Milwaukee, WI - Milwaukee, WI, 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 | WEINTRAUB Maia M. | - | 1% | 7% | 22% | 35% | 27% | 8% |
2 | MAK Tinney | - | - | 4% | 19% | 42% | 34% | |
3 | TAN Helen | - | 4% | 16% | 33% | 31% | 14% | 2% |
3 | LAM Justina | - | - | - | 1% | 9% | 36% | 55% |
5 | HAO Alicia | - | 2% | 12% | 28% | 34% | 20% | 5% |
6 | TAN Elisha | - | - | 2% | 12% | 30% | 37% | 18% |
7 | PUSTILNIK Nicole | - | - | - | 2% | 13% | 42% | 43% |
8 | LEE Annora Y. | - | - | 4% | 18% | 37% | 32% | 10% |
9 | CHO Sabrina N. | - | - | 4% | 19% | 38% | 31% | 8% |
10 | PROESTAKIS Katina A. | - | 1% | 5% | 21% | 36% | 29% | 9% |
11 | YAROSHENKO Karina | - | 1% | 8% | 25% | 37% | 23% | 4% |
12 | CHUSID Renata (Renata Chusid) M. | - | - | - | 1% | 11% | 39% | 48% |
13 | GUO Jessica Zi Jia | - | - | - | 1% | 6% | 32% | 62% |
14 | HORSLEY Asherah | - | - | - | 2% | 16% | 47% | 35% |
15 | KIM Rachael | - | 4% | 20% | 39% | 31% | 7% | |
16 | LIN Annie X. | 2% | 12% | 31% | 34% | 17% | 3% | - |
17 | FLANAGAN Catherine H. | - | - | 2% | 12% | 32% | 38% | 16% |
18 | RHODES Zander | - | - | - | 2% | 14% | 41% | 42% |
19 | LEE Allison (Allie) | - | 1% | 9% | 29% | 41% | 20% | 1% |
20 | NISHIMURA Madeleine A. | - | 5% | 19% | 33% | 29% | 12% | 2% |
21 | KOKES Gabrielle | - | 2% | 11% | 28% | 35% | 21% | 4% |
22 | WEINTRAUB Rei H. | - | 1% | 10% | 28% | 36% | 21% | 4% |
23 | AHN Gabriella | - | - | 6% | 23% | 36% | 27% | 8% |
24 | KOO Haley B. | - | 2% | 9% | 25% | 35% | 23% | 6% |
25 | LESLIE Ryanne T. | - | 1% | 5% | 17% | 32% | 32% | 13% |
26 | APELIAN Katherine | - | 1% | 5% | 20% | 36% | 30% | 9% |
27 | FERRARI Christina M. | 2% | 11% | 26% | 32% | 21% | 7% | 1% |
28 | CHOI Lenna K. | - | 2% | 11% | 29% | 35% | 20% | 4% |
29 | JING Alexandra | - | - | 2% | 15% | 44% | 32% | 7% |
30 | SOOD Ishani S. | 1% | 9% | 26% | 36% | 23% | 5% | |
31 | LEE Paulina | - | 5% | 19% | 33% | 29% | 12% | 2% |
32 | FERNANDES Thea | 1% | 11% | 34% | 38% | 15% | 2% | - |
33 | LEE Brianna J. | - | - | 3% | 13% | 32% | 36% | 16% |
34 | NOVOSELTSEVA Anna V. | - | 1% | 6% | 24% | 38% | 25% | 6% |
35 | TALAVERA Daena | - | - | - | 3% | 18% | 48% | 31% |
36 | YANKOVSKIY Anastasia | - | - | 3% | 17% | 43% | 37% | |
37 | SHEN Jasmine N. | - | 3% | 16% | 35% | 33% | 12% | 1% |
38 | ZAROFF Roxanne | - | 5% | 20% | 34% | 28% | 11% | 2% |
39 | PETROVA Kristina | - | 1% | 10% | 27% | 35% | 21% | 5% |
40 | CHEN Shiuan-An Shannon | - | - | 4% | 18% | 39% | 31% | 7% |
41 | MOLHO Sofia | - | 6% | 23% | 36% | 25% | 8% | 1% |
42 | FANG Sabrina | - | 1% | 7% | 22% | 36% | 27% | 7% |
43 | KOENIG Charlotte R. | - | 2% | 14% | 33% | 33% | 15% | 3% |
44 | HE Elizabeth W. | - | 1% | 8% | 25% | 36% | 24% | 6% |
45 | LIN Maggie | 1% | 8% | 25% | 35% | 23% | 7% | 1% |
46 | LI Grace Q. | - | 1% | 8% | 29% | 42% | 19% | 2% |
47 | PAPADAKIS Lily | - | 2% | 11% | 27% | 34% | 21% | 5% |
48 | YAMAGUCHI Kate M. | - | 1% | 12% | 39% | 40% | 7% | - |
49 | STAMOS Maria | - | - | 4% | 16% | 33% | 33% | 12% |
50 | BRADFORD Meeah | - | 3% | 16% | 35% | 33% | 12% | 1% |
51 | ZHENG Ivy | - | - | 1% | 9% | 28% | 40% | 21% |
52 | LI Phoebe J. | 2% | 12% | 29% | 34% | 18% | 4% | - |
53 | SARTORI Taylor M. | - | 2% | 13% | 30% | 35% | 17% | 3% |
54 | CHENG Evelyn | 3% | 16% | 33% | 30% | 14% | 3% | - |
55 | ABAYEVA Sasha | 3% | 16% | 32% | 31% | 15% | 3% | |
56 | LEE Alina | - | 4% | 15% | 31% | 31% | 16% | 3% |
57 | HALL Velma | 3% | 23% | 38% | 26% | 9% | 1% | - |
58 | HUNG Juliana K. | 1% | 9% | 24% | 33% | 24% | 8% | 1% |
59 | ALFONSO Czarina M. | 1% | 15% | 36% | 33% | 14% | 3% | - |
60 | PARK Rowan M. | - | 1% | 7% | 26% | 42% | 22% | 3% |
61 | KIM Kayla A. | - | 4% | 21% | 39% | 30% | 6% | - |
62 | GOMES Rafaella T. | - | 2% | 11% | 27% | 34% | 21% | 5% |
63 | FREEDMAN Miranda W. | 25% | 42% | 25% | 7% | 1% | - | - |
64 | WONG Julia M. | - | 6% | 27% | 45% | 20% | 2% | - |
65 | KNIGHT Skylar | - | - | - | 1% | 12% | 51% | 36% |
66 | ZHENG Vivian | - | 4% | 18% | 33% | 30% | 13% | 2% |
67 | CHON Samantha | - | 1% | 7% | 32% | 41% | 18% | 2% |
67 | HO Brianna W. | - | 5% | 19% | 35% | 30% | 10% | 1% |
69 | CAO Arianna L. | - | 2% | 14% | 33% | 34% | 14% | 2% |
70 | NOVOSELTSEVA Elizabeth (Liza) M. | 1% | 9% | 30% | 40% | 19% | 3% | |
71 | GUERRA Sofia E. | - | 1% | 8% | 24% | 36% | 25% | 6% |
72 | LIAO Lu Jia (Lucy) | 2% | 16% | 35% | 32% | 13% | 2% | - |
73 | IBEN Claire L. | - | 5% | 22% | 36% | 26% | 9% | 1% |
74 | MAROTTA Veronica L. | 1% | 8% | 27% | 36% | 22% | 6% | 1% |
74 | REN Olivia Y. | - | 4% | 16% | 31% | 31% | 15% | 3% |
76 | KOO Rachel A. | - | - | - | 3% | 21% | 53% | 23% |
77 | SERBAN Samantha M. | 1% | 5% | 18% | 33% | 29% | 12% | 2% |
78 | XU Christine | - | 1% | 6% | 20% | 34% | 29% | 10% |
79 | KIM Lauren Hyomin | 1% | 6% | 21% | 32% | 27% | 11% | 2% |
80 | SHEN Sophia H. | 10% | 39% | 36% | 13% | 2% | - | - |
81 | LAU Sydnee M. | - | 1% | 7% | 26% | 39% | 23% | 4% |
82 | QIAN Crystal | - | - | 4% | 17% | 34% | 33% | 12% |
83 | VOHRA Anusha | 11% | 40% | 35% | 12% | 2% | - | - |
84 | BALOT Corinne | 3% | 16% | 32% | 31% | 15% | 3% | |
85 | SADAN Jordan E. | 3% | 16% | 33% | 33% | 14% | 2% | |
86 | BREKER Anika | 1% | 9% | 29% | 38% | 20% | 3% | |
87 | CHENG Lydia A. | 1% | 11% | 32% | 37% | 17% | 3% | - |
88 | WU Catherine | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
89 | AHN Isabella | 1% | 8% | 24% | 34% | 25% | 8% | 1% |
90 | WALKER Mayah J. | 4% | 20% | 35% | 28% | 11% | 2% | - |
91 | OUTHRED Maya E. | - | 5% | 20% | 34% | 27% | 11% | 2% |
92 | YHIP Mikaela M. | - | 5% | 19% | 34% | 30% | 11% | 1% |
93 | KONG Olivia | - | 5% | 21% | 39% | 28% | 6% | - |
94 | RAMAN Tanvi | 1% | 9% | 26% | 35% | 22% | 7% | 1% |
95 | LUO ZIWEN | 1% | 7% | 26% | 39% | 22% | 5% | - |
96 | WU Julianna Y. | 2% | 17% | 36% | 31% | 12% | 2% | - |
97 | UYANIK Nerine | - | 6% | 32% | 40% | 18% | 3% | |
98 | KIM Elisabeth (Gracie) | - | 3% | 17% | 41% | 33% | 6% | |
99 | CHEN Kelly | 11% | 31% | 35% | 19% | 5% | - | |
100 | CHON Sydney | 24% | 43% | 25% | 7% | 1% | - | |
101 | WEINTRAUB Io H. | 1% | 7% | 24% | 37% | 25% | 6% | |
102 | SABATINI Isabella Ravenne | 3% | 17% | 37% | 31% | 11% | 2% | - |
103 | CASTANEDA Erika L. | - | 1% | 7% | 26% | 41% | 22% | 3% |
104 | MASSICK Laine | - | 1% | 9% | 29% | 38% | 20% | 3% |
105 | CHEN Nicole Y. | 1% | 11% | 32% | 35% | 17% | 3% | - |
106 | UPTON Elizabeth | - | 1% | 5% | 18% | 35% | 32% | 10% |
107 | FANG Serena | 9% | 28% | 34% | 21% | 7% | 1% | - |
108 | VEERKAMP Molly | 5% | 21% | 35% | 28% | 10% | 2% | - |
109 | HOBSON Leena | 30% | 52% | 16% | 2% | - | - | - |
110 | SEAL Grace (Gracie) C. | 14% | 36% | 34% | 14% | 3% | - | - |
111 | TRAN Ava D. | 1% | 11% | 30% | 34% | 19% | 5% | - |
111 | ALTEN Ayaka | 4% | 22% | 37% | 27% | 9% | 1% | - |
113 | CONWAY Josephina (JoJo) J. | 4% | 19% | 35% | 28% | 11% | 2% | - |
114 | LUNG Katerina | - | 1% | 6% | 26% | 40% | 23% | 4% |
115 | LIN Ashley | 1% | 11% | 32% | 36% | 17% | 3% | - |
116 | GALAVOTTI Claire Teresa | 2% | 13% | 32% | 33% | 16% | 3% | - |
117 | CEPERO Rosabel | 10% | 36% | 35% | 15% | 3% | - | - |
118 | CHUSID Mikayla | 5% | 24% | 37% | 25% | 8% | 1% | - |
119 | JO Mia C. | - | 4% | 18% | 36% | 30% | 10% | 1% |
119 | HE Xiangxin | 1% | 12% | 31% | 34% | 17% | 4% | - |
121 | THOMAS Aaria S. | 28% | 43% | 23% | 6% | 1% | - | - |
122 | LAU Chloe M. | 10% | 29% | 35% | 20% | 6% | 1% | - |
123 | SHANG Andrea | 2% | 14% | 31% | 32% | 16% | 4% | - |
124 | OH Erin H. | 7% | 28% | 37% | 21% | 6% | 1% | - |
125 | CHO Gracie L. | - | 1% | 7% | 22% | 35% | 27% | 8% |
125 | LEVI Lea | - | 12% | 41% | 36% | 10% | 1% | - |
127 | SCHATZ Kristina J. | - | 1% | 4% | 18% | 36% | 31% | 10% |
128 | HOLLE Aviella S. | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
129 | VONA Elena M. | 9% | 31% | 36% | 19% | 4% | - | - |
130 | TAN Clarisse | 4% | 19% | 34% | 29% | 12% | 2% | - |
131 | SIMPSON Lydia Q. | 3% | 16% | 32% | 31% | 15% | 3% | - |
132 | RATSEP Ariel | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
133 | HIRSCH Sophie A. | 27% | 47% | 22% | 4% | - | - | |
134 | ATLURI Srija | 5% | 30% | 40% | 21% | 4% | - | |
134 | SONG ShuXuan (Liliya) | 44% | 41% | 14% | 2% | - | - | |
136 | JING Emily | 2% | 17% | 40% | 31% | 9% | 1% | |
137 | CHUNG Ashley J. | 27% | 41% | 24% | 7% | 1% | - | - |
138 | SANTOS Annika Beatrice I. | 10% | 35% | 38% | 15% | 2% | - | - |
139 | KONG Chin-Yi | 3% | 17% | 34% | 31% | 13% | 2% | - |
140 | BOODELL Ella | 5% | 23% | 37% | 25% | 8% | 1% | - |
140 | YEH Marissa E. | 6% | 27% | 37% | 23% | 7% | 1% | - |
142 | LOCKE Savannah | - | < 1% | 6% | 24% | 40% | 26% | 4% |
143 | PO Edith | 2% | 13% | 30% | 33% | 18% | 5% | - |
144 | WU Irene M. | 11% | 32% | 34% | 17% | 5% | 1% | - |
145 | PERLMAN Talia | 10% | 31% | 35% | 19% | 5% | - | - |
146 | RASO Sofia G. | - | < 1% | 3% | 16% | 39% | 34% | 8% |
146 | SU Alysa J. | 14% | 37% | 33% | 13% | 2% | - | - |
148 | LEE Angelina S. | 27% | 43% | 24% | 5% | 1% | - | - |
148 | KLINE Melissa C. | 18% | 44% | 32% | 6% | - | - | - |
150 | NARANG Maya | 7% | 27% | 36% | 22% | 7% | 1% | - |
151 | SHITAMOTO Audrey F. | 18% | 38% | 30% | 11% | 2% | - | - |
151 | HEISER Anna M. | 37% | 43% | 17% | 3% | - | - | - |
153 | SHEPTAK Gabrielle | 28% | 46% | 22% | 4% | - | - | - |
154 | DRAGNE Alexis D. | 28% | 44% | 22% | 4% | - | - | - |
155 | YIN Helen | 51% | 37% | 11% | 2% | - | - | - |
156 | SULLIVAN Aya M. | 18% | 41% | 31% | 9% | 1% | - | - |
157 | ADAMS KIM Natalie | 8% | 29% | 37% | 20% | 5% | - | - |
157 | CHUNG Rachel J. | 2% | 12% | 30% | 33% | 18% | 4% | - |
159 | KELBLEY Elena J. | 28% | 44% | 22% | 5% | 1% | - | - |
160 | SCHWARTZMAN Salma | 13% | 37% | 36% | 13% | 1% | - | - |
160 | WANG ROBIN | 16% | 40% | 33% | 10% | 1% | - | - |
160 | BOLES Sophia | 28% | 43% | 23% | 6% | 1% | - | - |
163 | HICKS Bronwen | 30% | 47% | 20% | 3% | - | - | - |
164 | POWERS Kathryn | 43% | 41% | 14% | 2% | - | - | - |
165 | MULLENEX Laura | 70% | 28% | 2% | - | - | - | - |
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.