Pasadena Convention Center - Exhibit Halls A & B - Pasadena, CA, 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 | BAE Yooju | - | - | - | - | - | 8% | 91% |
| 2 | KIM Sydney | - | - | 1% | 11% | 43% | 44% | |
| 3 | MIYASHIRO Katelyn | - | - | - | 5% | 33% | 61% | |
| 3 | YAO abby | - | 1% | 6% | 24% | 43% | 26% | |
| 5 | RUI Jessie | - | - | 1% | 8% | 27% | 41% | 22% |
| 6 | LI Joy | - | - | - | 1% | 8% | 34% | 58% |
| 7 | XIA Isabella | 2% | 16% | 37% | 33% | 11% | 1% | |
| 8 | PARK Lauren | - | 1% | 6% | 25% | 45% | 23% | |
| 9 | LI Alice | - | - | - | 1% | 7% | 33% | 60% |
| 10 | ZOU JIAYING | 3% | 15% | 31% | 32% | 16% | 3% | < 1% |
| 11 | FANG Kelervia | - | - | 3% | 24% | 50% | 23% | |
| 12 | ZEE Savannah | - | 1% | 6% | 24% | 42% | 28% | |
| 13 | KENSICKI Phoebe | - | 1% | 9% | 30% | 40% | 19% | |
| 14 | DENG Claire | 1% | 8% | 32% | 40% | 17% | 2% | |
| 15 | SOE Hayleigh | - | 2% | 14% | 35% | 36% | 13% | |
| 16 | LIM Kensie | - | 2% | 19% | 48% | 27% | 4% | |
| 17 | LIU Ariana | - | 1% | 9% | 30% | 41% | 19% | |
| 18 | WANG Doreen | - | - | 3% | 14% | 33% | 36% | 13% |
| 19 | HSIAO Ariya | - | 1% | 9% | 29% | 41% | 19% | 1% |
| 20 | OLSHANSKY Dalia | - | 3% | 15% | 32% | 32% | 15% | 3% |
| 21 | CHANG Olivia | - | 3% | 14% | 31% | 35% | 16% | 2% |
| 22 | DAI Iris Yuyang | - | - | 7% | 34% | 47% | 12% | |
| 23 | ZHOU Joi | - | 1% | 7% | 27% | 43% | 23% | |
| 24 | ZHANG Queeny | 1% | 9% | 28% | 37% | 21% | 4% | - |
| 25 | ZHAO Olivia | - | 3% | 14% | 30% | 34% | 17% | 2% |
| 26 | CHEN Madeleine | 2% | 20% | 40% | 29% | 9% | 1% | |
| 27 | HUGHES Olivia | 1% | 9% | 30% | 37% | 19% | 4% | |
| 28 | SAIFEE Zahra | - | 2% | 18% | 47% | 29% | 4% | |
| 29 | LIU Ashley | 1% | 8% | 27% | 38% | 22% | 5% | |
| 30 | WANG Yanxuan (Alicia) | - | - | 5% | 22% | 43% | 28% | 1% |
| 31 | LIM Kora | 18% | 42% | 29% | 9% | 1% | - | |
| 32 | LUCAS Ava | - | 8% | 29% | 39% | 20% | 4% | |
| 33 | XI Sophia | 1% | 9% | 30% | 38% | 19% | 3% | - |
| 34 | YUNG Zoe | 9% | 30% | 36% | 19% | 5% | 1% | - |
| 35 | ZHANG Hannah | 1% | 10% | 26% | 35% | 22% | 6% | - |
| 36 | MIYOSHI Kylie | 1% | 11% | 33% | 36% | 16% | 3% | |
| 37 | TENKAYALA Keertana | - | 1% | 10% | 33% | 43% | 14% | |
| 38 | BENNYHOFF Myla | 25% | 42% | 25% | 6% | 1% | - | |
| 39 | YUEN Kaitlyn | 12% | 48% | 32% | 7% | - | - | |
| 40 | SAIFEE Sakina | 2% | 12% | 29% | 33% | 19% | 5% | - |
| 41 | KIM Natalie | 1% | 7% | 22% | 35% | 26% | 8% | 1% |
| 42 | TU Averie | 18% | 37% | 30% | 12% | 2% | - | - |
| 43 | CHEN Yifan | 17% | 36% | 31% | 13% | 3% | - | - |
| 44 | BHANGOO Paloma | 41% | 42% | 15% | 2% | - | - | - |
| 45 | DESAI Zoya | 9% | 36% | 37% | 15% | 3% | - | |
| 46 | AHN Hayley | 8% | 43% | 40% | 9% | 1% | - | |
| 47 | KIM Phoebe | 66% | 31% | 3% | - | - | - | |
| 48 | YANG Grace | 3% | 17% | 37% | 31% | 11% | 1% | |
| 49 | DAM Sofi | 6% | 35% | 44% | 14% | 1% | - | |
| 50 | CHU Lauren | 3% | 24% | 40% | 25% | 7% | 1% | |
| 50 | VIERTEL Etta | 62% | 33% | 5% | - | - | - | |
| 52 | CHAMOUN Audrey | 3% | 19% | 39% | 29% | 9% | 1% | - |
| 53 | MCLANAHAN Jasmine | 5% | 21% | 36% | 27% | 10% | 1% | - |
| 54 | GOWDA Siyona | 11% | 36% | 36% | 15% | 2% | - | - |
| 55 | FAN Sophia | 1% | 9% | 26% | 34% | 23% | 7% | - |
| 56 | TANG Amelia | 4% | 19% | 33% | 29% | 12% | 2% | - |
| 57 | WANG Ellen | 26% | 44% | 24% | 6% | 1% | - | - |
| 58 | YU Xintong | 52% | 38% | 9% | 1% | - | - | |
| 59 | YATAVELLI Aria | 70% | 26% | 3% | - | - | - | |
| 60 | NICOLETTI Thea | 2% | 25% | 51% | 19% | 2% | - | |
| 61 | BUSCHKOETTER Gwen | 16% | 40% | 32% | 11% | 1% | - | |
| 61 | WANG Gabrielle | 36% | 45% | 17% | 3% | - | - | |
| 63 | DE JESUS Rachel | 1% | 19% | 39% | 30% | 10% | 1% | - |
| 63 | LEI Yifei Faye | 1% | 10% | 34% | 37% | 16% | 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.