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2013 Virsliga Season

135 games

Final

Champion

Ventspils

67 points

Relegated

No relegation

Biggest Overachiever

Ventspils

14.63 points above expected

67 points · 52.37 expected points

Biggest Disappointment

Spartaks Jurmala

9.37 points below expected

25 points · 34.37 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 Ventspils 27 21 4 2 67 65 19 +46 52.37 +14.63
2 Skonto 27 18 8 1 62 68 11 +57 60.68 +1.32
3 Daugava 27 15 7 5 52 44 19 +25 49.79 +2.21
4 Daugava Riga 27 14 6 7 48 44 21 +23 40.61 +7.39
5 Liepajas Metalurgs 27 11 7 9 40 54 35 +19 46.03 -6.03
6 Jurmala 27 7 5 15 26 20 52 -32 29.02 -3.02
7 Spartaks Jurmala 27 7 4 16 25 30 49 -19 34.37 -9.37
8 Jelgava 27 5 8 14 23 26 46 -20 22.56 +0.44
9 Metta 27 4 7 16 19 15 47 -32 21.25 -2.25
10 Ilukste NSS 27 2 6 19 12 26 93 -67 17.82 -5.82

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 Ventspils 67 52.37 +14.63
2 Daugava Riga 48 40.61 +7.39
3 Daugava 52 49.79 +2.21
4 Skonto 62 60.68 +1.32
5 Jelgava 23 22.56 +0.44

Biggest Disappointments

# Team Actual Sim vsSim
1 Spartaks Jurmala 25 34.37 -9.37
2 Liepajas Metalurgs 40 46.03 -6.03
3 Ilukste NSS 12 17.82 -5.82
4 Jurmala 26 29.02 -3.02
5 Metta 19 21.25 -2.25

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 Jelgava 3 Oct 26 – Nov 9 1 in 901
2 Spartaks Jurmala 3 May 12 – May 20 1 in 25
3 Ventspils 5 May 10 – Jun 21 1 in 19
4 Daugava 4 May 15 – Jun 14 1 in 8
5 Skonto 6 Aug 10 – Sep 15 1 in 6

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Jelgava 6 May 20 – Jul 13 1 in 55
2 Jurmala 6 Apr 27 – Jun 16 1 in 34
3 Spartaks Jurmala 6 Sep 28 – Nov 9 1 in 34
4 Skonto 1 Nov 9 – Nov 9 1 in 30
5 Ilukste NSS 7 Sep 29 – Nov 9 1 in 19

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Jelgava 8 Sep 14 – Nov 9 1 in 1,764
2 Ventspils 22 May 10 – Nov 9 1 in 128
3 Daugava Riga 6 Mar 30 – May 10 1 in 95
4 Skonto 26 Mar 31 – Nov 2 1 in 31
5 Metta 4 Jul 13 – Aug 9 1 in 16

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Spartaks Jurmala 11 Aug 18 – Nov 9 1 in 97
2 Daugava 4 Aug 30 – Sep 25 1 in 24
3 Jelgava 15 May 16 – Sep 22 1 in 19
4 Metta 12 Mar 29 – Jun 26 1 in 11
5 Ilukste NSS 11 Mar 31 – Jun 26 1 in 9

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
Ventspils 1557 67 +41 15 12.2 +2.8
Skonto 1583 62 -67 8 11.5 -3.5
Daugava 1426 52 +6 10 10.2 -0.2
Daugava Riga 1359 48 +17 9 9.8 -0.8
Liepajas Metalurgs 1374 40 +85 10 9.1 +0.9
Jurmala 1092 26 -62 3 3.6 -0.6
Spartaks Jurmala 1038 25 -127 0 4.5 -4.5
Jelgava 1198 23 +136 11 4.0 +7.0
Metta 1099 19 +31 7 4.3 +2.7
Ilukste NSS 937 12 -51 0 1.5 -1.5

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 DR IN JEL JUR LM MET SKO SJ VEN
Daugava —
1-1-1
5.44
3-0-0
7.29
2-1-0
6.83
3-0-0
6.75
1-2-0
4.76
2-0-1
7.05
0-2-1
2.47
3-0-0
5.80
0-1-2
3.59
Daugava Riga
1-1-1
2.85
 —
3-0-0
6.84
2-0-1
6.66
3-0-0
5.27
2-1-0
3.27
2-1-0
6.74
0-1-2
1.96
1-2-0
4.69
0-0-3
2.87
Ilukste NSS
0-0-3
1.13
0-0-3
1.53
 —
1-1-1
3.74
0-2-1
2.67
0-0-3
1.35
0-2-1
3.68
0-0-3
1.07
1-1-1
2.01
0-0-3
0.81
Jelgava
0-1-2
1.54
1-0-2
1.68
1-1-1
4.53
 —
0-1-2
3.28
0-2-1
1.64
1-2-0
4.07
1-1-1
0.88
1-0-2
2.84
0-0-3
1.52
Jurmala
0-0-3
1.60
0-0-3
3.03
1-2-0
5.61
2-1-0
5.00
 —
1-0-2
1.79
2-0-1
5.34
0-1-2
1.53
1-1-1
3.40
0-0-3
1.55
Liepajas Metalurgs
0-2-1
3.52
0-1-2
5.02
3-0-0
7.03
1-2-0
6.71
2-0-1
6.55
 —
2-1-0
6.58
0-0-3
1.66
2-0-1
5.63
1-1-1
3.02
Metta
1-0-2
1.34
0-1-2
1.61
1-2-0
4.59
0-2-1
4.20
1-0-2
2.94
0-1-2
1.77
 —
0-1-2
1.06
1-0-2
2.30
0-0-3
1.14
Skonto
1-2-0
5.83
2-1-0
6.37
3-0-0
7.40
1-1-1
7.61
2-1-0
6.87
3-0-0
6.69
2-1-0
7.40
 —
3-0-0
7.09
1-2-0
5.27
Spartaks Jurmala
0-0-3
2.50
0-2-1
3.60
1-1-1
6.31
2-0-1
5.45
1-1-1
4.88
1-0-2
2.67
2-0-1
6.00
0-0-3
1.32
 —
0-0-3
2.24
Ventspils
2-1-0
4.68
3-0-0
5.42
3-0-0
7.69
3-0-0
6.85
3-0-0
6.83
1-1-1
5.27
3-0-0
7.28
0-2-1
3.01
3-0-0
6.07
 —

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 +9.3
Allowed 0.78 -7.0
Differential 0.93 +4.7

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
011.85%7.41%5.93%4.81%2.59%3.33%35.93%
17.41%5.19%6.30%2.59%0.74%1.85%24.07%
25.93%6.30%5.93%0.74%1.11%0.74%20.74%
34.81%2.59%0.74%—0.37%—8.52%
42.59%0.74%1.11%0.37%——4.81%
5+3.33%1.85%0.74%———5.93%
Total35.93%24.07%20.74%8.52%4.81%5.93%100%

Summary Statistics

Scored Allowed Difference
Mean 1.45 1.45 +0.00
SD 1.63 1.63 2.53
CV 1.12 1.12 —
Max 10 10 +8
Min 0 0 -8

Games Played: 135

↓ Scored | Allowed →012345+Total
018.52%11.11%————29.63%
114.81%3.70%——3.70%—22.22%
211.11%7.41%3.70%———22.22%
311.11%—3.70%—3.70%—18.52%
4———————
5+3.70%3.70%————7.41%
Total59.26%25.93%7.41%—7.41%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.63 0.70 +0.93
SD 1.57 1.14 1.82
CV 0.96 1.62 —
Max 6 4 +5
Min 0 0 -3

Games Played: 27

↓ Scored | Allowed →012345+Total
014.81%14.81%3.70%——3.70%37.04%
114.81%3.70%3.70%———22.22%
27.41%7.41%3.70%———18.52%
33.70%—————3.70%
47.41%—————7.41%
5+3.70%3.70%3.70%———11.11%
Total51.85%29.63%14.81%——3.70%100%

Summary Statistics

Scored Allowed Difference
Mean 1.63 0.78 +0.85
SD 1.90 1.12 2.32
CV 1.17 1.44 —
Max 7 5 +6
Min 0 0 -5

Games Played: 27

↓ Scored | Allowed →012345+Total
07.41%—11.11%—3.70%11.11%33.33%
1—7.41%7.41%11.11%3.70%14.81%44.44%
2—3.70%7.41%——7.41%18.52%
3———————
4——3.70%———3.70%
5+———————
Total7.41%11.11%29.63%11.11%7.41%33.33%100%

Summary Statistics

Scored Allowed Difference
Mean 0.96 3.44 -2.48
SD 0.94 2.45 2.56
CV 0.98 0.71 —
Max 4 10 +2
Min 0 0 -8

Games Played: 27

↓ Scored | Allowed →012345+Total
011.11%7.41%3.70%14.81%3.70%—40.74%
17.41%7.41%14.81%———29.63%
23.70%—11.11%—7.41%—22.22%
3—7.41%————7.41%
4———————
5+———————
Total22.22%22.22%29.63%14.81%11.11%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.96 1.70 -0.74
SD 0.98 1.30 1.63
CV 1.02 0.76 —
Max 3 4 +2
Min 0 0 -4

Games Played: 27

↓ Scored | Allowed →012345+Total
011.11%14.81%7.41%11.11%3.70%11.11%59.26%
17.41%3.70%3.70%——3.70%18.52%
23.70%7.41%3.70%———14.81%
3—3.70%————3.70%
4——3.70%———3.70%
5+———————
Total22.22%29.63%18.52%11.11%3.70%14.81%100%

Summary Statistics

Scored Allowed Difference
Mean 0.74 1.93 -1.19
SD 1.10 1.77 2.27
CV 1.48 0.92 —
Max 4 6 +2
Min 0 0 -5

Games Played: 27

↓ Scored | Allowed →012345+Total
07.41%7.41%7.41%——3.70%25.93%
1—3.70%11.11%3.70%——18.52%
23.70%7.41%14.81%———25.93%
311.11%7.41%————18.52%
43.70%—————3.70%
5+3.70%—3.70%———7.41%
Total29.63%25.93%37.04%3.70%—3.70%100%

Summary Statistics

Scored Allowed Difference
Mean 2.00 1.30 +0.70
SD 2.17 1.17 2.67
CV 1.08 0.90 —
Max 10 5 +8
Min 0 0 -5

Games Played: 27

↓ Scored | Allowed →012345+Total
011.11%11.11%11.11%11.11%14.81%—59.26%
13.70%11.11%11.11%———25.93%
23.70%7.41%3.70%———14.81%
3———————
4———————
5+———————
Total18.52%29.63%25.93%11.11%14.81%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.56 1.74 -1.19
SD 0.75 1.32 1.73
CV 1.35 0.76 —
Max 2 4 +2
Min 0 0 -4

Games Played: 27

↓ Scored | Allowed →012345+Total
018.52%—3.70%———22.22%
1—7.41%————7.41%
214.81%7.41%3.70%———25.93%
311.11%3.70%————14.81%
43.70%3.70%————7.41%
5+18.52%3.70%————22.22%
Total66.67%25.93%7.41%———100%

Summary Statistics

Scored Allowed Difference
Mean 2.52 0.41 +2.11
SD 1.97 0.64 2.14
CV 0.78 1.56 —
Max 7 2 +6
Min 0 0 -2

Games Played: 27

↓ Scored | Allowed →012345+Total
011.11%7.41%11.11%7.41%—3.70%40.74%
17.41%—11.11%7.41%——25.93%
2—7.41%3.70%7.41%3.70%—22.22%
3—3.70%————3.70%
43.70%—3.70%———7.41%
5+———————
Total22.22%18.52%29.63%22.22%3.70%3.70%100%

Summary Statistics

Scored Allowed Difference
Mean 1.11 1.81 -0.70
SD 1.22 1.44 1.96
CV 1.10 0.79 —
Max 4 6 +4
Min 0 0 -6

Games Played: 27

↓ Scored | Allowed →012345+Total
07.41%——3.70%——11.11%
118.52%3.70%—3.70%——25.93%
211.11%7.41%3.70%———22.22%
311.11%—3.70%———14.81%
47.41%3.70%—3.70%——14.81%
5+3.70%7.41%————11.11%
Total59.26%22.22%7.41%11.11%——100%

Summary Statistics

Scored Allowed Difference
Mean 2.41 0.70 +1.70
SD 1.80 1.03 2.05
CV 0.75 1.46 —
Max 7 3 +6
Min 0 0 -3

Games Played: 27

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
Skonto 1583 62 60.68 +1.32 64.0% 47 52 57 60 64 72 74
Ventspils 1557 67 52.37 +14.63 100.0% 33 43 48 52 56 61 65
Daugava 1426 52 49.79 +2.21 67.0% 36 41 45 49 54 60 65
Liepajas Metalurgs 1374 40 46.03 -6.03 17.0% 35 38 42 46 50 56 59
Daugava Riga 1359 48 40.61 +7.39 90.0% 27 29 36 41 45 50 53
Jelgava 1198 23 22.56 +0.44 59.0% 9 14 19 23 25 31 39
Metta 1099 19 21.25 -2.25 40.0% 9 12 17 21 25 30 43
Jurmala 1092 26 29.02 -3.02 35.0% 16 19 25 29 33 39 44
Spartaks Jurmala 1038 25 34.37 -9.37 9.0% 18 23 31 35 39 43 50
Ilukste NSS 937 12 17.82 -5.82 18.0% 3 9 14 17 22 26 36

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
-5.93%
No Edge
35.56%22.96%41.48%
Elo Value
Home Edge: -20.61 Elo pts.
161 Elo
0.006 goals per Elo point
0500
Scoring Tilt
Expected
+0.01 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 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 5th * Longshot: 6th 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
1.8
One-Team Race
123410
Champion Preseason Odds
16%
Ventspils, 2nd of 10
LongshotFavorite
Title Margin
Expected
0.19/gm
Comfortable
00.270.5/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 4.58 * Some Luck: 4.58 to 6.87 * Lucky: 6.87 to 9.16 * Wild Swing: 9.16 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 0.6 * Close: 0.6 to 0.89 * Off: 0.89 to 1.19 * Way Off: 1.19 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 10 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 10 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 10 * As Expected: 10 to 16 * Several Outliers: 16 to 22 * Many Outliers: 22 and up.
Luck Spread
Expected
6.69 points
Some Luck
05.7314
Average Finish Error
Expected
0.60
Close
00.741.5
Biggest Overachiever
Expected 95.00%
100.00%
Ventspils
50100
Biggest Underachiever
Expected 5.00%
9.00%
Spartaks Jurmala
050
Season Outliers
Expected
1 of 10
Minimal Outliers
01.010

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
0.27
Top-Heavy
00.240.5
Noll-Scully
Elo SD: 224.61
2.76
Moderate Separation
12.552.953.5
Interquartile Edge
86%
Slight Edge
50%82%100%
Best vs. Worst
Baseline 99%
98%
Clear Edge
50%100%
Close Games
Expected
53%
Frequent
0%44%100%
Blowouts
Expected
28%
Frequent
0%33%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
0.50
Highly Predictable
00.532
Matchup Imbalance
0.56
Notable Separation
00.5
Strangeness
Expected
1.33
Wilder Than Modeled
01.002
Repeatability
0.79
Strong Carryover
00.620.761
Upset Rate
Expected
13%
Chalky
0%17%50%
Clear Favorite Upset Rate
Expected
12%
As Expected
0%14%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 0.26 * Well Above Noise: 0.26 and up.
Probability calibration
0.59
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.08
Calibrated
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.114
Well Within Noise
00.1310.3

Final Table Odds

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

Team12345678910
Ventspils16.00%39.00%27.00%14.00%3.00%—1.00%———
Skonto72.00%24.00%4.00%———————
Daugava8.00%25.00%37.00%19.00%7.00%3.00%1.00%———
Daugava Riga—4.00%6.00%28.00%37.00%14.00%10.00%1.00%——
Liepajas Metalurgs4.00%8.00%24.00%36.00%23.00%4.00%1.00%———
Jurmala———2.00%6.00%17.00%43.00%18.00%11.00%3.00%
Spartaks Jurmala——1.00%1.00%23.00%54.00%10.00%8.00%3.00%—
Jelgava————1.00%2.00%20.00%35.00%29.00%13.00%
Metta——1.00%——5.00%12.00%21.00%33.00%28.00%
Ilukste NSS—————1.00%2.00%17.00%24.00%56.00%

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
Daugava 100% — —
Daugava Riga 100% — —
Liepajas Metalurgs 100% — —
Skonto 100% — —
Spartaks Jurmala 97.00% 3.00% —
Ventspils 100% — —
Jurmala 86.00% 11.00% 3.00%
Jelgava 58.00% 29.00% 13.00%
Metta 39.00% 33.00% 28.00%
Ilukste NSS 20.00% 24.00% 56.00%

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
2013-03-29 Metta W 4-032.0 1368 1187 59.67% 23.18% 17.15%+1.00 +34.5 3
2013-03-29 @ Liepajas Metalurgs L 0-432.0 1187 1368 17.15% 23.18% 59.67%-1.00 -34.5 0
2013-03-30 Daugava Riga D 0-050.1 1368 1148 63.12% 22.65% 14.23%+1.24 -6.0 1
2013-03-30 @ Daugava D 0-050.1 1148 1368 14.23% 22.65% 63.12%-1.24 +6.0 1
2013-03-30 Jelgava W 4-031.9 1380 1192 60.33% 23.09% 16.58%+1.04 +33.5 3
2013-03-30 @ Ventspils L 0-431.9 1192 1380 16.58% 23.09% 60.33%-1.04 -33.5 0
2013-03-31 Ilukste NSS D 2-258.1 1266 1124 55.80% 23.62% 20.58%+0.76 -2.8 1
2013-03-31 @ Spartaks Jurmala D 2-258.1 1124 1266 20.58% 23.62% 55.80%-0.76 +2.8 1
2013-03-31 Jurmala D 0-050.4 1387 1243 56.00% 23.60% 20.40%+0.77 -4.2 1
2013-03-31 @ Skonto D 0-050.4 1243 1387 20.40% 23.60% 56.00%-0.77 +4.2 1
2013-04-05 Spartaks Jurmala L 0-138.9 1153 1264 23.72% 23.90% 52.38%-0.82 -12.8 0
2013-04-05 @ Metta W 1-038.9 1264 1153 52.38% 23.90% 23.72%+0.82 +12.8 4
2013-04-06 Daugava W 4-355.9 1413 1362 44.91% 24.26% 30.83%+0.19 +13.8 6
2013-04-06 @ Ventspils L 3-455.9 1362 1413 30.83% 24.26% 44.91%-0.19 -13.8 1
2013-04-06 Jurmala L 0-139.6 1158 1247 26.17% 24.06% 49.76%-0.68 -13.8 0
2013-04-06 @ Jelgava W 1-039.6 1247 1158 49.76% 24.06% 26.17%+0.68 +13.8 4
2013-04-07 Ilukste NSS W 5-029.5 1383 1127 65.98% 22.08% 11.95%+1.46 +30.4 4
2013-04-07 @ Skonto L 0-529.5 1127 1383 11.95% 22.08% 65.98%-1.46 -30.4 1
2013-04-07 Liepajas Metalurgs W 2-155.9 1154 1402 12.40% 22.20% 65.39%-1.67 +28.1 4
2013-04-07 @ Daugava Riga L 1-255.9 1402 1154 65.39% 22.20% 12.40%+1.67 -28.1 3
2013-04-12 Ilukste NSS D 1-153.4 1261 1097 58.09% 23.38% 18.54%+0.89 -4.2 5
2013-04-12 @ Jurmala D 1-153.4 1097 1261 18.54% 23.38% 58.09%-0.89 +4.2 2
2013-04-12 Metta W 4-029.8 1413 1140 67.26% 21.77% 10.96%+1.57 +22.7 7
2013-04-12 @ Skonto L 0-429.8 1140 1413 10.96% 21.77% 67.26%-1.57 -22.7 0
2013-04-13 Jelgava W 2-140.8 1348 1144 61.76% 22.87% 15.36%+1.14 +8.2 4
2013-04-13 @ Daugava L 1-240.8 1144 1348 15.36% 22.87% 61.76%-1.14 -8.2 0
2013-04-13 Ventspils W 3-151.4 1374 1427 30.64% 24.25% 45.11%-0.46 +34.7 6
2013-04-13 @ Liepajas Metalurgs L 1-351.4 1427 1374 45.11% 24.25% 30.64%+0.46 -34.7 6
2013-04-14 Daugava Riga L 0-147.0 1276 1182 50.37% 24.03% 25.60%+0.46 -23.4 4
2013-04-14 @ Spartaks Jurmala W 1-047.0 1182 1276 25.60% 24.03% 50.37%-0.46 +23.4 7
2013-04-19 Skonto D 0-050.9 1206 1436 13.52% 22.49% 63.99%-1.56 +6.2 8
2013-04-19 @ Daugava Riga D 0-050.9 1436 1206 63.99% 22.49% 13.52%+1.56 -6.2 8
2013-04-20 Ilukste NSS D 2-257.8 1136 1101 42.77% 24.31% 32.92%+0.09 -0.7 1
2013-04-20 @ Jelgava D 2-257.8 1101 1136 32.92% 24.31% 42.77%-0.09 +0.7 3
2013-04-20 Spartaks Jurmala W 1-039.0 1392 1253 55.48% 23.65% 20.87%+0.74 +11.5 9
2013-04-20 @ Ventspils L 0-139.0 1253 1392 20.87% 23.65% 55.48%-0.74 -11.5 4
2013-04-21 Jurmala L 1-242.4 1117 1257 20.80% 23.64% 55.56%-1.00 -10.8 0
2013-04-21 @ Metta W 2-142.4 1257 1117 55.56% 23.64% 20.80%+1.00 +10.8 8
2013-04-21 Liepajas Metalurgs D 1-155.9 1357 1409 30.65% 24.25% 45.10%-0.45 +1.4 5
2013-04-21 @ Daugava D 1-155.9 1409 1357 45.10% 24.25% 30.65%+0.45 -1.4 7
2013-04-26 Jelgava W 3-030.9 1408 1135 67.16% 21.80% 11.04%+1.56 +17.5 10
2013-04-26 @ Liepajas Metalurgs L 0-330.9 1135 1408 11.04% 21.80% 67.16%-1.56 -17.5 1
2013-04-27 Daugava Riga L 0-540.1 1268 1212 45.54% 24.24% 30.22%+0.22 -94.5 8
2013-04-27 @ Jurmala W 5-040.1 1212 1268 30.22% 24.24% 45.54%-0.22 +94.5 11
2013-04-27 Ventspils W 3-042.4 1430 1404 41.53% 24.33% 34.14%+0.03 +46.8 11
2013-04-27 @ Skonto L 0-342.4 1404 1430 34.14% 24.33% 41.53%-0.03 -46.8 9
2013-04-28 Daugava L 0-237.2 1242 1358 23.18% 23.86% 52.96%-0.85 -23.6 4
2013-04-28 @ Spartaks Jurmala W 2-037.2 1358 1242 52.96% 23.86% 23.18%+0.85 +23.6 8
2013-04-29 Metta D 1-153.0 1102 1106 37.14% 24.35% 38.50%-0.16 +0.1 4
2013-04-29 @ Ilukste NSS D 1-153.0 1106 1102 38.50% 24.35% 37.14%+0.16 -0.1 1
2013-05-10 Ilukste NSS W 4-030.9 1306 1102 61.82% 22.86% 15.32%+1.14 +31.1 14
2013-05-10 @ Daugava Riga L 0-430.9 1102 1306 15.32% 22.86% 61.82%-1.14 -31.1 4
2013-05-10 Jurmala W 3-033.0 1357 1173 59.92% 23.15% 16.93%+1.01 +26.1 12
2013-05-10 @ Ventspils L 0-333.0 1173 1357 16.93% 23.15% 59.92%-1.01 -26.1 8
2013-05-11 Metta W 1-042.5 1118 1106 39.50% 24.35% 36.15%-0.06 +17.8 4
2013-05-11 @ Jelgava L 0-142.5 1106 1118 36.15% 24.35% 39.50%+0.06 -17.8 1
2013-05-11 Skonto L 1-444.8 1382 1477 25.49% 24.02% 50.49%-0.72 -31.3 8
2013-05-11 @ Daugava W 4-144.8 1477 1382 50.49% 24.02% 25.49%+0.72 +31.3 14
2013-05-12 Spartaks Jurmala L 1-255.6 1425 1218 62.03% 22.83% 15.14%+1.16 -26.7 10
2013-05-12 @ Liepajas Metalurgs W 2-155.6 1218 1425 15.14% 22.83% 62.03%-1.16 +26.7 7
2013-05-14 Ventspils L 0-143.3 1337 1383 31.56% 24.28% 44.17%-0.41 -16.1 14
2013-05-14 @ Daugava Riga W 1-043.3 1383 1337 44.17% 24.28% 31.56%+0.41 +16.1 15
2013-05-15 Daugava L 1-239.3 1088 1350 11.61% 21.98% 66.42%-1.76 -6.3 1
2013-05-15 @ Metta W 2-139.3 1350 1088 66.42% 21.98% 11.61%+1.76 +6.3 11
2013-05-15 Liepajas Metalurgs L 1-238.0 1071 1398 8.42% 20.76% 70.82%-2.17 -4.6 4
2013-05-15 @ Ilukste NSS W 2-138.0 1398 1071 70.82% 20.76% 8.42%+2.17 +4.6 13
2013-05-16 Jelgava D 1-155.6 1508 1136 73.37% 19.86% 6.77%+2.19 -7.5 15
2013-05-16 @ Skonto D 1-155.6 1136 1508 6.77% 19.86% 73.37%-2.19 +7.5 5
2013-05-16 Spartaks Jurmala L 0-139.3 1147 1245 25.21% 24.00% 50.79%-0.74 -13.4 8
2013-05-16 @ Jurmala W 1-039.3 1245 1147 50.79% 24.00% 25.21%+0.74 +13.4 10
2013-05-19 Daugava Riga L 1-239.7 1082 1321 12.95% 22.35% 64.70%-1.62 -7.0 1
2013-05-19 @ Metta W 2-139.7 1321 1082 64.70% 22.35% 12.95%+1.62 +7.0 17
2013-05-20 Jelgava W 4-245.1 1258 1143 52.80% 23.87% 23.33%+0.59 +18.4 13
2013-05-20 @ Spartaks Jurmala L 2-445.1 1143 1258 23.33% 23.87% 52.80%-0.59 -18.4 5
2013-05-21 Daugava L 0-135.8 1134 1357 14.03% 22.60% 63.37%-1.51 -8.0 8
2013-05-21 @ Jurmala W 1-035.8 1357 1134 63.37% 22.60% 14.03%+1.51 +8.0 14
2013-05-31 Daugava Riga L 0-332.2 1125 1328 15.40% 22.88% 61.72%-1.39 -24.0 5
2013-05-31 @ Jelgava W 3-032.2 1328 1125 61.72% 22.88% 15.40%+1.39 +23.9 20
2013-05-31 Ilukste NSS W 5-028.4 1365 1066 68.97% 21.32% 9.71%+1.73 +24.8 17
2013-05-31 @ Daugava L 0-528.4 1066 1365 9.71% 21.32% 68.97%-1.73 -24.8 4
2013-06-01 Jurmala W 2-032.5 1403 1126 67.52% 21.71% 10.77%+1.60 +11.8 16
2013-06-01 @ Liepajas Metalurgs L 0-232.5 1126 1403 10.77% 21.71% 67.52%-1.60 -11.8 8
2013-06-01 Metta W 4-028.5 1399 1075 70.59% 20.84% 8.57%+1.89 +17.7 18
2013-06-01 @ Ventspils L 0-428.5 1075 1399 8.57% 20.84% 70.59%-1.89 -17.7 1
2013-06-01 Skonto L 1-243.0 1277 1500 13.96% 22.59% 63.45%-1.52 -7.5 13
2013-06-01 @ Spartaks Jurmala W 2-143.0 1500 1277 63.45% 22.59% 13.96%+1.52 +7.5 18
2013-06-14 Daugava L 0-144.0 1352 1389 32.68% 24.30% 43.02%-0.36 -16.5 20
2013-06-14 @ Daugava Riga W 1-044.0 1389 1352 43.02% 24.30% 32.68%+0.36 +16.5 20
2013-06-15 Metta D 0-050.7 1415 1057 72.55% 20.17% 7.28%+2.09 -8.2 17
2013-06-15 @ Liepajas Metalurgs D 0-050.7 1057 1415 7.28% 20.17% 72.55%-2.09 +8.2 2
2013-06-15 Ventspils L 1-238.4 1101 1417 8.92% 21.00% 70.08%-2.09 -4.9 5
2013-06-15 @ Jelgava W 2-138.4 1417 1101 70.08% 21.00% 8.92%+2.09 +4.9 21
2013-06-16 Skonto L 0-527.6 1114 1508 6.09% 19.39% 74.52%-2.58 -15.3 8
2013-06-16 @ Jurmala W 5-027.6 1508 1114 74.52% 19.39% 6.09%+2.58 +15.3 21
2013-06-16 Spartaks Jurmala L 1-337.9 1041 1269 13.69% 22.53% 63.78%-1.54 -12.8 4
2013-06-16 @ Ilukste NSS W 3-137.9 1269 1041 63.78% 22.53% 13.69%+1.54 +12.8 16
2013-06-20 Daugava Riga L 0-246.2 1406 1336 47.45% 24.17% 28.38%+0.31 -41.8 17
2013-06-20 @ Liepajas Metalurgs W 2-046.2 1336 1406 28.38% 24.17% 47.45%-0.31 +41.8 23
2013-06-20 Jelgava W 4-249.3 1099 1096 38.19% 24.36% 37.46%-0.11 +26.8 11
2013-06-20 @ Jurmala L 2-449.3 1096 1099 37.46% 24.36% 38.19%+0.11 -26.8 5
2013-06-20 Skonto L 1-727.8 1028 1523 3.70% 17.13% 79.17%-3.20 -8.8 4
2013-06-20 @ Ilukste NSS W 7-127.8 1523 1028 79.17% 17.13% 3.70%+3.20 +8.8 24
2013-06-21 Metta W 4-030.6 1282 1066 62.83% 22.70% 14.48%+1.22 +29.6 19
2013-06-21 @ Spartaks Jurmala L 0-430.6 1066 1282 14.48% 22.70% 62.83%-1.22 -29.6 2
2013-06-21 Ventspils L 0-146.6 1406 1422 35.59% 24.35% 40.06%-0.23 -17.6 20
2013-06-21 @ Daugava W 1-046.6 1422 1406 40.06% 24.35% 35.59%+0.23 +17.6 24
2013-06-26 Daugava Riga D 0-050.8 1311 1378 28.91% 24.19% 46.89%-0.54 +2.0 20
2013-06-26 @ Spartaks Jurmala D 0-050.8 1378 1311 46.89% 24.19% 28.91%+0.54 -2.0 24
2013-06-26 Jurmala L 0-236.7 1020 1125 24.30% 23.94% 51.75%-0.79 -24.6 4
2013-06-26 @ Ilukste NSS W 2-036.7 1125 1020 51.75% 23.94% 24.30%+0.79 +24.5 14
2013-06-26 Liepajas Metalurgs D 2-261.5 1439 1365 47.97% 24.15% 27.88%+0.34 -1.5 25
2013-06-26 @ Ventspils D 2-261.5 1365 1439 27.88% 24.15% 47.97%-0.34 +1.5 18
2013-06-26 Skonto L 0-229.2 1036 1532 3.68% 17.10% 79.22%-3.21 -3.8 2
2013-06-26 @ Metta W 2-029.2 1532 1036 79.22% 17.10% 3.68%+3.21 +3.8 27
2013-06-27 Daugava L 0-329.6 1069 1388 8.79% 20.94% 70.27%-2.11 -13.9 5
2013-06-27 @ Jelgava W 3-029.6 1388 1069 70.27% 20.94% 8.79%+2.11 +13.9 23
2013-07-13 Jelgava W 2-150.0 995 1055 29.66% 24.22% 46.12%-0.50 +20.4 7
2013-07-13 @ Ilukste NSS L 1-250.0 1055 995 46.12% 24.22% 29.66%+0.50 -20.4 5
2013-07-13 Metta L 1-252.0 1150 1032 53.14% 23.85% 23.02%+0.60 -23.1 14
2013-07-13 @ Jurmala W 2-152.0 1032 1150 23.02% 23.85% 53.14%-0.60 +23.1 5
2013-07-14 Daugava Riga W 5-038.3 1536 1376 57.65% 23.43% 18.92%+0.87 +46.4 30
2013-07-14 @ Skonto L 0-538.3 1376 1536 18.92% 23.43% 57.65%-0.87 -46.4 24
2013-07-14 Ventspils L 2-349.9 1313 1438 22.34% 23.79% 53.87%-0.90 -10.9 20
2013-07-14 @ Spartaks Jurmala W 3-249.9 1438 1313 53.87% 23.79% 22.34%+0.90 +10.8 28
2013-07-26 Jurmala W 1-036.2 1329 1127 61.62% 22.90% 15.48%+1.13 +8.8 27
2013-07-26 @ Daugava Riga L 0-136.2 1127 1329 15.48% 22.90% 61.62%-1.13 -8.8 14
2013-07-27 Ilukste NSS D 0-049.1 1055 1016 43.39% 24.30% 32.31%+0.12 -1.2 6
2013-07-27 @ Metta D 0-049.1 1016 1055 32.31% 24.30% 43.39%-0.12 +1.2 8
2013-07-28 Skonto D 0-060.4 1449 1582 21.42% 23.71% 54.88%-0.96 +3.9 29
2013-07-28 @ Ventspils D 0-060.4 1582 1449 54.88% 23.71% 21.42%+0.96 -3.9 31
2013-07-28 Spartaks Jurmala W 3-250.0 1402 1303 51.02% 23.99% 24.99%+0.49 +11.9 26
2013-07-28 @ Daugava L 2-350.0 1303 1402 24.99% 23.99% 51.02%-0.49 -11.9 20
2013-07-29 Liepajas Metalurgs D 2-259.0 1035 1366 8.28% 20.70% 71.02%-2.19 +5.3 6
2013-07-29 @ Jelgava D 2-259.0 1366 1035 71.02% 20.70% 8.28%+2.19 -5.3 19
2013-08-02 Jelgava D 0-049.0 1054 1040 39.79% 24.35% 35.86%-0.04 -0.4 7
2013-08-02 @ Metta D 0-049.0 1040 1054 35.86% 24.35% 39.79%+0.04 +0.4 7
2013-08-03 Daugava D 0-059.0 1578 1414 58.05% 23.38% 18.57%+0.89 -4.7 32
2013-08-03 @ Skonto D 0-059.0 1414 1578 18.57% 23.38% 58.05%-0.89 +4.7 27
2013-08-04 Daugava Riga L 2-536.8 1017 1338 8.69% 20.89% 70.42%-2.13 -10.0 8
2013-08-04 @ Ilukste NSS W 5-236.8 1338 1017 70.42% 20.89% 8.69%+2.13 +10.0 30
2013-08-04 Liepajas Metalurgs L 1-246.0 1291 1361 28.43% 24.17% 47.40%-0.56 -14.0 20
2013-08-04 @ Spartaks Jurmala W 2-146.0 1361 1291 47.40% 24.17% 28.43%+0.56 +14.0 22
2013-08-09 Metta D 1-154.1 1348 1054 68.70% 21.40% 9.90%+1.70 -6.6 31
2013-08-09 @ Daugava Riga D 1-154.1 1054 1348 9.90% 21.40% 68.70%-1.70 +6.6 8
2013-08-09 Spartaks Jurmala L 1-239.7 1041 1277 13.16% 22.40% 64.44%-1.60 -7.1 7
2013-08-09 @ Jelgava W 2-139.7 1277 1041 64.44% 22.40% 13.16%+1.60 +7.1 23
2013-08-10 Jurmala W 1-034.2 1419 1118 69.11% 21.28% 9.61%+1.74 +5.6 30
2013-08-10 @ Daugava L 0-134.2 1118 1419 9.61% 21.28% 69.11%-1.74 -5.6 14
2013-08-10 Skonto L 0-538.5 1375 1574 15.75% 22.95% 61.30%-1.36 -39.4 22
2013-08-10 @ Liepajas Metalurgs W 5-038.5 1574 1375 61.30% 22.95% 15.75%+1.36 +39.4 35
2013-08-13 Ilukste NSS W 4-132.1 1453 1007 77.04% 18.24% 4.72%+2.64 +6.1 32
2013-08-13 @ Ventspils L 1-432.1 1007 1453 4.72% 18.24% 77.04%-2.64 -6.1 8
2013-08-16 Jelgava W 1-033.6 1342 1034 69.58% 21.15% 9.27%+1.79 +5.4 34
2013-08-16 @ Daugava Riga L 0-133.6 1034 1342 9.27% 21.15% 69.58%-1.79 -5.4 7
2013-08-17 Ventspils L 0-230.3 1060 1459 5.96% 19.30% 74.75%-2.61 -6.4 8
2013-08-17 @ Metta W 2-030.3 1459 1060 74.75% 19.30% 5.96%+2.61 +6.4 35
2013-08-18 Daugava L 0-229.7 1001 1424 5.26% 18.74% 76.00%-2.76 -5.6 8
2013-08-18 @ Ilukste NSS W 2-029.7 1424 1001 76.00% 18.74% 5.26%+2.76 +5.6 33
2013-08-18 Liepajas Metalurgs W 3-153.1 1113 1335 14.03% 22.60% 63.37%-1.51 +47.2 17
2013-08-18 @ Jurmala L 1-353.1 1335 1113 63.37% 22.60% 14.03%+1.51 -47.2 22
2013-08-18 Spartaks Jurmala W 3-142.0 1613 1284 70.90% 20.74% 8.36%+1.92 +7.9 38
2013-08-18 @ Skonto L 1-342.0 1284 1613 8.36% 20.74% 70.90%-1.92 -7.9 23
2013-08-21 Liepajas Metalurgs W 2-037.6 1621 1288 71.11% 20.67% 8.22%+1.94 +9.0 41
2013-08-21 @ Skonto L 0-237.6 1288 1621 8.22% 20.67% 71.11%-1.94 -9.0 22
2013-08-23 Metta W 3-028.7 1430 1054 73.58% 19.77% 6.64%+2.21 +10.4 36
2013-08-23 @ Daugava L 0-328.7 1054 1430 6.64% 19.77% 73.58%-2.21 -10.4 8
2013-08-24 Daugava Riga W 2-146.9 1465 1347 53.17% 23.84% 22.98%+0.61 +11.7 38
2013-08-24 @ Ventspils L 1-246.9 1347 1465 22.98% 23.84% 53.17%-0.61 -11.7 34
2013-08-25 Jurmala D 0-049.5 1276 1160 52.95% 23.86% 23.19%+0.59 -3.4 24
2013-08-25 @ Spartaks Jurmala D 0-049.5 1160 1276 23.19% 23.86% 52.95%-0.59 +3.4 18
2013-08-25 Skonto L 0-326.9 1028 1630 2.18% 14.66% 83.16%-3.87 -3.1 7
2013-08-25 @ Jelgava W 3-026.9 1630 1028 83.16% 14.66% 2.18%+3.87 +3.1 44
2013-08-26 Liepajas Metalurgs L 1-336.6 995 1279 10.41% 21.59% 68.00%-1.90 -9.8 8
2013-08-26 @ Ilukste NSS W 3-136.6 1279 995 68.00% 21.59% 10.41%+1.90 +9.8 25
2013-08-30 Daugava Riga L 0-150.2 1440 1335 51.68% 23.95% 24.37%+0.53 -23.9 36
2013-08-30 @ Daugava W 1-050.2 1335 1440 24.37% 23.95% 51.68%-0.53 +23.9 37
2013-08-30 Jelgava W 2-029.5 1477 1025 77.30% 18.11% 4.59%+2.68 +4.8 41
2013-08-30 @ Ventspils L 0-229.5 1025 1477 4.59% 18.11% 77.30%-2.68 -4.8 7
2013-08-31 Ilukste NSS L 2-457.7 1273 985 68.21% 21.53% 10.26%+1.66 -45.3 24
2013-08-31 @ Spartaks Jurmala W 4-257.7 985 1273 10.26% 21.53% 68.21%-1.66 +45.3 11
2013-08-31 Jurmala W 5-028.9 1633 1163 78.10% 17.70% 4.20%+2.79 +10.2 47
2013-08-31 @ Skonto L 0-528.9 1163 1633 4.20% 17.70% 78.10%-2.79 -10.2 18
2013-08-31 Liepajas Metalurgs L 0-331.0 1043 1289 12.56% 22.25% 65.19%-1.66 -19.8 8
2013-08-31 @ Metta W 3-031.0 1289 1043 65.19% 22.25% 12.56%+1.66 +19.8 28
2013-09-13 Spartaks Jurmala W 2-047.6 1024 1227 15.39% 22.88% 61.73%-1.39 +53.2 11
2013-09-13 @ Metta L 0-247.6 1227 1024 61.73% 22.88% 15.39%+1.39 -53.2 24
2013-09-14 Jurmala D 2-257.9 1020 1153 21.50% 23.71% 54.79%-0.95 +2.6 8
2013-09-14 @ Jelgava D 2-257.9 1153 1020 54.79% 23.71% 21.50%+0.95 -2.6 19
2013-09-15 Daugava D 0-055.4 1482 1416 46.74% 24.20% 29.06%+0.28 -2.0 42
2013-09-15 @ Ventspils D 0-055.4 1416 1482 29.06% 24.20% 46.74%-0.28 +2.0 37
2013-09-15 Skonto L 0-228.7 1031 1643 2.06% 14.41% 83.53%-3.94 -2.0 11
2013-09-15 @ Ilukste NSS W 2-028.7 1643 1031 83.53% 14.41% 2.06%+3.94 +2.0 50
2013-09-16 Liepajas Metalurgs D 2-259.3 1359 1309 44.80% 24.26% 30.94%+0.18 -1.0 38
2013-09-16 @ Daugava Riga D 2-259.3 1309 1359 30.94% 24.26% 44.80%-0.18 +1.0 29
2013-09-20 Metta D 2-262.6 1645 1077 82.00% 15.43% 2.57%+3.40 -6.6 51
2013-09-20 @ Skonto D 2-262.6 1077 1645 2.57% 15.43% 82.00%-3.40 +6.6 12
2013-09-21 Ilukste NSS D 0-049.2 1150 1029 53.60% 23.81% 22.59%+0.63 -3.6 20
2013-09-21 @ Jurmala D 0-049.2 1029 1150 22.59% 23.81% 53.60%-0.63 +3.6 12
2013-09-21 Ventspils L 0-140.2 1310 1480 18.09% 23.32% 58.60%-1.18 -10.1 29
2013-09-21 @ Liepajas Metalurgs W 1-040.2 1480 1310 58.60% 23.32% 18.09%+1.18 +10.1 45
2013-09-22 Jelgava D 0-050.8 1418 1023 74.60% 19.36% 6.04%+2.33 -8.7 38
2013-09-22 @ Daugava D 0-050.8 1023 1418 6.04% 19.36% 74.60%-2.33 +8.7 9
2013-09-22 Spartaks Jurmala D 0-050.0 1358 1174 59.97% 23.14% 16.90%+1.02 -5.2 39
2013-09-22 @ Daugava Riga D 0-050.0 1174 1358 16.90% 23.14% 59.97%-1.02 +5.2 25
2013-09-25 Daugava D 2-259.9 1300 1410 23.85% 23.91% 52.24%-0.81 +2.2 30
2013-09-25 @ Liepajas Metalurgs D 2-259.9 1410 1300 52.24% 23.91% 23.85%+0.81 -2.2 39
2013-09-25 Ventspils L 0-231.9 1147 1490 7.82% 20.46% 71.72%-2.26 -8.5 20
2013-09-25 @ Jurmala W 2-031.9 1490 1147 71.72% 20.46% 7.82%+2.26 +8.5 48
2013-09-28 Spartaks Jurmala W 3-030.9 1498 1179 70.28% 20.94% 8.78%+1.86 +13.9 51
2013-09-28 @ Ventspils L 0-330.9 1179 1498 8.78% 20.94% 70.28%-1.86 -13.9 25
2013-09-29 Ilukste NSS W 3-145.6 1032 1032 37.75% 24.36% 37.90%-0.13 +30.2 12
2013-09-29 @ Jelgava L 1-345.6 1032 1032 37.90% 24.36% 37.75%+0.13 -30.2 12
2013-09-29 Liepajas Metalurgs W 1-040.9 1408 1302 51.73% 23.95% 24.32%+0.53 +13.0 42
2013-09-29 @ Daugava L 0-140.9 1302 1408 24.32% 23.95% 51.73%-0.53 -13.0 30
2013-09-30 Jurmala L 0-140.8 1083 1138 30.34% 24.24% 45.41%-0.47 -15.6 12
2013-09-30 @ Metta W 1-040.8 1138 1083 45.41% 24.24% 30.34%+0.47 +15.6 23
2013-09-30 Skonto L 0-241.4 1353 1638 10.34% 21.56% 68.10%-1.90 -11.3 39
2013-09-30 @ Daugava Riga W 2-041.4 1638 1353 68.10% 21.56% 10.34%+1.90 +11.3 54
2013-10-04 Jelgava D 0-049.7 1289 1062 63.72% 22.54% 13.74%+1.28 -6.1 31
2013-10-04 @ Liepajas Metalurgs D 0-049.7 1062 1289 13.74% 22.54% 63.72%-1.28 +6.1 13
2013-10-05 Daugava L 0-233.3 1165 1421 11.98% 22.09% 65.93%-1.72 -13.0 25
2013-10-05 @ Spartaks Jurmala W 2-033.3 1421 1165 65.93% 22.09% 11.98%+1.72 +13.0 45
2013-10-05 Metta L 1-244.9 1002 1068 28.95% 24.19% 46.86%-0.54 -14.1 12
2013-10-05 @ Ilukste NSS W 2-144.9 1068 1002 46.86% 24.19% 28.95%+0.54 +14.2 15
2013-10-05 Ventspils D 1-168.6 1650 1512 55.32% 23.67% 21.01%+0.73 -3.6 55
2013-10-05 @ Skonto D 1-168.6 1512 1650 21.01% 23.67% 55.32%-0.73 +3.6 52
2013-10-06 Daugava Riga L 0-431.6 1154 1342 16.61% 23.09% 60.30%-1.30 -33.5 23
2013-10-06 @ Jurmala W 4-031.6 1342 1154 60.30% 23.09% 16.61%+1.30 +33.5 42
2013-10-14 Ventspils L 1-727.2 988 1516 3.14% 16.36% 80.50%-3.41 -7.3 12
2013-10-14 @ Ilukste NSS W 7-127.2 1516 988 80.50% 16.36% 3.14%+3.41 +7.3 55
2013-10-18 Spartaks Jurmala W 6-032.7 1283 1152 54.56% 23.73% 21.71%+0.68 +62.0 34
2013-10-18 @ Liepajas Metalurgs L 0-632.7 1152 1283 21.71% 23.73% 54.56%-0.68 -62.0 25
2013-10-19 Metta D 1-153.0 1068 1082 35.82% 24.35% 39.83%-0.22 +0.4 14
2013-10-19 @ Jelgava D 1-153.0 1082 1068 39.83% 24.35% 35.82%+0.22 -0.4 16
2013-10-19 Skonto D 0-062.4 1434 1646 14.74% 22.75% 62.51%-1.45 +5.8 46
2013-10-19 @ Daugava D 0-062.4 1646 1434 62.51% 22.75% 14.74%+1.45 -5.8 56
2013-10-20 Jurmala W 6-130.5 1523 1120 74.96% 19.20% 5.83%+2.38 +12.1 58
2013-10-20 @ Ventspils L 1-630.5 1120 1523 5.83% 19.20% 74.96%-2.38 -12.1 23
2013-10-21 Ilukste NSS W 7-128.7 1375 980 74.56% 19.38% 6.06%+2.33 +14.9 45
2013-10-21 @ Daugava Riga L 1-728.7 980 1375 6.06% 19.38% 74.56%-2.33 -14.9 12
2013-10-25 Liepajas Metalurgs W 2-147.7 1640 1345 68.77% 21.38% 9.85%+1.71 +5.4 59
2013-10-25 @ Skonto L 1-247.7 1345 1640 9.85% 21.38% 68.77%-1.71 -5.4 34
2013-10-26 Jelgava L 1-346.6 1090 1068 40.93% 24.34% 34.73%+0.01 -32.1 25
2013-10-26 @ Spartaks Jurmala W 3-146.6 1068 1090 34.73% 24.34% 40.93%-0.01 +32.1 17
2013-10-27 Daugava L 0-329.7 1108 1439 8.28% 20.70% 71.02%-2.19 -13.1 23
2013-10-27 @ Jurmala W 3-029.7 1439 1108 71.02% 20.70% 8.28%+2.19 +13.1 49
2013-10-27 Ventspils L 0-524.7 966 1535 2.55% 15.40% 82.05%-3.67 -5.9 12
2013-10-27 @ Ilukste NSS W 5-024.7 1535 966 82.05% 15.40% 2.55%+3.67 +5.9 61
2013-10-28 Daugava Riga L 0-231.7 1082 1390 9.25% 21.14% 69.61%-2.05 -10.1 16
2013-10-28 @ Metta W 2-031.7 1390 1082 69.61% 21.14% 9.25%+2.05 +10.1 48
2013-11-02 Daugava Riga W 1-051.9 1100 1400 9.65% 21.30% 69.05%-1.99 +31.4 20
2013-11-02 @ Jelgava L 0-151.9 1400 1100 69.05% 21.30% 9.65%+1.99 -31.4 48
2013-11-02 Ilukste NSS W 6-128.2 1453 960 79.09% 17.17% 3.74%+2.94 +7.5 52
2013-11-02 @ Daugava L 1-628.2 960 1453 3.74% 17.17% 79.09%-2.94 -7.5 12
2013-11-02 Jurmala W 3-031.1 1339 1095 65.09% 22.27% 12.65%+1.39 +19.9 37
2013-11-02 @ Liepajas Metalurgs L 0-331.1 1095 1339 12.65% 22.27% 65.09%-1.39 -19.9 23
2013-11-02 Metta W 3-028.0 1541 1072 78.10% 17.71% 4.20%+2.79 +6.4 64
2013-11-02 @ Ventspils L 0-328.0 1072 1541 4.20% 17.71% 78.10%-2.79 -6.4 16
2013-11-02 Skonto L 0-327.5 1058 1646 2.33% 14.98% 82.68%-3.78 -3.3 25
2013-11-02 @ Spartaks Jurmala W 3-027.5 1646 1058 82.68% 14.98% 2.33%+3.78 +3.3 62
2013-11-09 Daugava W 1-053.1 1065 1460 6.06% 19.37% 74.57%-2.58 +33.5 19
2013-11-09 @ Metta L 0-153.1 1460 1065 74.57% 19.37% 6.06%+2.58 -33.5 52
2013-11-09 Jelgava L 0-254.4 1649 1132 80.08% 16.61% 3.31%+3.09 -66.3 62
2013-11-09 @ Skonto W 2-054.4 1132 1649 3.31% 16.61% 80.08%-3.09 +66.3 23
2013-11-09 Liepajas Metalurgs L 2-1028.1 952 1359 5.70% 19.10% 75.19%-2.66 -14.9 12
2013-11-09 @ Ilukste NSS W 10-228.1 1359 952 75.19% 19.10% 5.70%+2.66 +14.9 40
2013-11-09 Spartaks Jurmala W 2-146.7 1075 1055 40.73% 24.34% 34.93%+0.00 +16.4 26
2013-11-09 @ Jurmala L 1-246.7 1055 1075 34.93% 24.34% 40.73%+0.00 -16.4 25
2013-11-09 Ventspils L 0-143.5 1369 1547 17.34% 23.21% 59.45%-1.24 -9.7 48
2013-11-09 @ Daugava Riga W 1-043.5 1547 1369 59.45% 23.21% 17.34%+1.24 +9.7 67

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 2013-11-09 3.31% Jelgava 1132 2 @ Skonto 1649 0
2 2013-11-09 6.06% @ Metta 1065 1 Daugava 1460 0
3 2013-11-02 9.65% @ Jelgava 1100 1 Daugava Riga 1400 0
4 2013-08-31 10.26% Ilukste NSS 985 4 @ Spartaks Jurmala 1273 2
5 2013-04-07 12.40% @ Daugava Riga 1154 2 Liepajas Metalurgs 1402 1
6 2013-08-18 14.03% @ Jurmala 1113 3 Liepajas Metalurgs 1335 1
7 2013-05-12 15.14% Spartaks Jurmala 1218 2 @ Liepajas Metalurgs 1425 1
8 2013-09-13 15.39% @ Metta 1024 2 Spartaks Jurmala 1227 0
9 2013-07-13 23.02% Metta 1032 2 @ Jurmala 1150 1
10 2013-08-30 24.37% Daugava Riga 1335 1 @ Daugava 1440 0
11 2013-04-14 25.60% Daugava Riga 1182 1 @ Spartaks Jurmala 1276 0
12 2013-06-20 28.38% Daugava Riga 1336 2 @ Liepajas Metalurgs 1406 0
13 2013-07-13 29.66% @ Ilukste NSS 995 2 Jelgava 1055 1
14 2013-04-27 30.22% Daugava Riga 1212 5 @ Jurmala 1268 0
15 2013-04-13 30.64% @ Liepajas Metalurgs 1374 3 Ventspils 1427 1
16 2013-10-26 34.73% Jelgava 1068 3 @ Spartaks Jurmala 1090 1
17 2013-09-29 37.75% @ Jelgava 1032 3 Ilukste NSS 1032 1

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 2013-04-27 94.45 Daugava Riga 5 1212 30.22% @ Jurmala 0 1268 45.54% 24.24%
2 2013-11-09 66.30 Jelgava 2 1132 3.31% @ Skonto 0 1649 80.08% 16.61%
3 2013-10-18 62.02 @ Liepajas Metalurgs 6 1283 54.56% Spartaks Jurmala 0 1152 21.71% 23.73%
4 2013-09-13 53.19 @ Metta 2 1024 15.39% Spartaks Jurmala 0 1227 61.73% 22.88%
5 2013-08-18 47.24 @ Jurmala 3 1113 14.03% Liepajas Metalurgs 1 1335 63.37% 22.60%
6 2013-04-27 46.78 @ Skonto 3 1430 41.53% Ventspils 0 1404 34.14% 24.33%
7 2013-07-14 46.38 @ Skonto 5 1536 57.65% Daugava Riga 0 1376 18.92% 23.43%
8 2013-08-31 45.31 Ilukste NSS 4 985 10.26% @ Spartaks Jurmala 2 1273 68.21% 21.53%
9 2013-06-20 41.82 Daugava Riga 2 1336 28.38% @ Liepajas Metalurgs 0 1406 47.45% 24.17%
10 2013-08-10 39.36 Skonto 5 1574 61.30% @ Liepajas Metalurgs 0 1375 15.75% 22.95%
11 2013-04-13 34.70 @ Liepajas Metalurgs 3 1374 30.64% Ventspils 1 1427 45.11% 24.25%
12 2013-03-29 34.50 @ Liepajas Metalurgs 4 1368 59.67% Metta 0 1187 17.15% 23.18%
13 2013-10-06 33.51 Daugava Riga 4 1342 60.30% @ Jurmala 0 1154 16.61% 23.09%
14 2013-11-09 33.50 @ Metta 1 1065 6.06% Daugava 0 1460 74.57% 19.37%
15 2013-03-30 33.46 @ Ventspils 4 1380 60.33% Jelgava 0 1192 16.58% 23.09%
16 2013-10-26 32.07 Jelgava 3 1068 34.73% @ Spartaks Jurmala 1 1090 40.93% 24.34%
17 2013-11-02 31.37 @ Jelgava 1 1100 9.65% Daugava Riga 0 1400 69.05% 21.30%
18 2013-05-11 31.27 Skonto 4 1477 50.49% @ Daugava 1 1382 25.49% 24.02%
19 2013-05-10 31.14 @ Daugava Riga 4 1306 61.82% Ilukste NSS 0 1102 15.32% 22.86%
20 2013-04-07 30.38 @ Skonto 5 1383 65.98% Ilukste NSS 0 1127 11.95% 22.08%
21 2013-09-29 30.22 @ Jelgava 3 1032 37.75% Ilukste NSS 1 1032 37.90% 24.36%
22 2013-06-21 29.56 @ Spartaks Jurmala 4 1282 62.83% Metta 0 1066 14.48% 22.70%
23 2013-04-07 28.10 @ Daugava Riga 2 1154 12.40% Liepajas Metalurgs 1 1402 65.39% 22.20%
24 2013-06-20 26.79 @ Jurmala 4 1099 38.19% Jelgava 2 1096 37.46% 24.36%
25 2013-05-12 26.72 Spartaks Jurmala 2 1218 15.14% @ Liepajas Metalurgs 1 1425 62.03% 22.83%

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 2013-10-05 68.6 @ Skonto 1 1650 55.32% Ventspils 1 1512 21.01% 23.67%
2 2013-09-20 62.6 @ Skonto 2 1645 82.00% Metta 2 1077 2.57% 15.43%
3 2013-10-19 62.4 @ Daugava 0 1434 14.74% Skonto 0 1646 62.51% 22.75%
4 2013-06-26 61.5 @ Ventspils 2 1439 47.97% Liepajas Metalurgs 2 1365 27.88% 24.15%
5 2013-07-28 60.4 @ Ventspils 0 1449 21.42% Skonto 0 1582 54.88% 23.71%
6 2013-09-25 59.9 @ Liepajas Metalurgs 2 1300 23.85% Daugava 2 1410 52.24% 23.91%
7 2013-09-16 59.3 @ Daugava Riga 2 1359 44.80% Liepajas Metalurgs 2 1309 30.94% 24.26%
8 2013-07-29 59.0 @ Jelgava 2 1035 8.28% Liepajas Metalurgs 2 1366 71.02% 20.70%
9 2013-08-03 59.0 @ Skonto 0 1578 58.05% Daugava 0 1414 18.57% 23.38%
10 2013-03-31 58.1 @ Spartaks Jurmala 2 1266 55.80% Ilukste NSS 2 1124 20.58% 23.62%
11 2013-09-14 57.9 @ Jelgava 2 1020 21.50% Jurmala 2 1153 54.79% 23.71%
12 2013-04-20 57.8 @ Jelgava 2 1136 42.77% Ilukste NSS 2 1101 32.92% 24.31%
13 2013-08-31 57.7 Ilukste NSS 4 985 10.26% @ Spartaks Jurmala 2 1273 68.21% 21.53%
14 2013-04-06 55.9 @ Ventspils 4 1413 44.91% Daugava 3 1362 30.83% 24.26%
15 2013-04-07 55.9 @ Daugava Riga 2 1154 12.40% Liepajas Metalurgs 1 1402 65.39% 22.20%
16 2013-04-21 55.9 @ Daugava 1 1357 30.65% Liepajas Metalurgs 1 1409 45.10% 24.25%
17 2013-05-12 55.6 Spartaks Jurmala 2 1218 15.14% @ Liepajas Metalurgs 1 1425 62.03% 22.83%
18 2013-05-16 55.6 @ Skonto 1 1508 73.37% Jelgava 1 1136 6.77% 19.86%
19 2013-09-15 55.4 @ Ventspils 0 1482 46.74% Daugava 0 1416 29.06% 24.20%
20 2013-11-09 54.4 Jelgava 2 1132 3.31% @ Skonto 0 1649 80.08% 16.61%
21 2013-08-09 54.1 @ Daugava Riga 1 1348 68.70% Metta 1 1054 9.90% 21.40%
22 2013-04-12 53.4 @ Jurmala 1 1261 58.09% Ilukste NSS 1 1097 18.54% 23.38%
23 2013-08-18 53.1 @ Jurmala 3 1113 14.03% Liepajas Metalurgs 1 1335 63.37% 22.60%
24 2013-11-09 53.1 @ Metta 1 1065 6.06% Daugava 0 1460 74.57% 19.37%
25 2013-04-29 53.0 @ Ilukste NSS 1 1102 37.14% Metta 1 1106 38.50% 24.35%
# Date Excitement Winning Team Losing Team Tie %
Team Score Elo Win % Team Score Elo Win %
1 2013-10-27 24.7 Ventspils 5 1535 82.05% @ Ilukste NSS 0 966 2.55% 15.40%
2 2013-08-25 26.9 Skonto 3 1630 83.16% @ Jelgava 0 1028 2.18% 14.66%
3 2013-10-14 27.2 Ventspils 7 1516 80.50% @ Ilukste NSS 1 988 3.14% 16.36%
4 2013-11-02 27.5 Skonto 3 1646 82.68% @ Spartaks Jurmala 0 1058 2.33% 14.98%
5 2013-06-16 27.6 Skonto 5 1508 74.52% @ Jurmala 0 1114 6.09% 19.39%
6 2013-06-20 27.8 Skonto 7 1523 79.17% @ Ilukste NSS 1 1028 3.70% 17.13%
7 2013-11-02 28.0 @ Ventspils 3 1541 78.10% Metta 0 1072 4.20% 17.71%
8 2013-11-09 28.1 Liepajas Metalurgs 10 1359 75.19% @ Ilukste NSS 2 952 5.70% 19.10%
9 2013-11-02 28.2 @ Daugava 6 1453 79.09% Ilukste NSS 1 960 3.74% 17.17%
10 2013-05-31 28.4 @ Daugava 5 1365 68.97% Ilukste NSS 0 1066 9.71% 21.32%
11 2013-06-01 28.5 @ Ventspils 4 1399 70.59% Metta 0 1075 8.57% 20.84%
12 2013-08-23 28.7 @ Daugava 3 1430 73.58% Metta 0 1054 6.64% 19.77%
13 2013-09-15 28.7 Skonto 2 1643 83.53% @ Ilukste NSS 0 1031 2.06% 14.41%
14 2013-10-21 28.7 @ Daugava Riga 7 1375 74.56% Ilukste NSS 1 980 6.06% 19.38%
15 2013-08-31 28.9 @ Skonto 5 1633 78.10% Jurmala 0 1163 4.20% 17.70%
16 2013-06-26 29.2 Skonto 2 1532 79.22% @ Metta 0 1036 3.68% 17.10%
17 2013-04-07 29.5 @ Skonto 5 1383 65.98% Ilukste NSS 0 1127 11.95% 22.08%
18 2013-08-30 29.5 @ Ventspils 2 1477 77.30% Jelgava 0 1025 4.59% 18.11%
19 2013-06-27 29.6 Daugava 3 1388 70.27% @ Jelgava 0 1069 8.79% 20.94%
20 2013-08-18 29.7 Daugava 2 1424 76.00% @ Ilukste NSS 0 1001 5.26% 18.74%
21 2013-10-27 29.7 Daugava 3 1439 71.02% @ Jurmala 0 1108 8.28% 20.70%
22 2013-04-12 29.8 @ Skonto 4 1413 67.26% Metta 0 1140 10.96% 21.77%
23 2013-08-17 30.3 Ventspils 2 1459 74.75% @ Metta 0 1060 5.96% 19.30%
24 2013-10-20 30.5 @ Ventspils 6 1523 74.96% Jurmala 1 1120 5.83% 19.20%
25 2013-06-21 30.6 @ Spartaks Jurmala 4 1282 62.83% Metta 0 1066 14.48% 22.70%