Rockland Community College, Eugene Levy Field House - Suffern, NY, 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 | VILLER Alice | - | - | 1% | 5% | 22% | 42% | 30% |
| 2 | FURMAN Elizabeth | - | - | - | 2% | 12% | 41% | 46% |
| 3 | HAN Emma | - | - | 1% | 8% | 26% | 41% | 24% |
| 3 | TANG Jacquelyn | - | 3% | 17% | 36% | 33% | 11% | |
| 5 | CHEN Laila | - | - | 1% | 6% | 23% | 41% | 28% |
| 6 | YIN Elaine | - | - | 3% | 14% | 32% | 35% | 15% |
| 7 | LEE Zoe | - | - | 2% | 13% | 33% | 37% | 14% |
| 7 | BOUTSIKARIS Asha | - | - | 3% | 15% | 34% | 35% | 12% |
| 9 | KIM Charlotte | - | - | 2% | 12% | 32% | 38% | 16% |
| 10 | CHEN Madeline | - | - | - | 1% | 10% | 38% | 50% |
| 11 | LIU Brinley | - | - | 1% | 8% | 27% | 41% | 22% |
| 12 | LEE Nicole | - | 1% | 6% | 21% | 36% | 29% | 8% |
| 13 | YOUNG Penelope | - | 2% | 9% | 23% | 33% | 25% | 8% |
| 14 | SIU Mila | - | - | 4% | 19% | 36% | 31% | 9% |
| 15 | CHANEY Evelyn | - | - | 2% | 12% | 33% | 40% | 13% |
| 16 | HONG Catherine | - | - | 4% | 18% | 36% | 32% | 10% |
| 17 | KIM Abigail | - | - | 2% | 11% | 32% | 38% | 17% |
| 18 | SELASSIE Semara | - | 3% | 19% | 37% | 29% | 10% | 1% |
| 19 | ZHANG Yuchen A. | - | - | 1% | 9% | 28% | 42% | 20% |
| 20 | PATEL Aria | - | 1% | 7% | 25% | 39% | 23% | 4% |
| 21 | JI Susan | - | 1% | 6% | 22% | 37% | 27% | 7% |
| 22 | LIOU Skylar | - | 5% | 23% | 37% | 26% | 8% | 1% |
| 23 | LI Kayla | - | - | 3% | 16% | 35% | 34% | 12% |
| 23 | KAMENSKY Emilia | - | 2% | 12% | 29% | 34% | 19% | 4% |
| 25 | MEGGERS Arya | - | 1% | 7% | 25% | 38% | 24% | 5% |
| 26 | LIANG Kristy | 1% | 6% | 19% | 31% | 28% | 13% | 2% |
| 27 | OLVECZKY Camilla | - | 4% | 16% | 30% | 30% | 16% | 3% |
| 28 | LEE Iona | - | 3% | 18% | 36% | 30% | 11% | 2% |
| 29 | XIE ANDREA | - | - | 1% | 8% | 27% | 42% | 22% |
| 30 | CHOI Elina | - | 2% | 15% | 33% | 33% | 15% | 2% |
| 31 | WANG Hailie | - | 2% | 12% | 29% | 35% | 18% | 3% |
| 32 | CHUNG Yenna | - | 1% | 7% | 26% | 40% | 24% | 4% |
| 33 | YUSHCHENKO Ivanka | - | - | 3% | 15% | 34% | 35% | 13% |
| 34 | ZHANG Allison | - | - | 2% | 12% | 30% | 38% | 18% |
| 35 | CHOI Noah | - | 5% | 23% | 37% | 26% | 8% | 1% |
| 36 | CHEN Reina | - | 3% | 15% | 34% | 34% | 13% | |
| 37 | VENKATESH Uma | 2% | 12% | 28% | 32% | 19% | 5% | 1% |
| 38 | CHEN Emily | 1% | 6% | 23% | 37% | 25% | 7% | 1% |
| 39 | FAYEZ Malika | - | 1% | 5% | 19% | 35% | 30% | 10% |
| 40 | STEWART Emily | 3% | 17% | 35% | 31% | 12% | 2% | - |
| 41 | GORDON Winter | 4% | 20% | 34% | 28% | 11% | 2% | - |
| 42 | LIU sienna | 1% | 7% | 24% | 35% | 25% | 8% | 1% |
| 42 | HE Joyce | 4% | 19% | 33% | 29% | 13% | 3% | - |
| 44 | SHEN Sophia | - | 1% | 8% | 27% | 38% | 22% | 4% |
| 45 | WARD Imani | - | - | 1% | 6% | 24% | 43% | 27% |
| 46 | ZHANG Aaliyah | - | - | 3% | 14% | 32% | 36% | 15% |
| 47 | VAZIRANI Jiya | 23% | 41% | 27% | 8% | 1% | - | - |
| 47 | PATEL Agena | - | 4% | 16% | 32% | 31% | 14% | 2% |
| 49 | JIN Serena | 2% | 12% | 31% | 34% | 17% | 4% | - |
| 50 | SUN Alisha | - | - | 4% | 19% | 37% | 30% | 9% |
| 51 | NEMAT Kamila | 3% | 18% | 34% | 30% | 12% | 2% | - |
| 52 | MARGAGLIONE Veronica | 6% | 24% | 35% | 24% | 8% | 1% | - |
| 53 | KAUR Harman | 24% | 41% | 26% | 8% | 1% | - | - |
| 54 | MERHEJ Liv | 4% | 20% | 35% | 28% | 11% | 2% | - |
| 55 | LIN Amber | 5% | 21% | 33% | 27% | 11% | 3% | - |
| 56 | MENG Yinuo | 1% | 17% | 38% | 31% | 11% | 2% | - |
| 57 | WANG Jenny | 9% | 42% | 35% | 12% | 2% | - | - |
| 58 | WANG Katherine | 2% | 14% | 32% | 32% | 16% | 4% | - |
| 59 | MERHEJ Lea | 2% | 15% | 34% | 32% | 14% | 2% | - |
| 60 | SURENDAR Dhiya | 4% | 21% | 37% | 27% | 9% | 1% | - |
| 61 | BILIEN Yiwen | 1% | 11% | 30% | 35% | 18% | 4% | - |
| 62 | LEE Gloria | 1% | 7% | 21% | 32% | 26% | 11% | 2% |
| 63 | GURTIN Sasha | 1% | 7% | 21% | 32% | 27% | 11% | 2% |
| 64 | BIRZ Vivi | 28% | 43% | 22% | 5% | 1% | - | |
| 65 | VILLER Gabriella | 1% | 9% | 28% | 37% | 21% | 5% | |
| 66 | KUO Stella | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
| 67 | LOUGH Abbie | 28% | 47% | 20% | 4% | - | - | - |
| 68 | FEESER Alexia | 1% | 6% | 23% | 37% | 27% | 7% | |
| 69 | ZHAO Ailsa | 17% | 40% | 30% | 10% | 2% | - | |
| 70 | RYU Natalee | - | 3% | 14% | 31% | 33% | 16% | 3% |
| 71 | XIA Kaelynn | 3% | 16% | 32% | 31% | 15% | 3% | - |
| 72 | LIN Evelyn | 14% | 33% | 32% | 16% | 5% | 1% | - |
| 73 | SOLGI Ava | - | 3% | 16% | 34% | 32% | 13% | 2% |
| 74 | ZHENG Lina | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
| 75 | ZHAO Sophia | 11% | 32% | 34% | 18% | 5% | 1% | - |
| 76 | WU Caroline | 18% | 38% | 30% | 11% | 2% | - | - |
| 77 | LI Yisi | 1% | 8% | 28% | 36% | 21% | 6% | 1% |
| 78 | WATRELOT Seraphine | 3% | 16% | 34% | 31% | 13% | 2% | - |
| 79 | RODRIGUEZ Ivy | 2% | 15% | 33% | 31% | 15% | 3% | - |
| 80 | CHOI Serine | 16% | 39% | 31% | 11% | 2% | - | - |
| 81 | BONDE Trisha | 16% | 44% | 30% | 9% | 1% | - | - |
| 81 | SHANG Adeline | 13% | 37% | 34% | 13% | 2% | - | - |
| 83 | SALIBA Madison | 1% | 7% | 23% | 36% | 26% | 7% | 1% |
| 84 | ALVAREZ Megan | 16% | 40% | 32% | 11% | 2% | - | - |
| 85 | DARMAWAN Thea | 5% | 33% | 40% | 18% | 4% | - | - |
| 86 | QIN Olivia | 7% | 24% | 35% | 24% | 9% | 1% | - |
| 87 | KIM Natalie | 2% | 12% | 33% | 35% | 16% | 3% | - |
| 88 | YANG Emily | 22% | 40% | 28% | 9% | 1% | - | - |
| 89 | LEE Zerah | 15% | 36% | 32% | 13% | 3% | - | - |
| 90 | CARACCIOLO Emma | 56% | 34% | 8% | 1% | - | - | - |
| 91 | YULO Jamie | 69% | 27% | 4% | - | - | - | - |
| 92 | BERENSHTEYN Gabriella | 7% | 25% | 35% | 24% | 8% | 1% | - |
| 93 | YU Qinying | 6% | 24% | 36% | 25% | 9% | 1% | - |
| 94 | NAGARAJ Arya | 27% | 45% | 23% | 5% | - | - | - |
| 95 | LATORRE Alexa | 44% | 42% | 12% | 2% | - | - | - |
| 96 | TATINI Aria | 29% | 43% | 22% | 5% | 1% | - | - |
| 97 | CHO Angelina | 64% | 31% | 5% | - | - | - | - |
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.