Date | Name | Result | DN * | Pos/Neg ** | Prediction | Proba | Name | Result | DN | Pos/Neg | |
---|---|---|---|---|---|---|---|---|---|---|---|
2025-May-18 | Kuang Qing Xu | win | 1 | 99.57% |
|
Victor Lilov | loss | 4 | |||
2025-May-17 | Kuang Qing Xu | win | 9 | 67.45% |
|
Yassine Dlimi | loss | 2 | |||
2025-May-16 | Kuang Qing Xu | win | 8 | 67.45% |
|
Dan Martin | loss | 3 | |||
2025-May-15 | Kuang Qing Xu | win | 7 | 67.45% |
|
Nicolas Arseneault | loss | 1 | |||
2024-Nov-02 | Evangelos Kypriotis | win | 2 | 67.45% |
|
Kuang Qing Xu | loss | 8 | |||
2024-Oct-04 | Toprak Avcibasi | win | 5 | 67.45% |
|
Kuang Qing Xu | loss | 9 | |||
2024-May-02 | Aleksandr Lobanov | win | 5 | 67.45% |
|
Kuang Qing Xu | loss | 2 | |||
2024-Apr-15 | Alejandro Melero Kretzer | win | 7 | 99.96% |
|
Kuang Qing Xu | loss | 5 | |||
2024-Mar-31 | Kuang Qing Xu | win | 2 | 99.96% |
|
Nil Boixader Roca | loss | 3 | |||
2024-Feb-28 | Sergio Callejon Hernando | win | 9 | 67.45% |
|
Kuang Qing Xu | loss | 7 | |||
2024-Feb-20 | Gabriel Elicha Navas | win | 1 | 67.45% |
|
Kuang Qing Xu | loss | 8 | |||
2024-Feb-18 | Kuang Qing Xu | win | 6 | 99.96% |
|
Pablo Aunion | loss | 4 | |||
2024-Jan-07 | Karl Poling | win | 4 | 99.96% |
|
Kuang Qing Xu | loss | 3 | |||
2024-Jan-04 | Iker Urribarrens Ramirez | win | 7 | 67.45% |
|
Kuang Qing Xu | loss | 9 | |||
2023-Dec-11 | Colin Markes | win | 3 | 99.57% |
|
Kuang Qing Xu | loss | 8 | |||
2023-Dec-07 | Philip Sekulic | win | 2 | 99.96% |
|
Kuang Qing Xu | loss | 4 | |||
2023-Oct-26 | Dan Martin | win | 7 | 99.96% |
|
Kuang Qing Xu | loss | 3 | |||
2023-Oct-07 | Kuang Qing Xu | win | 2 | 99.96% |
|
Anirudh Rao | loss | 1 | |||
2023-Jun-03 | Joe Tyler | win | 1 | 99.96% |
|
Kuang Qing Xu | loss | 3 | |||
2023-Feb-10 | Evan Bynoe | win | 2 | 67.45% |
|
Kuang Qing Xu | loss | 6 | |||
2023-Jan-11 | Aziz Dougaz | win | 3 | 67.45% |
|
Kuang Qing Xu | loss | 6 | |||
2022-Oct-26 | Patrick Kypson | win | 2 | 67.45% |
|
Kuang Qing Xu | loss | 2 |
* Day_number.
** Positive_Negative_TextPositive multiplier the bigger the better. Negative multiplier the bigger the worse.