Dash

Dash has a 41.7% win rate across 559 tracked Silver Age matches (data through August 2026).

Board PresenceMidrange

Difficulty:

1.5

Silver Age

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

Silver Age Performance Summary

Data through August 2026

Overall Win Rate

41.7%

Total Matches

559

Record

233

326

Tournaments

Players ranked by Bayesian smoothed win rate with Dash 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 Emma Hollingsworth

Australia

Smoothed Win Rate

46.6%

Raw Win Rate

72.7%

Record

8-3-0

Events / Games

2 / 11

#2 Connor Bryant

United States

Smoothed Win Rate

45.4%

Raw Win Rate

60.0%

Record

9-6-0

Events / Games

3 / 15

#3 Joshua Lau

United States

Smoothed Win Rate

45.1%

Raw Win Rate

51.6%

Record

16-15-0

Events / Games

4 / 31

#4 Grant Kern

United States

Smoothed Win Rate

45.0%

Raw Win Rate

66.7%

Record

6-3-0

Events / Games

1 / 9

#5 Randy Stephen

Indonesia

Smoothed Win Rate

44.8%

Raw Win Rate

71.4%

Record

5-2-0

Events / Games

1 / 7

#6 Alfian Poon

Singapore

Smoothed Win Rate

44.5%

Raw Win Rate

58.3%

Record

7-5-0

Events / Games

1 / 12

#7 yaqiong Ju

Singapore

Smoothed Win Rate

44.5%

Raw Win Rate

58.3%

Record

7-5-0

Events / Games

1 / 12

#8 Eugene C

Hong Kong

Smoothed Win Rate

44.5%

Raw Win Rate

52.4%

Record

11-10-0

Events / Games

3 / 21

#9 Benjamin Cumming

United States

Smoothed Win Rate

43.7%

Raw Win Rate

54.5%

Record

6-5-0

Events / Games

2 / 11

#10 Nathan Crawford

United States

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#11 Cody Gebert

Australia

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#12 Isaac Katsakis

Australia

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#13 Nugroho Haryoputro

Indonesia

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#14 Hongbo Zhao

China

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#15 大和宮脇

Japan

Smoothed Win Rate

43.3%

Raw Win Rate

57.1%

Record

4-3-0

Events / Games

1 / 7

#16 Jason Brannick

United States

Smoothed Win Rate

43.1%

Raw Win Rate

60.0%

Record

3-2-0

Events / Games

1 / 5

#17 Danton Lima

Brazil

Smoothed Win Rate

42.9%

Raw Win Rate

50.0%

Record

5-5-0

Events / Games

2 / 10

#18 Andy Pham

Australia

Smoothed Win Rate

42.9%

Raw Win Rate

47.1%

Record

8-9-0

Events / Games

3 / 17

#19 Taufik Indrakesuma

Australia

Smoothed Win Rate

42.7%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

2 / 8

#20 Kevin Fontan

United States

Smoothed Win Rate

42.7%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#21 Borja Apellaniz Aparicio

Spain

Smoothed Win Rate

42.7%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#22 Mel Falcon

United States

Smoothed Win Rate

42.7%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#23 Franz Sawertal

Germany

Smoothed Win Rate

42.7%

Raw Win Rate

50.0%

Record

4-4-0

Events / Games

1 / 8

#24 Zoe Daniels

United States

Smoothed Win Rate

42.7%

Raw Win Rate

100.0%

Record

1-0-0

Events / Games

1 / 1

#25 Sander Deceuninck

Belgium

Smoothed Win Rate

42.4%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#26 William Bucknall

Australia

Smoothed Win Rate

42.4%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#27 Gennaro Ciampa Mango

Italy

Smoothed Win Rate

42.4%

Raw Win Rate

50.0%

Record

3-3-0

Events / Games

1 / 6

#28 Colin Marshall

United States

Smoothed Win Rate

42.3%

Raw Win Rate

45.5%

Record

5-6-0

Events / Games

2 / 11

#29 Sigurður Þormóðsson

Iceland

Smoothed Win Rate

42.3%

Raw Win Rate

45.5%

Record

5-6-0

Events / Games

1 / 11

#30 Olli Saarinen

Finland

Smoothed Win Rate

42.2%

Raw Win Rate

50.0%

Record

2-2-0

Events / Games

1 / 4

#31 Luca Scherner

Germany

Smoothed Win Rate

42.2%

Raw Win Rate

50.0%

Record

2-2-0

Events / Games

1 / 4

#32 Kyle McKeough

United States

Smoothed Win Rate

42.0%

Raw Win Rate

44.4%

Record

4-5-0

Events / Games

1 / 9

#33 Philippe Thai

Canada

Smoothed Win Rate

42.0%

Raw Win Rate

50.0%

Record

1-1-0

Events / Games

1 / 2

#34 David Gubau Jové

Spain

Smoothed Win Rate

41.8%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#35 Zackary Young

United States

Smoothed Win Rate

41.8%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#36 Kenneth Nathan Wijaya

Indonesia

Smoothed Win Rate

41.8%

Raw Win Rate

42.9%

Record

3-4-0

Events / Games

1 / 7

#37 Tino Mille

Germany

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#38 Kevin Lindenmayer

United States

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#39 Daniel Baxendale

United Kingdom

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#40 Zach Benton

United States

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#41 Ethan Gill

United States

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#42 Isuardi Therianto

Indonesia

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#43 jiayang you

China

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#44 Kairi Thompson

Australia

Smoothed Win Rate

41.6%

Raw Win Rate

40.0%

Record

2-3-0

Events / Games

1 / 5

#45 Robert Szura

Poland

Smoothed Win Rate

41.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#46 Remi Grasset

Australia

Smoothed Win Rate

41.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#47 James Trayler

United Kingdom

Smoothed Win Rate

41.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#48 Christopher Uramoto

United States

Smoothed Win Rate

41.3%

Raw Win Rate

33.3%

Record

1-2-0

Events / Games

1 / 3

#49 Tanner Lee

United States

Smoothed Win Rate

41.0%

Raw Win Rate

0.0%

Record

0-1-0

Events / Games

1 / 1

#50 Bryan Kong

Singapore

Smoothed Win Rate

41.0%

Raw Win Rate

0.0%

Record

0-1-0

Events / Games

1 / 1

Rank	Player	Win Rate	Raw %	Record	Events	Games
#1	Emma Hollingsworth Australia	46.6%	72.7%	8-3-0	2	11
#2	Connor Bryant United States	45.4%	60.0%	9-6-0	3	15
#3	Joshua Lau United States	45.1%	51.6%	16-15-0	4	31
#4	Grant Kern United States	45.0%	66.7%	6-3-0	1	9
#5	Randy Stephen Indonesia	44.8%	71.4%	5-2-0	1	7
#6	Alfian Poon Singapore	44.5%	58.3%	7-5-0	1	12
#7	yaqiong Ju Singapore	44.5%	58.3%	7-5-0	1	12
#8	Eugene C Hong Kong	44.5%	52.4%	11-10-0	3	21
#9	Benjamin Cumming United States	43.7%	54.5%	6-5-0	2	11
#10	Nathan Crawford United States	43.3%	57.1%	4-3-0	1	7
#11	Cody Gebert Australia	43.3%	57.1%	4-3-0	1	7
#12	Isaac Katsakis Australia	43.3%	57.1%	4-3-0	1	7
#13	Nugroho Haryoputro Indonesia	43.3%	57.1%	4-3-0	1	7
#14	Hongbo Zhao China	43.3%	57.1%	4-3-0	1	7
#15	大和宮脇 Japan	43.3%	57.1%	4-3-0	1	7
#16	Jason Brannick United States	43.1%	60.0%	3-2-0	1	5
#17	Danton Lima Brazil	42.9%	50.0%	5-5-0	2	10
#18	Andy Pham Australia	42.9%	47.1%	8-9-0	3	17
#19	Taufik Indrakesuma Australia	42.7%	50.0%	4-4-0	2	8
#20	Kevin Fontan United States	42.7%	50.0%	4-4-0	1	8
#21	Borja Apellaniz Aparicio Spain	42.7%	50.0%	4-4-0	1	8
#22	Mel Falcon United States	42.7%	50.0%	4-4-0	1	8
#23	Franz Sawertal Germany	42.7%	50.0%	4-4-0	1	8
#24	Zoe Daniels United States	42.7%	100.0%	1-0-0	1	1
#25	Sander Deceuninck Belgium	42.4%	50.0%	3-3-0	1	6
#26	William Bucknall Australia	42.4%	50.0%	3-3-0	1	6
#27	Gennaro Ciampa Mango Italy	42.4%	50.0%	3-3-0	1	6
#28	Colin Marshall United States	42.3%	45.5%	5-6-0	2	11
#29	Sigurður Þormóðsson Iceland	42.3%	45.5%	5-6-0	1	11
#30	Olli Saarinen Finland	42.2%	50.0%	2-2-0	1	4
#31	Luca Scherner Germany	42.2%	50.0%	2-2-0	1	4
#32	Kyle McKeough United States	42.0%	44.4%	4-5-0	1	9
#33	Philippe Thai Canada	42.0%	50.0%	1-1-0	1	2
#34	David Gubau Jové Spain	41.8%	42.9%	3-4-0	1	7
#35	Zackary Young United States	41.8%	42.9%	3-4-0	1	7
#36	Kenneth Nathan Wijaya Indonesia	41.8%	42.9%	3-4-0	1	7
#37	Tino Mille Germany	41.6%	40.0%	2-3-0	1	5
#38	Kevin Lindenmayer United States	41.6%	40.0%	2-3-0	1	5
#39	Daniel Baxendale United Kingdom	41.6%	40.0%	2-3-0	1	5
#40	Zach Benton United States	41.6%	40.0%	2-3-0	1	5
#41	Ethan Gill United States	41.6%	40.0%	2-3-0	1	5
#42	Isuardi Therianto Indonesia	41.6%	40.0%	2-3-0	1	5
#43	jiayang you China	41.6%	40.0%	2-3-0	1	5
#44	Kairi Thompson Australia	41.6%	40.0%	2-3-0	1	5
#45	Robert Szura Poland	41.3%	33.3%	1-2-0	1	3
#46	Remi Grasset Australia	41.3%	33.3%	1-2-0	1	3
#47	James Trayler United Kingdom	41.3%	33.3%	1-2-0	1	3
#48	Christopher Uramoto United States	41.3%	33.3%	1-2-0	1	3
#49	Tanner Lee United States	41.0%	0.0%	0-1-0	1	1
#50	Bryan Kong Singapore	41.0%	0.0%	0-1-0	1	1

Showing page 1 of 2

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 (41.7%), 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)