Baltimore, MD - Baltimore, 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 | LAI Adam J. | - | - | 2% | 10% | 29% | 40% | 19% |
2 | DODRILL Grant | - | - | 1% | 6% | 23% | 41% | 29% |
3 | SILBERZWEIG Jordan H. | - | - | - | 2% | 15% | 42% | 41% |
3 | NIL Michael Y. | - | - | 2% | 10% | 28% | 40% | 21% |
5 | HAMMERSTROM Jared | - | 1% | 6% | 24% | 43% | 26% | |
6 | CHIN Matthew W. | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
7 | FRISHMAN Ethan J. | - | - | 2% | 11% | 29% | 38% | 19% |
7 | SO Hananiah | - | - | 2% | 12% | 32% | 37% | 16% |
9 | LINSKY Matthew | - | - | 1% | 6% | 24% | 44% | 25% |
10 | JEAN Noe T. | - | 1% | 9% | 29% | 40% | 20% | |
10 | WIND Nicky E. | - | 1% | 8% | 27% | 41% | 23% | |
12 | DIACOS Jordan | - | - | 4% | 17% | 37% | 33% | 9% |
13 | HARGENRADER Kailen A. | - | 1% | 8% | 25% | 36% | 23% | 5% |
14 | LIU kelly | - | 3% | 15% | 34% | 35% | 13% | |
15 | MORRILL Justin | - | 2% | 11% | 33% | 39% | 15% | |
16 | SIMAK Joseph P. | - | 5% | 23% | 37% | 26% | 8% | 1% |
17 | KIM Avery J. | - | - | 3% | 16% | 42% | 39% | |
18 | WILSON Jude | - | - | 1% | 6% | 26% | 44% | 23% |
19 | JARAMILLO Tobias L. | - | 3% | 18% | 38% | 32% | 8% | |
20 | HONG Steven | - | 9% | 31% | 37% | 19% | 4% | - |
21 | CHEN Oscar | - | 3% | 14% | 32% | 33% | 16% | 3% |
22 | CHAN Matthew | - | 5% | 20% | 36% | 30% | 9% | |
23 | FENG Leo | 2% | 15% | 33% | 33% | 15% | 2% | |
24 | KEEFE Duncan | 1% | 10% | 28% | 36% | 21% | 4% | |
25 | WOODWARD Connor | 1% | 7% | 26% | 39% | 23% | 4% | |
26 | BERMAN Luca | - | 8% | 26% | 35% | 23% | 7% | 1% |
27 | ZHOU Justin | - | 1% | 7% | 21% | 35% | 28% | 8% |
28 | KOGAN Benjamin | - | 4% | 17% | 33% | 31% | 13% | 2% |
29 | HUANG Tyler T. | 27% | 42% | 24% | 6% | 1% | - | |
30 | MAKLIN Edward P. | 1% | 10% | 29% | 36% | 19% | 4% | - |
31 | GINIS Nathan | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
32 | GHENEA George Philipe | 7% | 32% | 39% | 18% | 4% | - | |
33 | MORRILL William | - | 1% | 5% | 19% | 36% | 30% | 9% |
34 | YANG Richard | - | 1% | 10% | 29% | 38% | 19% | 3% |
35 | HOUTZ Jackson | - | 3% | 15% | 31% | 33% | 16% | 3% |
36 | LEE Justin | 1% | 13% | 32% | 33% | 17% | 4% | - |
37 | CHAVES Matthew J. | 11% | 34% | 35% | 16% | 3% | - | |
38 | DENNER Maximilian P. | - | 2% | 14% | 33% | 35% | 15% | 2% |
39 | LU Timothy | 1% | 6% | 23% | 35% | 26% | 8% | 1% |
40 | COX Luis E. | 14% | 38% | 33% | 13% | 2% | - | - |
41 | CHAUDHURI Eeshaan A. | 9% | 33% | 37% | 17% | 3% | - | |
42 | REN Richard | 23% | 42% | 27% | 7% | 1% | - | |
43 | CHEONG Heonjae | - | 5% | 21% | 39% | 28% | 6% | |
44 | GREENBAUM Ian L. | 2% | 15% | 33% | 31% | 14% | 3% | - |
45 | ERACHSHAW Cyrus P. | - | 4% | 18% | 34% | 30% | 12% | 2% |
45 | BURDAN Gabriel | 51% | 37% | 11% | 1% | - | - | - |
47 | SHTEIN Yan | 38% | 41% | 17% | 4% | - | - | - |
48 | SHTEYN Mark | 3% | 18% | 34% | 29% | 12% | 3% | - |
49 | MEHTA Krish | 10% | 32% | 36% | 17% | 4% | - | - |
50 | ALTIRS Alexander | 2% | 19% | 39% | 30% | 9% | 1% | |
51 | PAN Andrew W. | 3% | 17% | 35% | 31% | 13% | 2% | |
52 | LEE Aydan J. | 4% | 20% | 36% | 29% | 10% | 1% | |
53 | GEORGE Daniel | 50% | 38% | 10% | 1% | - | - | |
54 | LO Alexander | 13% | 37% | 35% | 13% | 2% | - | |
55 | CHENG Cody | 8% | 30% | 38% | 19% | 4% | - | - |
56 | SHERWOOD Hayden F. | 2% | 19% | 36% | 29% | 11% | 2% | - |
57 | HUANG Maxwell H. | 4% | 32% | 40% | 19% | 4% | - | - |
58 | COLE Alexander | 1% | 11% | 28% | 33% | 19% | 6% | 1% |
59 | GRASS James D. | 1% | 6% | 22% | 35% | 26% | 9% | 1% |
60 | LOWHAM-RUZZO Alexander J. | 22% | 41% | 27% | 8% | 1% | - | - |
61 | NOBLE Colin | 6% | 25% | 37% | 24% | 7% | 1% | |
62 | WEIL Asher D. | 75% | 23% | 2% | - | - | - | - |
63 | CHENG Kyle | 24% | 41% | 26% | 8% | 1% | - | |
64 | MCCARTHY Gabriel | 3% | 20% | 37% | 28% | 10% | 2% | - |
65 | PANDEY Neil | 26% | 42% | 25% | 7% | 1% | - | - |
66 | OLIVER Isaac | 79% | 19% | 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.