BladeRunner ROC/RJC

Div I-A Men's Épée

Saturday, October 29, 2022 at 1:30 PM

Liontree Arena (RIMAC) @ UC San Diego - La Jolla, CA, USA

Probability density of pool victories

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Explore the pool victory probability density for each fencer, with their actual victories highlighted in a box. Learn more.

# Name Number of victories
0 1 2 3 4 5 6
1 IVE Isaac L. - - - 3% 18% 45% 34%
2 RONG Yao (Derek) - - - 1% 11% 42% 45%
3 BOYCE Samuel H. - - 2% 11% 30% 38% 18%
3 RONA Milan - - - 1% 11% 43% 45%
5 BRISLAWN Reilly R. - - - 4% 20% 42% 34%
6 MARKOTA Vedran - - 1% 9% 28% 41% 21%
7 KANG Philip F. - 1% 7% 24% 38% 25% 6%
8 HESSLEGRAVE Porter B. - - - 5% 27% 48% 19%
9 ZHANG Alec 1% 8% 27% 37% 22% 5% -
10 LO Jake 5% 24% 39% 26% 6% < 1% -
11 JIN Daniel - 3% 16% 35% 32% 12% 1%
12 KHAYAT Ziad N. - - - 3% 22% 51% 23%
13 ZHANG Nathan 11% 36% 36% 15% 3% - -
14 DIECK Logan O. - 1% 8% 24% 36% 25% 6%
15 KIM Donghyeok - - 4% 18% 37% 33% 9%
16 LOGUE Ethan D. - 2% 10% 26% 34% 22% 5%
17 YUMIACO Nolan C. - - 3% 14% 34% 36% 13%
18 HIGGINS Branford - 3% 14% 33% 34% 14% 2%
19 WONG Daniel - 1% 4% 17% 34% 33% 11%
20 SINGHA Orion - 1% 6% 21% 36% 29% 9%
21 KIM Benjamin I. - - 4% 16% 34% 34% 13%
22 WATT Darren 2% 13% 31% 32% 17% 4% -
23 KIM Nathan - 2% 12% 29% 35% 18% 3%
24 MA Victor 2% 13% 32% 34% 16% 3% -
25 SPROWLES Cameron D. - - 1% 10% 32% 41% 16%
26 HE Zhiheng 1% 12% 31% 34% 18% 4% -
27 UVAROV Andrii 1% 15% 34% 32% 14% 3% -
28 PARK Elliot - 3% 15% 33% 33% 14% 2%
29 WILSON Brent A. - - 2% 13% 33% 37% 14%
30 CHEN Bailey 21% 41% 28% 9% 1% - -
31 SMITH Justin C. - - 1% 8% 25% 41% 25%
32 PAK Elliot 5% 25% 38% 24% 8% 1% -
33 WRIGHT Christopher - 5% 18% 33% 29% 13% 2%
34 SARKAR Agniv - 6% 22% 35% 27% 9% 1%
35 KOPPE Alexander 7% 28% 38% 21% 5% < 1% -
36 GAO Chaney C. - 3% 19% 43% 28% 6% -
37 NIXON Mark - - 3% 15% 34% 34% 13%
38 WESTON Tom 2% 15% 32% 31% 15% 4% -
38 ZHENG Haoran - - 4% 17% 34% 33% 12%
40 GRABER Andrew J. - - - 3% 16% 43% 38%
41 DEMPSEY Connor - 1% 6% 21% 36% 28% 7%
42 POLAKOSKI David R. - - 1% 7% 25% 41% 25%
43 LIU Noah 20% 40% 28% 9% 2% - -
44 FRENCH Timothy - - 3% 13% 32% 37% 15%
45 ULINICH Alexander 1% 10% 27% 33% 21% 6% 1%
46 SHARMA Sanil - - 1% 10% 31% 42% 16%
47 KIM Sullivan 4% 22% 38% 26% 8% 1% -
48 MUNOZ Humberto 1% 9% 29% 36% 20% 4% -
49 FU Leon 1% 10% 26% 34% 22% 7% 1%
50 CHU Allan 5% 24% 38% 26% 7% 1% -
51 BAILEY Creston P. - 2% 11% 31% 36% 18% 3%
51 MING Nathan 3% 18% 35% 29% 12% 2% -
53 WANG Devon - 4% 18% 36% 31% 10% 1%
54 YAMASAKI Kyle A. - - < 1% 4% 19% 42% 35%
55 SARKAR Anish 3% 17% 35% 30% 13% 3% -
56 PARKER Lane S. - 6% 21% 34% 27% 11% 2%
57 GAINES Aaron - 1% 7% 29% 43% 19% 2%
58 HUSSAIN Kamran - 2% 12% 30% 34% 18% 4%
59 KNUDSEN Travis 7% 28% 37% 21% 6% 1% -
60 ZHUANG William 9% 34% 40% 15% 2% - -
61 YUEN Nathan 44% 39% 14% 3% - - -
62 LIU Felix 2% 14% 33% 32% 15% 3% -
62 LEE Bryson 26% 44% 24% 5% 1% - -
64 ALEXANDER Chuck 1% 6% 22% 36% 26% 8% 1%
65 CHIRASHNYA Daniel - 5% 20% 35% 28% 10% 1%
66 MENDOZA Zandro 28% 42% 24% 6% 1% - -
67 SINHA Zaan 10% 31% 35% 19% 5% 1% -
68 LOFTUS Luca 20% 44% 29% 6% - - -
69 PERKINS-OLLILA Justin W. - 4% 18% 34% 30% 12% 2%
70 MENDOZA Zachari 1% 10% 27% 33% 21% 6% 1%
71 PHEN Justin P. - - 3% 13% 30% 36% 18%
72 LIU Yikun 21% 39% 28% 10% 2% - -
73 ERLIKHMAN Adrian 18% 39% 30% 11% 2% - -
74 LIU Andrew 6% 27% 39% 23% 5% - -
75 HILLSTROM Nathan 2% 13% 30% 33% 17% 4% -
76 LOCASALE Nicholas A. 12% 36% 35% 14% 2% - -
77 DEKERMANJI Christopher 2% 13% 32% 34% 16% 4% -
78 ALI Adam 21% 41% 28% 9% 1% - -
79 LEE Richard U. 24% 44% 25% 6% 1% - -
79 JU Hanul 39% 41% 16% 3% - - -
81 HEWITT Frank F. 1% 10% 30% 35% 19% 5% -
82 KURITZ Marc M. - 1% 9% 25% 35% 23% 6%
83 MIAO Kunqi 28% 45% 23% 4% - - -
84 LEE Chun Po 4% 20% 34% 28% 11% 2% -
85 NALBANDIAN Vahan P. 23% 40% 27% 9% 2% - -
86 KIM Taeho 45% 40% 13% 2% - - -
87 PRAKASH Hari 37% 43% 17% 3% - - -
88 DOWDELL Riley 3% 16% 33% 31% 14% 3% -
89 SETTE Alessandro 19% 40% 30% 10% 2% - -
90 CHAKRAVARTHY Arjun 72% 24% 3% - - - -
91 MARSH Timothy G. < 1% 2% 11% 32% 39% 15% 2%

Explanation

The heatmap in this table provides a visual representation of the victory probability distribution for each fencer in their respective pools:

This heatmap visualization offers an immediate understanding of each fencer's expected performance compared to their actual results.