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2016-17 First Division B Season

124 games · 2 promotion-playoff teams

Final

Promoted

Antwerp

via playoff

Relegated

Lommel

via playoff

Biggest Overachiever

Roeselare

10.92 points above expected

50 points · 39.08 expected points

Biggest Disappointment

Lommel United

17.54 points below expected

18 points · 35.54 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 Lierse 28 15 10 3 55 51 25 +26 45.04 +9.96
2 Roeselare 28 14 8 6 50 42 32 +10 39.08 +10.92
3 Antwerp Promoted 28 13 10 5 49 40 26 +14 42.67 +6.33
4 Union SG 28 9 8 11 35 33 34 -1 35.04 -0.04
5 Tubize 28 10 4 14 34 42 53 -11 34.73 -0.73
6 Cercle Brugge 28 9 6 13 33 32 40 -8 35.17 -2.17
7 Oud-Heverlee Leuven 28 7 9 12 30 33 42 -9 39.32 -9.32
8 Lommel United 28 3 9 16 18 31 52 -21 35.54 -17.54
# Team GP W D L Pts GF GA GD SimPts vsSim
1 Lommel United 6 3 1 2 10 9 4 +5 — —
2 Oud-Heverlee Leuven 6 2 2 2 8 4 4 0 — —
3 Tubize 6 1 4 1 7 6 6 0 — —
4 Cercle Brugge 6 1 3 2 6 4 9 -5 — —

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.

Promotion Playoff

The path the promotion-playoff teams took to determine the final promotion spot. The full Promotion / Relegation tab has matchup heatmaps and round-by-round simulation outcomes.

Finals

Antwerp 5
Roeselare 2

Leg 1: Roeselare 1-2 Antwerp

Leg 2: Antwerp 3-1 Roeselare

Sim: 6.0%

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
Antwerp 1684 49 42.67 +6.33 85.1% 19 32 38 43 47 54 66
Lierse 1684 55 45.04 +9.96 94.0% 21 34 40 45 50 56 72
Roeselare 1606 50 39.08 +10.92 96.0% 13 28 35 39 44 50 65
Union SG 1585 35 35.04 -0.04 53.5% 12 25 31 35 39 46 62
Oud-Heverlee Leuven 1554 30 39.32 -9.32 9.4% 18 29 35 39 44 50 63
Lommel United 1541 18 35.54 -17.54 0.4% 9 25 31 35 40 46 62
Tubize 1538 34 34.73 -0.73 49.0% 13 24 30 35 39 46 57
Cercle Brugge 1512 33 35.17 -2.17 40.7% 14 25 31 35 40 46 61

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 ANT CB LIE LU OL ROE TUB US
Antwerp —
2-2-0
6.33
0-1-3
5.32
2-1-1
6.47
2-2-0
5.87
3-0-1
5.79
2-2-0
6.55
2-2-0
6.34
Cercle Brugge
0-2-2
4.62
 —
0-2-2
4.42
3-1-0
5.27
1-0-3
5.14
0-1-3
4.88
3-0-1
5.43
2-0-2
5.48
Lierse
3-1-0
5.62
2-2-0
6.55
 —
2-1-1
7.04
2-2-0
6.24
0-2-2
6.42
4-0-0
6.62
2-2-0
6.57
Lommel United
1-1-2
4.50
0-1-3
5.66
1-1-2
3.97
 —
0-3-1
5.05
0-1-3
5.18
1-0-3
5.55
0-2-2
5.57
Oud-Heverlee Leuven
0-2-2
5.08
3-0-1
5.81
0-2-2
4.69
1-3-0
5.88
 —
0-2-2
5.50
2-0-2
6.11
1-0-3
6.22
Roeselare
1-0-3
5.15
3-1-0
6.06
2-2-0
4.55
3-1-0
5.80
2-2-0
5.45
 —
1-1-2
6.06
2-1-1
5.99
Tubize
0-2-2
4.41
1-0-3
5.50
0-0-4
4.33
3-0-1
5.39
2-0-2
4.82
2-1-1
4.88
 —
2-1-1
5.47
Union SG
0-2-2
4.60
2-0-2
5.45
0-2-2
4.40
2-2-0
5.35
3-0-1
4.71
1-1-2
4.94
1-1-2
5.48
 —

Points vs. Goals Scored, Allowed, and Differential

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

Fit Metrics

R² Slope
Scored 0.69 +14.7
Allowed 0.73 -9.9
Differential 0.93 +7.7

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 →012345+Total
06.45%8.87%6.05%2.42%1.21%0.40%25.40%
18.87%13.71%8.87%2.82%1.21%0.81%36.29%
26.05%8.87%9.68%0.81%1.21%—26.61%
32.42%2.82%0.81%——0.40%6.45%
41.21%1.21%1.21%———3.63%
5+0.40%0.81%—0.40%——1.61%
Total25.40%36.29%26.61%6.45%3.63%1.61%100%

Summary Statistics

Scored Allowed Difference
Mean 1.32 1.32 +0.00
SD 1.14 1.14 1.66
CV 0.87 0.87 —
Max 6 6 +5
Min 0 0 -5

Games Played: 124

↓ Scored | Allowed →012345+Total
07.14%3.57%7.14%———17.86%
114.29%21.43%7.14%———42.86%
210.71%10.71%7.14%———28.57%
3———————
43.57%—7.14%———10.71%
5+———————
Total35.71%35.71%28.57%———100%

Summary Statistics

Scored Allowed Difference
Mean 1.43 0.93 +0.50
SD 1.14 0.81 1.32
CV 0.80 0.88 —
Max 4 2 +4
Min 0 0 -2

Games Played: 28

↓ Scored | Allowed →012345+Total
08.82%14.71%5.88%2.94%—2.94%35.29%
111.76%11.76%5.88%2.94%2.94%—35.29%
2—8.82%5.88%2.94%2.94%—20.59%
3—5.88%————5.88%
4—2.94%————2.94%
5+———————
Total20.59%44.12%17.65%8.82%5.88%2.94%100%

Summary Statistics

Scored Allowed Difference
Mean 1.06 1.44 -0.38
SD 1.04 1.26 1.61
CV 0.98 0.87 —
Max 4 5 +3
Min 0 0 -5

Games Played: 34

↓ Scored | Allowed →012345+Total
07.14%—7.14%———14.29%
110.71%14.29%3.57%———28.57%
210.71%7.14%14.29%———32.14%
310.71%3.57%3.57%———17.86%
4———————
5+—7.14%————7.14%
Total39.29%32.14%28.57%———100%

Summary Statistics

Scored Allowed Difference
Mean 1.82 0.89 +0.93
SD 1.31 0.83 1.56
CV 0.72 0.93 —
Max 5 2 +4
Min 0 0 -2

Games Played: 28

↓ Scored | Allowed →012345+Total
05.88%14.71%5.88%2.94%——29.41%
12.94%14.71%14.71%5.88%—2.94%41.18%
22.94%5.88%8.82%—2.94%—20.59%
3—————2.94%2.94%
42.94%—————2.94%
5+2.94%—————2.94%
Total17.65%35.29%29.41%8.82%2.94%5.88%100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 1.65 -0.47
SD 1.17 1.39 1.78
CV 0.99 0.84 —
Max 5 6 +5
Min 0 0 -4

Games Played: 34

↓ Scored | Allowed →012345+Total
05.88%11.76%5.88%2.94%2.94%—29.41%
111.76%11.76%11.76%2.94%——38.24%
28.82%2.94%14.71%2.94%——29.41%
3———————
4——2.94%———2.94%
5+———————
Total26.47%26.47%35.29%8.82%2.94%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.09 1.35 -0.26
SD 0.93 1.07 1.40
CV 0.86 0.79 —
Max 4 4 +2
Min 0 0 -4

Games Played: 34

↓ Scored | Allowed →012345+Total
03.57%10.71%————14.29%
13.57%14.29%3.57%3.57%3.57%—28.57%
27.14%32.14%10.71%———50.00%
33.57%3.57%————7.14%
4———————
5+———————
Total17.86%60.71%14.29%3.57%3.57%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.50 1.14 +0.36
SD 0.84 0.89 1.28
CV 0.56 0.78 —
Max 3 4 +3
Min 0 0 -3

Games Played: 28

↓ Scored | Allowed →012345+Total
02.94%5.88%8.82%5.88%2.94%—26.47%
18.82%11.76%5.88%5.88%2.94%2.94%38.24%
22.94%2.94%8.82%—2.94%—17.65%
32.94%5.88%————8.82%
4—5.88%————5.88%
5+———2.94%——2.94%
Total17.65%32.35%23.53%14.71%8.82%2.94%100%

Summary Statistics

Scored Allowed Difference
Mean 1.41 1.74 -0.32
SD 1.40 1.33 2.03
CV 0.99 0.77 —
Max 6 5 +3
Min 0 0 -4

Games Played: 34

↓ Scored | Allowed →012345+Total
010.71%7.14%7.14%3.57%3.57%—32.14%
17.14%10.71%17.86%———35.71%
27.14%3.57%7.14%———17.86%
33.57%3.57%3.57%———10.71%
43.57%—————3.57%
5+———————
Total32.14%25.00%35.71%3.57%3.57%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.18 1.21 -0.04
SD 1.12 1.07 1.73
CV 0.95 0.88 —
Max 4 4 +4
Min 0 0 -4

Games Played: 28

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 Roeselare 50 39.08 +10.92
2 Lierse 55 45.04 +9.96
3 Antwerp 49 42.67 +6.33
4 Union SG 35 35.04 -0.04
5 Tubize 34 34.73 -0.73

Biggest Disappointments

# Team Actual Sim vsSim
1 Lommel United 18 35.54 -17.54
2 Oud-Heverlee Leuven 30 39.32 -9.32
3 Cercle Brugge 33 35.17 -2.17
4 Tubize 34 34.73 -0.73
5 Union SG 35 35.04 -0.04

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 Roeselare 5 Sep 11 – Oct 5 1 in 570
2 Antwerp 5 Dec 16 – Jan 29 1 in 69
3 Lierse 3 Sep 9 – Sep 25 1 in 30
4 Lommel United 2 Aug 14 – Aug 19 1 in 13
5 Union SG 2 Oct 29 – Nov 6 1 in 11

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Oud-Heverlee Leuven 5 Jan 8 – Feb 5 1 in 90
2 Lommel United 3 Sep 11 – Sep 25 1 in 65
3 Cercle Brugge 3 Sep 18 – Oct 1 1 in 21
4 Union SG 3 Sep 24 – Oct 4 1 in 20
5 Tubize 3 Oct 16 – Oct 30 1 in 10

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Roeselare 16 Sep 11 – Dec 17 1 in 1,765
2 Antwerp 11 Nov 13 – Feb 4 1 in 60
3 Union SG 7 Jan 8 – Feb 19 1 in 43
4 Lierse 11 Dec 2 – Feb 26 1 in 22
5 Oud-Heverlee Leuven 5 Sep 18 – Oct 9 1 in 8

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Lommel United 15 Nov 6 – Feb 26 1 in 321
2 Oud-Heverlee Leuven 7 Dec 10 – Feb 5 1 in 16
3 Union SG 6 Nov 11 – Dec 17 1 in 13
4 Antwerp 5 Aug 19 – Sep 25 1 in 10
5 Cercle Brugge 5 Sep 18 – Oct 9 1 in 9

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).

Team12345678
Lierse39.42%22.04%14.16%9.81%6.43%4.28%2.60%1.26%
Roeselare10.80%14.80%16.30%15.15%13.66%11.97%9.68%7.64%
Antwerp23.85%22.22%17.18%12.70%9.86%6.94%4.76%2.49%
Union SG3.81%6.46%10.19%11.95%13.56%16.05%18.85%19.13%
Tubize3.06%6.24%8.40%11.21%14.20%16.19%18.87%21.83%
Cercle Brugge3.95%6.67%9.31%11.90%14.49%15.62%17.81%20.25%
Oud-Heverlee Leuven11.30%14.75%14.88%14.90%14.18%12.03%10.00%7.96%
Lommel United3.81%6.82%9.58%12.38%13.62%16.92%17.43%19.44%

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
+10.48%
Slight Edge
40.32%29.84%29.84%
Elo Value
Home Edge: 36.56 Elo pts.
274 Elo
0.004 goals per Elo point
0800
Scoring Tilt
Expected
+0.19 goals
Neutral
-2+0.13+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 4th * Longshot: 5th or lower.
Title Margin
Points-per-game gap between the champion and the runner-up. Shown per game so it reads the same across long and short seasons. The gold line is the winning margin the model expected, so a dot to the right means a more one-sided race than projected. A title won on goal difference shows 0.00.
Photo Finish: under 0.15 * Tight Race: 0.15 to 0.4 * Comfortable: 0.4 to 0.75 * Runaway: 0.75 and up.
Title-Race Openness
4.1
Open
12468
Champion Preseason Odds
39%
Lierse, 1st of 8
LongshotFavorite
Title Margin
Expected
0.18/gm
Tight Race
00.160.5/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 5.26 * Some Luck: 5.26 to 7.89 * Lucky: 7.89 to 10.52 * Wild Swing: 10.52 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 1.46 * Close: 1.46 to 2.19 * Off: 2.19 to 2.92 * Way Off: 2.92 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 8 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 8 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 8 * As Expected: 8 to 12.8 * Several Outliers: 12.8 to 17.6 * Many Outliers: 17.6 and up.
Unexpected Relegations
Number of teams that were actually relegated but were not in the model's projected bottom field of the same size. The gold line is how many the model expected to miss on average.
As Expected: under 1 * A Surprise: 1 to 1.6 * Several Surprises: 1.6 to 2.2 * Many Surprises: 2.2 and up.
Luck Spread
Expected
9.07 points
Lucky
06.5716
Average Finish Error
Expected
2.00
Close
01.824
Biggest Overachiever
Expected 93.75%
95.95%
Roeselare
50100
Biggest Underachiever
Expected
0.39%
Lommel United
06.25%50
Season Outliers
Expected
2 of 8
Minimal Outliers
00.88
Unexpected Relegations
Expected 1.0
1 of 1
A Surprise
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
1.56
Moderate Separation
01.003
Interquartile Edge
61%
Slight Edge
50%60%70%80%100%
Best vs. Worst
Baseline
77%
Clear Edge
50%78%100%
Close Games
Expected
67%
Very Frequent
0%63%100%
Blowouts
Expected
13%
Occasional
0%13%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
0.66
Hard to Predict
00.622
Matchup Imbalance
0.31
Lopsided
00.10.180.280.5
Strangeness
Expected
1.91
Chaotic
01.002
Repeatability
-0.62
Weak Carryover
00.30.60.851
Upset Rate
Expected
27%
As Expected
0%25%50%
Clear Favorite Upset Rate
Expected
29%
Shaky Favorites
0%23%50%

Calibration

How these are measured

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

Probability calibration
An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope
Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE)
The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.13 * Near Noise Ceiling: 0.13 to 0.2 * Above Noise: 0.2 to 0.27 * Well Above Noise: 0.27 and up.
Probability calibration
0.47
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
0.93
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.087
Well Within Noise
00.1340.3

Elo Progression Through The Playoffs

How each team's Elo rating moved through the playoff games. Game 0 is the starting Elo just before the first game; each later point is the post-game Elo after that fixture. Steep upward moves are wins over higher-rated opponents; sharp drops are losses to lower-rated opponents.

Stochastic Promotion/Relegation Outcomes

Across 100,000 regular-season simulations from preseason Elo, the probability of each team's next-season outcome — promotion-positive outcomes on the left, relegation-positive on the right. The round buttons switch to heatmaps of how often each pair of teams met in that round of the playoff across the simulations, since every iteration produces a different field.

Team Qualified for promotion playoff Lost promotion playoff Same level Qualified for relegation playoff
Antwerp — 100% — —
Cercle Brugge 47.92% 10.62% 21.21% 20.25%
Lierse 13.31% 61.46% 23.97% 1.26%
Lommel United 47.97% 10.63% 21.96% 19.44%
Oud-Heverlee Leuven 36.21% 26.05% 29.78% 7.96%
Roeselare — 100% — —
Tubize 49.26% 9.30% 19.61% 21.83%
Union SG 48.46% 10.27% 22.14% 19.13%
Loser →
↓ Winner
AntwerpCercle BruggeLierseLommel UnitedOud-Heverlee LeuvenRoeselareTubizeUnion SG
Antwerp100.0%2.00%68.8%16.00%100.0%4.00%83.3%6.00%85.7%7.00%75.0%4.00%50.0%2.00%
Cercle Brugge0.0%2.00%33.3%6.00%0.0%1.00%0.0%1.00%0.0%1.00%50.0%2.00%
Lierse31.2%16.00%66.7%6.00%80.0%5.00%46.2%13.00%84.6%13.00%33.3%3.00%100.0%3.00%
Lommel United0.0%4.00%20.0%5.00%0.0%1.00%0.0%1.00%50.0%2.00%
Oud-Heverlee Leuven16.7%6.00%100.0%1.00%53.8%13.00%100.0%1.00%75.0%4.00%50.0%2.00%
Roeselare14.3%7.00%100.0%1.00%15.4%13.00%100.0%1.00%25.0%4.00%0.0%1.00%
Tubize25.0%4.00%100.0%1.00%66.7%3.00%50.0%2.00%
Union SG50.0%2.00%50.0%2.00%0.0%3.00%50.0%2.00%100.0%1.00%

Actual Promotion/Relegation Outcomes

Just the teams that actually reached the promotion playoff. With the field fixed in place, the playoff sim re-runs every tie and tallies how often each team won each round — the table gives those probabilities, and the final round's column is the chance of winning the playoff outright. The round buttons switch to heatmaps of how often each pairing met in that round.

Team Finals
Antwerp 57.12%
Roeselare 42.88%
Loser →
↓ Winner
AntwerpRoeselare
Antwerp57.1%100.00%
Roeselare42.9%100.00%

Actual Promotion/Relegation Outcomes

Across 100,000 simulations that fixed the regular-season standings and projected only the promotion/relegation playoff, each participating team's chance of going up versus staying at this level.

Team Qualified for promotion playoff Qualified for relegation playoff
Cercle Brugge 100% —
Lommel United — 100%
Oud-Heverlee Leuven 100% —
Tubize 100% —

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
2016-08-05 Lierse D 2-2 1541 1586 41.71% 27.46% 30.84% -0.3 1
2016-08-05 @ Roeselare D 2-2 1586 1541 30.84% 27.46% 41.71% +0.3 1
2016-08-06 Union SG D 2-2 1592 1546 53.40% 25.64% 20.96% -1.1 1
2016-08-06 @ Tubize D 2-2 1546 1592 20.96% 25.64% 53.40% +1.1 1
2016-08-07 Antwerp D 1-1 1597 1612 45.73% 27.06% 27.21% -0.8 1
2016-08-07 @ Cercle Brugge D 1-1 1612 1597 27.21% 27.06% 45.73% +0.8 1
2016-08-07 Oud-Heverlee Leuven D 2-2 1603 1636 43.38% 27.32% 29.30% -0.4 1
2016-08-07 @ Lommel United D 2-2 1636 1603 29.30% 27.32% 43.38% +0.5 1
2016-08-12 Union SG L 0-3 1636 1547 58.38% 24.20% 17.42% -32.0 1
2016-08-12 @ Oud-Heverlee Leuven W 3-0 1547 1636 17.42% 24.20% 58.38% +32.0 4
2016-08-13 Roeselare W 1-0 1613 1540 56.59% 24.76% 18.64% +4.6 4
2016-08-13 @ Antwerp L 0-1 1540 1613 18.64% 24.76% 56.59% -4.6 1
2016-08-14 Cercle Brugge W 2-0 1586 1596 46.39% 26.97% 26.64% +11.9 4
2016-08-14 @ Lierse L 0-2 1596 1586 26.64% 26.97% 46.39% -11.9 1
2016-08-14 Lommel United L 0-4 1591 1603 46.18% 27.00% 26.82% -34.5 1
2016-08-14 @ Tubize W 4-0 1603 1591 26.82% 27.00% 46.18% +34.5 4
2016-08-19 Lommel United L 0-1 1618 1637 45.21% 27.13% 27.67% -9.5 4
2016-08-19 @ Antwerp W 1-0 1637 1618 27.67% 27.13% 45.21% +9.5 7
2016-08-20 Oud-Heverlee Leuven D 2-2 1536 1604 38.38% 27.62% 34.00% -0.1 2
2016-08-20 @ Roeselare D 2-2 1604 1536 34.00% 27.62% 38.38% +0.1 2
2016-08-21 Lierse D 2-2 1579 1598 45.31% 27.11% 27.58% -0.6 5
2016-08-21 @ Union SG D 2-2 1598 1579 27.58% 27.11% 45.31% +0.6 5
2016-08-21 Tubize W 4-1 1584 1556 51.28% 26.12% 22.59% +12.7 4
2016-08-21 @ Cercle Brugge L 1-4 1556 1584 22.59% 26.12% 51.28% -12.7 1
2016-09-02 Oud-Heverlee Leuven D 2-2 1598 1604 46.95% 26.90% 26.15% -0.7 6
2016-09-02 @ Lierse D 2-2 1604 1598 26.15% 26.90% 46.95% +0.7 3
2016-09-03 Cercle Brugge D 1-1 1647 1597 53.87% 25.52% 20.61% -1.5 8
2016-09-03 @ Lommel United D 1-1 1597 1647 20.61% 25.52% 53.87% +1.5 5
2016-09-04 Antwerp D 1-1 1579 1608 43.82% 27.28% 28.91% -0.6 6
2016-09-04 @ Union SG D 1-1 1608 1579 28.91% 27.28% 43.82% +0.6 5
2016-09-04 Roeselare W 4-1 1544 1535 48.77% 26.61% 24.62% +13.7 4
2016-09-04 @ Tubize L 1-4 1535 1544 24.62% 26.61% 48.77% -13.7 2
2016-09-09 Lierse L 1-2 1609 1598 49.18% 26.53% 24.28% -9.6 5
2016-09-09 @ Antwerp W 2-1 1598 1609 24.28% 26.53% 49.18% +9.6 9
2016-09-10 Union SG W 2-1 1599 1578 50.33% 26.32% 23.35% +5.3 8
2016-09-10 @ Cercle Brugge L 1-2 1578 1599 23.35% 26.32% 50.33% -5.3 6
2016-09-11 Roeselare L 1-2 1645 1522 62.04% 22.88% 15.08% -11.6 8
2016-09-11 @ Lommel United W 2-1 1522 1645 15.08% 22.88% 62.04% +11.6 5
2016-09-11 Tubize L 0-1 1605 1557 53.68% 25.57% 20.75% -10.9 3
2016-09-11 @ Oud-Heverlee Leuven W 1-0 1557 1605 20.75% 25.57% 53.68% +10.9 7
2016-09-16 Lommel United W 3-1 1573 1634 39.52% 27.58% 32.91% +12.2 9
2016-09-16 @ Union SG L 1-3 1634 1573 32.91% 27.58% 39.52% -12.2 8
2016-09-17 Tubize W 5-1 1607 1568 52.63% 25.82% 21.54% +15.7 12
2016-09-17 @ Lierse L 1-5 1568 1607 21.54% 25.82% 52.63% -15.7 7
2016-09-18 Antwerp D 1-1 1594 1599 47.06% 26.88% 26.06% -0.9 4
2016-09-18 @ Oud-Heverlee Leuven D 1-1 1599 1594 26.06% 26.88% 47.06% +0.9 6
2016-09-18 Cercle Brugge W 2-1 1533 1604 38.12% 27.62% 34.25% +7.2 8
2016-09-18 @ Roeselare L 1-2 1604 1533 34.25% 27.62% 38.12% -7.2 8
2016-09-24 Union SG W 2-1 1541 1585 41.80% 27.45% 30.75% +6.7 11
2016-09-24 @ Roeselare L 1-2 1585 1541 30.75% 27.45% 41.80% -6.7 9
2016-09-25 Antwerp D 2-2 1552 1600 41.30% 27.48% 31.22% -0.3 8
2016-09-25 @ Tubize D 2-2 1600 1552 31.22% 27.48% 41.30% +0.3 7
2016-09-25 Lierse L 0-3 1621 1623 47.52% 26.81% 25.67% -27.0 8
2016-09-25 @ Lommel United W 3-0 1623 1621 25.67% 26.81% 47.52% +27.0 15
2016-09-25 Oud-Heverlee Leuven L 2-4 1597 1593 48.16% 26.71% 25.13% -14.6 8
2016-09-25 @ Cercle Brugge W 4-2 1593 1597 25.13% 26.71% 48.16% +14.6 7
2016-09-30 Tubize L 0-1 1578 1552 51.05% 26.17% 22.78% -10.5 9
2016-09-30 @ Union SG W 1-0 1552 1578 22.78% 26.17% 51.05% +10.5 11
2016-10-01 Cercle Brugge W 2-1 1601 1582 50.11% 26.36% 23.53% +5.4 10
2016-10-01 @ Antwerp L 1-2 1582 1601 23.53% 26.36% 50.11% -5.4 8
2016-10-02 Lommel United D 2-2 1608 1594 49.47% 26.48% 24.04% -0.9 8
2016-10-02 @ Oud-Heverlee Leuven D 2-2 1594 1608 24.04% 26.48% 49.47% +0.8 9
2016-10-02 Roeselare L 0-2 1650 1547 59.87% 23.69% 16.44% -22.5 15
2016-10-02 @ Lierse W 2-0 1547 1650 16.44% 23.69% 59.87% +22.5 14
2016-10-04 Union SG W 4-0 1606 1568 52.52% 25.85% 21.63% +18.9 13
2016-10-04 @ Antwerp L 0-4 1568 1606 21.63% 25.85% 52.52% -18.9 9
2016-10-05 Lommel United W 2-0 1570 1595 44.39% 27.22% 28.39% +12.6 17
2016-10-05 @ Roeselare L 0-2 1595 1570 28.39% 27.22% 44.39% -12.6 9
2016-10-05 Oud-Heverlee Leuven L 0-1 1563 1607 41.77% 27.45% 30.77% -8.9 11
2016-10-05 @ Tubize W 1-0 1607 1563 30.77% 27.45% 41.77% +8.9 11
2016-10-06 Lierse D 0-0 1577 1628 40.90% 27.51% 31.59% -0.4 9
2016-10-06 @ Cercle Brugge D 0-0 1628 1577 31.59% 27.51% 40.90% +0.4 16
2016-10-08 Tubize L 3-6 1583 1554 51.39% 26.10% 22.51% -19.5 9
2016-10-08 @ Lommel United W 6-3 1554 1583 22.51% 26.10% 51.39% +19.5 14
2016-10-09 Antwerp W 2-0 1628 1625 48.12% 26.72% 25.16% +11.4 19
2016-10-09 @ Lierse L 0-2 1625 1628 25.16% 26.72% 48.12% -11.4 13
2016-10-09 Cercle Brugge W 3-2 1549 1576 44.12% 27.25% 28.63% +6.0 12
2016-10-09 @ Union SG L 2-3 1576 1549 28.63% 27.25% 44.12% -6.0 9
2016-10-09 Roeselare D 1-1 1616 1582 51.96% 25.98% 22.07% -1.3 12
2016-10-09 @ Oud-Heverlee Leuven D 1-1 1582 1616 22.07% 25.98% 51.96% +1.4 18
2016-10-14 Lommel United W 3-1 1570 1563 48.66% 26.63% 24.72% +9.7 12
2016-10-14 @ Cercle Brugge L 1-3 1563 1570 24.72% 26.63% 48.66% -9.7 9
2016-10-15 Union SG W 2-1 1639 1555 57.88% 24.36% 17.76% +4.1 22
2016-10-15 @ Lierse L 1-2 1555 1639 17.76% 24.36% 57.88% -4.1 12
2016-10-16 Oud-Heverlee Leuven W 2-1 1614 1615 47.61% 26.80% 25.59% +5.8 16
2016-10-16 @ Antwerp L 1-2 1615 1614 25.59% 26.80% 47.61% -5.8 12
2016-10-16 Tubize W 1-0 1584 1573 49.10% 26.55% 24.35% +5.9 21
2016-10-16 @ Roeselare L 0-1 1573 1584 24.35% 26.55% 49.10% -5.9 14
2016-10-21 Lierse L 1-3 1567 1644 37.30% 27.64% 35.06% -13.4 14
2016-10-21 @ Tubize W 3-1 1644 1567 35.06% 27.64% 37.30% +13.4 25
2016-10-22 Cercle Brugge W 2-0 1609 1580 51.38% 26.10% 22.52% +10.4 15
2016-10-22 @ Oud-Heverlee Leuven L 0-2 1580 1609 22.52% 26.10% 51.38% -10.3 12
2016-10-23 Antwerp D 1-1 1553 1619 38.77% 27.61% 33.63% -0.2 10
2016-10-23 @ Lommel United D 1-1 1619 1553 33.63% 27.61% 38.77% +0.2 17
2016-10-24 Roeselare L 1-2 1551 1590 42.56% 27.39% 30.05% -8.5 12
2016-10-24 @ Union SG W 2-1 1590 1551 30.05% 27.39% 42.56% +8.5 24
2016-10-28 Roeselare L 0-3 1570 1598 43.97% 27.26% 28.77% -25.4 12
2016-10-28 @ Cercle Brugge W 3-0 1598 1570 28.77% 27.26% 43.97% +25.4 27
2016-10-29 Oud-Heverlee Leuven W 2-0 1542 1619 37.21% 27.64% 35.15% +14.8 15
2016-10-29 @ Union SG L 0-2 1619 1542 35.15% 27.64% 37.21% -14.8 15
2016-10-30 Lommel United L 0-2 1657 1553 59.97% 23.65% 16.38% -22.5 25
2016-10-30 @ Lierse W 2-0 1553 1657 16.38% 23.65% 59.97% +22.5 13
2016-10-30 Tubize W 2-0 1620 1554 55.76% 25.01% 19.23% +9.0 20
2016-10-30 @ Antwerp L 0-2 1554 1620 19.23% 25.01% 55.76% -8.9 14
2016-11-06 Antwerp W 2-1 1624 1629 47.08% 26.88% 26.05% +5.9 30
2016-11-06 @ Roeselare L 1-2 1629 1624 26.05% 26.88% 47.08% -5.9 20
2016-11-06 Cercle Brugge W 4-1 1545 1544 47.82% 26.76% 25.41% +14.1 17
2016-11-06 @ Tubize L 1-4 1544 1545 25.41% 26.76% 47.82% -14.1 12
2016-11-06 Lierse L 0-1 1604 1634 43.78% 27.28% 28.94% -9.2 15
2016-11-06 @ Oud-Heverlee Leuven W 1-0 1634 1604 28.94% 27.28% 43.78% +9.2 28
2016-11-06 Union SG L 1-2 1576 1557 50.12% 26.36% 23.52% -9.7 13
2016-11-06 @ Lommel United W 2-1 1557 1576 23.52% 26.36% 50.12% +9.7 18
2016-11-11 Union SG W 1-0 1644 1567 57.02% 24.63% 18.34% +4.5 31
2016-11-11 @ Lierse L 0-1 1567 1644 18.34% 24.63% 57.02% -4.5 18
2016-11-12 Oud-Heverlee Leuven D 2-2 1566 1595 43.88% 27.27% 28.85% -0.5 14
2016-11-12 @ Lommel United D 2-2 1595 1566 28.85% 27.27% 43.88% +0.5 16
2016-11-12 Tubize D 1-1 1629 1559 56.29% 24.85% 18.86% -1.7 31
2016-11-12 @ Roeselare D 1-1 1559 1629 18.86% 24.85% 56.29% +1.7 18
2016-11-13 Cercle Brugge D 0-0 1623 1530 58.76% 24.07% 17.16% -2.2 21
2016-11-13 @ Antwerp D 0-0 1530 1623 17.16% 24.07% 58.76% +2.2 13
2016-11-18 Antwerp D 0-0 1596 1621 44.45% 27.21% 28.33% -0.8 17
2016-11-18 @ Oud-Heverlee Leuven D 0-0 1621 1596 28.33% 27.21% 44.45% +0.8 22
2016-11-19 Roeselare D 0-0 1562 1628 38.85% 27.60% 33.55% -0.2 19
2016-11-19 @ Union SG D 0-0 1628 1562 33.55% 27.60% 38.85% +0.2 32
2016-11-20 Lierse L 0-3 1561 1648 35.71% 27.65% 36.65% -21.7 18
2016-11-20 @ Tubize W 3-0 1648 1561 36.65% 27.65% 35.71% +21.7 34
2016-11-20 Lommel United W 1-0 1532 1566 43.33% 27.32% 29.34% +6.8 16
2016-11-20 @ Cercle Brugge L 0-1 1566 1532 29.34% 27.32% 43.33% -6.8 14
2016-11-25 Lierse W 2-1 1628 1670 42.13% 27.42% 30.44% +6.6 35
2016-11-25 @ Roeselare L 1-2 1670 1628 30.44% 27.42% 42.13% -6.6 34
2016-11-26 Tubize L 1-2 1559 1539 50.24% 26.34% 23.42% -9.7 14
2016-11-26 @ Lommel United W 2-1 1539 1559 23.42% 26.34% 50.24% +9.7 21
2016-11-26 Union SG W 2-0 1621 1562 55.03% 25.21% 19.76% +9.2 25
2016-11-26 @ Antwerp L 0-2 1562 1621 19.76% 25.21% 55.03% -9.2 19
2016-11-27 Cercle Brugge W 1-0 1595 1539 54.59% 25.33% 20.08% +4.9 20
2016-11-27 @ Oud-Heverlee Leuven L 0-1 1539 1595 20.08% 25.33% 54.59% -4.9 16
2016-12-02 Antwerp D 2-2 1663 1631 51.84% 26.00% 22.16% -1.0 35
2016-12-02 @ Lierse D 2-2 1631 1663 22.16% 26.00% 51.84% +1.0 26
2016-12-03 Cercle Brugge L 1-2 1553 1534 50.09% 26.37% 23.54% -9.7 19
2016-12-03 @ Union SG W 2-1 1534 1553 23.54% 26.37% 50.09% +9.7 19
2016-12-03 Oud-Heverlee Leuven L 0-2 1549 1600 40.86% 27.51% 31.63% -16.5 21
2016-12-03 @ Tubize W 2-0 1600 1549 31.63% 27.51% 40.86% +16.5 23
2016-12-04 Lommel United W 2-1 1635 1549 57.99% 24.33% 17.68% +4.1 38
2016-12-04 @ Roeselare L 1-2 1549 1635 17.68% 24.33% 57.99% -4.1 14
2016-12-09 Lommel United D 1-1 1543 1545 47.50% 26.81% 25.68% -1.0 20
2016-12-09 @ Union SG D 1-1 1545 1543 25.68% 26.81% 47.50% +1.0 15
2016-12-10 Lierse L 0-1 1544 1662 31.49% 27.50% 41.01% -7.2 19
2016-12-10 @ Cercle Brugge W 1-0 1662 1544 41.01% 27.50% 31.49% +7.2 38
2016-12-10 Roeselare L 1-2 1616 1639 44.80% 27.17% 28.02% -8.9 23
2016-12-10 @ Oud-Heverlee Leuven W 2-1 1639 1616 28.02% 27.17% 44.80% +8.9 41
2016-12-11 Tubize D 1-1 1632 1532 59.50% 23.82% 16.68% -2.0 27
2016-12-11 @ Antwerp D 1-1 1532 1632 16.68% 23.82% 59.50% +2.0 22
2016-12-16 Antwerp L 2-4 1546 1630 36.24% 27.65% 36.12% -11.7 15
2016-12-16 @ Lommel United W 4-2 1630 1546 36.12% 27.65% 36.24% +11.7 30
2016-12-17 Cercle Brugge W 3-1 1648 1537 60.73% 23.38% 15.90% +6.4 44
2016-12-17 @ Roeselare L 1-3 1537 1648 15.90% 23.38% 60.73% -6.4 19
2016-12-17 Union SG W 3-0 1534 1542 46.71% 26.93% 26.36% +17.2 25
2016-12-17 @ Tubize L 0-3 1542 1534 26.36% 26.93% 46.71% -17.2 20
2016-12-18 Oud-Heverlee Leuven D 1-1 1669 1607 55.32% 25.13% 19.55% -1.6 39
2016-12-18 @ Lierse D 1-1 1607 1669 19.55% 25.13% 55.32% +1.6 24
2017-01-06 Roeselare W 1-0 1641 1654 46.08% 27.02% 26.91% +6.4 33
2017-01-06 @ Antwerp L 0-1 1654 1641 26.91% 27.02% 46.08% -6.4 44
2017-01-07 Tubize W 2-1 1530 1551 44.97% 27.15% 27.88% +6.2 22
2017-01-07 @ Cercle Brugge L 1-2 1551 1530 27.88% 27.15% 44.97% -6.2 25
2017-01-08 Lommel United W 5-1 1668 1534 63.11% 22.45% 14.44% +10.6 42
2017-01-08 @ Lierse L 1-5 1534 1668 14.44% 22.45% 63.11% -10.6 15
2017-01-08 Oud-Heverlee Leuven W 4-0 1525 1609 36.17% 27.65% 36.19% +28.6 23
2017-01-08 @ Union SG L 0-4 1609 1525 36.19% 27.65% 36.17% -28.6 24
2017-01-13 Roeselare D 1-1 1523 1648 30.74% 27.45% 41.81% +0.5 16
2017-01-13 @ Lommel United D 1-1 1648 1523 41.81% 27.45% 30.74% -0.5 45
2017-01-14 Tubize L 1-3 1580 1545 52.16% 25.93% 21.91% -17.4 24
2017-01-14 @ Oud-Heverlee Leuven W 3-1 1545 1580 21.91% 25.93% 52.16% +17.4 28
2017-01-15 Antwerp L 0-1 1536 1648 32.43% 27.56% 40.01% -7.4 22
2017-01-15 @ Cercle Brugge W 1-0 1648 1536 40.01% 27.56% 32.43% +7.4 36
2017-01-15 Lierse D 0-0 1554 1678 30.64% 27.44% 41.92% +0.5 24
2017-01-15 @ Union SG D 0-0 1678 1554 41.92% 27.44% 30.64% -0.5 43
2017-01-20 Lommel United W 2-0 1563 1524 52.56% 25.84% 21.60% +10.0 31
2017-01-20 @ Tubize L 0-2 1524 1563 21.60% 25.84% 52.56% -10.0 16
2017-01-21 Cercle Brugge D 1-1 1678 1529 64.61% 21.82% 13.56% -2.4 44
2017-01-21 @ Lierse D 1-1 1529 1678 13.56% 21.82% 64.61% +2.4 23
2017-01-21 Oud-Heverlee Leuven W 2-0 1655 1563 58.69% 24.10% 17.21% +8.0 39
2017-01-21 @ Antwerp L 0-2 1563 1655 17.21% 24.10% 58.69% -8.0 24
2017-01-22 Union SG L 0-1 1647 1554 58.81% 24.05% 17.13% -11.8 45
2017-01-22 @ Roeselare W 1-0 1554 1647 17.13% 24.05% 58.81% +11.8 27
2017-01-27 Lierse L 2-3 1555 1675 31.21% 27.48% 41.30% -6.4 24
2017-01-27 @ Oud-Heverlee Leuven W 3-2 1675 1555 41.30% 27.48% 31.21% +6.4 47
2017-01-28 Roeselare D 2-2 1532 1635 33.42% 27.60% 38.98% +0.2 24
2017-01-28 @ Cercle Brugge D 2-2 1635 1532 38.98% 27.60% 33.42% -0.2 46
2017-01-28 Union SG D 0-0 1514 1566 40.76% 27.52% 31.72% -0.4 17
2017-01-28 @ Lommel United D 0-0 1566 1514 31.72% 27.52% 40.76% +0.4 28
2017-01-29 Antwerp L 2-4 1573 1663 35.27% 27.64% 37.08% -11.5 31
2017-01-29 @ Tubize W 4-2 1663 1573 37.08% 27.64% 35.27% +11.5 42
2017-02-03 Cercle Brugge L 0-1 1514 1532 45.36% 27.11% 27.54% -9.5 17
2017-02-03 @ Lommel United W 1-0 1532 1514 27.54% 27.11% 45.36% +9.5 27
2017-02-04 Antwerp D 1-1 1566 1675 32.82% 27.57% 39.61% +0.3 29
2017-02-04 @ Union SG D 1-1 1675 1566 39.61% 27.57% 32.82% -0.3 43
2017-02-04 Tubize W 3-0 1682 1561 61.77% 22.98% 15.24% +10.3 50
2017-02-04 @ Lierse L 0-3 1561 1682 15.24% 22.98% 61.77% -10.3 31
2017-02-05 Oud-Heverlee Leuven W 2-1 1635 1549 58.10% 24.29% 17.61% +4.1 49
2017-02-05 @ Roeselare L 1-2 1549 1635 17.61% 24.29% 58.10% -4.1 24
2017-02-10 Union SG L 0-1 1541 1567 44.40% 27.22% 28.39% -9.4 27
2017-02-10 @ Cercle Brugge W 1-0 1567 1541 28.39% 27.22% 44.40% +9.4 32
2017-02-11 Lierse L 0-2 1674 1692 45.39% 27.10% 27.51% -17.9 43
2017-02-11 @ Antwerp W 2-0 1692 1674 27.51% 27.10% 45.39% +17.9 53
2017-02-11 Lommel United W 2-1 1545 1504 52.79% 25.79% 21.43% +5.0 27
2017-02-11 @ Oud-Heverlee Leuven L 1-2 1504 1545 21.43% 25.79% 52.79% -5.0 17
2017-02-12 Roeselare W 3-1 1551 1639 35.56% 27.64% 36.80% +13.2 34
2017-02-12 @ Tubize L 1-3 1639 1551 36.80% 27.64% 35.56% -13.2 49
2017-02-17 Lierse D 1-1 1499 1710 21.23% 25.72% 53.05% +1.5 18
2017-02-17 @ Lommel United D 1-1 1710 1499 53.05% 25.72% 21.23% -1.4 54
2017-02-18 Antwerp L 1-2 1626 1656 43.73% 27.29% 28.98% -8.7 49
2017-02-18 @ Roeselare W 2-1 1656 1626 28.98% 27.29% 43.73% +8.7 46
2017-02-18 Oud-Heverlee Leuven W 1-0 1532 1549 45.43% 27.10% 27.47% +6.5 30
2017-02-18 @ Cercle Brugge L 0-1 1549 1532 27.47% 27.10% 45.43% -6.5 27
2017-02-19 Tubize W 2-0 1576 1564 49.26% 26.52% 24.22% +11.0 35
2017-02-19 @ Union SG L 0-2 1564 1576 24.22% 26.52% 49.26% -11.0 34
2017-02-26 Cercle Brugge L 1-3 1553 1538 49.60% 26.46% 23.94% -16.7 34
2017-02-26 @ Tubize W 3-1 1538 1553 23.94% 26.46% 49.60% +16.7 33
2017-02-26 Lommel United W 1-0 1665 1501 66.15% 21.14% 12.71% +3.1 49
2017-02-26 @ Antwerp L 0-1 1501 1665 12.71% 21.14% 66.15% -3.1 18
2017-02-26 Roeselare D 1-1 1709 1617 58.63% 24.12% 17.25% -1.9 55
2017-02-26 @ Lierse D 1-1 1617 1709 17.25% 24.12% 58.63% +1.9 50
2017-02-26 Union SG W 2-0 1543 1587 41.86% 27.44% 30.69% +13.3 30
2017-02-26 @ Oud-Heverlee Leuven L 0-2 1587 1543 30.69% 27.44% 41.86% -13.4 35

Second Phase Game Log

Every second-phase (championship / middle / relegation round) game from each team's perspective, filtered by the team selected at the top of the tab; the table scrolls within its frame. Sort any column by clicking its header. @ before an opponent name indicates an away game. The final column is running points within the second phase only.

Date Opponent Score Pre Elo Opp Elo Win % Tie % Loss % Elo Δ Points
2017-03-24 Tubize D 1-1 1556 1536 50.28% 26.33% 23.39% -1.2 1
2017-03-24 @ Oud-Heverlee Leuven D 1-1 1536 1556 23.39% 26.33% 50.28% +1.2 1
2017-03-26 Lommel United L 0-5 1555 1497 54.81% 25.27% 19.92% -48.9 0
2017-03-26 @ Cercle Brugge W 5-0 1497 1555 19.92% 25.27% 54.81% +48.9 3
2017-03-31 Cercle Brugge D 2-2 1537 1506 51.68% 26.04% 22.28% -1.0 2
2017-03-31 @ Tubize D 2-2 1506 1537 22.28% 26.04% 51.68% +1.0 1
2017-04-01 Oud-Heverlee Leuven W 2-1 1546 1555 46.60% 26.95% 26.45% +5.9 6
2017-04-01 @ Lommel United L 1-2 1555 1546 26.45% 26.95% 46.60% -5.9 1
2017-04-01 Mechelen W 3-0 1574 1824 17.95% 24.45% 57.60% +31.7 3
2017-04-01 @ Union SG L 0-3 1824 1574 57.60% 24.45% 17.95% -31.7 0
2017-04-01 Roeselare D 2-2 1673 1603 56.28% 24.86% 18.87% -1.3 1
2017-04-01 @ Eupen D 2-2 1603 1673 18.87% 24.86% 56.28% +1.3 1
2017-04-02 Standard Liege W 1-0 1707 1791 36.21% 27.65% 36.14% +8.0 3
2017-04-02 @ Lierse L 0-1 1791 1707 36.14% 27.65% 36.21% -8.0 0
2017-04-07 Cercle Brugge W 1-0 1549 1507 52.98% 25.74% 21.28% +5.2 4
2017-04-07 @ Oud-Heverlee Leuven L 0-1 1507 1549 21.28% 25.74% 52.98% -5.2 1
2017-04-08 Lommel United D 0-0 1536 1552 45.66% 27.07% 27.27% -0.9 3
2017-04-08 @ Tubize D 0-0 1552 1536 27.27% 27.07% 45.66% +0.9 7
2017-04-08 Genk L 0-1 1604 1870 16.80% 23.88% 59.32% -4.2 1
2017-04-08 @ Roeselare W 1-0 1870 1604 59.32% 23.88% 16.80% +4.2 3
2017-04-08 Union SG L 1-4 1668 1605 55.44% 25.10% 19.46% -25.9 0
2017-04-08 @ Waasland-Beveren W 4-1 1605 1668 19.46% 25.10% 55.44% +25.9 6
2017-04-09 Lierse W 1-0 1792 1715 57.10% 24.61% 18.29% +4.5 3
2017-04-09 @ Mechelen L 0-1 1715 1792 18.29% 24.61% 57.10% -4.5 3
2017-04-14 Oud-Heverlee Leuven D 0-0 1502 1554 40.66% 27.52% 31.81% -0.4 2
2017-04-14 @ Cercle Brugge D 0-0 1554 1502 31.81% 27.52% 40.66% +0.4 5
2017-04-14 Standard Liege D 2-2 1631 1781 27.53% 27.11% 45.36% +0.6 7
2017-04-14 @ Union SG D 2-2 1781 1631 45.36% 27.11% 27.53% -0.6 1
2017-04-15 Lierse W 2-1 1713 1710 48.11% 26.72% 25.17% +5.7 3
2017-04-15 @ Sint-Truiden L 1-2 1710 1713 25.17% 26.72% 48.11% -5.7 3
2017-04-15 Royal Excel Mouscron L 3-5 1600 1652 40.70% 27.52% 31.78% -12.1 1
2017-04-15 @ Roeselare W 5-3 1652 1600 31.78% 27.52% 40.70% +12.1 3
2017-04-17 Tubize W 2-1 1553 1536 49.98% 26.39% 23.63% +5.4 10
2017-04-17 @ Lommel United L 1-2 1536 1553 23.63% 26.39% 49.98% -5.4 3
2017-04-21 Cercle Brugge L 0-1 1559 1501 54.77% 25.28% 19.95% -11.1 10
2017-04-21 @ Lommel United W 1-0 1501 1559 19.95% 25.28% 54.77% +11.1 5
2017-04-22 Oud-Heverlee Leuven W 1-0 1530 1555 44.49% 27.21% 28.30% +6.6 6
2017-04-22 @ Tubize L 0-1 1555 1530 28.30% 27.21% 44.49% -6.6 5
2017-04-22 Roeselare W 2-1 1727 1588 63.63% 22.24% 14.13% +3.3 3
2017-04-22 @ Sporting Lokeren L 1-2 1588 1727 14.13% 22.24% 63.63% -3.3 1
2017-04-22 Waasland-Beveren L 2-3 1704 1636 56.04% 24.93% 19.03% -10.1 3
2017-04-22 @ Lierse W 3-2 1636 1704 19.03% 24.93% 56.04% +10.1 3
2017-04-22 Union SG L 0-1 1719 1632 58.16% 24.27% 17.57% -11.7 3
2017-04-22 @ Sint-Truiden W 1-0 1632 1719 17.57% 24.27% 58.16% +11.7 10
2017-04-25 Kortrijk L 2-3 1585 1694 32.65% 27.57% 39.79% -6.6 1
2017-04-25 @ Roeselare W 3-2 1694 1585 39.79% 27.57% 32.65% +6.6 3
2017-04-25 Lierse L 1-3 1643 1694 40.87% 27.51% 31.62% -14.3 10
2017-04-25 @ Union SG W 3-1 1694 1643 31.62% 27.51% 40.87% +14.3 6
2017-04-28 Lommel United W 1-0 1548 1548 47.82% 26.76% 25.42% +6.1 8
2017-04-28 @ Oud-Heverlee Leuven L 0-1 1548 1548 25.42% 26.76% 47.82% -6.1 10
2017-04-28 Tubize D 1-1 1513 1537 44.53% 27.20% 28.26% -0.7 6
2017-04-28 @ Cercle Brugge D 1-1 1537 1513 28.26% 27.20% 44.53% +0.7 7
2017-04-28 Union SG W 3-1 1752 1629 61.98% 22.90% 15.12% +6.1 4
2017-04-28 @ Standard Liege L 1-3 1629 1752 15.12% 22.90% 61.98% -6.1 10
2017-04-29 Mechelen D 0-0 1709 1813 33.42% 27.60% 38.99% +0.3 7
2017-04-29 @ Lierse D 0-0 1813 1709 38.99% 27.60% 33.42% -0.3 4
2017-04-30 Roeselare W 1-0 1652 1578 56.73% 24.72% 18.55% +4.6 6
2017-04-30 @ Royal Excel Mouscron L 0-1 1578 1652 18.55% 24.72% 56.73% -4.6 1
2017-05-06 Roeselare L 0-3 1694 1574 61.72% 23.00% 15.28% -33.5 3
2017-05-06 @ Kortrijk W 3-0 1574 1694 15.28% 23.00% 61.72% +33.5 4
2017-05-06 Union SG W 2-1 1709 1623 58.04% 24.31% 17.65% +4.1 10
2017-05-06 @ Lierse L 1-2 1623 1709 17.65% 24.31% 58.04% -4.1 10
2017-05-13 Lierse W 3-2 1681 1713 43.53% 27.30% 29.16% +6.1 6
2017-05-13 @ Waasland-Beveren L 2-3 1713 1681 29.16% 27.30% 43.53% -6.1 10
2017-05-13 Sint-Truiden L 1-4 1619 1719 33.87% 27.61% 38.51% -17.6 10
2017-05-13 @ Union SG W 4-1 1719 1619 38.51% 27.61% 33.87% +17.6 6
2017-05-13 Sporting Lokeren L 2-3 1607 1741 29.48% 27.34% 43.19% -6.1 4
2017-05-13 @ Roeselare W 3-2 1741 1607 43.19% 27.34% 29.48% +6.1 6
2017-05-16 Sint-Truiden L 1-3 1707 1737 43.77% 27.28% 28.95% -15.1 10
2017-05-16 @ Lierse W 3-1 1737 1707 28.95% 27.28% 43.77% +15.1 9
2017-05-16 Union SG W 1-0 1778 1601 67.35% 20.59% 12.06% +2.9 7
2017-05-16 @ Mechelen L 0-1 1601 1778 12.06% 20.59% 67.35% -2.9 10
2017-05-17 Roeselare W 3-1 1920 1601 79.09% 14.28% 6.63% +2.3 6
2017-05-17 @ Genk L 1-3 1601 1920 6.63% 14.28% 79.09% -2.3 4
2017-05-19 Lierse W 2-0 1777 1692 57.98% 24.33% 17.69% +8.3 7
2017-05-19 @ Standard Liege L 0-2 1692 1777 17.69% 24.33% 57.98% -8.3 10
2017-05-19 Waasland-Beveren L 1-3 1598 1674 37.38% 27.64% 34.99% -13.4 10
2017-05-19 @ Union SG W 3-1 1674 1598 34.99% 27.64% 37.38% +13.4 9
2017-05-20 Eupen W 3-2 1599 1693 34.68% 27.63% 37.69% +7.4 7
2017-05-20 @ Roeselare L 2-3 1693 1599 37.69% 27.63% 34.68% -7.4 1

Playoff Game Log

Every playoff game for the team selected at the top of the tab (empty if they didn't reach the postseason). Sort any column by clicking its header. @ before an opponent name indicates an away game; the record column shows the team's running playoff record.

Date Opponent Score Pre Elo Opp Elo Win % Tie % Loss % Elo Δ Record
2017-03-05 Roeselare W 3-1 1668 1619 53.78% 25.54% 20.67% +8.3 1-0
2017-03-05 @ Antwerp L 1-3 1619 1668 20.67% 25.54% 53.78% -8.3 0-1
2017-03-11 Antwerp L 1-2 1611 1676 38.85% 27.60% 33.55% -8.0 0-2
2017-03-11 @ Roeselare W 2-1 1676 1611 33.55% 27.60% 38.85% +8.0 2-0

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 2016-09-11 15.08% Roeselare 1522 2 @ Lommel United 1645 1
2 2016-10-30 16.38% Lommel United 1553 2 @ Lierse 1657 0
3 2016-10-02 16.44% Roeselare 1547 2 @ Lierse 1650 0
4 2017-01-22 17.13% Union SG 1554 1 @ Roeselare 1647 0
5 2016-08-12 17.42% Union SG 1547 3 @ Oud-Heverlee Leuven 1636 0
6 2017-03-26 19.92% Lommel United 1497 5 @ Cercle Brugge 1555 0
7 2017-04-21 19.95% Cercle Brugge 1501 1 @ Lommel United 1559 0
8 2016-09-11 20.75% Tubize 1557 1 @ Oud-Heverlee Leuven 1605 0
9 2017-01-14 21.91% Tubize 1545 3 @ Oud-Heverlee Leuven 1580 1
10 2016-10-08 22.51% Tubize 1554 6 @ Lommel United 1583 3
11 2016-09-30 22.78% Tubize 1552 1 @ Union SG 1578 0
12 2016-11-26 23.42% Tubize 1539 2 @ Lommel United 1559 1
13 2016-11-06 23.52% Union SG 1557 2 @ Lommel United 1576 1
14 2016-12-03 23.54% Cercle Brugge 1534 2 @ Union SG 1553 1
15 2017-02-26 23.94% Cercle Brugge 1538 3 @ Tubize 1553 1
16 2016-09-09 24.28% Lierse 1598 2 @ Antwerp 1609 1
17 2016-09-25 25.13% Oud-Heverlee Leuven 1593 4 @ Cercle Brugge 1597 2
18 2016-09-25 25.67% Lierse 1623 3 @ Lommel United 1621 0
19 2016-08-14 26.82% Lommel United 1603 4 @ Tubize 1591 0
20 2017-02-11 27.51% Lierse 1692 2 @ Antwerp 1674 0
21 2017-02-03 27.54% Cercle Brugge 1532 1 @ Lommel United 1514 0
22 2016-08-19 27.67% Lommel United 1637 1 @ Antwerp 1618 0
23 2016-12-10 28.02% Roeselare 1639 2 @ Oud-Heverlee Leuven 1616 1
24 2017-02-10 28.39% Union SG 1567 1 @ Cercle Brugge 1541 0
25 2016-10-28 28.77% Roeselare 1598 3 @ Cercle Brugge 1570 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 2017-03-26 48.94 Lommel United 5 1497 19.92% @ Cercle Brugge 0 1555 54.81% 25.27%
2 2016-08-14 34.51 Lommel United 4 1603 26.82% @ Tubize 0 1591 46.18% 27.00%
3 2016-08-12 32.03 Union SG 3 1547 17.42% @ Oud-Heverlee Leuven 0 1636 58.38% 24.20%
4 2017-01-08 28.64 @ Union SG 4 1525 36.17% Oud-Heverlee Leuven 0 1609 36.19% 27.65%
5 2016-09-25 27.03 Lierse 3 1623 25.67% @ Lommel United 0 1621 47.52% 26.81%
6 2016-10-28 25.40 Roeselare 3 1598 28.77% @ Cercle Brugge 0 1570 43.97% 27.26%
7 2016-10-30 22.54 Lommel United 2 1553 16.38% @ Lierse 0 1657 59.97% 23.65%
8 2016-10-02 22.51 Roeselare 2 1547 16.44% @ Lierse 0 1650 59.87% 23.69%
9 2016-11-20 21.71 Lierse 3 1648 36.65% @ Tubize 0 1561 35.71% 27.65%
10 2016-10-08 19.48 Tubize 6 1554 22.51% @ Lommel United 3 1583 51.39% 26.10%
11 2016-10-04 18.95 @ Antwerp 4 1606 52.52% Union SG 0 1568 21.63% 25.85%
12 2017-02-11 17.94 Lierse 2 1692 27.51% @ Antwerp 0 1674 45.39% 27.10%
13 2017-01-14 17.39 Tubize 3 1545 21.91% @ Oud-Heverlee Leuven 1 1580 52.16% 25.93%
14 2016-12-17 17.18 @ Tubize 3 1534 46.71% Union SG 0 1542 26.36% 26.93%
15 2017-02-26 16.69 Cercle Brugge 3 1538 23.94% @ Tubize 1 1553 49.60% 26.46%
16 2016-12-03 16.53 Oud-Heverlee Leuven 2 1600 31.63% @ Tubize 0 1549 40.86% 27.51%
17 2016-09-17 15.73 @ Lierse 5 1607 52.63% Tubize 1 1568 21.54% 25.82%
18 2016-10-29 14.78 @ Union SG 2 1542 37.21% Oud-Heverlee Leuven 0 1619 35.15% 27.64%
19 2016-09-25 14.58 Oud-Heverlee Leuven 4 1593 25.13% @ Cercle Brugge 2 1597 48.16% 26.71%
20 2016-11-06 14.06 @ Tubize 4 1545 47.82% Cercle Brugge 1 1544 25.41% 26.76%
21 2016-09-04 13.69 @ Tubize 4 1544 48.77% Roeselare 1 1535 24.62% 26.61%
22 2016-10-21 13.37 Lierse 3 1644 35.06% @ Tubize 1 1567 37.30% 27.64%
23 2017-02-26 13.35 @ Oud-Heverlee Leuven 2 1543 41.86% Union SG 0 1587 30.69% 27.44%
24 2017-02-12 13.23 @ Tubize 3 1551 35.56% Roeselare 1 1639 36.80% 27.64%
25 2016-08-21 12.71 @ Cercle Brugge 4 1584 51.28% Tubize 1 1556 22.59% 26.12%