Liontree Arena (RIMAC) @ UC San Diego - La Jolla, CA, USA
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 | CHIRASHNYA Daniel | - | - | 5% | 20% | 36% | 29% | 9% |
2 | KIM Sullivan | - | 1% | 6% | 22% | 36% | 28% | 7% |
3 | KIM Benjamin I. | - | - | 2% | 12% | 31% | 38% | 17% |
3 | LIN Kyran | - | - | 2% | 13% | 33% | 38% | 15% |
5 | SHARMA Sanil | - | - | - | 1% | 11% | 41% | 46% |
6 | RONG Yao | - | - | - | 1% | 8% | 38% | 54% |
7 | SINGHA Orion | - | - | 2% | 10% | 32% | 41% | 15% |
8 | LO Jake | - | - | 2% | 12% | 31% | 38% | 17% |
9 | GOHEL Dayus T. | - | - | - | 3% | 15% | 40% | 43% |
10 | KHANNA Nikhil | - | 1% | 12% | 32% | 36% | 16% | 3% |
11 | KHAYAT Ziad N. | - | - | 1% | 6% | 22% | 42% | 30% |
12 | YAMASAKI Kyle A. | - | - | 1% | 5% | 23% | 43% | 29% |
13 | PHILIPPINE Matthias A. | - | - | 1% | 7% | 30% | 47% | 16% |
13 | WONG Baron | 2% | 15% | 33% | 32% | 14% | 3% | - |
15 | PAK Elliot | 1% | 8% | 23% | 34% | 25% | 8% | 1% |
16 | GALLO James | - | 1% | 10% | 31% | 36% | 18% | 3% |
17 | ZHENG Haoran | - | - | - | 3% | 15% | 41% | 42% |
18 | CALDERON Diego | - | - | - | 1% | 12% | 42% | 46% |
18 | WONG Daniel | - | 1% | 7% | 24% | 37% | 25% | 6% |
20 | BRISLAWN Reilly R. | - | - | 1% | 8% | 28% | 41% | 21% |
21 | MCDANIELS Jeremy | - | - | 1% | 9% | 29% | 41% | 20% |
22 | CHOI Kaiden I. | - | - | 4% | 18% | 37% | 32% | 8% |
23 | JOHNSTON Conner S. | - | 1% | 8% | 26% | 36% | 23% | 6% |
24 | MOSES Alexander | - | - | - | 1% | 9% | 34% | 56% |
25 | DRAGONETTI Walter E. | - | - | - | 4% | 19% | 43% | 33% |
26 | MIAO Quentin | 1% | 10% | 27% | 34% | 21% | 6% | - |
27 | FU Leon | - | - | 1% | 9% | 30% | 43% | 15% |
28 | DIECK Logan O. | - | - | 2% | 14% | 35% | 36% | 12% |
29 | DOWDELL Riley | 1% | 17% | 38% | 31% | 12% | 2% | - |
30 | AMELI Sean | - | - | 1% | 8% | 34% | 44% | 14% |
30 | STEPHAN Jens | - | - | 1% | 7% | 26% | 43% | 23% |
32 | CHIEN Brandon | - | < 1% | 2% | 16% | 42% | 33% | 7% |
33 | SMITH Justin C. | - | 1% | 10% | 32% | 40% | 15% | 2% |
34 | LIU Yikun | - | 3% | 13% | 30% | 34% | 18% | 3% |
35 | WU Johnny y. | 14% | 37% | 35% | 13% | 2% | - | - |
36 | KIM Ian | 1% | 9% | 26% | 34% | 22% | 6% | - |
37 | KIM Nathan | - | - | 4% | 16% | 34% | 33% | 12% |
38 | NIXON Mark | - | 2% | 13% | 32% | 34% | 16% | 3% |
39 | WELDON Benjamin | - | 1% | 7% | 24% | 37% | 25% | 6% |
40 | GONZALES Wesley | 1% | 8% | 25% | 35% | 23% | 7% | 1% |
41 | CHANG Andrew | 1% | 14% | 33% | 33% | 15% | 3% | - |
42 | VILLALOBOSKOWALSKI Demetrious C. | - | 4% | 17% | 33% | 31% | 13% | 2% |
43 | ANDERSON Kai | 10% | 32% | 37% | 17% | 3% | - | - |
44 | MA Victor | - | 1% | 10% | 29% | 38% | 19% | 3% |
45 | CHEN Bailey | 4% | 23% | 37% | 26% | 9% | 1% | - |
46 | WANG Joey | - | 3% | 15% | 33% | 33% | 14% | 2% |
47 | SWANSON Carl G. | 2% | 14% | 33% | 33% | 15% | 3% | - |
48 | KIM Jayden | 1% | 9% | 32% | 37% | 18% | 4% | - |
49 | MCNAMARA Scott | 13% | 36% | 35% | 14% | 2% | - | - |
50 | ROBITZSKI Daniel A. | - | 3% | 14% | 32% | 34% | 15% | 2% |
51 | ERLIKHMAN Adrian | 2% | 11% | 28% | 33% | 20% | 5% | - |
52 | HIGGINS Branford | - | 4% | 18% | 34% | 30% | 11% | 1% |
53 | UVAROV Andrii | 1% | 7% | 23% | 36% | 26% | 7% | - |
54 | SINGH Aryaman | 1% | 14% | 38% | 35% | 11% | 1% | - |
55 | LI Yunji (Rain) | 8% | 31% | 37% | 19% | 4% | - | - |
56 | SCHROEDER Dylan | 2% | 13% | 32% | 34% | 16% | 3% | - |
57 | LEE Jake (JiYuen) | 7% | 41% | 38% | 13% | 2% | - | - |
58 | LEE Tobias (Toby) T. | - | - | 3% | 15% | 34% | 35% | 13% |
58 | LEE Joseph J. | 1% | 9% | 25% | 34% | 23% | 7% | 1% |
60 | CLAWSON Brian C. | - | 5% | 19% | 34% | 29% | 11% | 2% |
61 | WICKBOLDT Eric | - | 3% | 17% | 34% | 31% | 13% | 2% |
62 | HILLSTROM Nathan | 1% | 12% | 32% | 34% | 17% | 4% | - |
63 | WAGHOLIKAR Prathit | 70% | 26% | 3% | - | - | - | - |
64 | RONG Gordon | 21% | 49% | 25% | 5% | - | - | - |
65 | MAYCHROWITZ Matt | - | 1% | 9% | 28% | 37% | 21% | 4% |
66 | BELL Scott S. | 28% | 43% | 23% | 6% | 1% | - | - |
67 | HEINS Dylan | 1% | 11% | 33% | 35% | 16% | 3% | - |
68 | HEWITT Frank F. | 1% | 13% | 37% | 34% | 13% | 2% | - |
69 | YU Austin | 1% | 9% | 25% | 34% | 23% | 7% | 1% |
70 | MARSH Timothy G. | - | 5% | 22% | 36% | 27% | 9% | 1% |
70 | GOROZA Eric | 39% | 41% | 16% | 3% | - | - | - |
72 | KIM Alexander | 8% | 28% | 36% | 21% | 6% | 1% | - |
73 | NAIK Saininad | 1% | 10% | 30% | 37% | 19% | 4% | - |
74 | FIECHTNER Thomas A. | - | 2% | 13% | 34% | 34% | 14% | 2% |
75 | LEVENTAL Mark | 8% | 27% | 35% | 22% | 7% | 1% | - |
76 | DILLON Anik | 2% | 18% | 36% | 30% | 11% | 2% | - |
76 | MORIN-JIANG Jake | 14% | 49% | 29% | 7% | 1% | - | - |
78 | BAILEY Creston P. | 1% | 11% | 30% | 35% | 18% | 4% | - |
79 | AGGELER Donovan | 3% | 17% | 34% | 31% | 12% | 2% | - |
80 | PAINTER Noah | 21% | 43% | 27% | 7% | 1% | - | - |
81 | KIM Remington | 53% | 39% | 8% | 1% | - | - | - |
82 | DEMPSEY Connor | - | 7% | 30% | 40% | 19% | 3% | - |
83 | GETSLA Christopher W. | 1% | 19% | 38% | 29% | 10% | 2% | - |
84 | YUMIACO Nolan C. | - | < 1% | 5% | 20% | 36% | 30% | 9% |
85 | KURITZ Marc M. | 1% | 11% | 30% | 34% | 19% | 5% | - |
85 | ZAROTSKY Ronald | 3% | 16% | 32% | 31% | 15% | 3% | - |
87 | KIM Tristan | 60% | 34% | 6% | - | - | - | - |
88 | STAFFORD Bryan | 23% | 41% | 27% | 8% | 1% | - | - |
88 | MCLAREN Mason | 47% | 42% | 10% | 1% | - | - | - |
90 | ALLEN David | 16% | 36% | 31% | 13% | 3% | - | - |
91 | PRAKASH Hari | 29% | 41% | 23% | 6% | 1% | - | - |
92 | SETTE Alessandro | 17% | 41% | 30% | 10% | 2% | - | - |
93 | BROWN Korbyn | 56% | 35% | 8% | 1% | - | - | - |
94 | SHEN Orlando | 29% | 45% | 22% | 4% | - | - | - |
94 | CAMP Ryder | 85% | 14% | 1% | - | - | - | - |
96 | LEE Royce | 18% | 50% | 26% | 6% | 1% | - | - |
97 | LOCASALE Nicholas A. | 6% | 25% | 39% | 25% | 5% | - | - |
98 | CHARETTE Matt | 43% | 40% | 14% | 2% | - | - | - |
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.