32.93% | 22.37% | 44.70% | +0.5 | 32 |
| 2016-03-06 | Skive | W 2-1 | 1397 | 1314 | 55.71% | 21.33% | 22.96% | +4.5 | 26 |
| 2016-03-06 | @ Helsingor | L 1-2 | 1314 | 1397 | 22.96% | 21.33% | 55.71% | -4.5 | 17 |
| 2016-03-06 | Vendsyssel | W 1-0 | 1357 | 1420 | 36.28% | 22.48% | 41.24% | +7.8 | 27 |
| 2016-03-06 | @ HB Koge | L 0-1 | 1420 | 1357 | 41.24% | 22.48% | 36.28% | -7.8 | 36 |
| 2016-03-10 | Vestsjaelland | FW | 1399 | 1352 | 51.45% | 21.87% | 26.67% | +0.0 | 31 |
| 2016-03-10 | @ Silkeborg | FL | 1352 | 1399 | 26.67% | 21.87% | 51.45% | +0.0 | 13 |
| 2016-03-10 | Fredericia | L 0-1 | 1399 | 1358 | 50.64% | 21.95% | 27.41% | -9.2 | 31 |
| 2016-03-10 | @ Silkeborg | W 1-0 | 1358 | 1399 | 27.41% | 21.95% | 50.64% | +9.2 | 28 |
| 2016-03-13 | Vestsjaelland | FW | 1404 | 1352 | 52.03% | 21.81% | 26.16% | +0.0 | 35 |
| 2016-03-13 | @ Horsens | FL | 1352 | 1404 | 26.16% | 21.81% | 52.03% | +0.0 | 13 |
| 2016-03-13 | HB Koge | L 1-3 | 1402 | 1365 | 50.13% | 22.00% | 27.87% | -14.9 | 26 |
| 2016-03-13 | @ Helsingor | W 3-1 | 1365 | 1402 | 27.87% | 22.00% | 50.13% | +14.9 | 30 |
| 2016-03-13 | Naestved | L 1-2 | 1400 | 1330 | 54.25% | 21.54% | 24.21% | -9.2 | 30 |
| 2016-03-13 | @ Vejle BK | W 2-1 | 1330 | 1400 | 24.21% | 21.54% | 54.25% | +9.2 | 21 |
| 2016-03-13 | Skive | D 1-1 | 1452 | 1310 | 62.23% | 20.09% | 17.68% | -1.9 | 42 |
| 2016-03-13 | @ Lyngby | D 1-1 | 1310 | 1452 | 17.68% | 20.09% | 62.23% | +1.9 | 18 |
| 2016-03-13 | Vendsyssel | W 3-1 | 1335 | 1412 | 34.29% | 22.43% | 43.28% | +13.2 | 21 |
| 2016-03-13 | @ FC Roskilde | L 1-3 | 1412 | 1335 | 43.28% | 22.43% | 34.29% | -13.2 | 36 |
| 2016-03-17 | Lyngby | L 0-2 | 1399 | 1451 | 37.97% | 22.50% | 39.53% | -13.7 | 36 |
| 2016-03-17 | @ Vendsyssel | W 2-0 | 1451 | 1399 | 39.53% | 22.50% | 37.97% | +13.7 | 45 |
| 2016-03-20 | Helsingor | FL | 1352 | 1387 | 40.30% | 22.49% | 37.21% | +0.0 | 13 |
| 2016-03-20 | @ Vestsjaelland | FW | 1387 | 1352 | 37.21% | 22.49% | 40.30% | +0.0 | 29 |
| 2016-03-20 | FC Roskilde | L 1-2 | 1380 | 1348 | 49.43% | 22.07% | 28.50% | -8.5 | 30 |
| 2016-03-20 | @ HB Koge | W 2-1 | 1348 | 1380 | 28.50% | 22.07% | 49.43% | +8.5 | 24 |
| 2016-03-20 | Horsens | W 4-3 | 1391 | 1404 | 43.37% | 22.42% | 34.21% | +5.8 | 33 |
| 2016-03-20 | @ Vejle BK | L 3-4 | 1404 | 1391 | 34.21% | 22.42% | 43.37% | -5.8 | 35 |
| 2016-03-20 | Naestved | W 2-1 | 1367 | 1339 | 49.03% | 22.10% | 28.87% | +5.5 | 31 |
| 2016-03-20 | @ Fredericia | L 1-2 | 1339 | 1367 | 28.87% | 22.10% | 49.03% | -5.5 | 21 |
| 2016-03-20 | Silkeborg | D 1-1 | 1312 | 1390 | 34.23% | 22.42% | 43.35% | +0.3 | 19 |
| 2016-03-20 | @ Skive | D 1-1 | 1390 | 1312 | 43.35% | 22.42% | 34.23% | -0.3 | 32 |
| 2016-03-23 | Vendsyssel | D 1-1 | 1390 | 1386 | 45.79% | 22.32% | 31.89% | -0.6 | 33 |
| 2016-03-23 | @ Silkeborg | D 1-1 | 1386 | 1390 | 31.89% | 22.32% | 45.79% | +0.5 | 37 |
| 2016-03-24 | Vejle BK | FL | 1352 | 1397 | 38.90% | 22.50% | 38.60% | +0.0 | 13 |
| 2016-03-24 | @ Vestsjaelland | FW | 1397 | 1352 | 38.60% | 22.50% | 38.90% | +0.0 | 36 |
| 2016-03-24 | Fredericia | W 3-0 | 1398 | 1373 | 48.58% | 22.13% | 29.29% | +16.2 | 38 |
| 2016-03-24 | @ Horsens | L 0-3 | 1373 | 1398 | 29.29% | 22.13% | 48.58% | -16.2 | 31 |
| 2016-03-24 | HB Koge | D 1-1 | 1464 | 1371 | 56.92% | 21.14% | 21.94% | -1.5 | 46 |
| 2016-03-24 | @ Lyngby | D 1-1 | 1371 | 1464 | 21.94% | 21.14% | 56.92% | +1.5 | 31 |
| 2016-03-24 | Helsingor | L 0-2 | 1356 | 1387 | 40.93% | 22.48% | 36.59% | -14.6 | 24 |
| 2016-03-24 | @ FC Roskilde | W 2-0 | 1387 | 1356 | 36.59% | 22.48% | 40.93% | +14.6 | 32 |
| 2016-03-24 | Skive | L 1-3 | 1333 | 1312 | 48.02% | 22.18% | 29.80% | -14.4 | 21 |
| 2016-03-24 | @ Naestved | W 3-1 | 1312 | 1333 | 29.80% | 22.18% | 48.02% | +14.4 | 22 |
| 2016-03-28 | Vestsjaelland | FW | 1357 | 1352 | 45.88% | 22.31% | 31.81% | +0.0 | 34 |
| 2016-03-28 | @ Fredericia | FL | 1352 | 1357 | 31.81% | 22.31% | 45.88% | +0.0 | 13 |
| 2016-03-28 | Lyngby | D 0-0 | 1342 | 1463 | 28.79% | 22.09% | 49.12% | +0.9 | 25 |
| 2016-03-28 | @ FC Roskilde | D 0-0 | 1463 | 1342 | 49.12% | 22.09% | 28.79% | -0.9 | 47 |
| 2016-03-28 | Naestved | W 2-0 | 1372 | 1319 | 52.19% | 21.79% | 26.01% | +10.1 | 34 |
| 2016-03-28 | @ HB Koge | L 0-2 | 1319 | 1372 | 26.01% | 21.79% | 52.19% | -10.1 | 21 |
| 2016-03-28 | Silkeborg | L 0-1 | 1401 | 1389 | 46.84% | 22.26% | 30.91% | -8.6 | 32 |
| 2016-03-28 | @ Helsingor | W 1-0 | 1389 | 1401 | 30.91% | 22.26% | 46.84% | +8.6 | 36 |
| 2016-03-28 | Vejle BK | L 0-3 | 1327 | 1397 | 35.36% | 22.46% | 42.18% | -18.8 | 22 |
| 2016-03-28 | @ Skive | W 3-0 | 1397 | 1327 | 42.18% | 22.46% | 35.36% | +18.9 | 39 |
| 2016-03-31 | Vendsyssel | D 0-0 | 1415 | 1386 | 49.12% | 22.09% | 28.79% | -0.9 | 40 |
| 2016-03-31 | @ Vejle BK | D 0-0 | 1386 | 1415 | 28.79% | 22.09% | 49.12% | +0.9 | 38 |
| 2016-04-03 | Lyngby | FL | 1352 | 1462 | 30.13% | 22.20% | 47.67% | +0.0 | 13 |
| 2016-04-03 | @ Vestsjaelland | FW | 1462 | 1352 | 47.67% | 22.20% | 30.13% | +0.0 | 50 |
| 2016-04-03 | FC Roskilde | W 6-2 | 1398 | 1343 | 52.41% | 21.77% | 25.82% | +13.4 | 39 |
| 2016-04-03 | @ Silkeborg | L 2-6 | 1343 | 1398 | 25.82% | 21.77% | 52.41% | -13.4 | 25 |
| 2016-04-03 | HB Koge | W 2-0 | 1414 | 1383 | 49.44% | 22.06% | 28.50% | +10.9 | 41 |
| 2016-04-03 | @ Horsens | L 0-2 | 1383 | 1414 | 28.50% | 22.06% | 49.44% | -10.9 | 34 |
| 2016-04-03 | Helsingor | W 1-0 | 1309 | 1393 | 33.47% | 22.40% | 44.13% | +8.2 | 24 |
| 2016-04-03 | @ Naestved | L 0-1 | 1393 | 1309 | 44.13% | 22.40% | 33.47% | -8.2 | 32 |
| 2016-04-03 | Skive | D 0-0 | 1357 | 1308 | 51.62% | 21.85% | 26.52% | -1.1 | 35 |
| 2016-04-03 | @ Fredericia | D 0-0 | 1308 | 1357 | 26.52% | 21.85% | 51.62% | +1.1 | 23 |
| 2016-04-07 | Silkeborg | L 0-2 | 1462 | 1411 | 51.82% | 21.83% | 26.35% | -17.7 | 50 |
| 2016-04-07 | @ Lyngby | W 2-0 | 1411 | 1462 | 26.35% | 21.83% | 51.82% | +17.7 | 42 |
| 2016-04-10 | Vestsjaelland | FW | 1309 | 1352 | 39.18% | 22.50% | 38.32% | +0.0 | 26 |
| 2016-04-10 | @ Skive | FL | 1352 | 1309 | 38.32% | 22.50% | 39.18% | +0.0 | 13 |
| 2016-04-10 | Fredericia | L 1-2 | 1387 | 1356 | 49.37% | 22.07% | 28.56% | -8.5 | 38 |
| 2016-04-10 | @ Vendsyssel | W 2-1 | 1356 | 1387 | 28.56% | 22.07% | 49.37% | +8.5 | 38 |
| 2016-04-10 | Horsens | L 0-3 | 1385 | 1425 | 39.51% | 22.50% | 37.99% | -20.6 | 32 |
| 2016-04-10 | @ Helsingor | W 3-0 | 1425 | 1385 | 37.99% | 22.50% | 39.51% | +20.6 | 44 |
| 2016-04-10 | Naestved | W 3-2 | 1329 | 1317 | 46.84% | 22.26% | 30.90% | +5.5 | 28 |
| 2016-04-10 | @ FC Roskilde | L 2-3 | 1317 | 1329 | 30.90% | 22.26% | 46.84% | -5.5 | 24 |
| 2016-04-10 | Vejle BK | L 1-2 | 1372 | 1415 | 39.18% | 22.50% | 38.32% | -7.0 | 34 |
| 2016-04-10 | @ HB Koge | W 2-1 | 1415 | 1372 | 38.32% | 22.50% | 39.18% | +7.0 | 43 |
| 2016-04-14 | Helsingor | L 2-3 | 1422 | 1364 | 52.68% | 21.74% | 25.58% | -8.5 | 43 |
| 2016-04-14 | @ Vejle BK | W 3-2 | 1364 | 1422 | 25.58% | 21.74% | 52.68% | +8.5 | 35 |
| 2016-04-17 | Silkeborg | FL | 1352 | 1429 | 34.37% | 22.43% | 43.20% | +0.0 | 13 |
| 2016-04-17 | @ Vestsjaelland | FW | 1429 | 1352 | 43.20% | 22.43% | 34.37% | +0.0 | 45 |
| 2016-04-17 | FC Roskilde | W 2-1 | 1446 | 1335 | 58.91% | 20.79% | 20.30% | +4.0 | 47 |
| 2016-04-17 | @ Horsens | L 1-2 | 1335 | 1446 | 20.30% | 20.79% | 58.91% | -4.0 | 28 |
| 2016-04-17 | HB Koge | L 0-3 | 1364 | 1365 | 45.14% | 22.35% | 32.51% | -22.9 | 38 |
| 2016-04-17 | @ Fredericia | W 3-0 | 1365 | 1364 | 32.51% | 22.35% | 45.14% | +22.9 | 37 |
| 2016-04-17 | Lyngby | L 0-2 | 1312 | 1444 | 27.44% | 21.96% | 50.60% | -10.5 | 24 |
| 2016-04-17 | @ Naestved | W 2-0 | 1444 | 1312 | 50.60% | 21.96% | 27.44% | +10.5 | 53 |
| 2016-04-17 | Vendsyssel | W 2-1 | 1309 | 1378 | 35.42% | 22.46% | 42.12% | +7.4 | 29 |
| 2016-04-17 | @ Skive | L 1-2 | 1378 | 1309 | 42.12% | 22.46% | 35.42% | -7.5 | 38 |
| 2016-04-20 | Horsens | L 0-3 | 1371 | 1450 | 34.17% | 22.42% | 43.41% | -18.3 | 38 |
| 2016-04-20 | @ Vendsyssel | W 3-0 | 1450 | 1371 | 43.41% | 22.42% | 34.17% | +18.4 | 50 |
| 2016-04-21 | Vejle BK | W 2-0 | 1331 | 1413 | 33.69% | 22.40% | 43.91% | +15.4 | 31 |
| 2016-04-21 | @ FC Roskilde | L 0-2 | 1413 | 1331 | 43.91% | 22.40% | 33.69% | -15.4 | 43 |
| 2016-04-24 | Vestsjaelland | FW | 1353 | 1352 | 45.32% | 22.34% | 32.34% | +0.0 | 41 |
| 2016-04-24 | @ Vendsyssel | FL | 1352 | 1353 | 32.34% | 22.34% | 45.32% | +0.0 | 13 |
| 2016-04-24 | Fredericia | L 1-2 | 1373 | 1341 | 49.37% | 22.07% | 28.56% | -8.5 | 35 |
| 2016-04-24 | @ Helsingor | W 2-1 | 1341 | 1373 | 28.56% | 22.07% | 49.37% | +8.5 | 41 |
| 2016-04-24 | Horsens | D 0-0 | 1455 | 1468 | 43.35% | 22.42% | 34.23% | -0.4 | 54 |
| 2016-04-24 | @ Lyngby | D 0-0 | 1468 | 1455 | 34.23% | 22.42% | 43.35% | +0.4 | 51 |
| 2016-04-24 | Naestved | W 3-0 | 1429 | 1301 | 60.74% | 20.42% | 18.84% | +10.9 | 48 |
| 2016-04-24 | @ Silkeborg | L 0-3 | 1301 | 1429 | 18.84% | 20.42% | 60.74% | -10.9 | 24 |
| 2016-04-24 | Skive | D 1-1 | 1388 | 1316 | 54.33% | 21.53% | 24.14% | -1.2 | 38 |
| 2016-04-24 | @ HB Koge | D 1-1 | 1316 | 1388 | 24.14% | 21.53% | 54.33% | +1.2 | 30 |
| 2016-04-28 | Silkeborg | W 1-0 | 1353 | 1440 | 33.04% | 22.38% | 44.59% | +8.3 | 44 |
| 2016-04-28 | @ Vendsyssel | L 0-1 | 1440 | 1353 | 44.59% | 22.38% | 33.04% | -8.3 | 48 |
| 2016-05-01 | Vestsjaelland | FW | 1398 | 1352 | 51.23% | 21.90% | 26.88% | +0.0 | 46 |
| 2016-05-01 | @ Vejle BK | FL | 1352 | 1398 | 26.88% | 21.90% | 51.23% | +0.0 | 13 |
| 2016-05-01 | FC Roskilde | W 3-1 | 1364 | 1346 | 47.62% | 22.21% | 30.17% | +9.9 | 38 |
| 2016-05-01 | @ Helsingor | L 1-3 | 1346 | 1364 | 30.17% | 22.21% | 47.62% | -9.9 | 31 |
| 2016-05-01 | Horsens | L 0-2 | 1350 | 1469 | 29.07% | 22.12% | 48.81% | -11.1 | 41 |
| 2016-05-01 | @ Fredericia | W 2-0 | 1469 | 1350 | 48.81% | 22.12% | 29.07% | +11.1 | 54 |
| 2016-05-01 | Lyngby | L 0-3 | 1386 | 1454 | 35.62% | 22.46% | 41.91% | -19.0 | 38 |
| 2016-05-01 | @ HB Koge | W 3-0 | 1454 | 1386 | 41.91% | 22.46% | 35.62% | +19.0 | 57 |
| 2016-05-01 | Naestved | L 2-4 | 1318 | 1290 | 48.87% | 22.11% | 29.01% | -13.0 | 30 |
| 2016-05-01 | @ Skive | W 4-2 | 1290 | 1318 | 29.01% | 22.11% | 48.87% | +13.1 | 27 |
| 2016-05-05 | Fredericia | D 0-0 | 1398 | 1339 | 52.86% | 21.72% | 25.43% | -1.2 | 47 |
| 2016-05-05 | @ Vejle BK | D 0-0 | 1339 | 1398 | 25.43% | 21.72% | 52.86% | +1.3 | 42 |
| 2016-05-08 | FC Roskilde | FL | 1352 | 1336 | 47.30% | 22.23% | 30.47% | +0.0 | 13 |
| 2016-05-08 | @ Vestsjaelland | FW | 1336 | 1352 | 30.47% | 22.23% | 47.30% | +0.0 | 34 |
| 2016-05-08 | HB Koge | W 1-0 | 1432 | 1367 | 53.52% | 21.63% | 24.84% | +5.1 | 51 |
| 2016-05-08 | @ Silkeborg | L 0-1 | 1367 | 1432 | 24.84% | 21.63% | 53.52% | -5.1 | 38 |
| 2016-05-08 | Helsingor | W 1-0 | 1473 | 1374 | 57.61% | 21.03% | 21.37% | +4.5 | 60 |
| 2016-05-08 | @ Lyngby | L 0-1 | 1374 | 1473 | 21.37% | 21.03% | 57.61% | -4.5 | 38 |
| 2016-05-08 | Skive | W 3-2 | 1480 | 1305 | 65.43% | 19.28% | 15.30% | +2.9 | 57 |
| 2016-05-08 | @ Horsens | L 2-3 | 1305 | 1480 | 15.30% | 19.28% | 65.43% | -2.9 | 30 |
| 2016-05-08 | Vendsyssel | L 0-1 | 1303 | 1361 | 37.05% | 22.49% | 40.46% | -7.1 | 27 |
| 2016-05-08 | @ Naestved | W 1-0 | 1361 | 1303 | 40.46% | 22.49% | 37.05% | +7.1 | 47 |
| 2016-05-11 | Vestsjaelland | FW | 1369 | 1352 | 47.58% | 22.21% | 30.21% | +0.0 | 41 |
| 2016-05-11 | @ Helsingor | FL | 1352 | 1369 | 30.21% | 22.21% | 47.58% | +0.0 | 13 |
| 2016-05-11 | Fredericia | D 0-0 | 1296 | 1340 | 39.03% | 22.50% | 38.47% | -0.0 | 28 |
| 2016-05-11 | @ Naestved | D 0-0 | 1340 | 1296 | 38.47% | 22.50% | 39.03% | +0.0 | 43 |
| 2016-05-11 | HB Koge | D 2-2 | 1336 | 1362 | 41.59% | 22.47% | 35.94% | -0.2 | 35 |
| 2016-05-11 | @ FC Roskilde | D 2-2 | 1362 | 1336 | 35.94% | 22.47% | 41.59% | +0.2 | 39 |
| 2016-05-11 | Skive | W 3-1 | 1437 | 1302 | 61.48% | 20.26% | 18.26% | +6.3 | 54 |
| 2016-05-11 | @ Silkeborg | L 1-3 | 1302 | 1437 | 18.26% | 20.26% | 61.48% | -6.3 | 30 |
| 2016-05-11 | Vejle BK | L 0-1 | 1483 | 1396 | 56.10% | 21.27% | 22.63% | -10.1 | 57 |
| 2016-05-11 | @ Horsens | W 1-0 | 1396 | 1483 | 22.63% | 21.27% | 56.10% | +10.1 | 50 |
| 2016-05-11 | Vendsyssel | L 0-1 | 1478 | 1368 | 58.76% | 20.82% | 20.42% | -10.5 | 60 |
| 2016-05-11 | @ Lyngby | W 1-0 | 1368 | 1478 | 20.42% | 20.82% | 58.76% | +10.5 | 50 |
| 2016-05-16 | Horsens | FL | 1352 | 1472 | 28.85% | 22.10% | 49.05% | +0.0 | 13 |
| 2016-05-16 | @ Vestsjaelland | FW | 1472 | 1352 | 49.05% | 22.10% | 28.85% | +0.0 | 60 |
| 2016-05-16 | FC Roskilde | W 3-2 | 1379 | 1336 | 50.81% | 21.94% | 27.25% | +5.0 | 53 |
| 2016-05-16 | @ Vendsyssel | L 2-3 | 1336 | 1379 | 27.25% | 21.94% | 50.81% | -5.0 | 35 |
| 2016-05-16 | Helsingor | L 0-1 | 1362 | 1369 | 44.22% | 22.39% | 33.39% | -8.2 | 39 |
| 2016-05-16 | @ HB Koge | W 1-0 | 1369 | 1362 | 33.39% | 22.39% | 44.22% | +8.2 | 44 |
| 2016-05-16 | Lyngby | D 2-2 | 1295 | 1467 | 23.22% | 21.38% | 55.40% | +1.0 | 31 |
| 2016-05-16 | @ Skive | D 2-2 | 1467 | 1295 | 55.40% | 21.38% | 23.22% | -1.0 | 61 |
| 2016-05-16 | Naestved | W 2-1 | 1406 | 1296 | 58.85% | 20.80% | 20.35% | +4.0 | 53 |
| 2016-05-16 | @ Vejle BK | L 1-2 | 1296 | 1406 | 20.35% | 20.80% | 58.85% | -4.0 | 28 |
| 2016-05-16 | Silkeborg | L 1-4 | 1340 | 1443 | 31.00% | 22.26% | 46.74% | -14.3 | 43 |
| 2016-05-16 | @ Fredericia | W 4-1 | 1443 | 1340 | 46.74% | 22.26% | 31.00% | +14.3 | 57 |
| 2016-05-22 | Naestved | FL | 1352 | 1292 | 52.97% | 21.70% | 25.33% | +0.0 | 13 |
| 2016-05-22 | @ Vestsjaelland | FW | 1292 | 1352 | 25.33% | 21.70% | 52.97% | +0.0 | 31 |
| 2016-05-22 | FC Roskilde | D 3-3 | 1326 | 1331 | 44.46% | 22.38% | 33.16% | -0.3 | 44 |
| 2016-05-22 | @ Fredericia | D 3-3 | 1331 | 1326 | 33.16% | 22.38% | 44.46% | +0.3 | 36 |
| 2016-05-22 | HB Koge | L 0-1 | 1384 | 1354 | 49.13% | 22.09% | 28.78% | -9.0 | 53 |
| 2016-05-22 | @ Vendsyssel | W 1-0 | 1354 | 1384 | 28.78% | 22.09% | 49.13% | +9.0 | 42 |
| 2016-05-22 | Helsingor | L 0-1 | 1296 | 1378 | 33.82% | 22.41% | 43.77% | -6.6 | 31 |
| 2016-05-22 | @ Skive | W 1-0 | 1378 | 1296 | 43.77% | 22.41% | 33.82% | +6.6 | 47 |
| 2016-05-22 | Lyngby | L 3-4 | 1411 | 1466 | 37.34% | 22.49% | 40.17% | -6.3 | 53 |
| 2016-05-22 | @ Vejle BK | W 4-3 | 1466 | 1411 | 40.17% | 22.49% | 37.34% | +6.3 | 64 |
| 2016-05-22 | Silkeborg | L 1-3 | 1472 | 1457 | 47.23% | 22.23% | 30.54% | -14.2 | 60 |
| 2016-05-22 | @ Horsens | W 3-1 | 1457 | 1472 | 30.54% | 22.23% | 47.23% | +14.2 | 60 |
| 2016-05-28 | Vestsjaelland | FW | 1363 | 1352 | 46.73% | 22.26% | 31.01% | +0.0 | 45 |
| 2016-05-28 | @ HB Koge | FL | 1352 | 1363 | 31.01% | 22.26% | 46.73% | +0.0 | 13 |
| 2016-05-28 | Fredericia | L 2-3 | 1473 | 1325 | 62.70% | 19.98% | 17.32% | -10.0 | 64 |
| 2016-05-28 | @ Lyngby | W 3-2 | 1325 | 1473 | 17.32% | 19.98% | 62.70% | +10.0 | 47 |
| 2016-05-28 | Horsens | W 5-1 | 1292 | 1458 | 23.79% | 21.47% | 54.74% | +29.4 | 34 |
| 2016-05-28 | @ Naestved | L 1-5 | 1458 | 1292 | 54.74% | 21.47% | 23.79% | -29.4 | 60 |
| 2016-05-28 | Skive | W 4-3 | 1331 | 1290 | 50.70% | 21.95% | 27.35% | +4.9 | 39 |
| 2016-05-28 | @ FC Roskilde | L 3-4 | 1290 | 1331 | 27.35% | 21.95% | 50.70% | -4.9 | 31 |
| 2016-05-28 | Vejle BK | W 5-0 | 1472 | 1404 | 53.88% | 21.59% | 24.53% | +22.3 | 63 |
| 2016-05-28 | @ Silkeborg | L 0-5 | 1404 | 1472 | 24.53% | 21.59% | 53.88% | -22.3 | 53 |
| 2016-05-28 | Vendsyssel | L 0-2 | 1384 | 1375 | 46.52% | 22.28% | 31.20% | -16.2 | 47 |
| 2016-05-28 | @ Helsingor | W 2-0 | 1375 | 1384 | 31.20% | 22.28% | 46.52% | +16.2 | 56 |
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 | ||||
|---|---|---|---|---|---|---|---|---|
| Team | Elo | Score | Team | Elo | Score | |||
| 1 | 2016-05-28 | 17.32% | Fredericia | 1325 | 3 | @ Lyngby | 1473 | 2 |
| 2 | 2016-05-11 | 20.42% | Vendsyssel | 1368 | 1 | @ Lyngby | 1478 | 0 |
| 3 | 2015-11-29 | 20.55% | Naestved | 1312 | 3 | @ Horsens | 1421 | 1 |
| 4 | 2016-05-11 | 22.63% | Vejle BK | 1396 | 1 | @ Horsens | 1483 | 0 |
| 5 | 2015-10-18 | 23.63% | Skive | 1325 | 3 | @ Vejle BK | 1401 | 2 |
| 6 | 2016-05-28 | 23.79% | @ Naestved | 1292 | 5 | Horsens | 1458 | 1 |
| 7 | 2016-03-13 | 24.21% | Naestved | 1330 | 2 | @ Vejle BK | 1400 | 1 |
| 8 | 2016-04-14 | 25.58% | Helsingor | 1364 | 3 | @ Vejle BK | 1422 | 2 |
| 9 | 2015-10-04 | 25.65% | HB Koge | 1345 | 1 | @ Vejle BK | 1402 | 0 |
| 10 | 2015-09-13 | 26.28% | Naestved | 1329 | 2 | @ Vestsjaelland | 1380 | 0 |
| 11 | 2016-04-07 | 26.35% | Silkeborg | 1411 | 2 | @ Lyngby | 1462 | 0 |
| 12 | 2015-11-01 | 27.04% | Skive | 1327 | 1 | @ Vestsjaelland | 1371 | 0 |
| 13 | 2016-03-10 | 27.41% | Fredericia | 1358 | 1 | @ Silkeborg | 1399 | 0 |
| 14 | 2015-11-29 | 27.62% | Helsingor | 1389 | 3 | @ Vendsyssel | 1428 | 2 |
| 15 | 2016-03-13 | 27.87% | HB Koge | 1365 | 3 | @ Helsingor | 1402 | 1 |
| 16 | 2016-03-20 | 28.50% | FC Roskilde | 1348 | 2 | @ HB Koge | 1380 | 1 |
| 17 | 2016-04-10 | 28.56% | Fredericia | 1356 | 2 | @ Vendsyssel | 1387 | 1 |
| 18 | 2016-04-24 | 28.56% | Fredericia | 1341 | 2 | @ Helsingor | 1373 | 1 |
| 19 | 2016-05-22 | 28.78% | HB Koge | 1354 | 1 | @ Vendsyssel | 1384 | 0 |
| 20 | 2015-11-28 | 28.79% | Silkeborg | 1385 | 3 | @ Vejle BK | 1415 | 1 |
| 21 | 2015-11-29 | 28.86% | HB Koge | 1340 | 2 | @ Vestsjaelland | 1369 | 0 |
| 22 | 2016-05-01 | 29.01% | Naestved | 1290 | 4 | @ Skive | 1318 | 2 |
| 23 | 2015-11-08 | 29.47% | Vejle BK | 1389 | 3 | @ Helsingor | 1413 | 0 |
| 24 | 2016-03-24 | 29.80% | Skive | 1312 | 3 | @ Naestved | 1333 | 1 |
| 25 | 2015-09-27 | 30.20% | Skive | 1320 | 1 | @ Naestved | 1338 | 0 |
Biggest Elo Changes
The 25 games that resulted in the largest shift in Elo rating.
| # | Date | Elo Δ | Winning Team | Losing Team | Tie % | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Team | Score | Elo | Win % | Team | Score | Elo | Win % | ||||
| 1 | 2016-05-28 | 29.41 | @ Naestved | 5 | 1292 | 23.79% | Horsens | 1 | 1458 | 54.74% | 21.47% |
| 2 | 2015-08-02 | 27.09 | @ Fredericia | 4 | 1335 | 37.58% | FC Roskilde | 0 | 1389 | 39.92% | 22.50% |
| 3 | 2015-09-20 | 26.81 | Helsingor | 4 | 1413 | 38.10% | @ HB Koge | 0 | 1371 | 39.40% | 22.50% |
| 4 | 2015-11-08 | 24.26 | Vejle BK | 3 | 1389 | 29.47% | @ Helsingor | 0 | 1413 | 48.38% | 22.15% |
| 5 | 2016-04-17 | 22.89 | HB Koge | 3 | 1365 | 32.51% | @ Fredericia | 0 | 1364 | 45.14% | 22.35% |
| 6 | 2015-07-26 | 22.42 | @ FC Roskilde | 3 | 1366 | 33.59% | Helsingor | 0 | 1449 | 44.01% | 22.40% |
| 7 | 2015-10-04 | 22.35 | @ Vestsjaelland | 3 | 1357 | 33.76% | Helsingor | 0 | 1438 | 43.83% | 22.41% |
| 8 | 2016-05-28 | 22.35 | @ Silkeborg | 5 | 1472 | 53.88% | Vejle BK | 0 | 1404 | 24.53% | 21.59% |
| 9 | 2016-04-10 | 20.57 | Horsens | 3 | 1425 | 37.99% | @ Helsingor | 0 | 1385 | 39.51% | 22.50% |
| 10 | 2016-05-01 | 18.97 | Lyngby | 3 | 1454 | 41.91% | @ HB Koge | 0 | 1386 | 35.62% | 22.46% |
| 11 | 2016-03-28 | 18.86 | Vejle BK | 3 | 1397 | 42.18% | @ Skive | 0 | 1327 | 35.36% | 22.46% |
| 12 | 2015-09-13 | 18.73 | @ Horsens | 3 | 1370 | 42.48% | HB Koge | 0 | 1390 | 35.07% | 22.45% |
| 13 | 2016-04-20 | 18.35 | Horsens | 3 | 1450 | 43.41% | @ Vendsyssel | 0 | 1371 | 34.17% | 22.42% |
| 14 | 2015-09-13 | 17.75 | Naestved | 2 | 1329 | 26.28% | @ Vestsjaelland | 0 | 1380 | 51.90% | 21.83% |
| 15 | 2016-04-07 | 17.73 | Silkeborg | 2 | 1411 | 26.35% | @ Lyngby | 0 | 1462 | 51.82% | 21.83% |
| 16 | 2015-08-28 | 17.23 | @ Lyngby | 4 | 1389 | 38.32% | Helsingor | 1 | 1438 | 39.18% | 22.50% |
| 17 | 2015-11-29 | 17.11 | Naestved | 3 | 1312 | 20.55% | @ Horsens | 1 | 1421 | 58.60% | 20.85% |
| 18 | 2015-08-07 | 16.93 | @ Vejle BK | 3 | 1362 | 46.79% | Horsens | 0 | 1351 | 30.95% | 22.26% |
| 19 | 2015-11-29 | 16.90 | HB Koge | 2 | 1340 | 28.86% | @ Vestsjaelland | 0 | 1369 | 49.04% | 22.10% |
| 20 | 2016-03-24 | 16.17 | @ Horsens | 3 | 1398 | 48.58% | Fredericia | 0 | 1373 | 29.29% | 22.13% |
| 21 | 2016-05-28 | 16.17 | Vendsyssel | 2 | 1375 | 31.20% | @ Helsingor | 0 | 1384 | 46.52% | 22.28% |
| 22 | 2015-07-26 | 15.72 | Vendsyssel | 2 | 1358 | 32.64% | @ Skive | 0 | 1357 | 45.00% | 22.36% |
| 23 | 2015-09-17 | 15.54 | Vejle BK | 2 | 1388 | 33.26% | @ Silkeborg | 0 | 1381 | 44.36% | 22.39% |
| 24 | 2016-04-21 | 15.41 | @ FC Roskilde | 2 | 1331 | 33.69% | Vejle BK | 0 | 1413 | 43.91% | 22.40% |
| 25 | 2015-08-28 | 15.36 | Horsens | 2 | 1355 | 33.85% | @ Skive | 0 | 1344 | 43.74% | 22.41% |