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 | ZHANG XUANYI | - | - | - | 3% | 19% | 48% | 30% |
| 2 | WANG Gloria | - | - | - | 4% | 20% | 43% | 33% |
| 3 | SCHMIDT Isabel | - | - | 2% | 16% | 43% | 39% | |
| 3 | TAN Adelyn | - | 2% | 15% | 37% | 35% | 10% | |
| 5 | TSE Angelina | - | - | - | 2% | 17% | 47% | 34% |
| 6 | GAUTAM Sahana | - | - | 3% | 16% | 41% | 40% | |
| 7 | LIU Sydney | - | - | 2% | 11% | 31% | 41% | 16% |
| 8 | STONE Coral | - | 1% | 10% | 34% | 41% | 14% | |
| 9 | KANG Ellie | - | - | 5% | 27% | 46% | 21% | |
| 10 | LEI Zitong (Meya) | - | 3% | 20% | 38% | 29% | 9% | 1% |
| 11 | LIN Annika | - | 4% | 21% | 44% | 26% | 5% | |
| 12 | CONG Anne | 1% | 9% | 28% | 37% | 21% | 4% | |
| 13 | MANN Sophia J. | - | - | 4% | 24% | 45% | 26% | |
| 14 | HUAI Delilah | - | - | - | 4% | 20% | 43% | 33% |
| 15 | CHEN Colette | - | 6% | 29% | 42% | 20% | 3% | |
| 16 | BORDAS HILL Georgiana | - | 1% | 5% | 21% | 38% | 28% | 7% |
| 17 | DANG Kelia | - | - | 5% | 25% | 45% | 25% | |
| 18 | WANG Peijia | 1% | 8% | 30% | 37% | 19% | 4% | - |
| 19 | MORALES Camila Avisac | 2% | 18% | 37% | 30% | 11% | 2% | - |
| 20 | CHAN Jolene | - | 5% | 22% | 37% | 28% | 8% | 1% |
| 21 | TRILLO Maya Izabella | - | 1% | 4% | 17% | 33% | 33% | 12% |
| 21 | SUNG Isabella | 3% | 17% | 34% | 30% | 13% | 2% | - |
| 23 | VINOGOROVA Sofiia | - | - | 4% | 18% | 42% | 36% | |
| 24 | MARTINEZ MARIA | 1% | 10% | 29% | 36% | 20% | 3% | |
| 25 | KINKADE Ellie | - | - | 2% | 17% | 45% | 36% | |
| 26 | LIAO Jieni | 1% | 8% | 29% | 40% | 20% | 3% | |
| 27 | KU Alathea-Joy | - | 6% | 23% | 36% | 26% | 8% | 1% |
| 28 | LO Chloe | - | 2% | 12% | 31% | 36% | 17% | 2% |
| 29 | WONG Cerise | 20% | 40% | 29% | 10% | 1% | - | |
| 30 | YAM Danika | - | - | 2% | 15% | 42% | 41% | |
| 31 | LIN Elaine | - | 5% | 23% | 42% | 25% | 5% | |
| 32 | TURIANO Nadelle | 1% | 9% | 25% | 35% | 23% | 6% | 1% |
| 33 | MUNGUIA Mila | 2% | 19% | 38% | 30% | 11% | 2% | - |
| 34 | BAERENWALD Welles | 1% | 9% | 32% | 38% | 17% | 2% | |
| 35 | GAY Sasha | 4% | 21% | 37% | 28% | 9% | 1% | |
| 36 | NING Lynn | 11% | 32% | 35% | 18% | 4% | - | |
| 37 | LIN Kyleen | - | 1% | 6% | 24% | 39% | 25% | 5% |
| 38 | HAN Emma | 13% | 33% | 33% | 16% | 4% | - | - |
| 39 | LIU kai yin aria | 4% | 29% | 44% | 20% | 3% | - | |
| 40 | LEE Irene | 3% | 16% | 34% | 32% | 13% | 2% | |
| 41 | YUEN Nicole | 28% | 47% | 21% | 4% | - | - | |
| 42 | SENGUPTA Jia | 1% | 9% | 35% | 39% | 15% | 2% | |
| 43 | SEBASTIAN Ava | 24% | 46% | 25% | 5% | - | - | |
| 44 | TONG Laurie | 12% | 35% | 34% | 15% | 3% | - | |
| 45 | KNULL Emma | - | 1% | 9% | 25% | 35% | 24% | 6% |
| 46 | MISHEV Lila | 2% | 17% | 34% | 31% | 13% | 2% | - |
| 47 | HUANG Shiloh | 1% | 14% | 35% | 33% | 14% | 3% | - |
| 48 | SHEARER Alena | - | 5% | 21% | 36% | 28% | 9% | 1% |
| 49 | HUYANG xinke | 19% | 39% | 30% | 10% | 2% | - | |
| 50 | BAIRD Kaleah | 34% | 46% | 18% | 3% | - | - | |
| 51 | ZHAI AMY | 1% | 8% | 25% | 37% | 24% | 5% | |
| 51 | WANG Jiayi | 3% | 19% | 41% | 29% | 8% | 1% | |
| 53 | KIM Satie | 24% | 51% | 22% | 3% | - | - | |
| 54 | GAIKWAD Ashmiee | 2% | 12% | 31% | 35% | 17% | 3% | |
| 55 | LIN Abbey | 8% | 39% | 39% | 13% | 1% | - | |
| 56 | JOHNSON Heaven | 4% | 20% | 35% | 28% | 11% | 2% | - |
| 57 | GIGUERE Nikita | 65% | 29% | 5% | - | - | - | - |
| 58 | LIN Ariel | 5% | 22% | 35% | 26% | 10% | 2% | - |
| 59 | STAPLEY Claire | 23% | 48% | 24% | 5% | - | - | - |
| 60 | KIM Alice | 60% | 34% | 6% | - | - | - | |
| 61 | LEE Madeleine | 31% | 46% | 19% | 3% | - | - | |
| 62 | ROBBINS Adele | 41% | 44% | 13% | 2% | - | - | - |
| 62 | LIU Hannah | 56% | 35% | 8% | 1% | - | - | - |
| 64 | JUNG Sienna | 49% | 42% | 8% | 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.