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2016 Virsliga Season

112 games

Final

Champion

Spartaks Jurmala

55 points

Relegated

No relegation

Biggest Overachiever

Spartaks Jurmala

12.08 points above expected

55 points · 42.92 expected points

Biggest Disappointment

Liepaja

8.13 points below expected

42 points · 50.13 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 Spartaks Jurmala 28 17 4 7 55 46 22 +24 42.92 +12.08
2 Jelgava 28 16 3 9 51 37 24 +13 44.80 +6.20
3 Ventspils 28 15 6 7 51 47 28 +19 53.03 -2.03
4 Liepaja 28 12 6 10 42 38 31 +7 50.13 -8.13
5 Riga FC 28 8 12 8 36 28 24 +4 41.19 -5.19
6 FK RFS 28 9 8 11 35 22 31 -9 38.43 -3.43
7 Metta 28 8 6 14 30 32 47 -15 24.33 +5.67
8 Daugavpils 28 2 5 21 11 13 56 -43 17.13 -6.13

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 Spartaks Jurmala 55 42.92 +12.08
2 Jelgava 51 44.80 +6.20
3 Metta 30 24.33 +5.67
4 Ventspils 51 53.03 -2.03
5 FK RFS 35 38.43 -3.43

Biggest Disappointments

# Team Actual Sim vsSim
1 Liepaja 42 50.13 -8.13
2 Daugavpils 11 17.13 -6.13
3 Riga FC 36 41.19 -5.19
4 FK RFS 35 38.43 -3.43
5 Ventspils 51 53.03 -2.03

Top Streaks

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

Most Unlikely Winning Streaks

# Team Games Dates Probability
1 Spartaks Jurmala 5 May 27 – Jul 10 1 in 62
2 Jelgava 4 Jun 22 – Aug 8 1 in 28
3 Metta 2 May 8 – May 15 1 in 13
4 Ventspils 5 Apr 2 – May 8 1 in 11
5 Liepaja 3 Apr 30 – May 14 1 in 7

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Liepaja 3 Jul 30 – Aug 13 1 in 98
2 Spartaks Jurmala 3 Sep 24 – Oct 16 1 in 59
3 Daugavpils 6 Apr 16 – May 27 1 in 26
4 Jelgava 3 Apr 4 – Apr 22 1 in 24
5 Ventspils 2 Jun 22 – Jul 10 1 in 20

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Jelgava 9 Jun 22 – Sep 10 1 in 24
2 Riga FC 6 Oct 1 – Nov 5 1 in 18
3 Spartaks Jurmala 8 Jul 30 – Sep 17 1 in 14
4 FK RFS 5 Sep 16 – Oct 21 1 in 10
5 Ventspils 9 Mar 12 – May 26 1 in 8

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Liepaja 6 Sep 17 – Oct 29 1 in 55
2 Spartaks Jurmala 5 Sep 11 – Oct 16 1 in 29
3 Daugavpils 19 Apr 16 – Sep 18 1 in 25
4 Ventspils 3 Oct 22 – Nov 5 1 in 17
5 Riga FC 5 Aug 20 – Sep 25 1 in 10

Position Race

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

Recent Form

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

Team Elo Season Pts Form Elo Δ (5) Points (5) Expected (5) Actual − Exp
Spartaks Jurmala 1321 55 -40 6 8.2 -2.2
Jelgava 1363 51 +3 9 8.9 +0.1
Ventspils 1385 51 -10 7 9.7 -2.7
Liepaja 1305 42 -58 4 9.8 -5.8
Riga FC 1322 36 +59 11 6.7 +4.3
FK RFS 1238 35 +6 8 6.5 +1.5
Metta 1146 30 +45 9 3.0 +6.0
Daugavpils 1005 11 -30 0 2.4 -2.4

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 DAU FR JEL LIE MET RIG SJ VEN
Daugavpils —
1-1-2
2.73
0-1-3
1.97
0-0-4
1.92
0-2-2
4.71
0-1-3
2.48
1-0-3
2.62
0-0-4
1.82
FK RFS
2-1-1
8.43
 —
2-0-2
4.81
2-1-1
4.23
2-2-0
7.61
0-3-1
5.26
0-0-4
4.54
1-1-2
3.57
Jelgava
3-1-0
9.29
2-0-2
6.26
 —
3-0-1
4.94
2-0-2
8.47
2-1-1
6.32
1-1-2
5.95
3-0-1
4.30
Liepaja
4-0-0
9.35
1-1-2
6.85
1-0-3
6.13
 —
2-0-2
8.68
2-2-0
6.38
2-1-1
6.62
0-2-2
5.15
Metta
2-2-0
6.35
0-2-2
3.51
2-0-2
2.70
2-0-2
2.50
 —
1-1-2
3.13
0-0-4
3.00
1-1-2
2.22
Riga FC
3-1-0
8.71
1-3-0
5.80
1-1-2
4.75
0-2-2
4.68
2-1-1
7.99
 —
1-2-1
4.78
0-2-2
4.02
Spartaks Jurmala
3-0-1
8.57
4-0-0
6.53
2-1-1
5.11
1-1-2
4.47
4-0-0
8.15
1-2-1
6.29
 —
2-0-2
4.05
Ventspils
4-0-0
9.47
2-1-1
7.54
1-0-3
6.78
2-2-0
5.92
2-1-1
9.00
2-2-0
7.07
2-0-2
7.05
 —

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 0.83 +11.2
Allowed 0.78 -10.4
Differential 0.97 +6.5

Scoreline Distribution

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

↓ Scored | Allowed →012345+Total
08.04%12.50%8.04%4.91%0.89%0.45%34.82%
112.50%9.82%5.80%2.23%0.89%0.45%31.70%
28.04%5.80%3.57%1.79%——19.20%
34.91%2.23%1.79%0.89%0.89%—10.71%
40.89%0.89%—0.89%——2.68%
5+0.45%0.45%————0.89%
Total34.82%31.70%19.20%10.71%2.68%0.89%100%

Summary Statistics

Scored Allowed Difference
Mean 1.17 1.17 +0.00
SD 1.15 1.15 1.72
CV 0.98 0.98 —
Max 5 5 +5
Min 0 0 -5

Games Played: 112

↓ Scored | Allowed →012345+Total
07.14%21.43%21.43%14.29%3.57%3.57%71.43%
13.57%—3.57%3.57%3.57%—14.29%
2—3.57%7.14%———10.71%
3———3.57%——3.57%
4———————
5+———————
Total10.71%25.00%32.14%21.43%7.14%3.57%100%

Summary Statistics

Scored Allowed Difference
Mean 0.46 2.00 -1.54
SD 0.84 1.25 1.45
CV 1.81 0.62 —
Max 3 5 +1
Min 0 0 -5

Games Played: 28

↓ Scored | Allowed →012345+Total
010.71%7.14%14.29%3.57%3.57%—39.29%
121.43%17.86%7.14%3.57%——50.00%
23.57%—————3.57%
33.57%—3.57%———7.14%
4———————
5+———————
Total39.29%25.00%25.00%7.14%3.57%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.79 1.11 -0.32
SD 0.83 1.13 1.56
CV 1.06 1.02 —
Max 3 4 +3
Min 0 0 -4

Games Played: 28

↓ Scored | Allowed →012345+Total
07.14%21.43%—7.14%——35.71%
114.29%3.57%3.57%———21.43%
217.86%7.14%————25.00%
3—7.14%3.57%———10.71%
43.57%——3.57%——7.14%
5+———————
Total42.86%39.29%7.14%10.71%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.32 0.86 +0.46
SD 1.28 0.97 1.62
CV 0.97 1.13 —
Max 4 3 +4
Min 0 0 -3

Games Played: 28

↓ Scored | Allowed →012345+Total
010.71%10.71%3.57%———25.00%
121.43%3.57%3.57%7.14%——35.71%
23.57%—7.14%10.71%——21.43%
310.71%3.57%————14.29%
4———3.57%——3.57%
5+———————
Total46.43%17.86%14.29%21.43%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.36 1.11 +0.25
SD 1.13 1.23 1.48
CV 0.83 1.11 —
Max 4 3 +3
Min 0 0 -2

Games Played: 28

↓ Scored | Allowed →012345+Total
0—7.14%17.86%7.14%——32.14%
17.14%14.29%7.14%3.57%3.57%—35.71%
2—10.71%3.57%3.57%——17.86%
33.57%3.57%3.57%3.57%——14.29%
4———————
5+———————
Total10.71%35.71%32.14%17.86%3.57%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.14 1.68 -0.54
SD 1.04 1.02 1.57
CV 0.91 0.61 —
Max 3 4 +3
Min 0 0 -3

Games Played: 28

↓ Scored | Allowed →012345+Total
014.29%17.86%—3.57%——35.71%
17.14%21.43%7.14%———35.71%
27.14%7.14%7.14%———21.43%
37.14%—————7.14%
4———————
5+———————
Total35.71%46.43%14.29%3.57%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.00 0.86 +0.14
SD 0.94 0.80 1.30
CV 0.94 0.94 —
Max 3 3 +3
Min 0 0 -3

Games Played: 28

↓ Scored | Allowed →012345+Total
010.71%7.14%3.57%3.57%——25.00%
114.29%3.57%7.14%———25.00%
217.86%7.14%————25.00%
37.14%3.57%——3.57%—14.29%
4—7.14%————7.14%
5+—3.57%————3.57%
Total50.00%32.14%10.71%3.57%3.57%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.64 0.79 +0.86
SD 1.39 1.03 1.72
CV 0.85 1.31 —
Max 5 4 +4
Min 0 0 -3

Games Played: 28

↓ Scored | Allowed →012345+Total
03.57%7.14%3.57%———14.29%
110.71%14.29%7.14%——3.57%35.71%
214.29%10.71%3.57%———28.57%
37.14%—3.57%—3.57%—14.29%
43.57%—————3.57%
5+3.57%—————3.57%
Total42.86%32.14%17.86%—3.57%3.57%100%

Summary Statistics

Scored Allowed Difference
Mean 1.68 1.00 +0.68
SD 1.22 1.25 1.87
CV 0.73 1.25 —
Max 5 5 +5
Min 0 0 -4

Games Played: 28

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
Ventspils 1385 51 53.03 -2.03 44.0% 35 40 48 53 59 65 68
Jelgava 1363 51 44.80 +6.20 89.0% 26 34 41 45 48 56 70
Riga FC 1322 36 41.19 -5.19 24.0% 25 29 37 41 45 51 58
Spartaks Jurmala 1321 55 42.92 +12.08 97.0% 27 34 38 43 47 52 63
Liepaja 1305 42 50.13 -8.13 11.0% 36 40 45 50 54 62 65
FK RFS 1238 35 38.43 -3.43 32.0% 25 29 34 38 43 48 58
Metta 1146 30 24.33 +5.67 83.0% 8 14 20 23 28 36 43
Daugavpils 1005 11 17.13 -6.13 19.0% 5 8 13 17 21 25 30

Point Totals in Context

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

Home-Field Advantage Edge

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

Season Trends

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

Edges & Scoring

How these are measured

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

Home Edge
Share of matches won by the home team minus the share won by the away team.
No Edge: under 2.5% * Slight Edge: 2.5% to 6% * Clear Edge: 6% to 11% * Strong Edge: 11% 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
+16.96%
Strong Edge
47.32%22.32%30.36%
Elo Value
Home Edge: 59.52 Elo pts.
230 Elo
0.004 goals per Elo point
0600
Scoring Tilt
Expected
+0.37 goals
Neutral
-2+0.26+2

Title Race

How these are measured

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

Title-Race Openness
Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 3 * Open: 3 to 4 * Wide Open: 4 and up.
Champion Preseason Odds
Preseason probability that the eventual champion would finish 1st, from the simulation. The dot marks their rank across all teams, from longshot to favorite.
Preseason Favorite: 1st * Among the Favorites: 2nd * 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 0.09 * Tight Race: 0.09 to 0.16 * Comfortable: 0.16 to 0.3 * Runaway: 0.3 and up.
Title-Race Openness
2.8
Top-Heavy
12348
Champion Preseason Odds
7%
Spartaks Jurmala, 3rd of 8
LongshotFavorite
Title Margin
Expected
0.14/gm
Tight Race
00.210.5/gm

Simulation-Based Surprises

How these are measured

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

Luck Spread
Standard deviation of the gap between each team's actual points and their simulated average points. The gold line is the spread the model expected from chance alone.
As Expected: under 5.18 * Some Luck: 5.18 to 7.77 * Lucky: 7.77 to 10.36 * Wild Swing: 10.36 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 0.72 * Close: 0.72 to 1.08 * Off: 1.08 to 1.45 * Way Off: 1.45 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.
Luck Spread
Expected
6.74 points
Some Luck
06.4816
Average Finish Error
Expected
1.00
Close
00.902
Biggest Overachiever
Expected 93.75%
97.00%
Spartaks Jurmala
50100
Biggest Underachiever
Expected
11.00%
Liepaja
06.25%50
Season Outliers
Expected
1 of 8
Minimal Outliers
00.88

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 0.24 * Even: 0.24 to 0.27 * Top-Heavy: 0.27 to 0.28 * Lopsided: 0.28 and up.
Noll-Scully
Take a league where every match is a coin flip and nobody is better than anybody. You would still get a table, with a leader and a bottom club, purely by luck, and you can work out how far apart that table would be. This is the real table measured against it. At 1.00 the season was no more spread out than pure chance; at 2.00 it was twice as spread out, which takes genuine differences in quality. Dividing by the luck figure is what makes seasons of different lengths comparable, because a short season spreads a table by luck alone far more than a long one does. Elo SD in the corner is the same question in rating points: how far apart the teams finished on the ratings.
Coin-Flip Parity: under 2.55 * Moderate Separation: 2.55 to 2.8 * Strong Separation: 2.8 to 2.95 * Wide Separation: 2.95 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 82% * Slight Edge: 82% to 86.5% * Clear Edge: 86.5% to 91.5% * Wide Edge: 91.5% 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 97% * Clear Edge: 97% to 98% * Strong Edge: 98% to 99% * Dominant: 99% and up.
Close Games
Share of matches decided by 1 goal or fewer, draws included. The gold line is how many close games the matchups and the scoring value of an Elo point predict.
Few: under 49% * Some Drama: 49% to 51% * Frequent: 51% to 57.5% * Very Frequent: 57.5% 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 21% * Occasional: 21% to 27.5% * Frequent: 27.5% to 32% * Very Frequent: 32% and up.
Gini Index
0.19
Balanced
00.240.5
Noll-Scully
Elo SD: 127.94
2.03
Coin-Flip Parity
12.552.953.5
Interquartile Edge
66%
Even
50%82%100%
Best vs. Worst
Baseline
90%
Even
50%91%100%
Close Games
Expected
64%
Very Frequent
0%62%100%
Blowouts
Expected
15%
Rare
0%15%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 0.51 * Slight Separation: 0.51 to 0.55 * Notable Separation: 0.55 to 0.58 * Lopsided: 0.58 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 0.62 * Some Carryover: 0.62 to 0.76 * Strong Carryover: 0.76 to 0.83 * Near-Lock: 0.83 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 13.5% * As Expected: 13.5% to 16.5% * Upset-Prone: 16.5% to 18.5% * Very Upset-Prone: 18.5% and up.
Clear Favorite Upset Rate
Share of matches the underdog won, counting only games with a clear favorite (at least 60% likely to win once a draw is set aside). The gold line is how often the model expected these favorites to slip.
Solid Favorites: under 12% * As Expected: 12% to 14% * Shaky Favorites: 14% to 15% * Very Shaky: 15% and up.
Brier Score
Expected
0.59
Predictable
00.572
Matchup Imbalance
0.43
Very Even
00.5
Strangeness
Expected
1.14
Wilder Than Modeled
01.002
Repeatability
0.57
Weak Carryover
00.620.761
Upset Rate
Expected
25%
Very Upset-Prone
0%22%50%
Clear Favorite Upset Rate
Expected
25%
Very Shaky
0%19%50%

Calibration

How these are measured

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

Probability calibration
An all-in-one chi-square test of the model's probabilities. Matches are grouped by how confident the model was, and within each group the predicted and actual counts of home wins, draws, and away wins are compared. The p-value is plotted; above 0.05 means well-calibrated.
Miscalibrated: under 0.05 * Borderline: 0.05 to 0.1 * Well Calibrated: 0.1 to 0.5 * Excellent: 0.5 and up.
Calibration slope
Checks whether the spread of the probabilities is right. Each probability is turned into log-odds and a line is fit predicting the actual results. A slope of 1.00 is perfect; below 1 is overconfidence (favorites lost more than their odds implied); above 1 is under-confidence.
Overconfident: under 0.85 * Calibrated: 0.85 to 1.15 * Underconfident: 1.15 to 1.3 * Very Underconfident: 1.3 and up.
Calibration error (ECE)
The average gap between the model's stated chances and how often the predicted result actually happened. Smaller is better. The gold line is the noise ceiling, the error luck alone can produce even with perfect probabilities; below it, the model's error is no larger than chance.
Well Within Noise: under 0.16 * Near Noise Ceiling: 0.16 to 0.24 * Above Noise: 0.24 to 0.31 * Well Above Noise: 0.31 and up.
Probability calibration
0.34
Well Calibrated
0.010.050.10.51
Calibration slope
Ideal
0.69
Overconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.091
Well Within Noise
00.1570.4

Final Table Odds

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

Team12345678
Spartaks Jurmala7.00%14.00%18.00%18.00%27.00%15.00%1.00%—
Jelgava7.00%16.00%30.00%19.00%15.00%11.00%2.00%—
Ventspils50.00%23.00%13.00%7.00%3.00%4.00%——
Liepaja30.00%34.00%11.00%16.00%6.00%3.00%——
Riga FC5.00%9.00%19.00%15.00%28.00%20.00%4.00%—
FK RFS1.00%4.00%9.00%22.00%19.00%41.00%4.00%—
Metta———3.00%2.00%6.00%70.00%19.00%
Daugavpils——————19.00%81.00%

Points Required Per Position

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

Next-Season Status

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

Team Same level Qualified for relegation playoff Direct relegation
FK RFS 96.00% 4.00% —
Jelgava 98.00% 2.00% —
Liepaja 100% — —
Riga FC 96.00% 4.00% —
Spartaks Jurmala 99.00% 1.00% —
Ventspils 100% — —
Metta 11.00% 70.00% 19.00%
Daugavpils — 19.00% 81.00%

Overall Game Log

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

Date Opponent ScoreExcitement Pre Elo Opp Elo Win % Tie % Loss %Proj. Margin Elo Δ Points
2016-03-11 Spartaks Jurmala L 1-255.7 1349 1177 65.27% 20.64% 14.09%+1.00 -15.1 0
2016-03-11 @ Liepaja W 2-155.7 1177 1349 14.09% 20.64% 65.27%-1.00 +15.1 3
2016-03-12 FK RFS W 4-033.9 1332 1312 48.97% 23.29% 27.74%+0.34 +28.2 3
2016-03-12 @ Jelgava L 0-433.9 1312 1332 27.74% 23.29% 48.97%-0.34 -28.2 0
2016-03-12 Riga FC D 1-157.1 1380 1312 54.78% 22.70% 22.52%+0.55 -1.8 1
2016-03-12 @ Ventspils D 1-157.1 1312 1380 22.52% 22.70% 54.78%-0.55 +1.8 1
2016-03-13 Daugavpils W 2-146.5 1098 1123 43.11% 23.60% 33.29%+0.15 +8.6 3
2016-03-13 @ Metta L 1-246.5 1123 1098 33.29% 23.60% 43.11%-0.15 -8.6 0
2016-03-19 Daugavpils W 3-030.7 1192 1114 55.98% 22.53% 21.49%+0.60 +17.3 6
2016-03-19 @ Spartaks Jurmala L 0-330.7 1114 1192 21.49% 22.53% 55.98%-0.60 -17.3 0
2016-03-19 Metta W 3-244.7 1284 1107 65.80% 20.50% 13.70%+1.03 +3.7 3
2016-03-19 @ FK RFS L 2-344.7 1107 1284 13.70% 20.50% 65.80%-1.03 -3.7 3
2016-03-20 Jelgava D 1-156.6 1314 1360 40.10% 23.66% 36.24%+0.06 -0.2 2
2016-03-20 @ Riga FC D 1-156.6 1360 1314 36.24% 23.66% 40.10%-0.06 +0.2 4
2016-03-20 Liepaja D 2-263.3 1378 1333 52.09% 23.01% 24.90%+0.45 -1.1 2
2016-03-20 @ Ventspils D 2-263.3 1333 1378 24.90% 23.01% 52.09%-0.45 +1.1 1
2016-04-02 Riga FC W 1-047.3 1103 1314 20.21% 22.30% 57.49%-0.66 +14.3 6
2016-04-02 @ Metta L 0-147.3 1314 1103 57.49% 22.30% 20.21%+0.66 -14.3 2
2016-04-02 Spartaks Jurmala W 2-140.8 1377 1210 64.92% 20.74% 14.34%+0.99 +4.1 5
2016-04-02 @ Ventspils L 1-240.8 1210 1377 14.34% 20.74% 64.92%-0.99 -4.1 6
2016-04-03 FK RFS W 1-046.7 1097 1288 22.07% 22.63% 55.30%-0.57 +13.8 3
2016-04-03 @ Daugavpils L 0-146.7 1288 1097 55.30% 22.63% 22.07%+0.57 -13.8 3
2016-04-04 Liepaja L 0-146.9 1360 1335 49.75% 23.23% 27.02%+0.37 -12.6 4
2016-04-04 @ Jelgava W 1-046.9 1335 1360 27.02% 23.23% 49.75%-0.37 +12.6 4
2016-04-16 Jelgava W 3-039.9 1205 1348 27.30% 23.25% 49.44%-0.36 +34.3 9
2016-04-16 @ Spartaks Jurmala L 0-339.9 1348 1205 49.44% 23.25% 27.30%+0.36 -34.3 4
2016-04-16 Ventspils L 0-529.4 1111 1381 15.43% 21.11% 63.47%-0.92 -20.5 3
2016-04-16 @ Daugavpils W 5-029.4 1381 1111 63.47% 21.11% 15.43%+0.92 +20.5 8
2016-04-17 FK RFS D 0-050.6 1300 1274 49.72% 23.23% 27.04%+0.37 -1.4 3
2016-04-17 @ Riga FC D 0-050.6 1274 1300 27.04% 23.23% 49.72%-0.37 +1.4 4
2016-04-17 Liepaja L 0-231.9 1117 1347 18.56% 21.96% 59.48%-0.74 -10.4 6
2016-04-17 @ Metta W 2-031.9 1347 1117 59.48% 21.96% 18.56%+0.74 +10.4 7
2016-04-22 Jelgava W 1-038.1 1402 1314 57.06% 22.37% 20.57%+0.64 +6.1 11
2016-04-22 @ Ventspils L 0-138.1 1314 1402 20.57% 22.37% 57.06%-0.64 -6.1 4
2016-04-23 Riga FC L 0-232.4 1090 1298 20.46% 22.35% 57.19%-0.65 -11.4 3
2016-04-23 @ Daugavpils W 2-032.4 1298 1090 57.19% 22.35% 20.46%+0.65 +11.4 6
2016-04-23 Spartaks Jurmala L 0-138.8 1107 1240 28.44% 23.35% 48.22%-0.32 -8.0 6
2016-04-23 @ Metta W 1-038.8 1240 1107 48.22% 23.35% 28.44%+0.32 +8.0 12
2016-04-24 Liepaja W 1-043.8 1276 1358 34.98% 23.64% 41.37%-0.10 +10.8 7
2016-04-24 @ FK RFS L 0-143.8 1358 1276 41.37% 23.64% 34.98%+0.10 -10.8 7
2016-04-30 Daugavpils W 3-134.6 1308 1079 70.00% 19.18% 10.83%+1.25 +5.3 7
2016-04-30 @ Jelgava L 1-334.6 1079 1308 10.83% 19.18% 70.00%-1.25 -5.3 3
2016-04-30 FK RFS W 2-037.6 1248 1286 41.14% 23.65% 35.21%+0.09 +18.0 15
2016-04-30 @ Spartaks Jurmala L 0-237.6 1286 1248 35.21% 23.65% 41.14%-0.09 -18.0 7
2016-04-30 Metta W 2-027.2 1408 1099 75.62% 16.90% 7.48%+1.60 +4.1 14
2016-04-30 @ Ventspils L 0-227.2 1099 1408 7.48% 16.90% 75.62%-1.60 -4.1 6
2016-04-30 Riga FC W 3-033.4 1347 1310 51.16% 23.11% 25.74%+0.42 +20.2 10
2016-04-30 @ Liepaja L 0-333.4 1310 1347 25.74% 23.11% 51.16%-0.42 -20.2 6
2016-05-08 Jelgava W 3-041.7 1095 1313 19.58% 22.18% 58.24%-0.69 +39.6 9
2016-05-08 @ Metta L 0-341.7 1313 1095 58.24% 22.18% 19.58%+0.69 -39.6 7
2016-05-08 Spartaks Jurmala D 0-050.5 1290 1266 49.49% 23.25% 27.26%+0.36 -1.4 7
2016-05-08 @ Riga FC D 0-050.5 1266 1290 27.26% 23.25% 49.49%-0.36 +1.4 16
2016-05-08 Ventspils L 1-246.2 1268 1412 27.18% 23.24% 49.57%-0.36 -7.3 7
2016-05-08 @ FK RFS W 2-146.2 1412 1268 49.57% 23.24% 27.18%+0.36 +7.3 17
2016-05-09 Liepaja L 0-328.0 1073 1367 13.88% 20.57% 65.55%-1.02 -11.4 3
2016-05-09 @ Daugavpils W 3-028.0 1367 1073 65.55% 20.57% 13.88%+1.02 +11.5 13
2016-05-13 Ventspils D 1-157.1 1288 1419 28.66% 23.36% 47.98%-0.31 +1.1 8
2016-05-13 @ Riga FC D 1-157.1 1419 1288 47.98% 23.36% 28.66%+0.31 -1.1 18
2016-05-14 Jelgava W 1-040.3 1261 1273 44.80% 23.54% 31.66%+0.21 +8.8 10
2016-05-14 @ FK RFS L 0-140.3 1273 1261 31.66% 23.54% 44.80%-0.21 -8.8 7
2016-05-14 Liepaja L 0-140.8 1267 1379 31.09% 23.51% 45.40%-0.23 -8.6 16
2016-05-14 @ Spartaks Jurmala W 1-040.8 1379 1267 45.40% 23.51% 31.09%+0.23 +8.6 16
2016-05-15 Metta L 0-141.2 1062 1134 36.32% 23.67% 40.02%-0.06 -9.8 3
2016-05-15 @ Daugavpils W 1-041.2 1134 1062 40.02% 23.67% 36.32%+0.06 +9.8 12
2016-05-26 Liepaja W 2-038.0 1418 1387 50.39% 23.18% 26.44%+0.39 +14.2 21
2016-05-26 @ Ventspils L 0-238.0 1387 1418 26.44% 23.18% 50.39%-0.39 -14.2 16
2016-05-27 Spartaks Jurmala L 0-232.4 1052 1258 20.64% 22.39% 56.98%-0.64 -11.5 3
2016-05-27 @ Daugavpils W 2-032.4 1258 1052 56.98% 22.39% 20.64%+0.64 +11.5 19
2016-05-28 FK RFS D 1-155.3 1144 1270 29.30% 23.41% 47.29%-0.29 +1.0 13
2016-05-28 @ Metta D 1-155.3 1270 1144 47.29% 23.41% 29.30%+0.29 -1.0 11
2016-05-28 Riga FC W 2-147.1 1264 1289 43.07% 23.60% 33.33%+0.15 +8.6 10
2016-05-28 @ Jelgava L 1-247.1 1289 1264 33.33% 23.60% 43.07%-0.15 -8.6 8
2016-06-10 Ventspils W 5-145.1 1270 1432 25.06% 23.03% 51.91%-0.45 +38.9 22
2016-06-10 @ Spartaks Jurmala L 1-545.1 1432 1270 51.91% 23.03% 25.06%+0.45 -38.9 21
2016-06-11 Jelgava L 0-148.6 1373 1273 58.33% 22.16% 19.50%+0.69 -14.5 16
2016-06-11 @ Liepaja W 1-048.6 1273 1373 19.50% 22.16% 58.33%-0.69 +14.5 13
2016-06-11 Metta W 2-141.1 1281 1145 61.93% 21.46% 16.61%+0.85 +4.7 11
2016-06-11 @ Riga FC L 1-241.1 1145 1281 16.61% 21.46% 61.93%-0.85 -4.7 13
2016-06-12 Daugavpils D 0-051.1 1269 1041 69.95% 19.19% 10.86%+1.25 -4.0 12
2016-06-12 @ FK RFS D 0-051.1 1041 1269 10.86% 19.19% 69.95%-1.25 +4.0 4
2016-06-17 Metta W 3-027.1 1358 1140 69.15% 19.47% 11.38%+1.21 +9.3 19
2016-06-17 @ Liepaja L 0-327.1 1140 1358 11.38% 19.47% 69.15%-1.21 -9.4 13
2016-06-18 Daugavpils W 3-024.2 1393 1045 78.07% 15.73% 6.21%+1.77 +4.8 24
2016-06-18 @ Ventspils L 0-324.2 1045 1393 6.21% 15.73% 78.07%-1.77 -4.8 4
2016-06-18 Spartaks Jurmala L 0-144.2 1288 1309 43.53% 23.59% 32.88%+0.17 -11.2 13
2016-06-18 @ Jelgava W 1-044.2 1309 1288 32.88% 23.59% 43.53%-0.17 +11.2 25
2016-06-19 Riga FC D 1-155.7 1265 1285 43.67% 23.58% 32.75%+0.17 -0.6 13
2016-06-19 @ FK RFS D 1-155.7 1285 1265 32.75% 23.58% 43.67%-0.17 +0.6 12
2016-06-22 Ventspils W 4-359.0 1276 1398 29.76% 23.44% 46.80%-0.27 +10.4 16
2016-06-22 @ Jelgava L 3-459.0 1398 1276 46.80% 23.44% 29.76%+0.27 -10.4 24
2016-06-25 Metta W 4-132.5 1320 1131 66.78% 20.22% 13.00%+1.08 +9.0 28
2016-06-25 @ Spartaks Jurmala L 1-432.5 1131 1320 13.00% 20.22% 66.78%-1.08 -9.0 13
2016-06-26 Daugavpils W 2-028.1 1286 1040 71.29% 18.70% 10.00%+1.33 +5.6 15
2016-06-26 @ Riga FC L 0-228.1 1040 1286 10.00% 18.70% 71.29%-1.33 -5.6 4
2016-06-26 FK RFS W 3-139.0 1368 1264 58.71% 22.10% 19.19%+0.71 +9.3 22
2016-06-26 @ Liepaja L 1-339.0 1264 1368 19.19% 22.10% 58.71%-0.71 -9.3 13
2016-07-01 Liepaja D 0-051.2 1291 1377 34.50% 23.63% 41.86%-0.11 +0.4 16
2016-07-01 @ Riga FC D 0-051.2 1377 1291 41.86% 23.63% 34.50%+0.11 -0.4 23
2016-07-08 Daugavpils W 1-030.1 1377 1034 77.70% 15.91% 6.39%+1.75 +1.8 26
2016-07-08 @ Liepaja L 0-130.1 1034 1377 6.39% 15.91% 77.70%-1.75 -1.8 4
2016-07-10 FK RFS L 0-149.4 1388 1255 61.68% 21.52% 16.81%+0.84 -15.2 24
2016-07-10 @ Ventspils W 1-049.4 1255 1388 16.81% 21.52% 61.68%-0.84 +15.2 16
2016-07-10 Metta W 2-030.2 1287 1122 64.65% 20.81% 14.54%+0.97 +8.2 19
2016-07-10 @ Jelgava L 0-230.2 1122 1287 14.54% 20.81% 64.65%-0.97 -8.2 13
2016-07-10 Riga FC W 1-038.9 1329 1292 51.17% 23.10% 25.72%+0.42 +7.4 31
2016-07-10 @ Spartaks Jurmala L 0-138.9 1292 1329 25.72% 23.10% 51.17%-0.42 -7.4 16
2016-07-23 Daugavpils D 2-261.4 1114 1032 56.34% 22.48% 21.18%+0.61 -1.5 14
2016-07-23 @ Metta D 2-261.4 1032 1114 21.18% 22.48% 56.34%-0.61 +1.5 5
2016-07-24 Spartaks Jurmala W 4-352.9 1378 1337 51.74% 23.05% 25.21%+0.44 +6.3 29
2016-07-24 @ Liepaja L 3-452.9 1337 1378 25.21% 23.05% 51.74%-0.44 -6.3 31
2016-07-24 Ventspils L 1-248.1 1285 1373 34.18% 23.63% 42.20%-0.12 -8.8 16
2016-07-24 @ Riga FC W 2-148.1 1373 1285 42.20% 23.63% 34.18%+0.12 +8.8 27
2016-07-25 FK RFS W 2-035.2 1295 1270 49.61% 23.24% 27.15%+0.37 +14.6 22
2016-07-25 @ Jelgava L 0-235.2 1270 1295 27.15% 23.24% 49.61%-0.37 -14.6 16
2016-07-30 Daugavpils W 4-130.0 1330 1034 74.81% 17.27% 7.93%+1.55 +5.3 34
2016-07-30 @ Spartaks Jurmala L 1-430.0 1034 1330 7.93% 17.27% 74.81%-1.55 -5.3 5
2016-07-30 Ventspils L 2-358.3 1385 1381 46.88% 23.43% 29.69%+0.27 -10.7 29
2016-07-30 @ Liepaja W 3-258.3 1381 1385 29.69% 23.43% 46.88%-0.27 +10.7 30
2016-08-01 Metta W 3-028.7 1256 1112 62.69% 21.29% 16.02%+0.88 +13.2 19
2016-08-01 @ FK RFS L 0-328.7 1112 1256 16.02% 21.29% 62.69%-0.88 -13.2 14
2016-08-05 Spartaks Jurmala L 0-148.3 1392 1336 53.48% 22.86% 23.66%+0.50 -13.4 30
2016-08-05 @ Ventspils W 1-048.3 1336 1392 23.66% 22.86% 53.48%-0.50 +13.4 37
2016-08-06 Riga FC D 1-155.4 1099 1276 23.54% 22.84% 53.62%-0.51 +1.7 15
2016-08-06 @ Metta D 1-155.4 1276 1099 53.62% 22.84% 23.54%+0.51 -1.7 17
2016-08-08 FK RFS L 0-135.1 1029 1269 17.71% 21.75% 60.54%-0.79 -5.3 5
2016-08-08 @ Daugavpils W 1-035.1 1269 1029 60.54% 21.75% 17.71%+0.79 +5.3 22
2016-08-08 Liepaja W 3-254.7 1310 1374 37.43% 23.67% 38.89%-0.02 +9.2 25
2016-08-08 @ Jelgava L 2-354.7 1374 1310 38.89% 23.67% 37.43%+0.02 -9.2 29
2016-08-13 Daugavpils W 2-026.1 1379 1023 78.45% 15.53% 6.01%+1.80 +3.2 33
2016-08-13 @ Ventspils L 0-226.1 1023 1379 6.01% 15.53% 78.45%-1.80 -3.2 5
2016-08-13 Jelgava D 0-051.4 1349 1319 50.31% 23.18% 26.51%+0.39 -1.5 38
2016-08-13 @ Spartaks Jurmala D 0-051.4 1319 1349 26.51% 23.18% 50.31%-0.39 +1.5 26
2016-08-13 Metta L 2-361.9 1365 1101 72.60% 18.20% 9.20%+1.41 -15.7 29
2016-08-13 @ Liepaja W 3-261.9 1101 1365 9.20% 18.20% 72.60%-1.41 +15.7 18
2016-08-14 FK RFS W 1-039.9 1274 1274 46.41% 23.46% 30.14%+0.26 +8.4 20
2016-08-14 @ Riga FC L 0-139.9 1274 1274 30.14% 23.46% 46.41%-0.26 -8.4 22
2016-08-19 Liepaja D 1-156.1 1266 1349 34.79% 23.64% 41.57%-0.10 +0.4 23
2016-08-19 @ FK RFS D 1-156.1 1349 1266 41.57% 23.64% 34.79%+0.10 -0.4 30
2016-08-19 Spartaks Jurmala L 1-337.9 1117 1348 18.47% 21.94% 59.59%-0.74 -9.0 18
2016-08-19 @ Metta W 3-137.9 1348 1117 59.59% 21.94% 18.47%+0.74 +9.0 41
2016-08-20 Riga FC D 2-261.9 1020 1282 16.01% 21.29% 62.70%-0.88 +2.0 6
2016-08-20 @ Daugavpils D 2-261.9 1282 1020 62.70% 21.29% 16.01%+0.88 -2.0 21
2016-08-20 Ventspils W 2-039.9 1320 1382 37.86% 23.68% 38.47%-0.01 +19.2 29
2016-08-20 @ Jelgava L 0-239.9 1382 1320 38.47% 23.68% 37.86%+0.01 -19.2 33
2016-08-24 Jelgava D 0-050.9 1022 1339 12.46% 19.98% 67.56%-1.12 +3.7 7
2016-08-24 @ Daugavpils D 0-050.9 1339 1022 67.56% 19.98% 12.46%+1.12 -3.7 30
2016-08-24 Spartaks Jurmala L 0-237.7 1266 1356 33.85% 23.62% 42.53%-0.13 -17.4 23
2016-08-24 @ FK RFS W 2-037.7 1356 1266 42.53% 23.62% 33.85%+0.13 +17.4 44
2016-08-24 Ventspils D 1-156.0 1108 1363 16.56% 21.45% 61.99%-0.85 +2.7 19
2016-08-24 @ Metta D 1-156.0 1363 1108 61.99% 21.45% 16.56%+0.85 -2.7 34
2016-08-26 Liepaja L 0-142.5 1280 1349 36.89% 23.67% 39.44%-0.04 -9.9 21
2016-08-26 @ Riga FC W 1-042.5 1349 1280 39.44% 23.67% 36.89%+0.04 +9.9 33
2016-08-28 Daugavpils W 2-026.8 1336 1026 75.69% 16.87% 7.44%+1.61 +4.1 33
2016-08-28 @ Jelgava L 0-226.8 1026 1336 7.44% 16.87% 75.69%-1.61 -4.1 7
2016-08-28 FK RFS W 2-142.2 1374 1249 60.94% 21.67% 17.39%+0.80 +4.9 47
2016-08-28 @ Spartaks Jurmala L 1-242.2 1249 1374 17.39% 21.67% 60.94%-0.80 -4.9 23
2016-08-28 Metta W 2-028.3 1360 1110 71.56% 18.60% 9.84%+1.34 +5.5 37
2016-08-28 @ Ventspils L 0-228.3 1110 1360 9.84% 18.60% 71.56%-1.34 -5.5 19
2016-09-10 Jelgava L 0-135.4 1105 1340 18.13% 21.86% 60.01%-0.76 -5.4 19
2016-09-10 @ Metta W 1-035.4 1340 1105 60.01% 21.86% 18.13%+0.76 +5.4 36
2016-09-10 Liepaja L 0-132.6 1022 1359 11.38% 19.47% 69.15%-1.21 -3.4 7
2016-09-10 @ Daugavpils W 1-032.6 1359 1022 69.15% 19.47% 11.38%+1.21 +3.4 36
2016-09-10 Ventspils L 0-334.3 1244 1365 29.79% 23.44% 46.77%-0.27 -22.8 23
2016-09-10 @ FK RFS W 3-034.3 1365 1244 46.77% 23.44% 29.79%+0.27 +22.8 40
2016-09-11 Spartaks Jurmala D 1-156.4 1271 1379 31.49% 23.53% 44.98%-0.21 +0.7 22
2016-09-11 @ Riga FC D 1-156.4 1379 1271 44.98% 23.53% 31.49%+0.21 -0.7 48
2016-09-16 Jelgava W 1-045.0 1221 1345 29.47% 23.42% 47.12%-0.28 +12.0 26
2016-09-16 @ FK RFS L 0-145.0 1345 1221 47.12% 23.42% 29.47%+0.28 -12.0 36
2016-09-17 Liepaja D 0-052.3 1378 1362 48.50% 23.33% 28.18%+0.33 -1.2 49
2016-09-17 @ Spartaks Jurmala D 0-052.3 1362 1378 28.18% 23.33% 48.50%-0.33 +1.3 37
2016-09-17 Riga FC W 1-036.6 1388 1271 60.11% 21.84% 18.05%+0.77 +5.4 43
2016-09-17 @ Ventspils L 0-136.6 1271 1388 18.05% 21.84% 60.11%-0.77 -5.4 22
2016-09-18 Metta D 3-364.5 1018 1099 35.13% 23.65% 41.22%-0.09 +0.2 8
2016-09-18 @ Daugavpils D 3-364.5 1099 1018 41.22% 23.65% 35.13%+0.09 -0.2 20
2016-09-23 Ventspils D 0-052.5 1363 1394 42.30% 23.62% 34.07%+0.13 -0.5 38
2016-09-23 @ Liepaja D 0-052.5 1394 1363 34.07% 23.62% 42.30%-0.13 +0.5 44
2016-09-24 FK RFS D 1-155.2 1099 1233 28.32% 23.34% 48.35%-0.32 +1.1 21
2016-09-24 @ Metta D 1-155.2 1233 1099 48.35% 23.34% 28.32%+0.32 -1.1 27
2016-09-24 Spartaks Jurmala W 2-156.5 1018 1377 10.32% 18.89% 70.79%-1.30 +16.2 11
2016-09-24 @ Daugavpils L 1-256.5 1377 1018 70.79% 18.89% 10.32%+1.30 -16.2 49
2016-09-25 Riga FC W 1-037.7 1333 1266 54.75% 22.70% 22.55%+0.55 +6.6 39
2016-09-25 @ Jelgava L 0-137.7 1266 1333 22.55% 22.70% 54.75%-0.55 -6.6 22
2016-09-30 Jelgava L 1-349.2 1363 1340 49.41% 23.26% 27.33%+0.36 -20.4 38
2016-09-30 @ Liepaja W 3-149.2 1340 1363 27.33% 23.26% 49.41%-0.36 +20.4 42
2016-10-01 Daugavpils W 2-029.2 1232 1035 67.46% 20.01% 12.53%+1.11 +7.1 30
2016-10-01 @ FK RFS L 0-229.2 1035 1232 12.53% 20.01% 67.46%-1.11 -7.1 11
2016-10-01 Metta W 2-140.3 1259 1100 64.15% 20.94% 14.91%+0.95 +4.2 25
2016-10-01 @ Riga FC L 1-240.3 1100 1259 14.91% 20.94% 64.15%-0.95 -4.2 21
2016-10-01 Ventspils L 0-145.5 1361 1394 41.85% 23.63% 34.52%+0.11 -10.9 49
2016-10-01 @ Spartaks Jurmala W 1-045.5 1394 1361 34.52% 23.63% 41.85%-0.11 +10.9 47
2016-10-15 Liepaja W 3-150.5 1096 1342 17.22% 21.63% 61.15%-0.81 +24.7 24
2016-10-15 @ Metta L 1-350.5 1342 1096 61.15% 21.63% 17.22%+0.81 -24.7 38
2016-10-16 Riga FC D 0-050.2 1239 1264 43.09% 23.60% 33.31%+0.15 -0.6 31
2016-10-16 @ FK RFS D 0-050.2 1264 1239 33.31% 23.60% 43.09%-0.15 +0.6 26
2016-10-16 Spartaks Jurmala W 2-037.1 1360 1350 47.79% 23.37% 28.83%+0.30 +15.3 45
2016-10-16 @ Jelgava L 0-237.1 1350 1360 28.83% 23.37% 47.79%-0.30 -15.3 49
2016-10-16 Ventspils L 0-425.9 1028 1405 9.45% 18.36% 72.20%-1.38 -10.0 11
2016-10-16 @ Daugavpils W 4-025.9 1405 1028 72.20% 18.36% 9.45%+1.38 +10.0 50
2016-10-19 Jelgava W 1-045.1 1264 1376 31.09% 23.51% 45.40%-0.23 +11.7 29
2016-10-19 @ Riga FC L 0-145.1 1376 1264 45.40% 23.51% 31.09%+0.23 -11.6 45
2016-10-21 FK RFS L 0-147.4 1318 1238 56.12% 22.51% 21.37%+0.60 -14.0 38
2016-10-21 @ Liepaja W 1-047.4 1238 1318 21.37% 22.51% 56.12%-0.60 +14.0 34
2016-10-22 Jelgava L 1-255.3 1415 1364 52.86% 22.93% 24.21%+0.48 -12.5 50
2016-10-22 @ Ventspils W 2-155.3 1364 1415 24.21% 22.93% 52.86%-0.48 +12.5 48
2016-10-22 Metta W 2-029.1 1334 1121 68.81% 19.58% 11.61%+1.19 +6.6 52
2016-10-22 @ Spartaks Jurmala L 0-229.1 1121 1334 11.61% 19.58% 68.81%-1.19 -6.6 24
2016-10-23 Daugavpils W 3-025.8 1276 1018 72.18% 18.36% 9.46%+1.38 +7.7 32
2016-10-23 @ Riga FC L 0-325.8 1018 1276 9.46% 18.36% 72.18%-1.38 -7.7 11
2016-10-29 Jelgava L 0-131.9 1010 1376 9.94% 18.66% 71.40%-1.33 -3.0 11
2016-10-29 @ Daugavpils W 1-031.9 1376 1010 71.40% 18.66% 9.94%+1.33 +3.0 51
2016-10-29 Riga FC D 2-262.0 1304 1283 49.06% 23.28% 27.66%+0.35 -0.9 39
2016-10-29 @ Liepaja D 2-262.0 1283 1304 27.66% 23.28% 49.06%-0.35 +0.9 33
2016-10-29 Spartaks Jurmala L 0-237.6 1252 1341 34.09% 23.62% 42.29%-0.13 -17.5 34
2016-10-29 @ FK RFS W 2-037.6 1341 1252 42.29% 23.62% 34.09%+0.13 +17.5 55
2016-10-29 Ventspils W 2-155.6 1114 1403 14.22% 20.69% 65.09%-0.99 +15.1 27
2016-10-29 @ Metta L 1-255.6 1403 1114 65.09% 20.69% 14.22%+0.99 -15.1 50
2016-11-05 Daugavpils W 1-030.8 1303 1007 74.78% 17.28% 7.94%+1.54 +2.3 42
2016-11-05 @ Liepaja L 0-130.8 1007 1303 7.94% 17.28% 74.78%-1.54 -2.3 11
2016-11-05 FK RFS D 1-156.9 1388 1235 63.57% 21.08% 15.35%+0.92 -2.8 51
2016-11-05 @ Ventspils D 1-156.9 1235 1388 15.35% 21.08% 63.57%-0.92 +2.9 35
2016-11-05 Metta L 1-256.9 1379 1129 71.60% 18.59% 9.81%+1.35 -16.4 51
2016-11-05 @ Jelgava W 2-156.9 1129 1379 9.81% 18.59% 71.60%-1.35 +16.4 30
2016-11-05 Riga FC L 0-342.1 1358 1284 55.52% 22.60% 21.88%+0.58 -38.0 55
2016-11-05 @ Spartaks Jurmala W 3-042.1 1284 1358 21.88% 22.60% 55.52%-0.58 +38.0 36

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 2016-08-13 9.20% Metta 1101 3 @ Liepaja 1365 2
2 2016-11-05 9.81% Metta 1129 2 @ Jelgava 1379 1
3 2016-09-24 10.32% @ Daugavpils 1018 2 Spartaks Jurmala 1377 1
4 2016-03-11 14.09% Spartaks Jurmala 1177 2 @ Liepaja 1349 1
5 2016-10-29 14.22% @ Metta 1114 2 Ventspils 1403 1
6 2016-07-10 16.81% FK RFS 1255 1 @ Ventspils 1388 0
7 2016-10-15 17.22% @ Metta 1096 3 Liepaja 1342 1
8 2016-06-11 19.50% Jelgava 1273 1 @ Liepaja 1373 0
9 2016-05-08 19.58% @ Metta 1095 3 Jelgava 1313 0
10 2016-04-02 20.21% @ Metta 1103 1 Riga FC 1314 0
11 2016-10-21 21.37% FK RFS 1238 1 @ Liepaja 1318 0
12 2016-11-05 21.88% Riga FC 1284 3 @ Spartaks Jurmala 1358 0
13 2016-04-03 22.07% @ Daugavpils 1097 1 FK RFS 1288 0
14 2016-08-05 23.66% Spartaks Jurmala 1336 1 @ Ventspils 1392 0
15 2016-10-22 24.21% Jelgava 1364 2 @ Ventspils 1415 1
16 2016-06-10 25.06% @ Spartaks Jurmala 1270 5 Ventspils 1432 1
17 2016-04-04 27.02% Liepaja 1335 1 @ Jelgava 1360 0
18 2016-04-16 27.30% @ Spartaks Jurmala 1205 3 Jelgava 1348 0
19 2016-09-30 27.33% Jelgava 1340 3 @ Liepaja 1363 1
20 2016-09-16 29.47% @ FK RFS 1221 1 Jelgava 1345 0
21 2016-07-30 29.69% Ventspils 1381 3 @ Liepaja 1385 2
22 2016-06-22 29.76% @ Jelgava 1276 4 Ventspils 1398 3
23 2016-10-19 31.09% @ Riga FC 1264 1 Jelgava 1376 0
24 2016-06-18 32.88% Spartaks Jurmala 1309 1 @ Jelgava 1288 0
25 2016-10-01 34.52% Ventspils 1394 1 @ Spartaks Jurmala 1361 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 2016-05-08 39.64 @ Metta 3 1095 19.58% Jelgava 0 1313 58.24% 22.18%
2 2016-06-10 38.93 @ Spartaks Jurmala 5 1270 25.06% Ventspils 1 1432 51.91% 23.03%
3 2016-11-05 37.97 Riga FC 3 1284 21.88% @ Spartaks Jurmala 0 1358 55.52% 22.60%
4 2016-04-16 34.27 @ Spartaks Jurmala 3 1205 27.30% Jelgava 0 1348 49.44% 23.25%
5 2016-03-12 28.15 @ Jelgava 4 1332 48.97% FK RFS 0 1312 27.74% 23.29%
6 2016-10-15 24.70 @ Metta 3 1096 17.22% Liepaja 1 1342 61.15% 21.63%
7 2016-09-10 22.85 Ventspils 3 1365 46.77% @ FK RFS 0 1244 29.79% 23.44%
8 2016-04-16 20.46 Ventspils 5 1381 63.47% @ Daugavpils 0 1111 15.43% 21.11%
9 2016-09-30 20.43 Jelgava 3 1340 27.33% @ Liepaja 1 1363 49.41% 23.26%
10 2016-04-30 20.24 @ Liepaja 3 1347 51.16% Riga FC 0 1310 25.74% 23.11%
11 2016-08-20 19.24 @ Jelgava 2 1320 37.86% Ventspils 0 1382 38.47% 23.68%
12 2016-04-30 17.98 @ Spartaks Jurmala 2 1248 41.14% FK RFS 0 1286 35.21% 23.65%
13 2016-10-29 17.53 Spartaks Jurmala 2 1341 42.29% @ FK RFS 0 1252 34.09% 23.62%
14 2016-08-24 17.43 Spartaks Jurmala 2 1356 42.53% @ FK RFS 0 1266 33.85% 23.62%
15 2016-03-19 17.31 @ Spartaks Jurmala 3 1192 55.98% Daugavpils 0 1114 21.49% 22.53%
16 2016-11-05 16.37 Metta 2 1129 9.81% @ Jelgava 1 1379 71.60% 18.59%
17 2016-09-24 16.22 @ Daugavpils 2 1018 10.32% Spartaks Jurmala 1 1377 70.79% 18.89%
18 2016-08-13 15.70 Metta 3 1101 9.20% @ Liepaja 2 1365 72.60% 18.20%
19 2016-10-16 15.31 @ Jelgava 2 1360 47.79% Spartaks Jurmala 0 1350 28.83% 23.37%
20 2016-07-10 15.25 FK RFS 1 1255 16.81% @ Ventspils 0 1388 61.68% 21.52%
21 2016-03-11 15.12 Spartaks Jurmala 2 1177 14.09% @ Liepaja 1 1349 65.27% 20.64%
22 2016-10-29 15.09 @ Metta 2 1114 14.22% Ventspils 1 1403 65.09% 20.69%
23 2016-07-25 14.58 @ Jelgava 2 1295 49.61% FK RFS 0 1270 27.15% 23.24%
24 2016-06-11 14.50 Jelgava 1 1273 19.50% @ Liepaja 0 1373 58.33% 22.16%
25 2016-04-02 14.31 @ Metta 1 1103 20.21% Riga FC 0 1314 57.49% 22.30%

Most & Least Exciting Games

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

# Date Excitement Winning Team Losing Team Tie %
Team Score Elo Win % Team Score Elo Win %
1 2016-09-18 64.5 @ Daugavpils 3 1018 35.13% Metta 3 1099 41.22% 23.65%
2 2016-03-20 63.3 @ Ventspils 2 1378 52.09% Liepaja 2 1333 24.90% 23.01%
3 2016-10-29 62.0 @ Liepaja 2 1304 49.06% Riga FC 2 1283 27.66% 23.28%
4 2016-08-13 61.9 Metta 3 1101 9.20% @ Liepaja 2 1365 72.60% 18.20%
5 2016-08-20 61.9 @ Daugavpils 2 1020 16.01% Riga FC 2 1282 62.70% 21.29%
6 2016-07-23 61.4 @ Metta 2 1114 56.34% Daugavpils 2 1032 21.18% 22.48%
7 2016-06-22 59.0 @ Jelgava 4 1276 29.76% Ventspils 3 1398 46.80% 23.44%
8 2016-07-30 58.3 Ventspils 3 1381 29.69% @ Liepaja 2 1385 46.88% 23.43%
9 2016-03-12 57.1 @ Ventspils 1 1380 54.78% Riga FC 1 1312 22.52% 22.70%
10 2016-05-13 57.1 @ Riga FC 1 1288 28.66% Ventspils 1 1419 47.98% 23.36%
11 2016-11-05 56.9 @ Ventspils 1 1388 63.57% FK RFS 1 1235 15.35% 21.08%
12 2016-11-05 56.9 Metta 2 1129 9.81% @ Jelgava 1 1379 71.60% 18.59%
13 2016-03-20 56.6 @ Riga FC 1 1314 40.10% Jelgava 1 1360 36.24% 23.66%
14 2016-09-24 56.5 @ Daugavpils 2 1018 10.32% Spartaks Jurmala 1 1377 70.79% 18.89%
15 2016-09-11 56.4 @ Riga FC 1 1271 31.49% Spartaks Jurmala 1 1379 44.98% 23.53%
16 2016-08-19 56.1 @ FK RFS 1 1266 34.79% Liepaja 1 1349 41.57% 23.64%
17 2016-08-24 56.0 @ Metta 1 1108 16.56% Ventspils 1 1363 61.99% 21.45%
18 2016-03-11 55.7 Spartaks Jurmala 2 1177 14.09% @ Liepaja 1 1349 65.27% 20.64%
19 2016-06-19 55.7 @ FK RFS 1 1265 43.67% Riga FC 1 1285 32.75% 23.58%
20 2016-10-29 55.6 @ Metta 2 1114 14.22% Ventspils 1 1403 65.09% 20.69%
21 2016-08-06 55.4 @ Metta 1 1099 23.54% Riga FC 1 1276 53.62% 22.84%
22 2016-05-28 55.3 @ Metta 1 1144 29.30% FK RFS 1 1270 47.29% 23.41%
23 2016-10-22 55.3 Jelgava 2 1364 24.21% @ Ventspils 1 1415 52.86% 22.93%
24 2016-09-24 55.2 @ Metta 1 1099 28.32% FK RFS 1 1233 48.35% 23.34%
25 2016-08-08 54.7 @ Jelgava 3 1310 37.43% Liepaja 2 1374 38.89% 23.67%
# Date Excitement Winning Team Losing Team Tie %
Team Score Elo Win % Team Score Elo Win %
1 2016-06-18 24.2 @ Ventspils 3 1393 78.07% Daugavpils 0 1045 6.21% 15.73%
2 2016-10-23 25.8 @ Riga FC 3 1276 72.18% Daugavpils 0 1018 9.46% 18.36%
3 2016-10-16 25.9 Ventspils 4 1405 72.20% @ Daugavpils 0 1028 9.45% 18.36%
4 2016-08-13 26.1 @ Ventspils 2 1379 78.45% Daugavpils 0 1023 6.01% 15.53%
5 2016-08-28 26.8 @ Jelgava 2 1336 75.69% Daugavpils 0 1026 7.44% 16.87%
6 2016-06-17 27.1 @ Liepaja 3 1358 69.15% Metta 0 1140 11.38% 19.47%
7 2016-04-30 27.2 @ Ventspils 2 1408 75.62% Metta 0 1099 7.48% 16.90%
8 2016-05-09 28.0 Liepaja 3 1367 65.55% @ Daugavpils 0 1073 13.88% 20.57%
9 2016-06-26 28.1 @ Riga FC 2 1286 71.29% Daugavpils 0 1040 10.00% 18.70%
10 2016-08-28 28.3 @ Ventspils 2 1360 71.56% Metta 0 1110 9.84% 18.60%
11 2016-08-01 28.7 @ FK RFS 3 1256 62.69% Metta 0 1112 16.02% 21.29%
12 2016-10-22 29.1 @ Spartaks Jurmala 2 1334 68.81% Metta 0 1121 11.61% 19.58%
13 2016-10-01 29.2 @ FK RFS 2 1232 67.46% Daugavpils 0 1035 12.53% 20.01%
14 2016-04-16 29.4 Ventspils 5 1381 63.47% @ Daugavpils 0 1111 15.43% 21.11%
15 2016-07-30 30.0 @ Spartaks Jurmala 4 1330 74.81% Daugavpils 1 1034 7.93% 17.27%
16 2016-07-08 30.1 @ Liepaja 1 1377 77.70% Daugavpils 0 1034 6.39% 15.91%
17 2016-07-10 30.2 @ Jelgava 2 1287 64.65% Metta 0 1122 14.54% 20.81%
18 2016-03-19 30.7 @ Spartaks Jurmala 3 1192 55.98% Daugavpils 0 1114 21.49% 22.53%
19 2016-11-05 30.8 @ Liepaja 1 1303 74.78% Daugavpils 0 1007 7.94% 17.28%
20 2016-04-17 31.9 Liepaja 2 1347 59.48% @ Metta 0 1117 18.56% 21.96%
21 2016-10-29 31.9 Jelgava 1 1376 71.40% @ Daugavpils 0 1010 9.94% 18.66%
22 2016-04-23 32.4 Riga FC 2 1298 57.19% @ Daugavpils 0 1090 20.46% 22.35%
23 2016-05-27 32.4 Spartaks Jurmala 2 1258 56.98% @ Daugavpils 0 1052 20.64% 22.39%
24 2016-06-25 32.5 @ Spartaks Jurmala 4 1320 66.78% Metta 1 1131 13.00% 20.22%
25 2016-09-10 32.6 Liepaja 1 1359 69.15% @ Daugavpils 0 1022 11.38% 19.47%