Fredericksburg Convention Center - Fredericksburg, VA, 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 | LEE Aiden | - | - | - | 4% | 18% | 41% | 37% |
| 2 | DOUBOV Andrew | - | - | - | 2% | 13% | 40% | 46% |
| 3 | CHEN Zhengyang (Allen) | - | - | - | 1% | 9% | 35% | 55% |
| 3 | RAPALSKI Thomas | - | 1% | 7% | 22% | 35% | 27% | 8% |
| 5 | OSBORN Hunter | - | - | 2% | 11% | 31% | 40% | 17% |
| 6 | LIDSKY Phineas | - | - | 1% | 6% | 23% | 42% | 28% |
| 7 | YI Nathan | - | - | 4% | 17% | 35% | 34% | 11% |
| 8 | YU Jason | - | - | 4% | 15% | 33% | 34% | 14% |
| 9 | LEE DoWon | - | - | 2% | 10% | 28% | 38% | 21% |
| 10 | SAUNIER Cameron | - | - | 1% | 6% | 23% | 42% | 28% |
| 11 | CHO Alex | - | 1% | 10% | 30% | 37% | 18% | 3% |
| 12 | SHOUSHA Hamza | - | - | 4% | 19% | 42% | 35% | |
| 13 | ARMSTRONG TyLee | - | 1% | 6% | 22% | 38% | 28% | 6% |
| 13 | LI Jade | - | - | 3% | 14% | 33% | 36% | 13% |
| 15 | MODANLOU Navid | - | - | - | 2% | 14% | 41% | 43% |
| 16 | SINGLETON Aman | - | 1% | 4% | 16% | 33% | 33% | 13% |
| 17 | MIDYANY Evan | - | - | - | 3% | 14% | 40% | 43% |
| 18 | CUELLAR Markus | - | 3% | 15% | 33% | 33% | 14% | 2% |
| 19 | CHEN Edward | - | 3% | 13% | 28% | 33% | 19% | 4% |
| 20 | HELMY Richard | - | 1% | 8% | 25% | 37% | 24% | 4% |
| 21 | LEE Henry | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
| 22 | WANG Marcus | - | 4% | 16% | 31% | 31% | 15% | 3% |
| 23 | KIM Remington | - | 4% | 16% | 32% | 32% | 14% | 2% |
| 23 | MIDYANY Ryan | - | 1% | 9% | 26% | 38% | 23% | 4% |
| 25 | KIM Gene | - | - | 4% | 18% | 36% | 32% | 9% |
| 26 | DILDA Griffin | 1% | 11% | 28% | 34% | 20% | 5% | - |
| 27 | LEE Benjamin | - | 4% | 16% | 32% | 32% | 14% | 2% |
| 28 | SINGH Ravin | - | - | 1% | 5% | 23% | 44% | 28% |
| 29 | MIKHAIL Lucas | 1% | 5% | 18% | 31% | 29% | 14% | 2% |
| 30 | SATISHKUMAR Pranav | 2% | 12% | 30% | 34% | 18% | 4% | - |
| 31 | TSIEN Richard | 2% | 16% | 36% | 31% | 12% | 2% | - |
| 32 | RICHMOND Ozan | 3% | 19% | 35% | 29% | 11% | 2% | - |
| 33 | ROBERTS Phoenix | - | 4% | 18% | 36% | 32% | 9% | |
| 34 | CHEN Jayden | - | - | 4% | 18% | 42% | 35% | |
| 35 | MAKOLO Hudson | 2% | 13% | 32% | 33% | 16% | 3% | - |
| 36 | ADDYSON Aidan | 5% | 22% | 36% | 26% | 9% | 2% | - |
| 37 | BROSNAN Solomon | 17% | 38% | 31% | 12% | 2% | - | |
| 38 | LIN Haley | 2% | 10% | 26% | 33% | 21% | 7% | 1% |
| 39 | KROPP Wesley | 1% | 6% | 23% | 35% | 25% | 8% | 1% |
| 40 | MILINKOVIC Maksim | 1% | 8% | 28% | 38% | 21% | 4% | |
| 41 | ZHANG Lucas | - | 3% | 14% | 31% | 34% | 16% | 3% |
| 42 | RODOCANACHI Hector | 2% | 13% | 30% | 33% | 17% | 4% | - |
| 42 | RAMEY Daylon | 4% | 19% | 35% | 29% | 11% | 2% | - |
| 44 | ZAHRAN Aiden | - | - | 4% | 17% | 37% | 33% | 8% |
| 44 | CRESPO Nathaniel Justus | - | 4% | 17% | 33% | 31% | 12% | 2% |
| 46 | LEE Anton | - | 1% | 4% | 16% | 33% | 33% | 13% |
| 46 | KONG Brandon | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
| 48 | HE Bronto | - | 6% | 24% | 37% | 25% | 7% | 1% |
| 49 | NILSEN Mark | 2% | 13% | 32% | 33% | 16% | 3% | - |
| 50 | ZHANG Austin | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
| 51 | SUNKARA Vishnu | 2% | 12% | 29% | 33% | 18% | 5% | 1% |
| 51 | CHO Adrian | 13% | 33% | 34% | 16% | 4% | - | - |
| 53 | SUN Lucas | - | 5% | 21% | 38% | 29% | 7% | |
| 54 | TSEN Mason | 15% | 41% | 32% | 10% | 1% | - | |
| 55 | DELONG Joshua | 1% | 11% | 29% | 34% | 19% | 5% | - |
| 56 | ZHU Eason | 3% | 15% | 34% | 33% | 13% | 2% | |
| 57 | PARKS-GOOD Tyler | 13% | 35% | 34% | 15% | 3% | - | |
| 58 | YANG Gary | - | - | 1% | 6% | 23% | 42% | 29% |
| 59 | MASSIE Jay | 2% | 12% | 29% | 32% | 18% | 5% | 1% |
| 60 | KE Sebastian | - | 2% | 9% | 26% | 36% | 23% | 4% |
| 61 | BANG Dylan | 2% | 13% | 31% | 34% | 17% | 3% | - |
| 62 | GRIGGS Kaiden | 14% | 36% | 33% | 14% | 3% | - | - |
| 63 | THOMAS Ethan | 2% | 13% | 31% | 33% | 17% | 4% | - |
| 64 | FOGEL Jake | 33% | 42% | 20% | 4% | - | - | - |
| 65 | SHILOV Maxim | 1% | 11% | 32% | 37% | 17% | 3% | |
| 66 | CHANEY Charles | 3% | 16% | 31% | 30% | 15% | 4% | - |
| 67 | MEDISETTI Arjun | 19% | 37% | 30% | 12% | 2% | - | - |
| 68 | ARZT Nicholas | 1% | 6% | 20% | 33% | 27% | 11% | 2% |
| 69 | KOGAN Yelisey L. | 4% | 20% | 33% | 28% | 12% | 2% | - |
| 70 | SMOTHERS Nathan | 6% | 24% | 35% | 25% | 9% | 1% | - |
| 71 | GATEWOOD Michael | 3% | 18% | 34% | 30% | 13% | 3% | - |
| 72 | CAFASSO Alexander | - | 5% | 19% | 34% | 29% | 11% | 1% |
| 73 | YAO Tristan | 4% | 19% | 33% | 28% | 13% | 3% | - |
| 74 | DAVIS Andrew | 6% | 23% | 36% | 25% | 8% | 1% | - |
| 75 | LEE Carson | - | 5% | 19% | 34% | 29% | 11% | 1% |
| 77 | LUO Alexander | - | 5% | 19% | 34% | 29% | 11% | 1% |
| 77 | LEECH Braedan | 2% | 11% | 27% | 33% | 21% | 6% | 1% |
| 79 | YU David | 3% | 18% | 34% | 29% | 12% | 2% | - |
| 80 | HALE Bradley | 23% | 40% | 27% | 8% | 1% | - | - |
| 81 | MCCABE Kian | 3% | 15% | 33% | 32% | 14% | 3% | - |
| 82 | ARMSTRONG Payson | 5% | 23% | 36% | 25% | 9% | 1% | - |
| 82 | FENG Xinmin | 19% | 39% | 30% | 11% | 2% | - | - |
| 84 | WILKERSON Tobias | 10% | 33% | 35% | 17% | 4% | - | - |
| 85 | WU Jiachen | 35% | 43% | 18% | 3% | - | - | |
| 86 | ROBERTS Arthur | 12% | 38% | 35% | 13% | 2% | - | - |
| 87 | BAYUS Oliver | 3% | 17% | 33% | 30% | 13% | 2% | - |
| 88 | JONES Gideon | 43% | 40% | 14% | 3% | - | - | - |
| 89 | GRIGORENKO Gleb E. | 11% | 31% | 33% | 18% | 6% | 1% | - |
| 90 | NAM Nathaniel | 4% | 21% | 37% | 28% | 9% | 1% | |
| 91 | ALABI Azryl | 9% | 30% | 36% | 20% | 5% | 1% | - |
| 92 | CHAN Ian | 36% | 41% | 18% | 4% | - | - | - |
| 93 | MAXWELL Sheito | 26% | 41% | 25% | 7% | 1% | - | - |
| 94 | PARY Jean Pierre | 39% | 40% | 17% | 4% | - | - | - |
| 95 | PERI Mourya | 36% | 41% | 18% | 4% | - | - | - |
| 96 | STRAFFORD Andrew | 41% | 42% | 14% | 2% | - | - | - |
| 97 | GUO Lucas | 4% | 18% | 32% | 29% | 13% | 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.