Lyath Goldmane

Vile Savant

Lyath Goldmane has a 42.4% win rate across 385 tracked Classic Constructed matches (data through August 2026).

ComboMidrange

Difficulty:

4.0

Classic Constructed

Classic Constructed Performance Summary

Data through August 2026

Overall Win Rate

42.4%

Total Matches

385

Record

156

212

Tournaments

Players ranked by Bayesian smoothed win rate with Lyath Goldmane in All Time

Time Period: Last 30 Days Last 3 Months Last 6 Months Last Year

Total Pilots

Time Period

All Time

Data Through

August 2026

#1 Ji Timm Lee

Malaysia

Smoothed Win Rate

48.7%

Raw Win Rate

76.9%

Record

10-3-0

Events / Games

1 / 13

#2 Chanon Puttaree

Thailand

Smoothed Win Rate

47.3%

Raw Win Rate

72.7%

Record

8-3-0

Events / Games

1 / 11

#3 Joshua Neitzel

United States

Smoothed Win Rate

47.2%

Raw Win Rate

77.8%

Record

7-2-0

Events / Games

1 / 9

#4 Liam Holden

United Kingdom

Smoothed Win Rate

46.6%

Raw Win Rate

66.7%

Record

8-4-0

Events / Games

1 / 12

#5 Jason Rolfe

United Kingdom

Smoothed Win Rate

46.6%

Raw Win Rate

66.7%

Record

8-4-0

Events / Games

1 / 12

#6 Franche Tan

United States

Smoothed Win Rate

45.6%

Raw Win Rate

71.4%

Record

5-2-0

Events / Games

1 / 7

#7 Jaap IJlst

Netherlands

Smoothed Win Rate

45.5%

Raw Win Rate

56.2%

Record

9-6-1

Events / Games

2 / 16

#8 Louis Glenn

Thailand

Smoothed Win Rate

45.3%

Raw Win Rate

57.1%

Record

8-6-0

Events / Games

2 / 14

#9 Cosmo Hahn

Germany

Smoothed Win Rate

44.9%

Raw Win Rate

62.5%

Record

5-2-1

Events / Games

1 / 8

#10 Oliver Berry

New Zealand

Smoothed Win Rate

44.3%

Raw Win Rate

55.6%

Record

5-2-2

Events / Games

1 / 9

#11 Alexandre Lebec

France

Smoothed Win Rate

44.1%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#12 Evan Brook

United States

Smoothed Win Rate

44.1%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#13 George Douglas

United Kingdom

Smoothed Win Rate

43.2%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#14 Hugh Wang

United States

Smoothed Win Rate

43.2%

Raw Win Rate

50.0%

Record

3-2-1

Events / Games

1 / 6

#15 廖皓然

Hong Kong

Smoothed Win Rate

43.0%

Raw Win Rate

45.5%

Record

5-6-0

Events / Games

1 / 11

#16 Warre Sevens

Belgium

Smoothed Win Rate

42.6%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#17 Nathaniel Brower

United States

Smoothed Win Rate

42.6%

Raw Win Rate

42.9%

Record

3-1-3

Events / Games

1 / 7

#18 Jun Sato

Japan

Smoothed Win Rate

42.6%

Raw Win Rate

42.9%

Record

3-3-1

Events / Games

1 / 7

#19 Jacob Smith

United States

Smoothed Win Rate

42.6%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#20 David Pantoja Sánchez

Spain

Smoothed Win Rate

42.6%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#21 Arthur Brunoni

France

Smoothed Win Rate

42.3%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#22 Noah Beygelman

United States

Smoothed Win Rate

42.3%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#23 Albert Purvis

United States

Smoothed Win Rate

42.1%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#24 Alexander Dobler

Australia

Smoothed Win Rate

41.7%

Raw Win Rate

33.3%

Record

2-4-0

Events / Games

1 / 6

#25 Paul Johnson

New Zealand

Smoothed Win Rate

41.4%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#26 Jordyn Denver

United States

Smoothed Win Rate

41.4%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#27 HAN LONG LIU

Taiwan

Smoothed Win Rate

41.4%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#28 Tomoyuki Yagura

Japan

Smoothed Win Rate

41.4%

Raw Win Rate

25.0%

Record

1-2-1

Events / Games

1 / 4

#29 Kidd Bliss

United States

Smoothed Win Rate

41.4%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#30 Aaron Franklin

United States

Smoothed Win Rate

41.2%

Raw Win Rate

35.7%

Record

5-9-0

Events / Games

2 / 14

#31 SATOSHI NAKATA

Japan

Smoothed Win Rate

41.1%

Raw Win Rate

0.0%

Record

0-2-0

Events / Games

1 / 2

#32 yanao kento

Japan

Smoothed Win Rate

41.1%

Raw Win Rate

0.0%

Record

0-2-0

Events / Games

1 / 2

#33 Ricardo de Campos Dorini

Brazil

Smoothed Win Rate

41.1%

Raw Win Rate

28.6%

Record

2-5-0

Events / Games

1 / 7

#34 Larry Durham

United States

Smoothed Win Rate

40.5%

Raw Win Rate

0.0%

Record

0-3-0

Events / Games

1 / 3

#35 Hidenori Yano

Japan

Smoothed Win Rate

40.5%

Raw Win Rate

0.0%

Record

0-3-0

Events / Games

1 / 3

#36 Adam Lucka

United States

Smoothed Win Rate

40.4%

Raw Win Rate

25.0%

Record

2-6-0

Events / Games

1 / 8

#37 Daniel Johnson : )

Australia

Smoothed Win Rate

40.1%

Raw Win Rate

16.7%

Record

1-5-0

Events / Games

2 / 6

#38 Trevor Valentine

United States

Smoothed Win Rate

39.8%

Raw Win Rate

0.0%

Record

0-3-1

Events / Games

1 / 4

#39 narihiko serikyaku

Japan

Smoothed Win Rate

39.8%

Raw Win Rate

0.0%

Record

0-4-0

Events / Games

1 / 4

#40 Nicolas Millaire

Canada

Smoothed Win Rate

39.5%

Raw Win Rate

14.3%

Record

1-6-0

Events / Games

1 / 7

#41 Luca Scherner

Germany

Smoothed Win Rate

39.2%

Raw Win Rate

0.0%

Record

0-5-0

Events / Games

1 / 5

#42 Dennis Hahn

Germany

Smoothed Win Rate

39.2%

Raw Win Rate

0.0%

Record

0-5-0

Events / Games

1 / 5

#43 Mikey Kell

United States

Smoothed Win Rate

38.6%

Raw Win Rate

0.0%

Record

0-6-0

Events / Games

1 / 6

#44 Shine Wong cm

Hong Kong

Smoothed Win Rate

37.8%

Raw Win Rate

10.0%

Record

1-7-2

Events / Games

2 / 10

Rank	Player	Win Rate	Raw %	Record	Events	Games
#1	Ji Timm Lee Malaysia	48.7%	76.9%	10-3-0	1	13
#2	Chanon Puttaree Thailand	47.3%	72.7%	8-3-0	1	11
#3	Joshua Neitzel United States	47.2%	77.8%	7-2-0	1	9
#4	Liam Holden United Kingdom	46.6%	66.7%	8-4-0	1	12
#5	Jason Rolfe United Kingdom	46.6%	66.7%	8-4-0	1	12
#6	Franche Tan United States	45.6%	71.4%	5-2-0	1	7
#7	Jaap IJlst Netherlands	45.5%	56.2%	9-6-1	2	16
#8	Louis Glenn Thailand	45.3%	57.1%	8-6-0	2	14
#9	Cosmo Hahn Germany	44.9%	62.5%	5-2-1	1	8
#10	Oliver Berry New Zealand	44.3%	55.6%	5-2-2	1	9
#11	Alexandre Lebec France	44.1%	57.1%	4-3-0	1	7
#12	Evan Brook United States	44.1%	57.1%	4-3-0	1	7
#13	George Douglas United Kingdom	43.2%	50.0%	3-3-0	1	6
#14	Hugh Wang United States	43.2%	50.0%	3-2-1	1	6
#15	廖皓然 Hong Kong	43.0%	45.5%	5-6-0	1	11
#16	Warre Sevens Belgium	42.6%	42.9%	3-4-0	1	7
#17	Nathaniel Brower United States	42.6%	42.9%	3-1-3	1	7
#18	Jun Sato Japan	42.6%	42.9%	3-3-1	1	7
#19	Jacob Smith United States	42.6%	42.9%	3-4-0	1	7
#20	David Pantoja Sánchez Spain	42.6%	42.9%	3-4-0	1	7
#21	Arthur Brunoni France	42.3%	40.0%	2-3-0	1	5
#22	Noah Beygelman United States	42.3%	40.0%	2-3-0	1	5
#23	Albert Purvis United States	42.1%	33.3%	1-2-0	1	3
#24	Alexander Dobler Australia	41.7%	33.3%	2-4-0	1	6
#25	Paul Johnson New Zealand	41.4%	25.0%	1-3-0	1	4
#26	Jordyn Denver United States	41.4%	25.0%	1-3-0	1	4
#27	HAN LONG LIU Taiwan	41.4%	25.0%	1-3-0	1	4
#28	Tomoyuki Yagura Japan	41.4%	25.0%	1-2-1	1	4
#29	Kidd Bliss United States	41.4%	25.0%	1-3-0	1	4
#30	Aaron Franklin United States	41.2%	35.7%	5-9-0	2	14
#31	SATOSHI NAKATA Japan	41.1%	0.0%	0-2-0	1	2
#32	yanao kento Japan	41.1%	0.0%	0-2-0	1	2
#33	Ricardo de Campos Dorini Brazil	41.1%	28.6%	2-5-0	1	7
#34	Larry Durham United States	40.5%	0.0%	0-3-0	1	3
#35	Hidenori Yano Japan	40.5%	0.0%	0-3-0	1	3
#36	Adam Lucka United States	40.4%	25.0%	2-6-0	1	8
#37	Daniel Johnson : ) Australia	40.1%	16.7%	1-5-0	2	6
#38	Trevor Valentine United States	39.8%	0.0%	0-3-1	1	4
#39	narihiko serikyaku Japan	39.8%	0.0%	0-4-0	1	4
#40	Nicolas Millaire Canada	39.5%	14.3%	1-6-0	1	7
#41	Luca Scherner Germany	39.2%	0.0%	0-5-0	1	5
#42	Dennis Hahn Germany	39.2%	0.0%	0-5-0	1	5
#43	Mikey Kell United States	38.6%	0.0%	0-6-0	1	6
#44	Shine Wong cm Hong Kong	37.8%	10.0%	1-7-2	2	10

How Performance is Calculated

This leaderboard uses Bayesian smoothing to provide more reliable win rate estimates. The smoothed win rate balances actual performance with the hero's average win rate (42.5%), giving more weight to actual results as sample size increases.

Formula: Smoothed Win Rate = (Wins + 59 × Hero Average) ÷ (Games + 59)
W = 59 (median games played in this period — self-calibrates with the dataset)