Ontario Convention Center - Hall A&B - Ontario, CA, 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 | JIANG Evelyn | - | 1% | 10% | 31% | 40% | 19% | |
| 2 | SCHMIDT Isabel | - | - | - | - | 3% | 23% | 73% |
| 3 | TONG Laurie | 1% | 5% | 19% | 33% | 29% | 12% | 2% |
| 3 | SUNG Olivia | - | 4% | 19% | 38% | 31% | 9% | |
| 5 | KANG Ellie | - | - | 1% | 11% | 38% | 50% | |
| 6 | HWANG Charlotte | 4% | 24% | 40% | 25% | 6% | 1% | |
| 7 | GAIKWAD Ashmiee | - | - | 3% | 15% | 34% | 35% | 12% |
| 8 | LIU Hannah | - | 4% | 19% | 34% | 29% | 12% | 2% |
| 9 | GAY Sasha | - | 1% | 6% | 25% | 45% | 24% | |
| 10 | SHEARER Alena | - | - | 3% | 13% | 31% | 36% | 16% |
| 11 | LEI Zitong (Meya) | - | 1% | 6% | 25% | 43% | 25% | |
| 12 | KIM Satie | - | 7% | 27% | 39% | 22% | 4% | |
| 13 | HAN Emma | - | 4% | 17% | 35% | 32% | 11% | |
| 14 | MARTINEZ MARIA | - | 3% | 17% | 37% | 33% | 10% | |
| 15 | MAO anna | 1% | 8% | 24% | 35% | 24% | 7% | - |
| 16 | KWON Hannah | 1% | 10% | 31% | 38% | 17% | 3% | |
| 17 | CONG Anne | - | 1% | 7% | 26% | 42% | 24% | |
| 18 | LIN Elaine | - | - | 1% | 5% | 21% | 41% | 33% |
| 19 | CHAN Jolene | - | - | - | 4% | 31% | 65% | |
| 20 | WANG Jiayi | - | 2% | 13% | 30% | 33% | 17% | 3% |
| 21 | LONG Chloe | 1% | 11% | 30% | 34% | 18% | 4% | - |
| 22 | ASPIRAS Avery | 36% | 42% | 18% | 4% | < 1% | - | - |
| 23 | LAUREYNS Ainsley | 2% | 15% | 44% | 32% | 7% | - | |
| 24 | ZHAO Abbie | 1% | 8% | 29% | 38% | 20% | 4% | |
| 25 | KINKADE Ellie | - | - | 1% | 9% | 28% | 40% | 21% |
| 26 | KIM Saeren | 1% | 8% | 24% | 35% | 25% | 7% | - |
| 27 | LIU kai yin aria | 1% | 7% | 21% | 33% | 27% | 10% | 1% |
| 28 | MISHEV Lila | - | 4% | 17% | 34% | 30% | 12% | 2% |
| 29 | BORTAI Eliza | 3% | 22% | 37% | 26% | 9% | 2% | - |
| 30 | PANCHAL Arya | 63% | 31% | 6% | - | - | - | |
| 31 | YU Skylar | 1% | 11% | 32% | 37% | 17% | 2% | |
| 32 | CAO arissa | 31% | 45% | 20% | 4% | - | - | |
| 33 | KU Alathea-Joy | - | 4% | 17% | 35% | 33% | 11% | |
| 33 | YUEN Nicole | - | - | 6% | 31% | 50% | 12% | |
| 35 | OCA Merci | 4% | 22% | 38% | 27% | 8% | 1% | |
| 36 | YAN Angela | - | 4% | 18% | 34% | 30% | 12% | 2% |
| 37 | ZHU Elaine | - | 5% | 20% | 36% | 29% | 9% | |
| 38 | WONG Natalie | 1% | 7% | 25% | 38% | 24% | 5% | |
| 39 | YU Stella | 2% | 15% | 34% | 32% | 14% | 2% | |
| 40 | WONG Cerise | - | 7% | 24% | 35% | 24% | 8% | 1% |
| 41 | SUNG Isabella | - | 4% | 16% | 33% | 32% | 13% | 1% |
| 42 | LONG Jessie | 2% | 14% | 30% | 32% | 17% | 4% | - |
| 42 | NGUYEN Summer | 1% | 5% | 19% | 33% | 29% | 12% | 2% |
| 44 | SENGUPTA Jia | - | 1% | 9% | 25% | 35% | 24% | 6% |
| 45 | HU Ashley | 2% | 12% | 29% | 33% | 18% | 4% | - |
| 46 | NING Lynn | 1% | 10% | 32% | 37% | 17% | 2% | |
| 47 | KIM Yeju | - | 7% | 32% | 44% | 15% | 1% | |
| 48 | HSIEH Lucia | 3% | 26% | 40% | 24% | 6% | - | |
| 49 | MORINAGA Mirai | 6% | 24% | 36% | 25% | 8% | 1% | - |
| 50 | JUNG Sienna | 24% | 40% | 26% | 8% | 1% | - | - |
| 51 | PARK Chloe | 10% | 33% | 36% | 17% | 4% | - | |
| 52 | CHANG Kaitlyn | 7% | 29% | 38% | 20% | 5% | - | |
| 53 | CHEN Colette | - | 3% | 16% | 36% | 34% | 11% | |
| 54 | LEE Madeleine | 15% | 39% | 33% | 11% | 2% | - | |
| 55 | DANG Madeleine | 37% | 42% | 17% | 3% | - | - | |
| 56 | PATIL Jyothi | 42% | 44% | 13% | 1% | - | - | |
| 57 | MAO Elsa | 3% | 17% | 32% | 30% | 14% | 3% | - |
| 58 | KIRBY Skye | 10% | 36% | 35% | 15% | 3% | - | - |
| 59 | STAPLEY Claire | 24% | 39% | 26% | 9% | 2% | - | - |
| 60 | HENRY Erin | 25% | 51% | 21% | 3% | - | - | |
| 61 | VILLAMATER Mia Franchesca | 26% | 47% | 22% | 4% | - | - | |
| 62 | ZHANG angelina | 27% | 43% | 23% | 6% | 1% | - | |
| 63 | DUFF Caitlin | 30% | 42% | 22% | 5% | 1% | - | |
| 64 | MEI Chloe | 63% | 31% | 6% | 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.