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2016-17 Armenian Premier League Season

90 games

Final

Champion

Alashkert

64 points · 2nd Title

Relegated

No relegation

Biggest Overachiever

Alashkert

9.40 points above expected

64 points · 54.60 expected points

Biggest Disappointment

Ararat

7.76 points below expected

12 points · 19.76 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 Alashkert Champion 30 19 7 4 64 59 26 +33 54.60 +9.40
2 Gandzasar Kapan 30 17 6 7 57 38 24 +14 51.59 +5.41
3 Shirak 30 16 5 9 53 31 24 +7 48.72 +4.28
4 Pyunik 30 12 9 9 45 35 27 +8 49.42 -4.42
5 Banants 30 5 6 19 21 18 44 -26 27.75 -6.75
6 Ararat 30 3 3 24 12 17 53 -36 19.76 -7.76

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 Alashkert 64 54.60 +9.40
2 Gandzasar Kapan 57 51.59 +5.41
3 Shirak 53 48.72 +4.28
4 Pyunik 45 49.42 -4.42
5 Banants 21 27.75 -6.75

Biggest Disappointments

# Team Actual Sim vsSim
1 Ararat 12 19.76 -7.76
2 Banants 21 27.75 -6.75
3 Pyunik 45 49.42 -4.42
4 Shirak 53 48.72 +4.28
5 Gandzasar Kapan 57 51.59 +5.41

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 Gandzasar Kapan 7 Dec 3 – Apr 16 1 in 43
2 Alashkert 5 Apr 7 – May 6 1 in 14
3 Pyunik 4 Oct 15 – Oct 30 1 in 14
4 Banants 2 Sep 17 – Sep 27 1 in 9
5 Shirak 3 Aug 6 – Aug 20 1 in 8

Most Unlikely Losing Streaks

# Team Games Dates Probability
1 Pyunik 3 Apr 7 – Apr 21 1 in 54
2 Gandzasar Kapan 4 Aug 21 – Sep 18 1 in 22
3 Shirak 3 Mar 12 – Apr 1 1 in 14
4 Banants 5 May 6 – May 31 1 in 13
5 Ararat 7 Dec 3 – Apr 15 1 in 11

Most Unlikely Unbeaten Streaks

# Team Games Dates Probability
1 Banants 3 Nov 19 – Nov 27 1 in 15
2 Shirak 6 Aug 6 – Sep 18 1 in 8
3 Ararat 2 Aug 27 – Sep 10 1 in 8
4 Pyunik 7 Oct 15 – Nov 22 1 in 7
5 Gandzasar Kapan 9 Dec 3 – Apr 29 1 in 7

Most Unlikely Winless Streaks

# Team Games Dates Probability
1 Pyunik 7 Apr 7 – May 20 1 in 44
2 Banants 13 Oct 2 – Mar 19 1 in 42
3 Ararat 18 Sep 17 – Apr 15 1 in 24
4 Alashkert 2 Aug 27 – Sep 10 1 in 5
5 Gandzasar Kapan 4 Aug 21 – Sep 18 1 in 5

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
Alashkert 1523 64 +47 13 11.0 +2.0
Gandzasar Kapan 1429 57 -27 8 10.4 -2.4
Shirak 1293 53 +43 10 7.6 +2.4
Pyunik 1241 45 -2 8 6.8 +1.2
Banants 984 21 -67 0 3.6 -3.6
Ararat 971 12 +6 3 2.7 +0.3

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 ALA ARA BAN GK PYU SHI
Alashkert —
5-0-1
14.49
6-0-0
12.56
3-1-2
9.48
2-3-1
9.38
3-3-0
9.50
Ararat
1-0-5
2.41
—
1-2-3
6.63
0-0-6
4.01
1-1-4
3.37
0-0-6
3.05
Banants
0-0-6
4.26
3-2-1
10.10
—
1-2-3
4.44
0-2-4
4.32
1-0-5
4.44
Gandzasar Kapan
2-1-3
7.26
6-0-0
12.84
3-2-1
12.38
—
3-2-1
9.44
3-1-2
9.07
Pyunik
1-3-2
7.37
4-1-1
13.44
4-2-0
12.46
1-2-3
7.31
—
2-1-3
8.37
Shirak
0-3-3
7.24
6-0-0
13.78
5-0-1
12.34
2-1-3
7.68
3-1-2
8.36
—

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 0.78 +12.0
Allowed 0.91 -16.1
Differential 0.97 +7.9

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
012.22%12.78%6.11%5.00%1.67%—37.78%
112.78%5.56%8.89%2.22%2.22%—31.67%
26.11%8.89%1.11%1.11%——17.22%
35.00%2.22%1.11%1.11%——9.44%
41.67%2.22%————3.89%
5+———————
Total37.78%31.67%17.22%9.44%3.89%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.10 1.10 +0.00
SD 1.13 1.13 1.72
CV 1.03 1.03 —
Max 4 4 +4
Min 0 0 -4

Games Played: 90

↓ Scored | Allowed →012345+Total
013.33%———3.33%—16.67%
16.67%3.33%6.67%3.33%——20.00%
26.67%13.33%3.33%———23.33%
320.00%6.67%—3.33%——30.00%
4—10.00%————10.00%
5+———————
Total46.67%33.33%10.00%6.67%3.33%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.97 0.87 +1.10
SD 1.27 1.07 1.75
CV 0.65 1.24 —
Max 4 4 +3
Min 0 0 -4

Games Played: 30

↓ Scored | Allowed →012345+Total
06.67%23.33%13.33%6.67%3.33%—53.33%
16.67%3.33%20.00%3.33%6.67%—40.00%
2———3.33%——3.33%
3—3.33%————3.33%
4———————
5+———————
Total13.33%30.00%33.33%13.33%10.00%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.57 1.77 -1.20
SD 0.73 1.17 1.30
CV 1.28 0.66 —
Max 3 4 +2
Min 0 0 -4

Games Played: 30

↓ Scored | Allowed →012345+Total
010.00%23.33%6.67%13.33%3.33%—56.67%
16.67%10.00%13.33%—3.33%—33.33%
23.33%3.33%————6.67%
3———————
4—3.33%————3.33%
5+———————
Total20.00%40.00%20.00%13.33%6.67%—100%

Summary Statistics

Scored Allowed Difference
Mean 0.60 1.47 -0.87
SD 0.89 1.17 1.59
CV 1.49 0.80 —
Max 4 4 +3
Min 0 0 -4

Games Played: 30

↓ Scored | Allowed →012345+Total
013.33%10.00%3.33%3.33%——30.00%
116.67%6.67%3.33%—3.33%—30.00%
210.00%20.00%————30.00%
3——3.33%———3.33%
46.67%—————6.67%
5+———————
Total46.67%36.67%10.00%3.33%3.33%—100%

Summary Statistics

Scored Allowed Difference
Mean 1.27 0.80 +0.47
SD 1.14 1.00 1.61
CV 0.90 1.25 —
Max 4 4 +4
Min 0 0 -3

Games Played: 30

↓ Scored | Allowed →012345+Total
020.00%6.67%10.00%3.33%——40.00%
16.67%6.67%6.67%3.33%——23.33%
26.67%13.33%————20.00%
310.00%——3.33%——13.33%
43.33%—————3.33%
5+———————
Total46.67%26.67%16.67%10.00%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.17 0.90 +0.27
SD 1.21 1.03 1.70
CV 1.03 1.14 —
Max 4 3 +4
Min 0 0 -3

Games Played: 30

↓ Scored | Allowed →012345+Total
010.00%13.33%3.33%3.33%——30.00%
133.33%3.33%3.33%3.33%——43.33%
210.00%3.33%3.33%3.33%——20.00%
3—3.33%3.33%———6.67%
4———————
5+———————
Total53.33%23.33%13.33%10.00%——100%

Summary Statistics

Scored Allowed Difference
Mean 1.03 0.80 +0.23
SD 0.89 1.03 1.30
CV 0.86 1.29 —
Max 3 3 +2
Min 0 0 -3

Games Played: 30

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
Alashkert 1523 64 54.60 +9.40 94.0% 35 44 50 55 58 65 72
Gandzasar Kapan 1429 57 51.59 +5.41 84.0% 26 43 49 51 55 61 69
Shirak 1293 53 48.72 +4.28 78.0% 33 36 44 49 53 59 69
Pyunik 1241 45 49.42 -4.42 31.0% 32 37 43 50 54 62 64
Banants 984 21 27.75 -6.75 23.0% 17 18 23 27 32 39 47
Ararat 971 12 19.76 -7.76 4.0% 4 13 16 20 23 28 33

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 5% * Slight Edge: 5% to 10% * Clear Edge: 10% to 14% * Strong Edge: 14% 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
-2.22%
No Edge
38.89%20.00%41.11%
Elo Value
Home Edge: -7.72 Elo pts.
273 Elo
0.004 goals per Elo point
0800
Scoring Tilt
Expected
+0.02 goals
Neutral
-2-0.03+2

Title Race

How these are measured

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

Title-Race Openness
Effective number of teams with a live shot at finishing 1st, from the simulation. 1 means the favorite is a near-lock; larger means a wide-open race. Equal to 1 divided by the sum of squared title odds.
One-Team Race: under 2 * Top-Heavy: 2 to 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 * Longshot: 4th 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 0.07 * Tight Race: 0.07 to 0.19 * Comfortable: 0.19 to 0.27 * Runaway: 0.27 and up.
Title-Race Openness
3.5
Open
12346
Champion Preseason Odds
41%
Alashkert, 1st of 6
LongshotFavorite
Title Margin
Expected
0.23/gm
Comfortable
00.180.5/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 5.17 * Some Luck: 5.17 to 7.75 * Lucky: 7.75 to 10.34 * Wild Swing: 10.34 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 0.57 * Close: 0.57 to 0.85 * Off: 0.85 to 1.14 * Way Off: 1.14 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 6 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 6 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 6 * As Expected: 6 to 9.6 * Several Outliers: 9.6 to 13.2 * Many Outliers: 13.2 and up.
Luck Spread
Expected
6.60 points
Some Luck
06.4616
Average Finish Error
Expected
0.33
Pinpoint
00.711.5
Biggest Overachiever
Expected
94.00%
Alashkert
5091.67%100
Biggest Underachiever
Expected
4.00%
Ararat
08.33%50
Season Outliers
Expected
1 of 6
Minimal Outliers
00.66

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 0.2 * Even: 0.2 to 0.25 * Top-Heavy: 0.25 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 2.25 * Moderate Separation: 2.25 to 2.55 * Strong Separation: 2.55 to 2.8 * Wide Separation: 2.8 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 72.5% * Slight Edge: 72.5% to 85% * Clear Edge: 85% to 89% * Wide Edge: 89% 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 93.5% * Clear Edge: 93.5% to 97.5% * Strong Edge: 97.5% 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 47% * Some Drama: 47% to 56% * Frequent: 56% to 64.5% * Very Frequent: 64.5% 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 15% * Occasional: 15% to 20.5% * Frequent: 20.5% to 32% * Very Frequent: 32% and up.
Gini Index
0.25
Even
00.20.280.5
Noll-Scully
Elo SD: 226.35
2.81
Wide Separation
12.252.553.5
Interquartile Edge
88%
Clear Edge
50%72.5%85%100%
Best vs. Worst
Baseline 97%
96%
Clear Edge
50%100%
Close Games
Expected
66%
Very Frequent
0%61%100%
Blowouts
Expected
18%
Occasional
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 0.45 * Slight Separation: 0.45 to 0.51 * Notable Separation: 0.51 to 0.57 * Lopsided: 0.57 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 0.37 * Some Carryover: 0.37 to 0.63 * Strong Carryover: 0.63 to 0.77 * Near-Lock: 0.77 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 16% * As Expected: 16% to 19% * Upset-Prone: 19% to 23% * Very Upset-Prone: 23% 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 12.5% * As Expected: 12.5% to 15% * Shaky Favorites: 15% to 19% * Very Shaky: 19% and up.
Brier Score
Expected
0.50
Highly Predictable
00.542
Matchup Imbalance
0.46
Slight Separation
00.5
Strangeness
Expected
1.16
Wilder Than Modeled
01.002
Repeatability
0.77
Near-Lock
00.370.630.771
Upset Rate
Expected
17%
As Expected
0%21%50%
Clear Favorite Upset Rate
Expected
11%
Solid Favorites
0%16%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 0.17 * Near Noise Ceiling: 0.17 to 0.26 * Above Noise: 0.26 to 0.35 * Well Above Noise: 0.35 and up.
Probability calibration
0.76
Excellent
0.010.050.10.51
Calibration slope
Ideal
1.34
Very Underconfident
0.51.001.5
Calibration error (ECE)
Noise ceiling
0.072
Well Within Noise
00.1740.4

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).

Team123456
Alashkert41.00%36.00%14.00%9.00%——
Gandzasar Kapan22.00%26.00%38.00%13.00%—1.00%
Shirak15.00%17.00%25.00%43.00%——
Pyunik22.00%21.00%21.00%32.00%4.00%—
Banants——2.00%2.00%79.00%17.00%
Ararat———1.00%17.00%82.00%

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
Alashkert 100%
Ararat 100%
Banants 100%
Gandzasar Kapan 100%
Pyunik 100%
Shirak 100%

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
2016-08-06 Ararat W 1-040.2 1204 1161 45.33% 21.17% 33.50%+0.13 +20.3 3
2016-08-06 @ Banants L 0-140.2 1161 1204 33.50% 21.17% 45.33%-0.13 -20.3 0
2016-08-06 Pyunik W 3-145.3 1274 1282 38.25% 21.21% 40.55%-0.06 +38.5 3
2016-08-06 @ Shirak L 1-345.3 1282 1274 40.55% 21.21% 38.25%+0.06 -38.5 0
2016-08-07 Gandzasar Kapan D 0-051.3 1295 1226 48.73% 21.12% 30.15%+0.22 -2.6 1
2016-08-07 @ Alashkert D 0-051.3 1226 1295 30.15% 21.12% 48.73%-0.22 +2.6 1
2016-08-13 Alashkert L 1-246.9 1243 1292 32.62% 21.16% 46.22%-0.21 -18.7 0
2016-08-13 @ Pyunik W 2-146.9 1292 1243 46.22% 21.16% 32.62%+0.21 +18.7 4
2016-08-13 Ararat W 2-034.7 1229 1141 51.25% 21.06% 27.70%+0.29 +32.7 4
2016-08-13 @ Gandzasar Kapan L 0-234.7 1141 1229 27.70% 21.06% 51.25%-0.29 -32.7 0
2016-08-14 Shirak L 0-138.8 1224 1312 27.68% 21.06% 51.26%-0.35 -17.3 3
2016-08-14 @ Banants W 1-038.8 1312 1224 51.26% 21.06% 27.68%+0.35 +17.3 6
2016-08-20 Ararat W 1-034.4 1329 1108 64.79% 20.28% 14.94%+0.78 +10.1 9
2016-08-20 @ Shirak L 0-134.4 1108 1329 14.94% 20.28% 64.79%-0.78 -10.1 0
2016-08-21 Gandzasar Kapan W 3-038.1 1224 1262 34.17% 21.18% 44.65%-0.17 +70.0 3
2016-08-21 @ Pyunik L 0-338.1 1262 1224 44.65% 21.18% 34.17%+0.17 -70.0 4
2016-08-21 Banants W 3-032.5 1311 1206 53.18% 21.00% 25.82%+0.35 +44.8 7
2016-08-21 @ Alashkert L 0-332.5 1206 1311 25.82% 21.00% 53.18%-0.35 -44.8 3
2016-08-27 Alashkert D 2-264.5 1340 1356 37.12% 21.20% 41.68%-0.09 +0.4 10
2016-08-27 @ Shirak D 2-264.5 1356 1340 41.68% 21.20% 37.12%+0.09 -0.4 8
2016-08-27 Pyunik D 0-051.2 1098 1294 16.87% 20.47% 62.66%-0.75 +6.8 1
2016-08-27 @ Ararat D 0-051.2 1294 1098 62.66% 20.47% 16.87%+0.75 -6.8 4
2016-08-28 Gandzasar Kapan W 4-142.3 1162 1192 35.17% 21.19% 43.64%-0.14 +57.9 6
2016-08-28 @ Banants L 1-442.3 1192 1162 43.64% 21.19% 35.17%+0.14 -57.9 4
2016-09-10 Ararat L 1-352.5 1355 1105 67.03% 20.03% 12.95%+0.89 -60.9 8
2016-09-10 @ Alashkert W 3-152.5 1105 1355 12.95% 20.03% 67.03%-0.89 +60.9 4
2016-09-11 Shirak L 0-134.9 1134 1340 16.09% 20.40% 63.52%-0.78 -10.8 4
2016-09-11 @ Gandzasar Kapan W 1-034.9 1340 1134 63.52% 20.40% 16.09%+0.78 +10.8 13
2016-09-11 Banants W 2-146.1 1287 1220 48.70% 21.12% 30.19%+0.22 +17.5 7
2016-09-11 @ Pyunik L 1-246.1 1220 1287 30.19% 21.12% 48.70%-0.22 -17.6 6
2016-09-17 Banants L 0-236.7 1166 1202 34.33% 21.18% 44.49%-0.16 -39.0 4
2016-09-17 @ Ararat W 2-036.7 1202 1166 44.49% 21.18% 34.33%+0.16 +39.0 9
2016-09-18 Alashkert L 0-232.0 1123 1294 19.02% 20.64% 60.34%-0.66 -23.6 4
2016-09-18 @ Gandzasar Kapan W 2-032.0 1294 1123 60.34% 20.64% 19.02%+0.66 +23.6 11
2016-09-18 Shirak D 0-052.2 1305 1351 33.06% 21.17% 45.77%-0.20 +1.7 8
2016-09-18 @ Pyunik D 0-052.2 1351 1305 45.77% 21.17% 33.06%+0.20 -1.7 14
2016-09-25 Gandzasar Kapan L 0-239.3 1127 1099 43.27% 21.19% 35.54%+0.07 -46.9 4
2016-09-25 @ Ararat W 2-039.3 1099 1127 35.54% 21.19% 43.27%-0.07 +46.9 7
2016-09-27 Pyunik D 0-051.9 1318 1307 40.98% 21.21% 37.81%+0.01 -0.4 12
2016-09-27 @ Alashkert D 0-051.9 1307 1318 37.81% 21.21% 40.98%-0.01 +0.4 9
2016-09-27 Banants L 0-146.9 1349 1241 53.61% 20.98% 25.41%+0.37 -30.0 14
2016-09-27 @ Shirak W 1-046.9 1241 1349 25.41% 20.98% 53.61%-0.37 +30.0 12
2016-10-01 Pyunik W 1-047.9 1146 1307 19.96% 20.71% 59.33%-0.62 +33.0 10
2016-10-01 @ Gandzasar Kapan L 0-147.9 1307 1146 59.33% 20.71% 19.96%+0.62 -33.0 9
2016-10-01 Shirak L 0-134.0 1080 1319 13.69% 20.12% 66.19%-0.90 -9.3 4
2016-10-01 @ Ararat W 1-034.0 1319 1080 66.19% 20.12% 13.69%+0.90 +9.3 17
2016-10-02 Alashkert L 0-335.0 1271 1317 32.96% 21.17% 45.87%-0.20 -54.8 12
2016-10-02 @ Banants W 3-035.0 1317 1271 45.87% 21.17% 32.96%+0.20 +54.8 15
2016-10-15 Ararat W 4-028.9 1274 1071 63.30% 20.42% 16.28%+0.72 +39.0 12
2016-10-15 @ Pyunik L 0-428.9 1071 1274 16.28% 20.42% 63.30%-0.72 -39.0 4
2016-10-15 Banants W 4-037.7 1179 1216 34.25% 21.18% 44.57%-0.16 +91.2 13
2016-10-15 @ Gandzasar Kapan L 0-437.7 1216 1179 44.57% 21.18% 34.25%+0.16 -91.2 12
2016-10-16 Shirak D 1-158.4 1372 1328 45.54% 21.17% 33.29%+0.13 -1.5 16
2016-10-16 @ Alashkert D 1-158.4 1328 1372 33.29% 21.17% 45.54%-0.13 +1.5 18
2016-10-22 Alashkert L 1-238.6 1032 1371 8.27% 19.10% 72.63%-1.27 -5.4 4
2016-10-22 @ Ararat W 2-138.6 1371 1032 72.63% 19.10% 8.27%+1.27 +5.4 19
2016-10-22 Gandzasar Kapan W 1-040.3 1330 1271 47.55% 21.14% 31.31%+0.19 +19.2 21
2016-10-22 @ Shirak L 0-140.3 1271 1330 31.31% 21.14% 47.55%-0.19 -19.2 13
2016-10-23 Pyunik L 0-135.3 1125 1313 17.53% 20.53% 61.94%-0.72 -11.7 12
2016-10-23 @ Banants W 1-035.3 1313 1125 61.94% 20.53% 17.53%+0.72 +11.7 15
2016-10-26 Ararat D 0-050.8 1113 1026 51.12% 21.06% 27.82%+0.29 -3.3 13
2016-10-26 @ Banants D 0-050.8 1026 1113 27.82% 21.06% 51.12%-0.29 +3.3 5
2016-10-26 Pyunik L 0-144.4 1349 1325 42.81% 21.20% 35.99%+0.06 -24.7 21
2016-10-26 @ Shirak W 1-044.4 1325 1349 35.99% 21.20% 42.81%-0.06 +24.7 18
2016-10-27 Gandzasar Kapan L 0-441.9 1376 1251 55.51% 20.91% 23.58%+0.43 -110.9 19
2016-10-27 @ Alashkert W 4-041.9 1251 1376 23.58% 20.91% 55.51%-0.43 +110.9 16
2016-10-29 Shirak L 1-241.2 1110 1324 15.46% 20.33% 64.21%-0.81 -9.8 13
2016-10-29 @ Banants W 2-141.2 1324 1110 64.21% 20.33% 15.46%+0.81 +9.8 24
2016-10-30 Alashkert W 2-146.0 1350 1265 50.77% 21.07% 28.16%+0.28 +16.6 21
2016-10-30 @ Pyunik L 1-246.0 1265 1350 28.16% 21.07% 50.77%-0.28 -16.6 19
2016-10-30 Ararat W 1-032.1 1362 1029 72.29% 19.17% 8.54%+1.19 +5.9 19
2016-10-30 @ Gandzasar Kapan L 0-132.1 1029 1362 8.54% 19.17% 72.29%-1.19 -5.9 5
2016-11-04 Ararat W 2-028.7 1334 1024 71.01% 19.42% 9.56%+1.11 +12.5 27
2016-11-04 @ Shirak L 0-228.7 1024 1334 9.56% 19.42% 71.01%-1.11 -12.5 5
2016-11-05 Gandzasar Kapan D 0-053.1 1366 1368 39.07% 21.21% 39.72%-0.04 +0.1 22
2016-11-05 @ Pyunik D 0-053.1 1368 1366 39.72% 21.21% 39.07%+0.04 -0.1 20
2016-11-05 Banants W 4-135.4 1249 1100 58.07% 20.78% 21.15%+0.52 +31.8 22
2016-11-05 @ Alashkert L 1-435.4 1100 1249 21.15% 20.78% 58.07%-0.52 -31.8 13
2016-11-19 Gandzasar Kapan D 1-157.2 1068 1368 10.10% 19.54% 70.36%-1.13 +8.3 14
2016-11-19 @ Banants D 1-157.2 1368 1068 70.36% 19.54% 10.10%+1.13 -8.3 21
2016-11-19 Pyunik L 1-238.3 1011 1366 7.62% 18.91% 73.46%-1.33 -5.0 5
2016-11-19 @ Ararat W 2-138.3 1366 1011 73.46% 18.91% 7.62%+1.33 +5.0 25
2016-11-20 Alashkert D 0-051.9 1347 1280 48.47% 21.12% 30.41%+0.21 -2.5 28
2016-11-20 @ Shirak D 0-051.9 1280 1347 30.41% 21.12% 48.47%-0.21 +2.5 23
2016-11-22 Banants D 1-157.2 1371 1077 70.03% 19.59% 10.38%+1.05 -8.2 26
2016-11-22 @ Pyunik D 1-157.2 1077 1371 10.38% 19.59% 70.03%-1.05 +8.2 15
2016-11-23 Ararat W 4-132.1 1283 1006 68.89% 19.77% 11.33%+0.99 +18.0 26
2016-11-23 @ Alashkert L 1-432.1 1006 1283 11.33% 19.77% 68.89%-0.99 -18.0 5
2016-11-23 Shirak W 1-043.1 1360 1344 41.66% 21.20% 37.14%+0.03 +22.0 24
2016-11-23 @ Gandzasar Kapan L 0-143.1 1344 1360 37.14% 21.20% 41.66%-0.03 -22.0 28
2016-11-26 Shirak L 0-241.5 1363 1322 45.13% 21.18% 33.70%+0.12 -48.6 26
2016-11-26 @ Pyunik W 2-041.5 1322 1363 33.70% 21.18% 45.13%-0.12 +48.6 31
2016-11-27 Alashkert L 1-253.3 1382 1301 50.36% 21.08% 28.56%+0.27 -26.7 24
2016-11-27 @ Gandzasar Kapan W 2-153.3 1301 1382 28.56% 21.08% 50.36%-0.27 +26.7 29
2016-11-27 Banants D 1-156.5 988 1085 26.67% 21.03% 52.30%-0.38 +3.2 6
2016-11-27 @ Ararat D 1-156.5 1085 988 52.30% 21.03% 26.67%+0.38 -3.2 16
2016-12-03 Gandzasar Kapan L 0-131.6 991 1355 7.29% 18.81% 73.90%-1.36 -5.1 6
2016-12-03 @ Ararat W 1-031.6 1355 991 73.90% 18.81% 7.29%+1.36 +5.0 27
2016-12-03 Shirak L 0-133.0 1082 1371 10.67% 19.65% 69.68%-1.09 -7.4 16
2016-12-03 @ Banants W 1-033.0 1371 1082 69.68% 19.65% 10.67%+1.09 +7.3 34
2016-12-04 Pyunik D 0-052.0 1328 1314 41.30% 21.21% 37.50%+0.02 -0.5 30
2016-12-04 @ Alashkert D 0-052.0 1314 1328 37.50% 21.21% 41.30%-0.02 +0.5 27
2017-03-04 Alashkert L 1-240.2 1074 1327 12.78% 20.00% 67.21%-0.95 -8.2 16
2017-03-04 @ Banants W 2-140.2 1327 1074 67.21% 20.00% 12.78%+0.95 +8.2 33
2017-03-05 Pyunik W 2-037.8 1360 1315 45.73% 21.17% 33.10%+0.14 +37.8 30
2017-03-05 @ Gandzasar Kapan L 0-237.8 1315 1360 33.10% 21.17% 45.73%-0.14 -37.8 27
2017-03-05 Shirak L 0-131.2 986 1378 6.32% 18.46% 75.22%-1.46 -4.4 6
2017-03-05 @ Ararat W 1-031.2 1378 986 75.22% 18.46% 6.32%+1.46 +4.4 37
2017-03-10 Ararat W 3-027.0 1277 982 70.07% 19.59% 10.34%+1.05 +19.5 30
2017-03-10 @ Pyunik L 0-327.0 982 1277 10.34% 19.59% 70.07%-1.05 -19.5 6
2017-03-11 Banants W 1-032.3 1398 1066 72.24% 19.18% 8.58%+1.19 +5.9 33
2017-03-11 @ Gandzasar Kapan L 0-132.3 1066 1398 8.58% 19.18% 72.24%-1.19 -6.0 16
2017-03-12 Shirak W 3-040.2 1335 1382 32.89% 21.17% 45.95%-0.20 +71.7 36
2017-03-12 @ Alashkert L 0-340.2 1382 1335 45.95% 21.17% 32.89%+0.20 -71.7 37
2017-03-17 Alashkert L 0-324.9 962 1407 4.81% 17.75% 77.44%-1.66 -9.1 6
2017-03-17 @ Ararat W 3-024.9 1407 962 77.44% 17.75% 4.81%+1.66 +9.1 39
2017-03-18 Gandzasar Kapan L 1-246.7 1311 1404 27.08% 21.04% 51.88%-0.37 -16.0 37
2017-03-18 @ Shirak W 2-146.7 1404 1311 51.88% 21.04% 27.08%+0.37 +16.0 36
2017-03-19 Pyunik L 0-328.3 1060 1297 13.87% 20.15% 65.98%-0.89 -25.8 16
2017-03-19 @ Banants W 3-028.3 1297 1060 65.98% 20.15% 13.87%+0.89 +25.8 33
2017-03-30 Gandzasar Kapan L 1-252.7 1416 1420 38.82% 21.21% 39.97%-0.04 -21.5 39
2017-03-30 @ Alashkert W 2-152.7 1420 1416 39.97% 21.21% 38.82%+0.04 +21.5 39
2017-03-31 Ararat W 2-145.1 1034 953 50.37% 21.08% 28.55%+0.27 +16.8 19
2017-03-31 @ Banants L 1-245.1 953 1034 28.55% 21.08% 50.37%-0.27 -16.8 6
2017-04-01 Pyunik L 0-238.0 1295 1322 35.49% 21.19% 43.31%-0.13 -40.0 37
2017-04-01 @ Shirak W 2-038.0 1322 1295 43.31% 21.19% 35.49%+0.13 +40.0 36
2017-04-07 Alashkert L 0-337.5 1362 1395 34.87% 21.19% 43.94%-0.15 -57.3 36
2017-04-07 @ Pyunik W 3-037.5 1395 1362 43.94% 21.19% 34.87%+0.15 +57.3 42
2017-04-07 Banants W 1-034.7 1255 1051 63.30% 20.42% 16.29%+0.72 +10.9 40
2017-04-07 @ Shirak L 0-134.7 1051 1255 16.29% 20.42% 63.30%-0.72 -10.9 19
2017-04-08 Ararat W 2-136.5 1442 937 79.59% 16.89% 3.52%+1.82 +2.3 42
2017-04-08 @ Gandzasar Kapan L 1-236.5 937 1442 3.52% 16.89% 79.59%-1.82 -2.2 6
2017-04-14 Banants W 2-027.5 1452 1040 76.10% 18.20% 5.70%+1.48 +7.4 45
2017-04-14 @ Alashkert L 0-227.5 1040 1452 5.70% 18.20% 76.10%-1.48 -7.4 19
2017-04-15 Ararat W 1-032.0 1266 934 72.20% 19.19% 8.61%+1.19 +6.0 43
2017-04-15 @ Shirak L 0-132.0 934 1266 8.61% 19.19% 72.20%-1.19 -6.0 6
2017-04-16 Gandzasar Kapan L 1-245.7 1305 1444 22.11% 20.84% 57.06%-0.54 -13.5 36
2017-04-16 @ Pyunik W 2-145.7 1444 1305 57.06% 20.84% 22.11%+0.54 +13.5 45
2017-04-21 Pyunik W 1-051.5 928 1292 7.31% 18.81% 73.87%-1.36 +41.1 9
2017-04-21 @ Ararat L 0-151.5 1292 928 73.87% 18.81% 7.31%+1.36 -41.1 36
2017-04-22 Gandzasar Kapan D 0-052.1 1033 1457 5.34% 18.03% 76.63%-1.58 +11.2 20
2017-04-22 @ Banants D 0-052.1 1457 1033 76.63% 18.03% 5.34%+1.58 -11.2 46
2017-04-23 Alashkert L 0-137.4 1272 1459 17.56% 20.53% 61.91%-0.72 -11.7 43
2017-04-23 @ Shirak W 1-037.4 1459 1272 61.91% 20.53% 17.56%+0.72 +11.7 48
2017-04-29 Ararat W 3-132.5 1471 969 79.48% 16.94% 3.58%+1.81 +4.0 51
2017-04-29 @ Alashkert L 1-332.5 969 1471 3.58% 16.94% 79.48%-1.81 -4.0 9
2017-04-29 Shirak W 3-248.4 1446 1260 61.77% 20.54% 17.69%+0.65 +10.5 49
2017-04-29 @ Gandzasar Kapan L 2-348.4 1260 1446 17.69% 20.54% 61.77%-0.65 -10.5 43
2017-04-30 Banants D 0-051.1 1250 1044 63.56% 20.39% 16.05%+0.73 -7.1 37
2017-04-30 @ Pyunik D 0-051.1 1044 1250 16.05% 20.39% 63.56%-0.73 +7.1 21
2017-05-06 Alashkert L 0-148.5 1457 1475 36.79% 21.20% 42.01%-0.10 -21.9 49
2017-05-06 @ Gandzasar Kapan W 1-048.5 1475 1457 42.01% 21.20% 36.79%+0.10 +21.9 54
2017-05-06 Shirak L 0-238.2 1243 1249 38.55% 21.21% 40.24%-0.05 -42.8 37
2017-05-06 @ Pyunik W 2-038.2 1249 1243 40.24% 21.21% 38.55%+0.05 +42.8 46
2017-05-06 Banants W 1-045.2 965 1051 27.99% 21.07% 50.94%-0.34 +28.6 12
2017-05-06 @ Ararat L 0-145.2 1051 965 50.94% 21.07% 27.99%+0.34 -28.6 21
2017-05-13 Gandzasar Kapan L 1-237.3 994 1435 4.91% 17.81% 77.28%-1.64 -3.2 12
2017-05-13 @ Ararat W 2-137.3 1435 994 77.28% 17.81% 4.91%+1.64 +3.2 52
2017-05-14 Pyunik D 3-368.1 1497 1201 70.14% 19.57% 10.28%+1.06 -5.1 55
2017-05-14 @ Alashkert D 3-368.1 1201 1497 10.28% 19.57% 70.14%-1.06 +5.1 38
2017-05-14 Banants W 1-033.2 1292 1022 68.40% 19.84% 11.76%+0.96 +8.1 49
2017-05-14 @ Shirak L 0-133.2 1022 1292 11.76% 19.84% 68.40%-0.96 -8.1 21
2017-05-19 Alashkert L 0-324.8 1014 1492 4.06% 17.29% 78.64%-1.78 -7.6 21
2017-05-19 @ Banants W 3-024.8 1492 1014 78.64% 17.29% 4.06%+1.78 +7.6 58
2017-05-20 Pyunik D 1-158.0 1438 1206 65.67% 20.18% 14.15%+0.82 -7.0 53
2017-05-20 @ Gandzasar Kapan D 1-158.0 1206 1438 14.15% 20.18% 65.67%-0.82 +7.0 39
2017-05-20 Shirak L 2-343.8 991 1300 9.63% 19.44% 70.94%-1.16 -6.0 12
2017-05-20 @ Ararat W 3-243.8 1300 991 70.94% 19.44% 9.63%+1.16 +5.9 52
2017-05-27 Ararat W 2-140.6 1213 985 65.32% 20.22% 14.46%+0.81 +9.2 42
2017-05-27 @ Pyunik L 1-240.6 985 1213 14.46% 20.22% 65.32%-0.81 -9.2 12
2017-05-27 Banants W 2-137.5 1431 1007 76.62% 18.03% 5.35%+1.53 +3.5 56
2017-05-27 @ Gandzasar Kapan L 1-237.5 1007 1431 5.35% 18.03% 76.62%-1.53 -3.5 21
2017-05-28 Shirak W 3-141.1 1499 1306 62.40% 20.49% 17.11%+0.68 +18.6 61
2017-05-28 @ Alashkert L 1-341.1 1306 1499 17.11% 20.49% 62.40%-0.68 -18.6 52
2017-05-31 Alashkert L 1-428.9 976 1518 2.90% 16.34% 80.76%-2.02 -4.5 12
2017-05-31 @ Ararat W 4-128.9 1518 976 80.76% 16.34% 2.90%+2.02 +4.5 64
2017-05-31 Gandzasar Kapan D 0-053.1 1287 1435 21.28% 20.79% 57.93%-0.57 +5.3 53
2017-05-31 @ Shirak D 0-053.1 1435 1287 57.93% 20.79% 21.28%+0.57 -5.3 57
2017-05-31 Pyunik L 0-230.6 1003 1222 15.13% 20.30% 64.58%-0.83 -19.2 21
2017-05-31 @ Banants W 2-030.6 1222 1003 64.58% 20.30% 15.13%+0.83 +19.2 45

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 2017-04-21 7.31% @ Ararat 928 1 Pyunik 1292 0
2 2016-09-10 12.95% Ararat 1105 3 @ Alashkert 1355 1
3 2016-10-01 19.96% @ Gandzasar Kapan 1146 1 Pyunik 1307 0
4 2016-10-27 23.58% Gandzasar Kapan 1251 4 @ Alashkert 1376 0
5 2016-09-27 25.41% Banants 1241 1 @ Shirak 1349 0
6 2017-05-06 27.99% @ Ararat 965 1 Banants 1051 0
7 2016-11-27 28.56% Alashkert 1301 2 @ Gandzasar Kapan 1382 1
8 2017-03-12 32.89% @ Alashkert 1335 3 Shirak 1382 0
9 2016-11-26 33.70% Shirak 1322 2 @ Pyunik 1363 0
10 2016-08-21 34.17% @ Pyunik 1224 3 Gandzasar Kapan 1262 0
11 2016-10-15 34.25% @ Gandzasar Kapan 1179 4 Banants 1216 0
12 2016-08-28 35.17% @ Banants 1162 4 Gandzasar Kapan 1192 1
13 2016-09-25 35.54% Gandzasar Kapan 1099 2 @ Ararat 1127 0
14 2016-10-26 35.99% Pyunik 1325 1 @ Shirak 1349 0
15 2016-08-06 38.25% @ Shirak 1274 3 Pyunik 1282 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 2016-10-27 110.93 Gandzasar Kapan 4 1251 23.58% @ Alashkert 0 1376 55.51% 20.91%
2 2016-10-15 91.24 @ Gandzasar Kapan 4 1179 34.25% Banants 0 1216 44.57% 21.18%
3 2017-03-12 71.67 @ Alashkert 3 1335 32.89% Shirak 0 1382 45.95% 21.17%
4 2016-08-21 69.95 @ Pyunik 3 1224 34.17% Gandzasar Kapan 0 1262 44.65% 21.18%
5 2016-09-10 60.91 Ararat 3 1105 12.95% @ Alashkert 1 1355 67.03% 20.03%
6 2016-08-28 57.88 @ Banants 4 1162 35.17% Gandzasar Kapan 1 1192 43.64% 21.19%
7 2017-04-07 57.33 Alashkert 3 1395 43.94% @ Pyunik 0 1362 34.87% 21.19%
8 2016-10-02 54.79 Alashkert 3 1317 45.87% @ Banants 0 1271 32.96% 21.17%
9 2016-11-26 48.60 Shirak 2 1322 33.70% @ Pyunik 0 1363 45.13% 21.18%
10 2016-09-25 46.92 Gandzasar Kapan 2 1099 35.54% @ Ararat 0 1127 43.27% 21.19%
11 2016-08-21 44.76 @ Alashkert 3 1311 53.18% Banants 0 1206 25.82% 21.00%
12 2017-05-06 42.76 Shirak 2 1249 40.24% @ Pyunik 0 1243 38.55% 21.21%
13 2017-04-21 41.07 @ Ararat 1 928 7.31% Pyunik 0 1292 73.87% 18.81%
14 2017-04-01 40.04 Pyunik 2 1322 43.31% @ Shirak 0 1295 35.49% 21.19%
15 2016-10-15 39.05 @ Pyunik 4 1274 63.30% Ararat 0 1071 16.28% 20.42%
16 2016-09-17 38.98 Banants 2 1202 44.49% @ Ararat 0 1166 34.33% 21.18%
17 2016-08-06 38.54 @ Shirak 3 1274 38.25% Pyunik 1 1282 40.55% 21.21%
18 2017-03-05 37.85 @ Gandzasar Kapan 2 1360 45.73% Pyunik 0 1315 33.10% 21.17%
19 2016-10-01 33.04 @ Gandzasar Kapan 1 1146 19.96% Pyunik 0 1307 59.33% 20.71%
20 2016-08-13 32.69 @ Gandzasar Kapan 2 1229 51.25% Ararat 0 1141 27.70% 21.06%
21 2016-11-05 31.81 @ Alashkert 4 1249 58.07% Banants 1 1100 21.15% 20.78%
22 2016-09-27 30.02 Banants 1 1241 25.41% @ Shirak 0 1349 53.61% 20.98%
23 2017-05-06 28.65 @ Ararat 1 965 27.99% Banants 0 1051 50.94% 21.07%
24 2016-11-27 26.73 Alashkert 2 1301 28.56% @ Gandzasar Kapan 1 1382 50.36% 21.08%
25 2017-03-19 25.80 Pyunik 3 1297 65.98% @ Banants 0 1060 13.87% 20.15%

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 2017-05-14 68.1 @ Alashkert 3 1497 70.14% Pyunik 3 1201 10.28% 19.57%
2 2016-08-27 64.5 @ Shirak 2 1340 37.12% Alashkert 2 1356 41.68% 21.20%
3 2016-10-16 58.4 @ Alashkert 1 1372 45.54% Shirak 1 1328 33.29% 21.17%
4 2017-05-20 58.0 @ Gandzasar Kapan 1 1438 65.67% Pyunik 1 1206 14.15% 20.18%
5 2016-11-19 57.2 @ Banants 1 1068 10.10% Gandzasar Kapan 1 1368 70.36% 19.54%
6 2016-11-22 57.2 @ Pyunik 1 1371 70.03% Banants 1 1077 10.38% 19.59%
7 2016-11-27 56.5 @ Ararat 1 988 26.67% Banants 1 1085 52.30% 21.03%
8 2016-11-27 53.3 Alashkert 2 1301 28.56% @ Gandzasar Kapan 1 1382 50.36% 21.08%
9 2016-11-05 53.1 @ Pyunik 0 1366 39.07% Gandzasar Kapan 0 1368 39.72% 21.21%
10 2017-05-31 53.1 @ Shirak 0 1287 21.28% Gandzasar Kapan 0 1435 57.93% 20.79%
11 2017-03-30 52.7 Gandzasar Kapan 2 1420 39.97% @ Alashkert 1 1416 38.82% 21.21%
12 2016-09-10 52.5 Ararat 3 1105 12.95% @ Alashkert 1 1355 67.03% 20.03%
13 2016-09-18 52.2 @ Pyunik 0 1305 33.06% Shirak 0 1351 45.77% 21.17%
14 2017-04-22 52.1 @ Banants 0 1033 5.34% Gandzasar Kapan 0 1457 76.63% 18.03%
15 2016-12-04 52.0 @ Alashkert 0 1328 41.30% Pyunik 0 1314 37.50% 21.21%
16 2016-09-27 51.9 @ Alashkert 0 1318 40.98% Pyunik 0 1307 37.81% 21.21%
17 2016-11-20 51.9 @ Shirak 0 1347 48.47% Alashkert 0 1280 30.41% 21.12%
18 2017-04-21 51.5 @ Ararat 1 928 7.31% Pyunik 0 1292 73.87% 18.81%
19 2016-08-07 51.3 @ Alashkert 0 1295 48.73% Gandzasar Kapan 0 1226 30.15% 21.12%
20 2016-08-27 51.2 @ Ararat 0 1098 16.87% Pyunik 0 1294 62.66% 20.47%
21 2017-04-30 51.1 @ Pyunik 0 1250 63.56% Banants 0 1044 16.05% 20.39%
22 2016-10-26 50.8 @ Banants 0 1113 51.12% Ararat 0 1026 27.82% 21.06%
23 2017-05-06 48.5 Alashkert 1 1475 42.01% @ Gandzasar Kapan 0 1457 36.79% 21.20%
24 2017-04-29 48.4 @ Gandzasar Kapan 3 1446 61.77% Shirak 2 1260 17.69% 20.54%
25 2016-10-01 47.9 @ Gandzasar Kapan 1 1146 19.96% Pyunik 0 1307 59.33% 20.71%
# Date Excitement Winning Team Losing Team Tie %
Team Score Elo Win % Team Score Elo Win %
1 2017-05-19 24.8 Alashkert 3 1492 78.64% @ Banants 0 1014 4.06% 17.29%
2 2017-03-17 24.9 Alashkert 3 1407 77.44% @ Ararat 0 962 4.81% 17.75%
3 2017-03-10 27.0 @ Pyunik 3 1277 70.07% Ararat 0 982 10.34% 19.59%
4 2017-04-14 27.5 @ Alashkert 2 1452 76.10% Banants 0 1040 5.70% 18.20%
5 2017-03-19 28.3 Pyunik 3 1297 65.98% @ Banants 0 1060 13.87% 20.15%
6 2016-11-04 28.7 @ Shirak 2 1334 71.01% Ararat 0 1024 9.56% 19.42%
7 2016-10-15 28.9 @ Pyunik 4 1274 63.30% Ararat 0 1071 16.28% 20.42%
8 2017-05-31 28.9 Alashkert 4 1518 80.76% @ Ararat 1 976 2.90% 16.34%
9 2017-05-31 30.6 Pyunik 2 1222 64.58% @ Banants 0 1003 15.13% 20.30%
10 2017-03-05 31.2 Shirak 1 1378 75.22% @ Ararat 0 986 6.32% 18.46%
11 2016-12-03 31.6 Gandzasar Kapan 1 1355 73.90% @ Ararat 0 991 7.29% 18.81%
12 2016-09-18 32.0 Alashkert 2 1294 60.34% @ Gandzasar Kapan 0 1123 19.02% 20.64%
13 2017-04-15 32.0 @ Shirak 1 1266 72.20% Ararat 0 934 8.61% 19.19%
14 2016-10-30 32.1 @ Gandzasar Kapan 1 1362 72.29% Ararat 0 1029 8.54% 19.17%
15 2016-11-23 32.1 @ Alashkert 4 1283 68.89% Ararat 1 1006 11.33% 19.77%
16 2017-03-11 32.3 @ Gandzasar Kapan 1 1398 72.24% Banants 0 1066 8.58% 19.18%
17 2016-08-21 32.5 @ Alashkert 3 1311 53.18% Banants 0 1206 25.82% 21.00%
18 2017-04-29 32.5 @ Alashkert 3 1471 79.48% Ararat 1 969 3.58% 16.94%
19 2016-12-03 33.0 Shirak 1 1371 69.68% @ Banants 0 1082 10.67% 19.65%
20 2017-05-14 33.2 @ Shirak 1 1292 68.40% Banants 0 1022 11.76% 19.84%
21 2016-10-01 34.0 Shirak 1 1319 66.19% @ Ararat 0 1080 13.69% 20.12%
22 2016-08-20 34.4 @ Shirak 1 1329 64.79% Ararat 0 1108 14.94% 20.28%
23 2016-08-13 34.7 @ Gandzasar Kapan 2 1229 51.25% Ararat 0 1141 27.70% 21.06%
24 2017-04-07 34.7 @ Shirak 1 1255 63.30% Banants 0 1051 16.29% 20.42%
25 2016-09-11 34.9 Shirak 1 1340 63.52% @ Gandzasar Kapan 0 1134 16.09% 20.40%