Jersey City, NJ - Jersey City, NJ, 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 | ANTIPAS Michael C. | - | 1% | 7% | 22% | 37% | 28% | 6% |
2 | SCARPA Ryan N. | - | - | 2% | 15% | 38% | 35% | 9% |
3 | HASSAN Mohamed H. | - | - | - | 4% | 18% | 42% | 36% |
3 | REYNOLDS Tyler C. | - | - | 4% | 17% | 36% | 33% | 10% |
5 | GROSS Liran | - | - | 2% | 14% | 46% | 32% | 6% |
6 | FIELD Miles | - | - | 1% | 9% | 30% | 42% | 17% |
7 | WOODS Jack H. | - | - | 1% | 6% | 25% | 44% | 23% |
8 | JU Alexander (Alex) Y. | - | 1% | 7% | 28% | 41% | 21% | 3% |
9 | HEMPE Jake | - | 8% | 28% | 38% | 22% | 4% | |
10 | LESNIKOV Kirel | - | 1% | 5% | 17% | 33% | 32% | 13% |
11 | PANTEL Adam S. | - | - | 3% | 16% | 36% | 34% | 10% |
12 | ZUSIN Zachary W. | - | 1% | 11% | 33% | 36% | 16% | 3% |
13 | HOLMES Andrew E. | - | - | - | 3% | 17% | 42% | 38% |
13 | HARTMARK Anders | - | - | 3% | 13% | 31% | 36% | 17% |
15 | ACINAPURO Philip M. | - | 2% | 12% | 30% | 34% | 18% | 4% |
16 | SCHLESINGER Nathan | - | 2% | 13% | 33% | 37% | 15% | |
17 | RICCIO Frank J. | - | 1% | 5% | 19% | 36% | 31% | 9% |
18 | KASI Sanjay | 1% | 7% | 24% | 35% | 24% | 8% | 1% |
19 | PRILUTSKY David B. | - | - | 1% | 8% | 26% | 41% | 25% |
20 | PRINCE Nicholas J. | 2% | 12% | 30% | 34% | 18% | 4% | |
21 | CARMAN Ian K. | 5% | 20% | 33% | 27% | 12% | 3% | - |
22 | LOCKWOOD Owen | 1% | 8% | 22% | 31% | 25% | 11% | 2% |
23 | MANGE Nathan | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
24 | LIU Eric P. | 4% | 21% | 35% | 28% | 10% | 2% | - |
25 | RITCHIE Luke W. | - | 5% | 20% | 35% | 28% | 10% | 1% |
26 | GEE Brandon | - | 2% | 11% | 28% | 35% | 20% | 4% |
27 | GU Jeffrey | 10% | 29% | 35% | 20% | 6% | 1% | - |
28 | CHU Derek | 12% | 32% | 34% | 17% | 4% | 1% | - |
29 | TSANG Matthew K. | 2% | 10% | 25% | 32% | 22% | 8% | 1% |
30 | ADLER Ian B. | - | 2% | 11% | 29% | 36% | 20% | 4% |
31 | LEE Daniel C. | 1% | 6% | 18% | 30% | 29% | 14% | 3% |
32 | DIVENTI Paul W. | 1% | 9% | 25% | 35% | 23% | 6% | |
33 | VITI Mark G. | 2% | 11% | 26% | 32% | 22% | 7% | 1% |
34 | VANNI Filippo A. | 5% | 23% | 37% | 26% | 8% | 1% | - |
35 | GORDON-SAND Spencer | 2% | 11% | 28% | 34% | 20% | 5% | - |
36 | WANG Michael | 1% | 7% | 23% | 34% | 26% | 9% | 1% |
37 | MARSHALL Ian | 2% | 17% | 36% | 31% | 12% | 2% | - |
38 | LIN Richard W. | - | 2% | 13% | 30% | 33% | 17% | 3% |
39 | PANTEL Glenn S. | 3% | 19% | 36% | 30% | 11% | 2% | |
40 | DUNAT Maximilian (Max) D. | 11% | 31% | 35% | 18% | 5% | 1% | - |
41 | ENGEL Henry R. | 13% | 34% | 33% | 15% | 3% | - | - |
42 | HEALY Griffen | - | 3% | 15% | 33% | 33% | 14% | 1% |
43 | BRANDT-OGMAN Adlai | 1% | 7% | 24% | 35% | 25% | 8% | 1% |
43 | BREIER Matthew F. | 3% | 15% | 30% | 31% | 16% | 4% | - |
45 | ZELTSER Lawrence M. | 5% | 22% | 36% | 26% | 9% | 1% | - |
46 | MA Alexander | - | 2% | 10% | 26% | 36% | 22% | 4% |
47 | SACCOCCIO Nicholas P. | 1% | 8% | 22% | 32% | 26% | 10% | 2% |
48 | PYO Michael M. | 14% | 36% | 33% | 13% | 3% | - | - |
49 | SINGH Dayaal | 2% | 12% | 26% | 31% | 21% | 7% | 1% |
50 | GAEHDE Christian P. | 25% | 43% | 25% | 6% | 1% | - | - |
51 | ONIK Elijah T. | 5% | 21% | 35% | 28% | 10% | 2% | - |
52 | SPIRLI Francesco | 1% | 8% | 27% | 36% | 22% | 5% | - |
53 | SANTULLI Tristan | 15% | 44% | 33% | 7% | 1% | - | - |
54 | LI Yulei | 14% | 40% | 35% | 10% | 1% | - | - |
55 | CHESTNA Samuel E. | 4% | 20% | 35% | 28% | 11% | 2% | - |
56 | MILLER Trent D. | 3% | 15% | 33% | 32% | 14% | 3% | - |
57 | KUZMAK Michael J. | 57% | 34% | 8% | 1% | - | - | - |
58 | SOUMAKIS Sarantos G. | 21% | 42% | 28% | 8% | 1% | - | - |
59 | SKOLNICK Michael W. | 45% | 42% | 12% | 2% | - | - | - |
60 | FRERE-CAROSSIO Quentin | 41% | 41% | 15% | 2% | - | - | |
61 | COSTELLO Chaissen F. | 1% | 17% | 35% | 31% | 13% | 3% | - |
62 | OZSOLAK Alex | 3% | 16% | 32% | 31% | 15% | 3% | - |
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.