Meadowlands Expo Center - Secaucus, NJ, 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 | YIN Julia | - | - | - | - | - | 10% | 89% |
| 2 | RAKHOVSKI Alexandra | - | - | - | - | 2% | 20% | 78% |
| 3 | PRESMAN Aerin | - | - | 3% | 19% | 45% | 33% | |
| 3 | SONG Angela | - | - | - | - | 4% | 31% | 65% |
| 5 | LEE Scarlett | - | - | - | - | 4% | 29% | 67% |
| 6 | SOBUS Yanka | - | 1% | 5% | 19% | 36% | 30% | 9% |
| 7 | KUMAR Anusha | - | - | 5% | 23% | 45% | 27% | |
| 8 | QI Jarynne Valerie | - | - | 1% | 5% | 22% | 43% | 29% |
| 9 | LEE Claire | - | - | 1% | 12% | 41% | 46% | |
| 10 | ZHU Serene M. | - | - | - | 3% | 19% | 50% | 29% |
| 11 | CHISHOLM Phoebe C. | - | - | 1% | 6% | 34% | 59% | |
| 12 | SMUK Alexandra S. | - | - | - | 1% | 6% | 31% | 63% |
| 13 | CAFASSO Natalya | - | - | - | 1% | 7% | 34% | 58% |
| 14 | MEYER Rachel | 1% | 10% | 26% | 34% | 22% | 7% | 1% |
| 15 | AZMEH nour | - | - | 1% | 10% | 38% | 51% | |
| 16 | LUO Amy | - | - | 2% | 11% | 33% | 40% | 14% |
| 17 | NOVOJILOV Anastasia | - | 1% | 9% | 29% | 39% | 19% | 3% |
| 18 | GANSER Nicole | - | - | 4% | 25% | 46% | 22% | 2% |
| 19 | TANG RUIRUI | - | - | 3% | 17% | 40% | 34% | 6% |
| 20 | SUN Zeyu | - | 2% | 14% | 36% | 39% | 9% | |
| 21 | STERN Savannah | 25% | 42% | 26% | 7% | 1% | - | |
| 22 | BO GENESIS | 1% | 8% | 26% | 36% | 22% | 6% | - |
| 23 | LEE Gloria | - | - | 1% | 9% | 35% | 46% | 10% |
| 23 | QI Julieanne | - | 1% | 6% | 25% | 42% | 24% | 3% |
| 25 | FRANGER Macy | - | 5% | 17% | 33% | 30% | 13% | 2% |
| 26 | WANG Trinity | - | 1% | 7% | 23% | 38% | 27% | 5% |
| 27 | TAM Connie | 1% | 7% | 22% | 34% | 27% | 9% | 1% |
| 28 | SU Evelyn | - | - | - | 3% | 16% | 43% | 39% |
| 29 | BAWA Jenya | 1% | 7% | 26% | 38% | 23% | 5% | - |
| 29 | MA Sophie | 1% | 8% | 23% | 34% | 26% | 8% | 1% |
| 31 | RICHARDSON Meredith | - | - | 5% | 24% | 45% | 25% | |
| 32 | KAUR Manroop | < 1% | 2% | 13% | 32% | 35% | 16% | 2% |
| 33 | KUMAR Eva | - | - | - | 4% | 18% | 41% | 36% |
| 34 | ZHANG Mingmeng | - | - | 3% | 14% | 32% | 35% | 15% |
| 35 | SHAYAKHMETOVA Suzanna | 1% | 8% | 25% | 35% | 24% | 7% | - |
| 36 | ILYAS Ayah | 11% | 34% | 35% | 16% | 3% | - | - |
| 37 | KANG Yenna | 9% | 31% | 36% | 19% | 5% | 1% | - |
| 38 | JIANG Serena | 1% | 6% | 24% | 39% | 25% | 5% | |
| 39 | LIN Laura | 1% | 9% | 35% | 39% | 14% | 1% | |
| 40 | IYER Ishana | - | 1% | 9% | 32% | 44% | 15% | |
| 41 | NGUYEN Ashley L. | - | 1% | 6% | 26% | 45% | 22% | |
| 42 | WANG Ziqiao | 1% | 10% | 30% | 36% | 18% | 4% | - |
| 43 | KANG kailin | 2% | 14% | 30% | 33% | 17% | 4% | - |
| 44 | AGAON Evelyn | - | 2% | 9% | 25% | 36% | 23% | 5% |
| 45 | LI Caroline | 7% | 28% | 37% | 22% | 6% | 1% | - |
| 46 | STEMPKOVSKA Dina | 4% | 21% | 38% | 28% | 9% | 1% | - |
| 47 | YU Eva | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
| 48 | KOVALCHUK Erika S. | - | 1% | 8% | 25% | 37% | 24% | 5% |
| 49 | FANG Jocelyn | 2% | 16% | 38% | 33% | 11% | 1% | |
| 50 | WANG Sophie Y. | 1% | 10% | 36% | 38% | 14% | 1% | |
| 51 | MISHIMA Audrey | 1% | 9% | 30% | 38% | 19% | 3% | |
| 52 | KROPP Anne | 2% | 15% | 37% | 34% | 11% | 1% | |
| 53 | BEATIE Isabella M. | - | 4% | 18% | 34% | 30% | 11% | 1% |
| 54 | FANG Kayla | 1% | 11% | 31% | 37% | 17% | 3% | - |
| 55 | CHEN Alina | 4% | 25% | 39% | 25% | 6% | 1% | - |
| 56 | JUN Bomie | - | 2% | 11% | 30% | 37% | 19% | 1% |
| 57 | CASHMAN Amanda | 5% | 23% | 37% | 26% | 8% | 1% | - |
| 58 | JEYOON Lauren | 8% | 30% | 38% | 19% | 4% | - | - |
| 59 | LIU Charlotte | 2% | 14% | 33% | 33% | 15% | 3% | - |
| 60 | JI Catherine | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 61 | WORKNEH Lulit | 6% | 27% | 39% | 23% | 5% | - | |
| 62 | SUICO Kyubi Emmanuelle | 4% | 21% | 38% | 28% | 8% | 1% | |
| 63 | FENG Iris | 3% | 17% | 36% | 32% | 11% | 1% | |
| 64 | WRIGHT Madison | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 65 | FLITMAN Gabrielle | 1% | 9% | 27% | 36% | 22% | 5% | - |
| 66 | SHETH Anayaà | 8% | 31% | 39% | 19% | 3% | - | |
| 67 | PAN Angela | 1% | 7% | 22% | 34% | 27% | 9% | - |
| 68 | BI Michelle | 3% | 18% | 35% | 30% | 12% | 2% | - |
| 69 | WU Madisen | 4% | 18% | 33% | 29% | 13% | 2% | - |
| 70 | DESANTIS-IBANEZ Elena | - | 4% | 23% | 44% | 24% | 4% | - |
| 71 | FOUX Abigail | 7% | 32% | 39% | 18% | 3% | - | |
| 72 | BISONO Valentina | 12% | 37% | 36% | 13% | 2% | - | |
| 73 | PANG Ashley | 1% | 8% | 29% | 40% | 19% | 3% | |
| 74 | WANG Cecilia | 8% | 30% | 38% | 20% | 4% | - | |
| 75 | YANG Emily | 10% | 47% | 34% | 9% | 1% | - | |
| 76 | SUREKA Krisha | 24% | 42% | 26% | 7% | 1% | - | |
| 77 | HOAGLAND Sally | 9% | 28% | 35% | 21% | 7% | 1% | - |
| 78 | LOBANOVA Varvara | 8% | 30% | 36% | 20% | 5% | 1% | - |
| 79 | WEI Sherry | 1% | 7% | 23% | 36% | 26% | 7% | - |
| 80 | MURPHY Katherine | 5% | 23% | 36% | 26% | 9% | 1% | - |
| 81 | FANG jenna kim | 3% | 23% | 45% | 24% | 4% | - | - |
| 82 | MEYER Rebecca | - | 5% | 18% | 34% | 30% | 12% | 1% |
| 83 | HU Chloe | 25% | 41% | 25% | 8% | 1% | - | - |
| 84 | KUPPUSAMY Mahaa | 50% | 38% | 11% | 1% | - | - | - |
| 85 | BINDAS Sigrid | 25% | 43% | 25% | 6% | 1% | - | - |
| 86 | ZHENG Erin | 15% | 41% | 32% | 10% | 1% | - | |
| 87 | LI Xiang (Shining) | 53% | 37% | 9% | 1% | - | - | |
| 88 | KRISHNA Rithika | 26% | 40% | 25% | 8% | 1% | - | - |
| 89 | DUDAKA Chaithra | 36% | 42% | 18% | 4% | - | - | - |
| 90 | CHUANG Ramona | 1% | 9% | 27% | 35% | 22% | 6% | 1% |
| 91 | MELLEBY Georgia | 18% | 47% | 29% | 6% | - | - | - |
| 92 | LY Hannah | 2% | 14% | 32% | 32% | 16% | 3% | - |
| 93 | LEE Claudia | 15% | 34% | 32% | 15% | 4% | - | - |
| 94 | WU Michelle | 4% | 23% | 39% | 26% | 7% | 1% | - |
| 95 | ZHONG Isabell | 32% | 44% | 20% | 4% | - | - | |
| 96 | DU Siqi | 48% | 42% | 9% | 1% | - | - | - |
| 97 | GAAFAR Jana | 24% | 42% | 26% | 7% | 1% | - | - |
| 98 | LI Nicole | 11% | 35% | 37% | 15% | 2% | - | - |
| 99 | ABRAGAN Isabel Grace | 64% | 31% | 5% | - | - | - | |
| 100 | DU Andria | 25% | 41% | 25% | 7% | 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.