National Harbor, MD - National Harbor, 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 | GORMAN Victoria M. | - | - | 2% | 9% | 26% | 40% | 24% |
| 2 | SHOMAN Jenna | - | - | - | - | 6% | 35% | 59% |
| 3 | WIGGERS Susan Q. | - | - | - | 1% | 10% | 39% | 50% |
| 3 | ANDRES Charmaine G. | - | 1% | 8% | 30% | 41% | 20% | |
| 5 | CHIOLDI Mina | - | - | - | 3% | 16% | 41% | 41% |
| 6 | ANDRES Katherine A. | - | - | - | 2% | 12% | 38% | 48% |
| 7 | HILD Nisha | - | - | 3% | 15% | 34% | 35% | 14% |
| 8 | LU Amy | - | 1% | 6% | 22% | 37% | 28% | 7% |
| 9 | ANTHONY Alexia B. | - | 3% | 15% | 33% | 32% | 14% | 2% |
| 10 | PRIEUR Lauren | - | - | 1% | 10% | 29% | 40% | 20% |
| 11 | ROMAGNOLI Isabella | - | - | - | 3% | 17% | 41% | 37% |
| 12 | BEVACQUA Aria F. | - | - | 4% | 18% | 36% | 32% | 10% |
| 13 | SOURIMTO Valeria | - | - | 3% | 14% | 35% | 38% | 11% |
| 14 | RIZKALA Joanna | - | - | 3% | 15% | 34% | 35% | 13% |
| 15 | LIGH Erenei J. | 1% | 9% | 27% | 36% | 21% | 6% | 1% |
| 16 | JOHNSON Dagny L. | - | 4% | 19% | 35% | 29% | 11% | 2% |
| 17 | BLUM Leah I. | - | - | - | - | 4% | 28% | 67% |
| 18 | CHEN Xiaohan | - | - | 2% | 15% | 37% | 36% | 10% |
| 19 | KIM Marley I. | - | 1% | 6% | 23% | 37% | 27% | 7% |
| 20 | SHI Cathleen | - | 1% | 8% | 27% | 40% | 22% | 2% |
| 21 | BALAKUMARAN Maya | - | 2% | 9% | 24% | 35% | 25% | 6% |
| 22 | FAN Grace | 2% | 18% | 37% | 30% | 11% | 2% | - |
| 23 | YANG Ashley M. | - | - | 3% | 13% | 32% | 36% | 16% |
| 24 | TODD Phoebe | 1% | 10% | 25% | 33% | 23% | 8% | 1% |
| 25 | GRINBERG Aliya | - | 4% | 19% | 35% | 30% | 11% | 1% |
| 26 | LEE Hannah | - | 1% | 9% | 26% | 36% | 23% | 5% |
| 27 | LEMUS-IAKOVIDOU ALEXANDRA | - | 10% | 30% | 35% | 19% | 5% | - |
| 28 | CHIANG Emily | - | 4% | 24% | 40% | 26% | 6% | |
| 29 | KER Grace | - | 1% | 8% | 28% | 42% | 20% | |
| 30 | XU ALINA | 19% | 50% | 26% | 5% | - | - | |
| 31 | DAI TONGXI | - | - | 3% | 15% | 33% | 35% | 13% |
| 32 | WANG Jianning | 3% | 16% | 34% | 32% | 12% | 2% | |
| 33 | WEI Vivian W. | 1% | 7% | 26% | 36% | 23% | 7% | 1% |
| 34 | SUBRAMANIAN Nitika | - | - | - | 9% | 39% | 43% | 10% |
| 35 | OGANEZOVA Valerie | 9% | 30% | 37% | 19% | 4% | - | |
| 36 | DUCKETT Madison | - | 1% | 8% | 27% | 42% | 23% | |
| 37 | CHEN Xinyan | - | - | 1% | 14% | 45% | 35% | 6% |
| 37 | YUAN Greta | - | 1% | 7% | 22% | 37% | 27% | 6% |
| 39 | LIAO Siwen | - | 3% | 15% | 32% | 32% | 15% | 2% |
| 40 | LU Elaine | - | 1% | 6% | 25% | 39% | 24% | 5% |
| 41 | JEONG Katie | - | 3% | 16% | 35% | 32% | 12% | 1% |
| 42 | JENKINS Scotland | 10% | 30% | 35% | 19% | 5% | 1% | - |
| 43 | PENG Florella | - | 1% | 6% | 23% | 40% | 27% | 3% |
| 44 | PAUL Lila | - | - | - | 4% | 19% | 42% | 35% |
| 45 | NAYAK Indra | - | 11% | 31% | 35% | 18% | 4% | - |
| 46 | DAVIS Jordan | - | 1% | 12% | 50% | 30% | 6% | - |
| 47 | CHEN Ashley | - | 1% | 8% | 25% | 37% | 24% | 6% |
| 48 | MCKEE Ainsley | - | 5% | 24% | 39% | 25% | 7% | 1% |
| 49 | SO Catelyn | - | 5% | 21% | 36% | 27% | 9% | 1% |
| 50 | LIU Sophie | 4% | 19% | 32% | 28% | 13% | 3% | - |
| 51 | ZENG Megan | 47% | 40% | 11% | 1% | - | - | - |
| 52 | WU Helen | - | 3% | 16% | 34% | 32% | 13% | 2% |
| 53 | FESTA Carina | - | 7% | 31% | 38% | 19% | 4% | - |
| 54 | NYSTROM Sofia C. | - | - | 4% | 20% | 37% | 30% | 8% |
| 55 | SAHNI Sophia | 18% | 38% | 30% | 11% | 2% | - | - |
| 56 | JAVERI Amaya | 3% | 16% | 35% | 31% | 13% | 2% | - |
| 57 | MIKA Veronica | - | - | 1% | 10% | 31% | 41% | 17% |
| 57 | NATH Trisha | - | 2% | 12% | 33% | 35% | 16% | 3% |
| 59 | CRUZ Sonia | 33% | 44% | 20% | 4% | - | - | - |
| 60 | XU Emily T. | 1% | 9% | 29% | 37% | 20% | 4% | - |
| 61 | TSUI Natalie | - | 5% | 25% | 39% | 25% | 6% | |
| 62 | WU Yuwei | 13% | 40% | 33% | 12% | 2% | - | - |
| 63 | NG Sarah W. | 6% | 23% | 34% | 25% | 10% | 2% | - |
| 64 | STRAYER Sofia I. | 54% | 39% | 7% | 1% | - | - | |
| 65 | DAMDINSUREN Sophie | 30% | 45% | 20% | 4% | < 1% | - | - |
| 66 | VADASZ Ibla P. | - | 1% | 12% | 35% | 38% | 14% | |
| 67 | CRISAFULLI Alessia | 11% | 42% | 42% | 5% | - | - | - |
| 68 | MU Vicki Y. | 2% | 11% | 28% | 34% | 20% | 5% | - |
| 69 | FEIG Sela | - | 5% | 18% | 33% | 30% | 12% | 2% |
| 70 | ILYIN Anna | 17% | 38% | 32% | 12% | 2% | - | |
| 71 | MONTORIO Lily M. | 6% | 25% | 37% | 24% | 7% | 1% | - |
| 72 | HALL Gianna | 29% | 47% | 20% | 3% | - | - | - |
| 73 | JOHNSON Lydia | - | 5% | 22% | 37% | 27% | 7% | 1% |
| 74 | YOUNG Audrey | 5% | 21% | 33% | 27% | 11% | 2% | - |
| 75 | LOPEZ-ONA Mia | 1% | 13% | 33% | 34% | 15% | 3% | - |
| 76 | NAYAK Anika | 6% | 26% | 37% | 23% | 7% | 1% | - |
| 77 | OBRADOVIC Ana | - | 2% | 11% | 29% | 35% | 19% | 4% |
| 78 | DAI Olivia | 18% | 50% | 26% | 5% | - | - | - |
| 79 | DENG Brooke | 1% | 10% | 33% | 36% | 17% | 4% | - |
| 80 | SHPILSKY Maya | 4% | 20% | 37% | 29% | 9% | 1% | - |
| 81 | DUBE Naomi | 67% | 28% | 4% | - | - | - | - |
| 82 | CHEN Kevy | 9% | 29% | 35% | 20% | 6% | 1% | - |
| 83 | YANG Lea | - | 9% | 28% | 36% | 21% | 6% | - |
| 84 | ZHAO Emily W. | 1% | 11% | 33% | 35% | 16% | 3% | - |
| 84 | WUNNAVA Elina | 18% | 42% | 30% | 9% | 1% | - | - |
| 86 | FEO ZAKHAROVA Isabella | 47% | 43% | 10% | 1% | - | - | - |
| 87 | XIAO julie | 3% | 14% | 30% | 31% | 17% | 5% | - |
| 88 | SCOTT Eve | 23% | 49% | 24% | 5% | - | - | - |
| 89 | BRIATORE Francesca | 20% | 50% | 26% | 4% | - | - | - |
| 90 | DANTULURI Shivani | 20% | 40% | 29% | 10% | 1% | - | - |
| 91 | HENRY Soraya S. | 8% | 29% | 37% | 20% | 5% | - | |
| 92 | ZHOU Ruoxi ( Jasmine) | 6% | 25% | 35% | 24% | 8% | 1% | - |
| 93 | COLBY Mercer | 46% | 40% | 12% | 2% | - | - | - |
| 94 | COLLINS Margaret L. | 37% | 46% | 16% | 1% | - | - | - |
| 95 | HONG Hannah | 83% | 16% | 1% | - | - | - | - |
| 96 | WU Selina | 11% | 35% | 37% | 14% | 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.