2023 Popular Culture Week 39

Region Leaderboard

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# PlayerAwards # Correct % Correct Average
Correct
Celerity
Std. Dev.
Celerity
Score
1 Matthew Marcotte Bronze TrophyGold TrophyBronze Trophy 9 90.0% .480 .223142
2 Jack Rousseau Blue RibbonSilver TrophyTop Five Ribbon 9 90.0% .326 .218126
3 Tomás Aguilar-Fraga Red RibbonBronze TrophyTop Ten Ribbon 8 80.0% .396 .236118
4 Andrew Dupont Red RibbonTop Five RibbonRed Ribbon 8 80.0% .395 .153118
5 Clifford Galiher Red RibbonBlue RibbonBlue Ribbon 9 90.0% .279 .183118
6 Mike Myers Red RibbonTop Ten RibbonRed Ribbon 8 80.0% .342 .204111
7 Erik Nickels White RibbonBronze TrophyBlue Ribbon 7 70.0% .429 .305107
8 Kyle Kahan White RibbonBlue RibbonRed Ribbon 8 80.0% .301 .215106
9 Daniel Chung White RibbonBlue RibbonWhite Ribbon 8 80.0% .250 .186102
10 Naveed Chowdhury White RibbonBlue RibbonWhite Ribbon 8 80.0% .232 .198101
11 Jenna Hull Yellow RibbonBlue RibbonWhite Ribbon 7 70.0% .367 .15799
12 Omar Sajjad Yellow RibbonTop Ten RibbonRed Ribbon 7 70.0% .354 .22599
13 James Kang Yellow RibbonBlue RibbonWhite Ribbon 8 80.0% .200 .17198
14 Paolo Pasco Yellow RibbonTop Ten RibbonWhite Ribbon 7 70.0% .325 .23396
15 Scott Latchem Yellow RibbonBlue RibbonWhite Ribbon 7 70.0% .303 .18695
16 Daniel Jude Yellow RibbonTop Ten RibbonYellow Ribbon 6 60.0% .467 .28294
17 Paul Campbell Green RibbonRed RibbonYellow Ribbon 7 70.0% .255 .23090
18 Lauren Cusitello Green RibbonWhite RibbonYellow Ribbon 7 70.0% .239 .21789
19 Max Smiley Red RibbonWhite RibbonBronze Trophy 7 70.0% .216 .15087
20 Stephen Liu Blue RibbonWhite Ribbon 6 60.0% .327 .20383
21 Anthony DiCarlo Top Ten Ribbon 6 60.0% .254 .25877
22 Ryan Hemmel Red RibbonWhite RibbonYellow Ribbon 6 60.0% .219 .14474
23 Andrey Goder Red RibbonGreen Ribbon 6 60.0% .163 .24372
24 Chauncey Lo Yellow Ribbon 6 60.0% .189 .14171
25 Ozzie Fallick Yellow RibbonGreen RibbonGreen Ribbon 6 60.0% .169 .09468
26 Lynn Yu Red RibbonWhite Ribbon 5 50.0% .242 .18964
27 Hidehiro Anto 4 40.0% .231 .16849
28 Arjun Sivakumar Red Ribbon 4 40.0% .208 .12648

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.

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