Rio Hotel and Casino - Las Vegas, NV, 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 | FRASER Morgan | - | - | - | - | 1% | 12% | 88% |
| 2 | CHENG Audrey | - | - | 1% | 6% | 22% | 41% | 30% |
| 3 | YOUN Davina | - | 6% | 24% | 40% | 26% | 4% | |
| 3 | ENRIQUEZ Bianca Perla | - | - | - | 2% | 14% | 40% | 44% |
| 5 | YANG Olivia | - | - | - | 1% | 7% | 34% | 59% |
| 6 | SHEN Gloria | - | - | 1% | 10% | 37% | 52% | |
| 7 | LIU Mia | - | 3% | 19% | 41% | 30% | 7% | |
| 8 | NAKAZATO Isabella | - | 1% | 7% | 22% | 34% | 27% | 8% |
| 9 | SAIFEE Sakina | - | 1% | 5% | 19% | 34% | 31% | 11% |
| 10 | LIU Anya | - | - | 3% | 19% | 46% | 32% | |
| 11 | SMIRNOV Victoria | - | 5% | 21% | 39% | 29% | 6% | |
| 12 | ARUNKISHORE Dakshina | - | - | 5% | 24% | 46% | 25% | |
| 13 | KIM Ines | 1% | 8% | 24% | 33% | 24% | 8% | 1% |
| 14 | TURBAT Celine | - | 1% | 6% | 21% | 37% | 29% | 7% |
| 15 | MCCLAIN Madison | - | 1% | 11% | 34% | 40% | 14% | |
| 16 | SHI Cathy | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
| 17 | ZHU Alivia | - | - | 1% | 7% | 34% | 59% | |
| 18 | CHEN Summer | - | - | 3% | 19% | 44% | 33% | |
| 19 | MAHAPATRA Alisha | - | 3% | 16% | 35% | 34% | 12% | |
| 20 | LAM Dorris Yandor | 1% | 6% | 20% | 33% | 27% | 11% | 2% |
| 21 | ELLISON Ingrid | - | - | 2% | 12% | 34% | 41% | 10% |
| 22 | ZHANG Annabelle | - | 2% | 12% | 30% | 37% | 18% | 1% |
| 23 | KHANAL Sarah | - | 7% | 26% | 38% | 24% | 5% | |
| 24 | FAN Lauren | 1% | 10% | 27% | 35% | 21% | 5% | - |
| 25 | MCCLAIN Grayce | 1% | 6% | 20% | 33% | 28% | 12% | 2% |
| 26 | LI Annabelle | - | 3% | 15% | 35% | 34% | 12% | |
| 27 | ZHU Claire | 1% | 12% | 34% | 37% | 14% | 2% | |
| 28 | VALOUEVA Katerina | 2% | 17% | 41% | 30% | 9% | 1% | |
| 29 | CLOUD Chrystie | 2% | 13% | 33% | 35% | 15% | 2% | |
| 30 | SHU Kayla | 2% | 15% | 32% | 33% | 15% | 3% | - |
| 31 | ZEE Bella | 5% | 26% | 39% | 24% | 6% | - | |
| 32 | TAGNE Zoey | 23% | 41% | 27% | 8% | 1% | - | |
| 33 | KO Adeline | 1% | 10% | 31% | 38% | 17% | 2% | |
| 34 | ZHANG Katie | 1% | 11% | 28% | 34% | 20% | 5% | - |
| 35 | JONES Parker | - | 4% | 16% | 31% | 31% | 15% | 3% |
| 36 | SUN Leia | 17% | 36% | 31% | 13% | 3% | - | - |
| 37 | LUO Olivia | 3% | 21% | 39% | 29% | 8% | 1% | |
| 38 | LIN Clara | - | 5% | 23% | 38% | 27% | 7% | |
| 39 | ZHOU athena | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 40 | CHEN Chloe | 9% | 31% | 36% | 19% | 5% | - | - |
| 41 | KIM Rylie | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 42 | KENT Audrey | - | 4% | 17% | 34% | 33% | 12% | - |
| 43 | LAI Olivia | 7% | 26% | 36% | 24% | 7% | 1% | - |
| 44 | FU Angela | 12% | 38% | 35% | 12% | 2% | - | |
| 45 | CAO Alexandra | 8% | 29% | 38% | 21% | 5% | - | |
| 46 | SUN April | 3% | 18% | 34% | 30% | 12% | 2% | - |
| 47 | TEOH Kaylee | 20% | 39% | 29% | 10% | 2% | - | - |
| 48 | LIN Tiffany | 7% | 28% | 38% | 22% | 5% | - | |
| 49 | TELEB Amina | 20% | 48% | 26% | 5% | - | - | |
| 50 | ARCE BASURCO Juliana | 4% | 22% | 40% | 27% | 6% | 1% | |
| 51 | TANG Clementine | 8% | 36% | 37% | 16% | 3% | - | |
| 52 | SUN Zoey | 37% | 43% | 17% | 3% | - | - | |
| 53 | GAMBREL Holland | 43% | 43% | 13% | 1% | - | - | |
| 54 | XIA Emily | 4% | 20% | 35% | 29% | 11% | 1% | - |
| 55 | CLOUD Cailynn | 8% | 27% | 36% | 22% | 7% | 1% | - |
| 56 | JIANG Mujing | 11% | 33% | 34% | 17% | 5% | 1% | - |
| 57 | DING Jessica | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
| 58 | FONG Isabel | 23% | 40% | 27% | 9% | 2% | - | - |
| 59 | ZHAI Muyan | 1% | 5% | 19% | 33% | 29% | 12% | 2% |
| 60 | TUNG Alison | 4% | 18% | 34% | 30% | 13% | 2% | - |
| 61 | HO Avery | 18% | 37% | 30% | 12% | 3% | - | - |
| 62 | JOE Everly | 17% | 37% | 31% | 12% | 2% | - | - |
| 63 | CHOI Mackenzie | 56% | 36% | 8% | 1% | - | - | |
| 64 | DONG Ena | 50% | 38% | 11% | 1% | - | - | |
| 65 | KIM Olivia | 2% | 11% | 29% | 35% | 19% | 4% | - |
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.