Sports Special Reprise
Grade Leaderboard
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| # | Player | Region | Games | TUH | # Correct | % Correct | Average Celerity | Score |
|---|---|---|---|---|---|---|---|---|
| 1 | Aum Mundhe | New Jersey | 1 | 50 | 46 | 92.0% | .306 | 622 |
| 2 | Jonah Gross | Illinois | 1 | 50 | 42 | 84.0% | .314 | 575 |
| 3 | Owen Riley | Minnesota | 1 | 50 | 43 | 86.0% | .290 | 570 |
| 4 | Ben Matz | Maryland | 1 | 50 | 47 | 94.0% | .194 | 569 |
| 5 | Maximilian Niebur | Indiana | 1 | 50 | 40 | 80.0% | .346 | 559 |
| 6 | Todd Feil | Pennsylvania | 1 | 50 | 42 | 84.0% | .263 | 543 |
| 7 | Paul Taton | Minnesota | 1 | 50 | 45 | 90.0% | .183 | 539 |
| 8 | Daniel Liu | Michigan | 1 | 50 | 38 | 76.0% | .352 | 534 |
| 9 | Aditya Mehta | Arizona | 1 | 50 | 37 | 74.0% | .325 | 509 |
| 10 | Yusuf Amanullah | California | 1 | 50 | 37 | 74.0% | .300 | 498 |
| 11 | Louis Li | Missouri | 1 | 50 | 37 | 74.0% | .299 | 498 |
| 12 | Ben Obert | Indiana | 1 | 50 | 35 | 70.0% | .334 | 482 |
| 13 | Aaron Dantzler | Florida | 1 | 50 | 37 | 74.0% | .230 | 464 |
| 14 | Alex Schapiro | Illinois | 1 | 50 | 36 | 72.0% | .252 | 460 |
| 15 | Neal Joshi | Indiana | 1 | 50 | 35 | 70.0% | .207 | 431 |
| 16 | Henry Huschke | Michigan | 1 | 50 | 34 | 68.0% | .232 | 428 |
| 17 | Soham Mehra | Florida | 1 | 50 | 35 | 70.0% | .199 | 427 |
| 18 | Rob Bundy | Virginia | 1 | 50 | 35 | 70.0% | .199 | 426 |
| 19 | Ryan Sharpe | Canada | 1 | 50 | 35 | 70.0% | .160 | 413 |
| 20 | Jacqueline Chin | Texas | 1 | 50 | 36 | 72.0% | .125 | 408 |
| 21 | Biniam Alaro | Florida | 1 | 50 | 26 | 52.0% | .269 | 340 |
| 22 | Zaid Siddiqui | Michigan | 1 | 50 | 28 | 56.0% | .152 | 328 |
| 23 | Cameron Tsai | South Carolina | 1 | 50 | 26 | 52.0% | .198 | 317 |
| 24 | Uriel Vargas | Texas | 1 | 50 | 29 | 58.0% | .087 | 316 |
| 25 | Keith Wiley | Tennessee | 1 | 50 | 26 | 52.0% | .130 | 298 |
| 26 | Kai Seidenberg | New Mexico | 1 | 50 | 25 | 50.0% | .101 | 276 |
| 27 | Sara Moore | Illinois | 1 | 50 | 25 | 50.0% | .090 | 273 |
| 28 | Aida Fong | Texas | 1 | 50 | 15 | 30.0% | .005 | 150 |
Celerity is the fraction of the question that had not been read at the time of a buzz (for which a correct answer was provided). 1.000 is an immediate buzz, .500 is an answer given halfway through the question in terms of time on the sound recording, and .000 is an answer given at the very end.