Huntington Convention Center of Cleveland - 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 | JOO Sara | - | - | - | - | 5% | 31% | 63% |
| 2 | XING Melly | - | - | - | 1% | 9% | 36% | 55% |
| 3 | TAO Isabella | - | - | 1% | 11% | 42% | 45% | |
| 3 | MA Sophia | - | 4% | 17% | 36% | 33% | 10% | < 1% |
| 5 | CHAN Jolene | - | - | 1% | 6% | 22% | 41% | 31% |
| 6 | FRASER Morgan | - | - | - | 1% | 8% | 35% | 57% |
| 7 | SAIFEE Sakina | 2% | 12% | 30% | 34% | 19% | 4% | |
| 8 | KASHUBA Mila | 2% | 11% | 29% | 35% | 20% | 4% | |
| 9 | WANG Joann | - | 1% | 6% | 25% | 43% | 26% | |
| 10 | YANG Olivia | - | - | - | 6% | 33% | 61% | |
| 11 | CHEN Yinuo | - | - | 4% | 17% | 36% | 33% | 10% |
| 12 | ENRIQUEZ Bianca Perla | - | - | 5% | 25% | 48% | 21% | |
| 13 | ZHENG Annalyn | - | 1% | 8% | 26% | 40% | 24% | |
| 14 | ZHANG Selina | - | - | 2% | 12% | 39% | 47% | |
| 15 | CHENG Audrey | - | - | 3% | 14% | 31% | 35% | 16% |
| 16 | SMART Athena | - | 1% | 8% | 25% | 38% | 24% | 3% |
| 17 | ZHU Audrey | - | 1% | 8% | 30% | 42% | 19% | |
| 18 | KHANAL Sarah | 1% | 11% | 31% | 35% | 18% | 4% | - |
| 19 | ZHU Alivia | - | - | 1% | 9% | 28% | 41% | 21% |
| 20 | CHEN Summer | - | 5% | 18% | 32% | 29% | 13% | 2% |
| 21 | CULLIVAN Elise | 1% | 6% | 20% | 33% | 28% | 11% | 1% |
| 22 | WU Gloria | 2% | 12% | 30% | 35% | 18% | 3% | |
| 23 | TURBAT Celine | - | 5% | 24% | 42% | 25% | 3% | |
| 24 | LUO lucy | - | - | 1% | 7% | 25% | 42% | 26% |
| 25 | KHETPAL Aalia | - | 1% | 7% | 27% | 39% | 22% | 3% |
| 26 | LI Annabelle | - | 4% | 19% | 35% | 29% | 11% | 1% |
| 27 | KENT Audrey | 7% | 41% | 38% | 12% | 2% | - | - |
| 28 | CHAN Hailey | - | 1% | 9% | 28% | 38% | 21% | 3% |
| 29 | LIU Anya | - | - | 5% | 20% | 38% | 30% | 8% |
| 30 | KIM Lael | 2% | 13% | 29% | 33% | 19% | 5% | - |
| 31 | WANG Christina | - | 2% | 11% | 27% | 34% | 21% | 5% |
| 32 | SAVIOZ Naomi | 2% | 13% | 35% | 37% | 12% | 1% | |
| 33 | SHEN Gloria | - | - | - | 4% | 20% | 42% | 33% |
| 34 | BYK Karalina | - | - | - | - | 4% | 27% | 68% |
| 35 | QIAO Lori-Ann | - | 1% | 10% | 31% | 40% | 17% | |
| 36 | HUANG Emma | - | 1% | 9% | 28% | 38% | 21% | 3% |
| 37 | ELLISON Ingrid | 1% | 5% | 19% | 32% | 29% | 13% | 2% |
| 38 | KIM Ines | 3% | 18% | 39% | 30% | 10% | 1% | - |
| 39 | LIU Bella | 1% | 9% | 29% | 37% | 20% | 4% | - |
| 40 | ZHU Claire | 4% | 17% | 32% | 30% | 15% | 3% | - |
| 41 | MAHAPATRA Alisha | - | 3% | 16% | 35% | 33% | 12% | 1% |
| 41 | HUANG Jiayu | - | 1% | 7% | 24% | 37% | 25% | 6% |
| 43 | LIU Sophia | - | 1% | 10% | 33% | 40% | 16% | |
| 44 | JAZWINSKI Ivy | - | - | 2% | 12% | 32% | 38% | 16% |
| 45 | YOUN Davina | 2% | 15% | 33% | 32% | 15% | 3% | - |
| 46 | ZHANG Katie | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 47 | CHEN bridgette | - | 1% | 9% | 28% | 38% | 21% | 3% |
| 48 | DING Jessica | 1% | 10% | 31% | 36% | 18% | 4% | - |
| 49 | ARUNKISHORE Dakshina | - | 3% | 15% | 32% | 34% | 14% | 1% |
| 50 | MCCLAIN Madison | - | 4% | 16% | 34% | 32% | 13% | 2% |
| 51 | ZHAN Catherine | - | 3% | 19% | 42% | 31% | 5% | |
| 52 | FAN Lauren | 7% | 29% | 41% | 20% | 3% | - | |
| 53 | WELTER Gemma | 4% | 20% | 35% | 28% | 11% | 1% | |
| 54 | KIM Yuna | - | 2% | 12% | 35% | 38% | 14% | |
| 55 | FENG Christy | 17% | 41% | 32% | 9% | 1% | - | |
| 56 | LAM Dorris Yandor | 7% | 25% | 36% | 24% | 7% | 1% | |
| 57 | ARCE BASURCO Juliana | 10% | 35% | 37% | 16% | 3% | - | |
| 58 | VALOUEVA Katerina | 15% | 39% | 34% | 11% | 2% | - | |
| 59 | KO Adeline | 7% | 26% | 37% | 23% | 7% | 1% | |
| 60 | LIU Mia | 1% | 9% | 25% | 34% | 23% | 7% | 1% |
| 61 | WANG Sally | 1% | 7% | 25% | 36% | 23% | 6% | - |
| 62 | MCCLAIN Grayce | 1% | 8% | 27% | 39% | 22% | 4% | |
| 63 | HUANG Rosalyn | 5% | 21% | 34% | 27% | 11% | 2% | - |
| 64 | MA Laurie | 28% | 41% | 23% | 7% | 1% | - | - |
| 65 | HO Avery | 20% | 47% | 26% | 5% | - | - | |
| 66 | MARENITCH Kara | 4% | 22% | 39% | 27% | 8% | 1% | |
| 67 | KLIVANS Gwyneth | 15% | 40% | 32% | 11% | 2% | - | - |
| 68 | RUPARELIYA Alisha | 3% | 16% | 34% | 32% | 14% | 2% | |
| 69 | JU Victoria | - | 1% | 8% | 26% | 37% | 23% | 4% |
| 70 | LAI Olivia | 8% | 36% | 37% | 15% | 3% | - | - |
| 71 | ZHANG Annabelle | 4% | 17% | 32% | 30% | 14% | 3% | - |
| 72 | KAGAN Natalie | 8% | 30% | 36% | 20% | 5% | 1% | - |
| 73 | GOWDA Adisha | 1% | 7% | 26% | 37% | 23% | 6% | 1% |
| 74 | YULTCHIEVA Julia | 22% | 40% | 28% | 9% | 2% | - | - |
| 75 | CLOUD Chrystie | 2% | 14% | 30% | 32% | 18% | 4% | - |
| 76 | ZHANG Selene T. | 2% | 14% | 33% | 32% | 15% | 3% | - |
| 77 | LUO Olivia | 17% | 41% | 32% | 9% | 1% | - | |
| 78 | JIANG Ziqi | 17% | 40% | 32% | 10% | 1% | - | |
| 79 | KIM Rylie | 6% | 24% | 37% | 25% | 7% | 1% | |
| 80 | TANG Clementine | 25% | 44% | 25% | 6% | - | - | |
| 80 | HOLSTAD Anneliese | 14% | 35% | 34% | 15% | 3% | - | |
| 82 | LIM EDELINE | 2% | 16% | 39% | 33% | 10% | 1% | |
| 83 | SHI Cathy | 14% | 35% | 33% | 15% | 3% | - | |
| 84 | PEROJO Angie | 4% | 17% | 32% | 30% | 15% | 3% | - |
| 85 | CHEUNG Carabelle | 27% | 42% | 24% | 6% | 1% | - | - |
| 86 | MILLER Anna | 1% | 10% | 27% | 33% | 21% | 7% | 1% |
| 87 | MILLER Sydney | 23% | 43% | 26% | 7% | 1% | - | - |
| 88 | XU Selina (Tai Ran) | 5% | 23% | 35% | 25% | 9% | 2% | - |
| 89 | TIAN Grace | - | 5% | 26% | 38% | 23% | 6% | 1% |
| 90 | LEE Isabella | 11% | 31% | 34% | 18% | 5% | 1% | - |
| 91 | ZMUDA Jordan | 37% | 44% | 17% | 3% | - | - | - |
| 92 | SUN YOUXI | < 1% | 2% | 16% | 36% | 32% | 12% | 2% |
| 93 | WANG Kelly | 3% | 16% | 33% | 31% | 14% | 2% | - |
| 94 | LUAN Senya | 39% | 44% | 15% | 2% | - | - | |
| 95 | HOO Bethia | 24% | 43% | 26% | 7% | 1% | - | - |
| 96 | KANASZ Peyton | 16% | 42% | 31% | 10% | 1% | - | - |
| 97 | KIM Lisel | 38% | 43% | 16% | 3% | - | - | |
| 98 | PATEL Tiana | 56% | 36% | 8% | 1% | - | - | - |
| 99 | MAYES-POURNARAS Zara | 54% | 36% | 9% | 1% | - | - | - |
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.