Rio Hotel and Casino - Las Vegas, NV, 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 | FU Nolan | - | - | - | 3% | 18% | 42% | 37% |
2 | WONG Aaron | - | - | 6% | 26% | 46% | 22% | |
3 | RONG Marcus | - | - | 1% | 6% | 22% | 42% | 29% |
3 | DU Evan | - | - | - | - | 4% | 28% | 68% |
5 | XUE Michael | - | - | - | 2% | 13% | 39% | 45% |
6 | HWANG Matthew | - | - | - | 7% | 28% | 43% | 21% |
7 | KIM Leejay | - | - | 4% | 22% | 40% | 28% | 6% |
8 | LEE Leo | - | 3% | 14% | 28% | 31% | 18% | 4% |
9 | KIM Julian | - | - | - | 4% | 18% | 41% | 37% |
10 | MOSLEY Wally | - | - | 2% | 16% | 45% | 37% | |
11 | PARRA Lucas | - | 1% | 8% | 27% | 39% | 23% | 3% |
12 | WU MiEr | - | - | 1% | 7% | 29% | 43% | 21% |
13 | RAU Shogun | - | 1% | 6% | 23% | 38% | 26% | 6% |
14 | LIU Xuyao | - | - | 4% | 19% | 37% | 31% | 9% |
15 | ZHANG Chaoyi(Joey) | - | 3% | 16% | 37% | 35% | 10% | |
16 | CHANG Matthew | - | - | 1% | 7% | 27% | 43% | 23% |
17 | WANG Lucas | - | - | 1% | 9% | 28% | 41% | 21% |
18 | WU Nathan | - | - | 1% | 9% | 29% | 41% | 19% |
19 | SCHIPPER Johann | - | 2% | 11% | 28% | 35% | 20% | 3% |
20 | MOU Jaydon | - | - | 1% | 5% | 20% | 42% | 33% |
21 | PARKE Nathaniel | - | - | - | 3% | 15% | 40% | 42% |
22 | ROBERTS Arthur | - | - | 4% | 17% | 36% | 33% | 11% |
23 | LIN Daniel | 1% | 8% | 22% | 32% | 25% | 11% | 2% |
24 | YI Alexander | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
25 | YUN Nicholas | 2% | 14% | 33% | 33% | 15% | 3% | - |
26 | SHOURIE Neel | - | 4% | 18% | 35% | 31% | 11% | 1% |
27 | MA Nolan | - | - | 2% | 9% | 27% | 39% | 22% |
28 | YAO Tristan | - | - | 1% | 9% | 29% | 40% | 20% |
28 | YU Brandon | - | 1% | 9% | 28% | 37% | 21% | 4% |
30 | WONG Kyle | - | 2% | 11% | 30% | 36% | 19% | 3% |
31 | HUA Nolan | 1% | 9% | 23% | 32% | 24% | 10% | 2% |
32 | ENG Kyler | - | - | 4% | 20% | 43% | 33% | |
33 | WANG Juehan | - | 3% | 15% | 34% | 33% | 13% | 2% |
34 | LIN Bryan | - | 1% | 6% | 20% | 36% | 29% | 8% |
35 | HANTOV Adrian | - | - | 3% | 14% | 34% | 36% | 13% |
36 | CHEN Aiden | 1% | 8% | 28% | 39% | 21% | 4% | |
37 | WONG Alexander | - | 1% | 9% | 26% | 35% | 23% | 5% |
38 | FU Benjamin | - | 4% | 18% | 34% | 30% | 12% | 2% |
39 | LI Vance | - | 4% | 17% | 33% | 31% | 13% | 2% |
40 | YUE Bryan | - | 2% | 12% | 29% | 34% | 19% | 4% |
40 | HUR Tyson | 10% | 31% | 34% | 19% | 5% | 1% | - |
42 | WU James | 5% | 24% | 37% | 25% | 8% | 1% | - |
43 | SHOURIE Seth | 1% | 6% | 20% | 31% | 27% | 12% | 2% |
44 | TIAN Dylan | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
45 | CHEN Linus | 1% | 7% | 26% | 36% | 23% | 6% | 1% |
46 | LIU Aiden | 1% | 9% | 33% | 40% | 16% | 2% | |
47 | GUO Jonathan | - | 1% | 8% | 34% | 38% | 16% | 2% |
48 | KO Ethan | 3% | 18% | 35% | 31% | 11% | 2% | - |
49 | LEE Joshua | 1% | 6% | 24% | 37% | 25% | 7% | - |
50 | NOLAN Morgan | 22% | 41% | 27% | 9% | 1% | - | - |
51 | LEE Lucas | - | - | 4% | 17% | 36% | 34% | 9% |
52 | LEUNG Joon | 1% | 6% | 22% | 35% | 26% | 9% | 1% |
53 | NGUYEN Ethan V. | - | 3% | 16% | 34% | 33% | 12% | 1% |
54 | LAU Caleb | 1% | 11% | 29% | 34% | 19% | 5% | - |
55 | JU Shang | 1% | 12% | 31% | 33% | 18% | 4% | - |
56 | PARADKAR Akshay | 2% | 15% | 35% | 32% | 14% | 3% | - |
57 | SAMOYLOV Daniel | 3% | 17% | 33% | 30% | 14% | 3% | - |
58 | WANG Mason | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
59 | SUN Jiarui (Jerry) | - | 3% | 13% | 28% | 32% | 19% | 5% |
60 | BEN-YOSEPH Rafael | 3% | 16% | 32% | 31% | 15% | 3% | - |
61 | PARK Sean | 4% | 23% | 37% | 26% | 9% | 2% | - |
62 | LI Kingston | 6% | 26% | 37% | 23% | 6% | 1% | - |
63 | PLUMMER Kellan | - | 4% | 16% | 33% | 31% | 13% | 2% |
64 | ZHAO Luke | 9% | 27% | 33% | 22% | 8% | 1% | - |
65 | YOO Lucas | 2% | 15% | 35% | 33% | 13% | 2% | |
66 | DING Max | - | 1% | 6% | 21% | 36% | 28% | 7% |
67 | FONG Ethan | 12% | 33% | 34% | 16% | 4% | - | - |
68 | SI Alexander | 12% | 37% | 34% | 14% | 3% | - | - |
69 | SZETO Zachary | 18% | 38% | 30% | 11% | 2% | - | - |
70 | YUN Mason | 2% | 13% | 32% | 34% | 16% | 3% | - |
71 | YOON Ian | 2% | 18% | 40% | 31% | 9% | 1% | |
72 | ZHANG JENSON | - | 4% | 16% | 32% | 32% | 14% | 2% |
73 | SHIH Derek | - | 7% | 24% | 37% | 24% | 7% | 1% |
74 | CHAN Joseph | 7% | 28% | 37% | 21% | 5% | 1% | - |
75 | CHEN Christopher | - | 3% | 13% | 30% | 34% | 18% | 3% |
76 | CAVALLARO Sebastian | 8% | 36% | 37% | 16% | 3% | - | |
77 | HAO hardy | 63% | 32% | 5% | - | - | - | |
78 | LI Stephen | - | < 1% | 4% | 18% | 36% | 32% | 10% |
79 | CHI Zachary | 12% | 38% | 34% | 13% | 2% | - | - |
79 | ELARDO Griffin | 5% | 24% | 37% | 25% | 7% | 1% | - |
81 | CHAUDHARY Oliver | 13% | 35% | 34% | 15% | 3% | - | - |
82 | CAVALLARO Xavier | 9% | 30% | 35% | 20% | 5% | 1% | - |
83 | LI Connor | 3% | 18% | 36% | 30% | 11% | 2% | - |
84 | ZHAO Kyle Zekai | 4% | 18% | 31% | 28% | 14% | 4% | - |
85 | TENG Eric | 3% | 17% | 33% | 30% | 14% | 3% | - |
86 | CHU Clayton | 13% | 33% | 33% | 16% | 4% | - | - |
87 | WANG Franklin | 16% | 37% | 32% | 13% | 2% | - | - |
88 | LI Ethan | 8% | 36% | 37% | 16% | 3% | - | - |
89 | DEMIRCHIAN Edward | 22% | 40% | 27% | 9% | 2% | - | - |
90 | MATUSOW Brandon | 1% | 12% | 32% | 35% | 17% | 3% | - |
91 | YANG Rony | 27% | 42% | 24% | 6% | 1% | - | - |
91 | KOU Logan | 15% | 42% | 34% | 8% | 1% | - | - |
93 | LAU Jesse | 17% | 43% | 33% | 7% | 1% | - | - |
94 | GAN Samuel | 29% | 46% | 22% | 3% | - | - | - |
95 | LIU Yihong | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
96 | ZHU Jayden | 49% | 39% | 11% | 1% | - | - | |
97 | VENERACION Marcus | 8% | 39% | 39% | 13% | 2% | - | |
98 | TAN Yichen | 53% | 37% | 9% | 1% | - | - | - |
98 | KIM Christian | 34% | 43% | 19% | 4% | - | - | - |
98 | LU Mark | 54% | 36% | 9% | 1% | - | - | - |
101 | LU Jayden | 36% | 42% | 18% | 3% | - | - | - |
101 | WON Jacob | 17% | 39% | 31% | 11% | 2% | - | - |
103 | LEE Connor | 40% | 42% | 15% | 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.