Kayo

Strong-arm

DefensiveMidrange

Difficulty:

2.5

Silver Age

All statistics and data on this page are for Silver Age format

Silver Age Performance Summary

Overall Win Rate

39.6%

Total Matches

111

Record

Tournaments

Players ranked by Bayesian smoothed win rate with Kayo 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 23, 2026 at 6:10 AM

#1 Bartłomiej Kubas

Poland

Smoothed Win Rate

43.9%

Raw Win Rate

75.0%

Record

6-2-0

Events / Games

1 / 8

#2 Alexander Heger

United States

Smoothed Win Rate

40.9%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#3 Gary White

Netherlands

Smoothed Win Rate

40.8%

Raw Win Rate

46.2%

Record

6-7-0

Events / Games

2 / 13

#4 Thomas Battaglia

United States

Smoothed Win Rate

40.6%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#5 Gaál Benjamin

Netherlands

Smoothed Win Rate

40.6%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#6 Tomoyuki Yagura

Japan

Smoothed Win Rate

40.6%

Raw Win Rate

45.5%

Record

5-6-0

Events / Games

2 / 11

#7 Dave Margetson

United Kingdom

Smoothed Win Rate

39.7%

Raw Win Rate

40.0%

Record

4-6-0

Events / Games

2 / 10

#8 Thore Ladicke

Germany

Smoothed Win Rate

39.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#9 Nico Stangel

Germany

Smoothed Win Rate

39.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#10 Chris Sov

United States

Smoothed Win Rate

39.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#11 Laurens Overgaauw

Netherlands

Smoothed Win Rate

39.1%

Raw Win Rate

36.4%

Record

4-7-0

Events / Games

2 / 11

#12 Edward Bayford

United Kingdom

Smoothed Win Rate

39.0%

Raw Win Rate

33.3%

Record

2-4-0

Events / Games

1 / 6

#13 Marnie Lamb

United Kingdom

Smoothed Win Rate

39.0%

Raw Win Rate

33.3%

Record

2-4-0

Events / Games

1 / 6

#14 James Micklewright

United Kingdom

Smoothed Win Rate

38.7%

Raw Win Rate

25.0%

Record

1-3-0

Events / Games

1 / 4

#15 Stuart Reeve

United Kingdom

Smoothed Win Rate

38.1%

Raw Win Rate

20.0%

Record

1-4-0

Events / Games

1 / 5

#16 Joseph Larkin

United Kingdom

Smoothed Win Rate

37.7%

Raw Win Rate

0.0%

Record

0-3-0

Events / Games

1 / 3

#17 Jacob Brady

United States

Smoothed Win Rate

36.5%

Raw Win Rate

0.0%

Record

0-5-0

Events / Games

1 / 5

Rank	Player	Win Rate	Raw %	Record	Events	Games
#1	Bartłomiej Kubas Poland	43.9%	75.0%	6-2-0	1	8
#2	Alexander Heger United States	40.9%	50.0%	4-4-0	1	8
#3	Gary White Netherlands	40.8%	46.2%	6-7-0	2	13
#4	Thomas Battaglia United States	40.6%	50.0%	3-3-0	1	6
#5	Gaál Benjamin Netherlands	40.6%	50.0%	3-3-0	1	6
#6	Tomoyuki Yagura Japan	40.6%	45.5%	5-6-0	2	11
#7	Dave Margetson United Kingdom	39.7%	40.0%	4-6-0	2	10
#8	Thore Ladicke Germany	39.3%	33.3%	1-2-0	1	3
#9	Nico Stangel Germany	39.3%	33.3%	1-2-0	1	3
#10	Chris Sov United States	39.3%	33.3%	1-2-0	1	3
#11	Laurens Overgaauw Netherlands	39.1%	36.4%	4-7-0	2	11
#12	Edward Bayford United Kingdom	39.0%	33.3%	2-4-0	1	6
#13	Marnie Lamb United Kingdom	39.0%	33.3%	2-4-0	1	6
#14	James Micklewright United Kingdom	38.7%	25.0%	1-3-0	1	4
#15	Stuart Reeve United Kingdom	38.1%	20.0%	1-4-0	1	5
#16	Joseph Larkin United Kingdom	37.7%	0.0%	0-3-0	1	3
#17	Jacob Brady United States	36.5%	0.0%	0-5-0	1	5

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 (39.6%), 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)