National Harbor, MD - National Harbor, MD, 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 | SUICO Zachary Emanuel O. | - | - | 1% | 9% | 27% | 40% | 22% |
2 | ZAFFT Maximo S. | - | - | 1% | 5% | 21% | 42% | 32% |
3 | KIM Ethan J. | - | - | - | 4% | 21% | 43% | 31% |
3 | LEE Daniel Y. | - | - | - | 4% | 21% | 45% | 29% |
5 | COLLYMORE Spencer T. | - | - | - | 4% | 20% | 42% | 34% |
6 | GOLDER Will W. | - | 1% | 5% | 19% | 35% | 31% | 10% |
7 | LEE Shwan | - | 1% | 4% | 17% | 34% | 33% | 11% |
8 | KROPP Jack | - | - | 3% | 15% | 34% | 35% | 13% |
9 | WIMMER Chandler M. | - | - | - | 3% | 17% | 41% | 39% |
10 | O'HARA Keegan J. | - | - | - | 4% | 17% | 41% | 38% |
11 | MUCCIARONE Massimo | - | 1% | 6% | 23% | 38% | 26% | 6% |
12 | RHYU Kozmo | - | - | - | 4% | 20% | 42% | 33% |
13 | EKE Frank | - | - | 1% | 6% | 26% | 43% | 24% |
14 | GALLANT Antoine | - | 1% | 6% | 20% | 36% | 29% | 8% |
15 | LI Jeffrey | - | 2% | 10% | 27% | 36% | 21% | 4% |
16 | VAYSBUKH Konstantin | - | - | 1% | 7% | 26% | 42% | 24% |
17 | PAVLENISHVILI David G. | - | - | 3% | 13% | 30% | 36% | 17% |
18 | LIU John | - | - | 3% | 15% | 33% | 35% | 14% |
19 | RINEHART Conner M. | - | - | 1% | 8% | 29% | 43% | 20% |
19 | PINERO Jose J. | - | 1% | 8% | 26% | 37% | 23% | 4% |
21 | YAVOROVSKIY Joshua I. | - | 1% | 7% | 27% | 40% | 23% | 4% |
22 | STEVENS George | - | 4% | 18% | 35% | 31% | 10% | 1% |
23 | RODRIGUEZ Ryan | - | 1% | 9% | 27% | 36% | 22% | 5% |
24 | CHONG christopher | - | 1% | 6% | 20% | 34% | 29% | 10% |
25 | MAAS Sean H. | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
26 | NESTEROV Andrew E. | - | 1% | 8% | 23% | 35% | 26% | 7% |
27 | GOLDFINE Ian J. | - | - | 2% | 10% | 29% | 39% | 20% |
28 | CHAWLA Armaan | - | 1% | 8% | 26% | 37% | 23% | 5% |
29 | THAYER Bryce | - | - | - | 2% | 16% | 43% | 38% |
30 | LAI Coby | - | 1% | 9% | 28% | 37% | 21% | 4% |
31 | LEONE III Charles D. | - | 3% | 13% | 28% | 32% | 19% | 4% |
32 | SALISBURY Cary | - | 3% | 17% | 34% | 31% | 13% | 2% |
33 | SALERNO Gaetano | - | 1% | 11% | 31% | 36% | 18% | 3% |
34 | PIERANUNZI Jules W. | - | 1% | 6% | 25% | 38% | 25% | 5% |
35 | JEYOON Ryan S. | - | 3% | 15% | 32% | 32% | 15% | 3% |
36 | CLICK Aiden | - | 1% | 7% | 24% | 36% | 25% | 6% |
37 | DYER Ian E. | - | 2% | 13% | 33% | 34% | 15% | 2% |
38 | JUN Jaywu | - | 2% | 12% | 31% | 35% | 18% | 3% |
39 | AGAON Shawn | - | 1% | 10% | 28% | 36% | 20% | 4% |
40 | ADLER Ethan M. | - | - | 3% | 17% | 36% | 33% | 10% |
41 | BORODITSKY Ethan | - | 1% | 8% | 25% | 36% | 24% | 5% |
42 | PARK Ian C. | - | - | 2% | 11% | 31% | 39% | 18% |
43 | FURST Matthew C. | - | 2% | 15% | 37% | 33% | 11% | 1% |
44 | BUYANOV Nikita V. | 1% | 8% | 22% | 33% | 25% | 10% | 1% |
44 | KIM Dylan J. | 1% | 8% | 26% | 36% | 22% | 6% | 1% |
46 | WOZNIAK Ignacy | - | - | 2% | 10% | 28% | 39% | 20% |
47 | KING Cameron | 1% | 6% | 20% | 32% | 28% | 12% | 2% |
47 | IVAKIMOV Vasil | - | - | 1% | 5% | 23% | 45% | 26% |
49 | TRIMMER Colin | - | 1% | 6% | 23% | 38% | 27% | 6% |
50 | KOKENGE Reid | - | 2% | 14% | 33% | 34% | 15% | 2% |
51 | TROAKE Henry R. | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
52 | SHAH Maximilian A. | - | - | 4% | 17% | 35% | 33% | 11% |
53 | HANRATTY Liam | 4% | 17% | 31% | 30% | 15% | 4% | - |
54 | WEI Michael | 2% | 15% | 38% | 32% | 12% | 2% | - |
55 | MORSE Tyler | - | - | 3% | 13% | 31% | 37% | 17% |
56 | GOHEL Dayus T. | - | - | 4% | 23% | 40% | 26% | 6% |
57 | SIVAKUMAR Ajit | - | 1% | 7% | 23% | 36% | 26% | 7% |
58 | LIEF Isaac R. | - | - | 3% | 21% | 40% | 29% | 7% |
59 | HENSAL Nicolas A. | - | - | 3% | 18% | 40% | 31% | 7% |
60 | BLUM Oliver | 7% | 24% | 34% | 24% | 9% | 2% | - |
61 | GALBIATI Leonardo | - | 2% | 10% | 28% | 35% | 21% | 5% |
62 | DU Drake | - | 3% | 19% | 36% | 30% | 11% | 2% |
63 | LI Benjamin | 2% | 12% | 28% | 32% | 20% | 6% | 1% |
64 | MACARTY Jordan T. | - | 4% | 17% | 33% | 30% | 13% | 2% |
65 | KRAVIT Connor B. | - | - | 1% | 4% | 18% | 40% | 37% |
66 | BASOK Nikita | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
67 | FLECKENSTEIN Benjamin T. | 1% | 6% | 20% | 33% | 28% | 11% | 2% |
68 | CAO Brad | 3% | 16% | 32% | 31% | 15% | 3% | - |
69 | MCCOMISKEY Aiden J. | - | 1% | 9% | 28% | 38% | 21% | 4% |
70 | WU Marcus | 1% | 9% | 26% | 34% | 22% | 7% | 1% |
71 | KOBI Samuel | 2% | 14% | 32% | 32% | 16% | 4% | - |
72 | YI Jason | 3% | 15% | 31% | 31% | 16% | 4% | - |
73 | LIU Yichen | 2% | 11% | 29% | 34% | 19% | 5% | 1% |
74 | DIXON Thomas | - | 6% | 23% | 36% | 26% | 9% | 1% |
74 | KIM Ryan | 21% | 38% | 28% | 11% | 2% | - | - |
76 | WANG Albert | 1% | 10% | 30% | 35% | 19% | 5% | - |
77 | O'CONNOR Riley | - | 1% | 5% | 17% | 33% | 32% | 12% |
78 | NIKOLOV Peter | 1% | 16% | 35% | 31% | 13% | 3% | - |
79 | KOLOCIN John | 4% | 23% | 43% | 25% | 6% | 1% | - |
80 | CHEN Zhong Han | 39% | 41% | 16% | 3% | - | - | - |
81 | PAHLAVI Kamran | 4% | 18% | 32% | 29% | 14% | 3% | - |
82 | KIM Byung | 3% | 14% | 30% | 31% | 17% | 4% | - |
83 | ROY NATHAN J | 3% | 16% | 34% | 32% | 13% | 2% | - |
83 | BAKER Toby | 11% | 34% | 35% | 16% | 4% | - | - |
85 | LAM Bill | 41% | 44% | 14% | 2% | - | - | - |
86 | PRIHODKO Max | 2% | 12% | 32% | 35% | 16% | 3% | - |
86 | PANTEL Derek F. | 5% | 20% | 33% | 27% | 12% | 3% | - |
86 | GOLCZEWSKI Benjamin | 2% | 12% | 29% | 33% | 18% | 5% | - |
89 | NORTH Alexander M. | - | 1% | 12% | 35% | 36% | 14% | 2% |
90 | GLECKNER Aidan | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
91 | CAUTHEN Edwin | 5% | 20% | 33% | 28% | 12% | 2% | - |
92 | DILLE Jackson K. | 1% | 13% | 35% | 34% | 14% | 3% | - |
93 | KUMAR Aidan | 3% | 20% | 37% | 28% | 10% | 2% | - |
94 | ALTUVE Alejandro J. | 1% | 9% | 29% | 36% | 20% | 5% | 1% |
95 | ZENG Zihan | - | 2% | 17% | 36% | 31% | 12% | 2% |
96 | KHANNA Nikhil | - | 4% | 17% | 34% | 31% | 12% | 1% |
97 | KHALITOV Alexander | 14% | 34% | 33% | 16% | 4% | - | - |
98 | REITINGER Luke M. | 34% | 42% | 19% | 4% | - | - | - |
99 | MORTIMER Gavin | 13% | 36% | 34% | 15% | 3% | - | - |
100 | ROYTBURD Samuel | 7% | 35% | 40% | 15% | 2% | - | - |
100 | CROSS Kieran | 21% | 39% | 28% | 10% | 2% | - | - |
102 | SUN Jason | 11% | 36% | 35% | 15% | 3% | - | - |
103 | ZHANG Caden | 49% | 41% | 10% | 1% | - | - | - |
104 | ILYAS Zakariya | 5% | 23% | 36% | 25% | 9% | 2% | - |
105 | KESTNER Jack | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
106 | LEE Hudson | 6% | 27% | 37% | 22% | 7% | 1% | - |
107 | WEGMAN Jack | 12% | 31% | 33% | 18% | 5% | 1% | - |
108 | VACCARO Dominick J. | 2% | 16% | 40% | 31% | 10% | 1% | - |
109 | RUNGE Patrick A. | 12% | 44% | 33% | 10% | 1% | - | - |
110 | NESTERCZUK Maddox W. | 18% | 49% | 27% | 6% | - | - | - |
111 | SAMMS-HAY Cameron | 20% | 40% | 29% | 9% | 1% | - | - |
112 | PARK Frederick | 11% | 35% | 34% | 15% | 3% | - | - |
113 | FU Ethan | 5% | 27% | 38% | 23% | 6% | 1% | - |
113 | MARGHUB Safi | 15% | 38% | 32% | 12% | 2% | - | - |
113 | OLSON William | 27% | 41% | 24% | 7% | 1% | - | - |
116 | GAO Daniel | 35% | 49% | 14% | 2% | - | - | - |
117 | ZHANG Andy | 52% | 38% | 9% | 1% | - | - | - |
118 | AGAON Ethan | 1% | 11% | 29% | 35% | 19% | 5% | - |
118 | TAN Connor | 37% | 42% | 17% | 3% | - | - | - |
120 | ZHUANG Alex | 30% | 47% | 20% | 3% | - | - | - |
121 | BANNEN Nicholas | 1% | 9% | 28% | 36% | 21% | 5% | 1% |
122 | CHEN Austin | 8% | 27% | 35% | 22% | 7% | 1% | - |
123 | KANACH Duncan | 22% | 46% | 26% | 6% | 1% | - | - |
124 | LEE Seungwon | 3% | 15% | 31% | 31% | 16% | 4% | - |
125 | MCALISTER Ian | 3% | 18% | 38% | 29% | 10% | 1% | - |
125 | ZHANG Andy | 30% | 47% | 20% | 3% | - | - | - |
127 | YUAN Calvin | 4% | 21% | 35% | 27% | 11% | 2% | - |
128 | SCHULZE Ethan | 38% | 48% | 13% | 1% | - | - | - |
129 | JORDAN Anton | 9% | 28% | 34% | 21% | 7% | 1% | - |
130 | GOLDMAN Isaac | 76% | 22% | 2% | - | - | - | - |
131 | SUN Jeffery | 52% | 37% | 10% | 1% | - | - | - |
132 | YANG James | 9% | 33% | 40% | 17% | 1% | - | - |
133 | CHOI Marcus | 39% | 45% | 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.