Betsy

Skin in the Game

Defensive

Difficulty:

2.0

Classic Constructed

Classic Constructed Performance Summary

Overall Win Rate

50.1%

Total Matches

346

Record

172

171

Tournaments

Players ranked by Bayesian smoothed win rate with Betsy in All Time

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

Total Pilots

Time Period

All Time

Last Updated

Jul 22, 2026 at 10:08 AM

#1 Dagan White

United States

Smoothed Win Rate

56.7%

Raw Win Rate

66.7%

Record

12-6-0

Events / Games

2 / 18

#2 Jonathan Magnuson

United States

Smoothed Win Rate

56.7%

Raw Win Rate

72.7%

Record

8-3-0

Events / Games

1 / 11

#3 David Lee

United States

Smoothed Win Rate

56.5%

Raw Win Rate

69.2%

Record

9-4-0

Events / Games

1 / 13

#4 Bryce Stroyek

United States

Smoothed Win Rate

56.0%

Raw Win Rate

70.0%

Record

7-3-0

Events / Games

1 / 10

#5 Masay Toda

Japan

Smoothed Win Rate

55.7%

Raw Win Rate

59.4%

Record

19-13-0

Events / Games

4 / 32

#6 KOHEI TAKANO

Japan

Smoothed Win Rate

55.5%

Raw Win Rate

60.0%

Record

15-10-0

Events / Games

2 / 25

#7 Florin-Cristian Loghin

Austria

Smoothed Win Rate

55.1%

Raw Win Rate

61.5%

Record

8-5-0

Events / Games

2 / 13

#8 Luke Shinn

United States

Smoothed Win Rate

55.1%

Raw Win Rate

61.5%

Record

8-5-0

Events / Games

2 / 13

#9 Zachary Wallach

United States

Smoothed Win Rate

55.1%

Raw Win Rate

61.5%

Record

8-4-1

Events / Games

1 / 13

#10 Garrett Johnson

United States

Smoothed Win Rate

54.6%

Raw Win Rate

60.0%

Record

6-4-0

Events / Games

1 / 10

#11 Bryan Knecht

United States

Smoothed Win Rate

54.1%

Raw Win Rate

60.0%

Record

3-2-0

Events / Games

1 / 5

#12 Romar Richardson

United States

Smoothed Win Rate

54.1%

Raw Win Rate

60.0%

Record

3-2-0

Events / Games

1 / 5

#13 Daniel Mckinlay

United Kingdom

Smoothed Win Rate

54.0%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#14 Andrew Rothermel

United States

Smoothed Win Rate

53.9%

Raw Win Rate

55.6%

Record

5-3-1

Events / Games

1 / 9

#15 nathan lapham

United States

Smoothed Win Rate

53.2%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#16 Joe Ellis

United States

Smoothed Win Rate

52.7%

Raw Win Rate

0.0%

Record

0-1-0

Events / Games

1 / 1

#17 Tony Nguyen

United States

Smoothed Win Rate

52.7%

Raw Win Rate

0.0%

Record

0-1-0

Events / Games

1 / 1

#18 Nick Soini

United States

Smoothed Win Rate

52.6%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#19 Ashley Southwood

United Kingdom

Smoothed Win Rate

52.5%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#20 Rowan Duffield

Australia

Smoothed Win Rate

51.8%

Raw Win Rate

0.0%

Record

0-2-0

Events / Games

1 / 2

#21 Luke Snyder

United States

Smoothed Win Rate

51.8%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#22 Kevin Brayer

United States

Smoothed Win Rate

50.9%

Raw Win Rate

20.0%

Record

1-4-0

Events / Games

1 / 5

#23 Markus Withakay

United States

Smoothed Win Rate

50.9%

Raw Win Rate

28.6%

Record

2-5-0

Events / Games

1 / 7

#24 Jian Hung Cheong

Singapore

Smoothed Win Rate

50.9%

Raw Win Rate

28.6%

Record

2-5-0

Events / Games

1 / 7

#25 Brandon Hartman

United States

Smoothed Win Rate

50.9%

Raw Win Rate

36.4%

Record

4-7-0

Events / Games

2 / 11

#26 Nando Nando

Australia

Smoothed Win Rate

50.8%

Raw Win Rate

38.5%

Record

5-8-0

Events / Games

2 / 13

#27 Kyujung Lee

South Korea

Smoothed Win Rate

50.1%

Raw Win Rate

30.0%

Record

3-7-0

Events / Games

2 / 10

Rank	Player	Win Rate	Raw %	Record	Events	Games
#1	Dagan White United States	56.7%	66.7%	12-6-0	2	18
#2	Jonathan Magnuson United States	56.7%	72.7%	8-3-0	1	11
#3	David Lee United States	56.5%	69.2%	9-4-0	1	13
#4	Bryce Stroyek United States	56.0%	70.0%	7-3-0	1	10
#5	Masay Toda Japan	55.7%	59.4%	19-13-0	4	32
#6	KOHEI TAKANO Japan	55.5%	60.0%	15-10-0	2	25
#7	Florin-Cristian Loghin Austria	55.1%	61.5%	8-5-0	2	13
#8	Luke Shinn United States	55.1%	61.5%	8-5-0	2	13
#9	Zachary Wallach United States	55.1%	61.5%	8-4-1	1	13
#10	Garrett Johnson United States	54.6%	60.0%	6-4-0	1	10
#11	Bryan Knecht United States	54.1%	60.0%	3-2-0	1	5
#12	Romar Richardson United States	54.1%	60.0%	3-2-0	1	5
#13	Daniel Mckinlay United Kingdom	54.0%	57.1%	4-3-0	1	7
#14	Andrew Rothermel United States	53.9%	55.6%	5-3-1	1	9
#15	nathan lapham United States	53.2%	50.0%	4-4-0	1	8
#16	Joe Ellis United States	52.7%	0.0%	0-1-0	1	1
#17	Tony Nguyen United States	52.7%	0.0%	0-1-0	1	1
#18	Nick Soini United States	52.6%	33.3%	1-2-0	1	3
#19	Ashley Southwood United Kingdom	52.5%	42.9%	3-4-0	1	7
#20	Rowan Duffield Australia	51.8%	0.0%	0-2-0	1	2
#21	Luke Snyder United States	51.8%	25.0%	1-3-0	1	4
#22	Kevin Brayer United States	50.9%	20.0%	1-4-0	1	5
#23	Markus Withakay United States	50.9%	28.6%	2-5-0	1	7
#24	Jian Hung Cheong Singapore	50.9%	28.6%	2-5-0	1	7
#25	Brandon Hartman United States	50.9%	36.4%	4-7-0	2	11
#26	Nando Nando Australia	50.8%	38.5%	5-8-0	2	13
#27	Kyujung Lee South Korea	50.1%	30.0%	3-7-0	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 (53.6%), giving more weight to actual results as sample size increases.

Formula: Smoothed Win Rate = (Wins + 58 × Hero Average) ÷ (Games + 58)
W = 58 (median games played in this period — self-calibrates with the dataset)