Cleveland, OH - Cleveland, OH, 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 | PEVZNER Victoria | - | - | - | 2% | 15% | 42% | 40% |
| 2 | JING Emily | - | - | - | 3% | 15% | 40% | 42% |
| 3 | GEBALA Gabrielle Grace A. | - | - | - | 1% | 11% | 40% | 48% |
| 3 | SHEN Lydia | - | 4% | 15% | 30% | 31% | 16% | 3% |
| 5 | CHEN Jia P. | - | - | - | 4% | 18% | 41% | 37% |
| 6 | GUERRA Sofia E. | - | - | 3% | 16% | 41% | 39% | |
| 7 | WONG Sophia M. | - | - | 2% | 13% | 35% | 36% | 13% |
| 8 | LUNG Katerina | - | - | 1% | 7% | 25% | 42% | 26% |
| 9 | ZHANG Alina C. | - | - | - | 4% | 22% | 47% | 28% |
| 10 | SOOD Ishani S. | - | - | - | 3% | 17% | 44% | 36% |
| 11 | PANT Anisha | - | - | - | 3% | 18% | 47% | 32% |
| 12 | HAMZA Malak | - | 1% | 5% | 17% | 33% | 32% | 12% |
| 13 | CHO Rebecca H. | - | 2% | 12% | 30% | 35% | 18% | 3% |
| 14 | LEE Bethanie | - | 1% | 4% | 16% | 32% | 33% | 14% |
| 15 | CHUSID Mikayla | - | 1% | 8% | 23% | 35% | 26% | 7% |
| 16 | CANNON Lira J. | 7% | 26% | 36% | 23% | 6% | 1% | |
| 17 | KOSTELNY Alexis | - | - | 1% | 9% | 32% | 43% | 15% |
| 18 | ZHAO Sophie L. | - | - | 3% | 16% | 34% | 34% | 12% |
| 19 | DAVIS Bonnie Z. | - | 1% | 6% | 23% | 37% | 26% | 6% |
| 20 | YEN Natalie | - | - | 1% | 9% | 29% | 43% | 18% |
| 21 | LI Rachel Y. | - | 4% | 16% | 31% | 31% | 15% | 3% |
| 22 | TAKAMIZAWA Yukari | - | - | - | 2% | 15% | 42% | 40% |
| 23 | SUN Chien-Yu | 1% | 7% | 23% | 37% | 26% | 6% | |
| 24 | KOSLOW Amicie | - | 4% | 19% | 40% | 29% | 8% | 1% |
| 24 | CHEN Allison V. | - | - | 2% | 12% | 33% | 38% | 15% |
| 26 | NIKOLIC Alexandra | - | 1% | 7% | 27% | 43% | 20% | 3% |
| 27 | TAN Kaitlyn N. | - | - | 2% | 15% | 38% | 36% | 9% |
| 28 | WANDJI Anais | - | 1% | 6% | 20% | 34% | 29% | 10% |
| 29 | NAMGALAURI Mariam | - | - | 3% | 16% | 36% | 35% | 10% |
| 30 | SEO IRENE Y. | - | 1% | 6% | 25% | 40% | 24% | 4% |
| 31 | ROY Layla | 2% | 14% | 33% | 34% | 14% | 2% | - |
| 32 | WANG Chloe | 2% | 16% | 34% | 31% | 14% | 3% | - |
| 33 | BATRA Chaahat | - | 2% | 11% | 29% | 35% | 19% | 3% |
| 34 | SENIC Adeline | - | - | 3% | 13% | 32% | 36% | 15% |
| 35 | CHUNG Jaein | - | 1% | 7% | 25% | 40% | 24% | 4% |
| 36 | TANG AI JIA | 2% | 13% | 31% | 33% | 17% | 4% | - |
| 37 | HWANG Jungmin | - | 4% | 20% | 37% | 28% | 9% | 1% |
| 38 | ZHAO Aileen Y. | 1% | 6% | 20% | 33% | 27% | 11% | 2% |
| 39 | LEE Lavender | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
| 40 | CHANG Elizabeth | - | 2% | 11% | 27% | 34% | 21% | 5% |
| 41 | EYER Hailey M. | - | 1% | 10% | 29% | 39% | 19% | 3% |
| 42 | TOM Caitlyn | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
| 43 | SU Alena J. | - | 2% | 11% | 28% | 35% | 20% | 4% |
| 44 | HU Felice | - | 1% | 7% | 23% | 35% | 26% | 8% |
| 45 | WU Celine | 2% | 13% | 32% | 33% | 16% | 4% | - |
| 46 | YU Nicole J. | 2% | 16% | 36% | 33% | 12% | 2% | - |
| 47 | SIMONOV Dasha | - | 1% | 9% | 26% | 36% | 22% | 4% |
| 48 | TUCKER ALARCON Frida | 6% | 23% | 34% | 25% | 10% | 2% | - |
| 49 | ORVANANOS Anice | - | 4% | 17% | 35% | 31% | 12% | 2% |
| 50 | VAUGHAN Norah | 9% | 33% | 36% | 17% | 4% | - | - |
| 51 | RANDOLPH Piper | - | 1% | 8% | 22% | 34% | 26% | 8% |
| 52 | LEE Samantha X. | 2% | 19% | 37% | 29% | 10% | 1% | - |
| 53 | LIN Victoria T. | 2% | 20% | 37% | 29% | 10% | 2% | - |
| 54 | SHINKAREV Olga | - | 3% | 14% | 29% | 32% | 17% | 4% |
| 55 | LIN Zhi tong | - | 4% | 17% | 33% | 31% | 13% | 2% |
| 56 | SOLDATOVA Maria | 2% | 14% | 34% | 33% | 14% | 2% | - |
| 57 | WANG Yudi | 24% | 42% | 26% | 7% | 1% | - | - |
| 58 | COOPER Piper W. | 16% | 38% | 32% | 12% | 2% | - | - |
| 59 | CHIRASHNYA Mika | 8% | 28% | 35% | 21% | 7% | 1% | - |
| 60 | KAPUSTINA Arina | 7% | 27% | 37% | 22% | 6% | 1% | - |
| 61 | LIU Angel(Daying) | - | - | 3% | 15% | 35% | 35% | 12% |
| 62 | GAMRADT Taylor | 11% | 32% | 35% | 18% | 4% | - | |
| 63 | LIU Jaelyn A. | 1% | 9% | 27% | 36% | 22% | 6% | - |
| 64 | KULKARNI Sohah A. | 2% | 11% | 27% | 33% | 21% | 7% | 1% |
| 65 | UPTON Sydney | 2% | 10% | 26% | 33% | 22% | 7% | 1% |
| 66 | NAIR Supriya | 4% | 19% | 35% | 29% | 11% | 1% | |
| 67 | ZHUANG Christina | 1% | 7% | 21% | 33% | 26% | 11% | 2% |
| 68 | NOVIKOV Allegra | 10% | 35% | 38% | 15% | 2% | - | - |
| 69 | MI Aileen | 10% | 31% | 36% | 18% | 5% | 1% | - |
| 70 | SHMAY Anastasia | 9% | 31% | 37% | 19% | 4% | - | - |
| 71 | SHORI Samantha | 3% | 20% | 39% | 29% | 8% | 1% | - |
| 72 | TAYLOR-CASAMAYOR Marisol | 37% | 44% | 17% | 2% | - | - | - |
| 73 | ZHUANG Sophie | 7% | 28% | 38% | 21% | 5% | - | - |
| 74 | ZHENG Julie | 1% | 5% | 21% | 35% | 27% | 10% | 1% |
| 75 | CUI Amy | 2% | 16% | 33% | 31% | 14% | 3% | - |
| 76 | TRACZ Calleigh D. | 48% | 41% | 10% | 1% | - | - | - |
| 76 | LI Sophia M. | - | 6% | 22% | 37% | 27% | 8% | 1% |
| 78 | SHA Yi Ling | 13% | 32% | 33% | 17% | 5% | 1% | - |
| 78 | BAWA Sahana | 12% | 33% | 34% | 17% | 4% | 1% | - |
| 80 | BASSIK Eva | 11% | 35% | 35% | 15% | 3% | - | - |
| 81 | SKOURLETOS Maria | 29% | 45% | 22% | 4% | - | - | - |
| 82 | HAN Ashley | 5% | 27% | 39% | 22% | 6% | 1% | - |
| 82 | THOMAS Saejel | 72% | 25% | 3% | - | - | - | - |
| 84 | LI Irina | 31% | 42% | 21% | 5% | 1% | - | - |
| 85 | POPOKH Aleksandra | 8% | 26% | 34% | 22% | 8% | 1% | - |
| 86 | CHEN Chloe I. | - | 7% | 26% | 36% | 23% | 6% | 1% |
| 87 | MANIKTALA Prisha | 12% | 33% | 34% | 17% | 4% | 1% | - |
| 88 | WANG Jasmine | 8% | 28% | 36% | 21% | 5% | - | |
| 89 | HAN Crystal | 2% | 12% | 32% | 35% | 16% | 3% | - |
| 90 | LUH Mia P. | 12% | 35% | 35% | 15% | 3% | - | - |
| 90 | TSANG Catherine | 21% | 39% | 28% | 10% | 2% | - | - |
| 92 | DESOLA Lyla | 21% | 41% | 29% | 9% | 1% | - | - |
| 93 | SHIM Grace | 46% | 40% | 12% | 2% | - | - | - |
| 94 | ZHENG Zoe | 3% | 24% | 42% | 24% | 6% | 1% | - |
| 96 | DESOLA Lucy | 15% | 38% | 34% | 12% | 2% | - | - |
| 97 | STEINHOBEL Jade | 9% | 34% | 38% | 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.