diff --git a/Data/Weekly_Data.csv b/Data/Weekly_Data.csv
index d047044..5295ae7 100644
--- a/Data/Weekly_Data.csv
+++ b/Data/Weekly_Data.csv
@@ -1,108 +1,110 @@
 Player,School,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI
-Jayden Daniels,LSU,197.7,22,4,1,17.857142857142858
-Michael Penix Jr.,Washington,189.9,20,0,1,25.0
-J.J. McCarthy,Michigan,195.9,14,3,1,25.0
-Jalen Milroe,Alabama,174.7,11,5,1,21.428571428571427
-Timmy Mcclain,UCF,177.7,9,1,1,12.5
-Kaidon Salter,Liberty,175.6,14,6,0,25.0
-Caleb Williams,USC,187.0,23,6,1,21.428571428571427
-Jaxson Dart,Ole Miss,167.8,12,4,1,20.833333333333336
-Diego Pavia,New Mexico State,167.0,14,2,0,14.285714285714285
-Kyle McCord,Ohio State,165.9,11,0,1,25.0
-Dillon Gabriel,Oklahoma,178.2,16,5,1,25.0
-Brady Cook,Missouri,168.7,14,4,1,21.428571428571427
-Tyler Van Dyke,Miami (FL),171.8,16,1,1,16.666666666666664
-Cardell Williams,Tulsa,151.6,8,3,0,12.5
-Quinn Ewers,Texas,163.8,11,5,1,20.833333333333336
-Brett Gabbert,Miami (OH),162.9,14,2,0,21.428571428571427
-Jordan McCloud,James Madison,168.1,14,2,0,25.0
-Carson Beck,Georgia,163.8,12,3,1,25.0
-Jack Plummer,Louisville,153.2,13,1,1,21.428571428571427
-Sam Hartman,Notre Dame,166.9,18,2,1,18.75
-Drake Maye,North Carolina,159.1,12,4,1,25.0
-JT Daniels,Rice,157.4,15,0,0,12.5
-Spencer Rattler,South Carolina,163.3,11,2,1,8.333333333333332
-D.J. Uiagalelei,Oregon State,158.9,15,5,1,21.428571428571427
-Keyone Jenkins,Florida International,133.5,5,4,0,10.714285714285714
-Garrett Greene,West Virginia,143.7,6,5,1,16.666666666666664
-Zeon Chriss,Louisiana,159.7,7,5,0,16.666666666666664
-TJ Finley,Texas State,160.5,14,3,0,17.857142857142858
-Bo Nix,Oregon,178.2,17,1,1,20.833333333333336
-Cooper Legas,Utah State,159.7,13,0,0,10.714285714285714
-Darren Grainger,Georgia State,154.4,8,5,0,20.833333333333336
-Graham Mertz,Florida,163.7,12,2,1,17.857142857142858
-Cameron Ward,Washington State,159.8,14,3,1,16.666666666666664
-Gunnar Watson,Troy,144.8,11,0,0,17.857142857142858
-Grayson McCall,Coastal Carolina,143.9,8,1,0,12.5
-Haynes King,Georgia Tech,155.4,16,2,1,12.5
-Grant Wilson,Old Dominion,134.8,7,1,0,12.5
-Chandler Rogers,North Texas,155.8,12,3,0,12.5
-Carter Bradley,South Alabama,149.2,11,1,0,12.5
-Jordan Travis,Florida State,154.1,13,4,1,25.0
-Shedeur Sanders,Colorado,160.3,21,3,1,14.285714285714285
-Dante Moore,UCLA,129.8,10,0,1,16.666666666666664
-DeQuan Finn,Toledo,149.3,12,4,0,21.428571428571427
-Seth Henigan,Memphis,144.7,13,3,0,16.666666666666664
-Joey Aguilar,Appalachian State,144.5,14,1,0,12.5
-Brayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,12.5
-Taulia Tagovailoa,Maryland,146.0,16,4,1,17.857142857142858
-K.J. Jefferson,Arkansas,148.9,14,1,1,7.142857142857142
-Garrett Shrader,Syracuse,135.5,8,6,1,14.285714285714285
-Dylan Hopkins,New Mexico,130.4,7,1,0,8.333333333333332
-Ashton Daniels,Stanford,139.6,7,0,1,8.333333333333332
-Noah Fifita,Arizona,156.7,8,0,1,14.285714285714285
-Max Johnson,Texas A&M,133.5,7,1,1,14.285714285714285
-Jacob Zeno,UAB,148.3,12,4,0,7.142857142857142
-Will Rogers,Mississippi State,138.7,10,0,1,12.5
-Thomas Castellanos,Boston College,135.5,10,7,1,12.5
-Preston Stone,SMU,137.6,14,1,0,16.666666666666664
-Mikey Keene,Fresno State,147.7,15,0,0,21.428571428571427
-Byrum Brown,South Florida,133.9,12,7,0,10.714285714285714
-Chevan Cordeiro,San Jose State,130.4,8,3,0,7.142857142857142
-Donovan Smith,Houston,144.5,13,4,1,12.5
-Phil Jurkovec,Pitt,124.6,6,1,1,8.333333333333332
-Brayden Schager,Hawaii,137.8,17,1,0,7.142857142857142
-Luke Altmyer,Illinois,127.7,8,3,1,10.714285714285714
-Cam Fancher,Marshall,135.0,7,2,0,16.666666666666664
-Will Howard,Kansas State,130.6,9,6,1,16.666666666666664
-Mitch Griffis,Wake Forest,129.8,9,0,1,12.5
-Riley Leonard,Duke,129.8,3,4,1,20.833333333333336
-Nicholas Vattiato,Middle Tennessee State,137.4,11,2,0,7.142857142857142
-Rocco Becht,Iowa State,134.4,12,2,1,14.285714285714285
-Devin Leary,Kentucky,130.2,14,1,1,17.857142857142858
-Emory Jones,Cincinnati,131.2,11,3,1,8.333333333333332
-Tayven Jackson,Indiana,118.3,2,1,1,8.333333333333332
-Rocky Lombardi,Northern Illinois,123.4,6,2,0,10.714285714285714
-Kyron Drones,Virginia Tech,128.3,6,4,1,10.714285714285714
-Taylen Green,Boise State,116.1,5,4,0,10.714285714285714
-Jack Turner,Louisiana Tech,121.1,5,2,0,9.375
-Jalen Mayden,San Diego State,125.1,6,3,0,10.714285714285714
-Joe Milton,Tennessee,133.6,10,3,1,20.833333333333336
-Drew Allar,Penn State,145.3,12,3,1,25.0
-Kurtis Rourke,Ohio,131.7,8,2,0,17.857142857142858
-Ta'Quan Roberson,Connecticut,131.6,7,1,0,4.166666666666666
-Austin Reed,Western Kentucky,134.2,14,3,0,16.666666666666664
-Noah Kim,Michigan State,119.0,6,0,1,8.333333333333332
-Andrew Peasley,Wyoming,141.6,12,4,0,17.857142857142858
-Michael Alaimo,Kent State,111.2,2,1,0,3.571428571428571
-Hudson Card,Purdue,121.1,7,3,1,7.142857142857142
-Heinrich Haarberg,Nebraska,116.9,4,3,1,12.5
-Davis Brin,Georgia Southern,130.3,12,1,0,16.666666666666664
-Cade Klubnik,Clemson,135.4,11,3,1,16.666666666666664
-Gavin Wimsatt,Rutgers,114.2,7,4,1,17.857142857142858
-E.J. Warner,Temple,121.3,12,0,0,7.142857142857142
-Jase Bauer,Central Michigan,112.2,4,7,0,14.285714285714285
-Payton Thorne,Auburn,118.6,4,2,1,12.5
-Billy Wiles,Southern Mississippi,112.7,7,1,0,4.166666666666666
-Tanner Mordecai,Wisconsin,118.8,3,4,1,16.666666666666664
-Alan Bowman,Oklahoma State,112.6,4,1,1,16.666666666666664
-Brennan Armstrong,North Carolina State,112.5,5,3,1,14.285714285714285
-Daniel Richardson,Florida Atlantic,121.7,5,0,0,12.5
-Jiya Wright,Louisiana-Monroe,114.1,6,1,0,8.333333333333332
-Athan Kaliakmanis,Minnesota,110.8,6,2,1,12.5
-Keegan Shoemaker,Sam Houston,116.2,6,0,0,0.0
-Austin Smith,Eastern Michigan,114.5,6,1,0,14.285714285714285
-Ben Bryant,Northwestern,115.9,6,2,1,12.5
+Jayden Daniels,LSU,197.7,22,4,1,9.996470516382256
+Michael Penix Jr.,Washington,189.9,20,0,1,22.69695237105186
+J.J. McCarthy,Michigan,195.9,14,3,1,21.270050538343227
+Jalen Milroe,Alabama,174.7,11,5,1,13.570723302000426
+Timmy Mcclain,UCF,177.7,9,1,1,1.6849078341013826
+Kaidon Salter,Liberty,175.6,14,6,0,12.20981023988543
+Caleb Williams,USC,187.0,23,6,1,8.420336946119777
+Jaxson Dart,Ole Miss,167.8,12,4,1,17.703387784662432
+Diego Pavia,New Mexico State,167.0,14,2,0,0.7450503077325233
+Kyle McCord,Ohio State,165.9,11,0,1,26.14413878407365
+Dillon Gabriel,Oklahoma,178.2,16,5,1,27.715560317738326
+Brady Cook,Missouri,168.7,14,4,1,16.729790617545717
+Tyler Van Dyke,Miami (FL),171.8,16,1,1,5.311439268232076
+Cardell Williams,Tulsa,151.6,8,3,0,2.171415441176471
+Quinn Ewers,Texas,163.8,11,5,1,20.75175441116404
+Brett Gabbert,Miami (OH),162.9,14,2,0,3.920146548570542
+Jordan McCloud,James Madison,168.1,14,2,0,19.975142045454543
+Carson Beck,Georgia,163.8,12,3,1,15.485074626865671
+Jack Plummer,Louisville,153.2,13,1,1,12.010369640535282
+Sam Hartman,Notre Dame,166.9,18,2,1,15.199267174586778
+Drake Maye,North Carolina,159.1,12,4,1,21.284646674865197
+JT Daniels,Rice,157.4,15,0,0,1.0250516408591794
+Spencer Rattler,South Carolina,163.3,11,2,1,1.2742037978468896
+D.J. Uiagalelei,Oregon State,158.9,15,5,1,14.987510612382634
+Keyone Jenkins,Florida International,133.5,5,4,0,0.618658613936305
+Garrett Greene,West Virginia,143.7,6,5,1,5.763090676883778
+Zeon Chriss,Louisiana,159.7,7,5,0,2.5762195121951215
+TJ Finley,Texas State,160.5,14,3,0,3.075065664479112
+Bo Nix,Oregon,178.2,17,1,1,10.974942044357128
+Cooper Legas,Utah State,159.7,13,0,0,1.8086380318333217
+Darren Grainger,Georgia State,154.4,8,5,0,9.702508336771178
+Graham Mertz,Florida,163.7,12,2,1,5.004320683556366
+Cameron Ward,Washington State,159.8,14,3,1,6.126747240028489
+Gunnar Watson,Troy,144.8,11,0,0,9.012728683930499
+Grayson McCall,Coastal Carolina,143.9,8,1,0,2.9700185403318238
+Haynes King,Georgia Tech,155.4,16,2,1,2.6717275943396226
+Grant Wilson,Old Dominion,134.8,7,1,0,1.1267314721369597
+Chandler Rogers,North Texas,155.8,12,3,0,0.9459459459459462
+Carter Bradley,South Alabama,149.2,11,1,0,2.035137287621359
+Jordan Travis,Florida State,154.1,13,4,1,23.00141752921983
+Jayden Maiava,UNLV,140.3,5,1,0,6.340255400405775
+Shedeur Sanders,Colorado,160.3,21,3,1,3.3095043052368793
+Dante Moore,UCLA,129.8,10,0,1,9.983896940418676
+DeQuan Finn,Toledo,149.3,12,4,0,3.4537886646609453
+Seth Henigan,Memphis,144.7,13,3,0,5.452094625112917
+Joey Aguilar,Appalachian State,144.5,14,1,0,1.9296139171269242
+Brayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,1.4417531718569778
+Taulia Tagovailoa,Maryland,146.0,16,4,1,4.004389579822285
+K.J. Jefferson,Arkansas,148.9,14,1,1,0.541213949654249
+Garrett Shrader,Syracuse,135.5,8,6,1,3.591105011169142
+Dylan Hopkins,New Mexico,130.4,7,1,0,0.298408819083788
+Ashton Daniels,Stanford,139.6,7,0,1,0.7859639513429152
+Chandler Morris,TCU,144.6,12,3,1,3.7084461597614493
+Noah Fifita,Arizona,156.7,8,0,1,3.4744936096058257
+Max Johnson,Texas A&M,133.5,7,1,1,3.307061073261007
+Jacob Zeno,UAB,148.3,12,4,0,0.40883006949742523
+Will Rogers,Mississippi State,138.7,10,0,1,1.602176870748299
+Thomas Castellanos,Boston College,135.5,10,7,1,2.5212681708644276
+Preston Stone,SMU,137.6,14,1,0,3.484857682635864
+Mikey Keene,Fresno State,147.7,15,0,0,4.465065626028063
+Byrum Brown,South Florida,133.9,12,7,0,1.4834943682158241
+Chevan Cordeiro,San Jose State,130.4,8,3,0,0.43959378759469797
+Donovan Smith,Houston,144.5,13,4,1,1.3569846082089552
+Phil Jurkovec,Pitt,124.6,6,1,1,0.5460516122693451
+Brayden Schager,Hawaii,137.8,17,1,0,0.3126073895065902
+Luke Altmyer,Illinois,127.7,8,3,1,1.8241426642919532
+Cam Fancher,Marshall,135.0,7,2,0,4.750060178127255
+Will Howard,Kansas State,130.6,9,6,1,7.379528677010535
+Mitch Griffis,Wake Forest,129.8,9,0,1,1.4392148740192017
+Riley Leonard,Duke,129.8,3,4,1,16.525516391324228
+Nicholas Vattiato,Middle Tennessee State,137.4,11,2,0,0.4310847491706042
+Rocco Becht,Iowa State,134.4,12,2,1,5.310806554517334
+Devin Leary,Kentucky,130.2,14,1,1,5.820780693229675
+Emory Jones,Cincinnati,131.2,11,3,1,0.8282001201923075
+Tayven Jackson,Indiana,118.3,2,1,1,0.6737526165150155
+Kedon Slovis,Brigham Young,128.1,10,3,1,2.71911029486787
+Rocky Lombardi,Northern Illinois,123.4,6,2,0,1.1935816216927155
+Kyron Drones,Virginia Tech,128.3,6,4,1,1.3726528468543207
+Taylen Green,Boise State,116.1,5,4,0,1.4237558654926838
+Jack Turner,Louisiana Tech,121.1,5,2,0,0.3865979381443298
+Jalen Mayden,San Diego State,125.1,6,3,0,1.5487259992754496
+Joe Milton,Tennessee,133.6,10,3,1,10.950425091911764
+Drew Allar,Penn State,145.3,12,3,1,24.810970139689864
+Kurtis Rourke,Ohio,131.7,8,2,0,3.418116014878859
+Ta'Quan Roberson,Connecticut,131.6,7,1,0,0.07637773686890442
+Austin Reed,Western Kentucky,134.2,14,3,0,4.995477883931683
+Noah Kim,Michigan State,119.0,6,0,1,0.9758874520779282
+Andrew Peasley,Wyoming,141.6,12,4,0,9.107826346139213
+Michael Alaimo,Kent State,111.2,2,1,0,0.035410592808551994
+Hudson Card,Purdue,121.1,7,3,1,0.5990409401488118
+Heinrich Haarberg,Nebraska,116.9,4,3,1,2.2462277091906726
+Davis Brin,Georgia Southern,130.3,12,1,0,3.1488850344069195
+Cade Klubnik,Clemson,135.4,11,3,1,8.347862188230616
+Gavin Wimsatt,Rutgers,114.2,7,4,1,6.405312421763326
+E.J. Warner,Temple,121.3,12,0,0,0.21086421327107283
+Jase Bauer,Central Michigan,112.2,4,7,0,2.099125364431487
+Payton Thorne,Auburn,118.6,4,2,1,2.153921072839992
+Billy Wiles,Southern Mississippi,112.7,7,1,0,0.08553542818445446
+Tanner Mordecai,Wisconsin,118.8,3,4,1,6.393294608234562
+Alan Bowman,Oklahoma State,112.6,4,1,1,6.270821085635898
+Brennan Armstrong,North Carolina State,112.5,5,3,1,4.095803331129478
+Daniel Richardson,Florida Atlantic,121.7,5,0,0,2.0897284533648164
+Jiya Wright,Louisiana-Monroe,114.1,6,1,0,0.45108611448337194
+Athan Kaliakmanis,Minnesota,110.8,6,2,1,3.5997308612440193
+Austin Smith,Eastern Michigan,114.5,6,1,0,1.1695764438716405
+Ben Bryant,Northwestern,115.9,6,2,1,2.9203424043062203
 Brendon Lewis,Nevada,102.4,2,3,0,0.0
-Cole Snyder,Buffalo,116.7,11,1,0,7.142857142857142
-Alex Flinn,East Carolina,85.5,1,0,0,4.166666666666666
+Cole Snyder,Buffalo,116.7,11,1,0,0.3553316852262804
+Alex Flinn,East Carolina,85.5,1,0,0,0.07646706398007125
diff --git a/Shiny_App/Weekly_Data.csv b/Shiny_App/Weekly_Data.csv
index d047044..5295ae7 100644
--- a/Shiny_App/Weekly_Data.csv
+++ b/Shiny_App/Weekly_Data.csv
@@ -1,108 +1,110 @@
 Player,School,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI
-Jayden Daniels,LSU,197.7,22,4,1,17.857142857142858
-Michael Penix Jr.,Washington,189.9,20,0,1,25.0
-J.J. McCarthy,Michigan,195.9,14,3,1,25.0
-Jalen Milroe,Alabama,174.7,11,5,1,21.428571428571427
-Timmy Mcclain,UCF,177.7,9,1,1,12.5
-Kaidon Salter,Liberty,175.6,14,6,0,25.0
-Caleb Williams,USC,187.0,23,6,1,21.428571428571427
-Jaxson Dart,Ole Miss,167.8,12,4,1,20.833333333333336
-Diego Pavia,New Mexico State,167.0,14,2,0,14.285714285714285
-Kyle McCord,Ohio State,165.9,11,0,1,25.0
-Dillon Gabriel,Oklahoma,178.2,16,5,1,25.0
-Brady Cook,Missouri,168.7,14,4,1,21.428571428571427
-Tyler Van Dyke,Miami (FL),171.8,16,1,1,16.666666666666664
-Cardell Williams,Tulsa,151.6,8,3,0,12.5
-Quinn Ewers,Texas,163.8,11,5,1,20.833333333333336
-Brett Gabbert,Miami (OH),162.9,14,2,0,21.428571428571427
-Jordan McCloud,James Madison,168.1,14,2,0,25.0
-Carson Beck,Georgia,163.8,12,3,1,25.0
-Jack Plummer,Louisville,153.2,13,1,1,21.428571428571427
-Sam Hartman,Notre Dame,166.9,18,2,1,18.75
-Drake Maye,North Carolina,159.1,12,4,1,25.0
-JT Daniels,Rice,157.4,15,0,0,12.5
-Spencer Rattler,South Carolina,163.3,11,2,1,8.333333333333332
-D.J. Uiagalelei,Oregon State,158.9,15,5,1,21.428571428571427
-Keyone Jenkins,Florida International,133.5,5,4,0,10.714285714285714
-Garrett Greene,West Virginia,143.7,6,5,1,16.666666666666664
-Zeon Chriss,Louisiana,159.7,7,5,0,16.666666666666664
-TJ Finley,Texas State,160.5,14,3,0,17.857142857142858
-Bo Nix,Oregon,178.2,17,1,1,20.833333333333336
-Cooper Legas,Utah State,159.7,13,0,0,10.714285714285714
-Darren Grainger,Georgia State,154.4,8,5,0,20.833333333333336
-Graham Mertz,Florida,163.7,12,2,1,17.857142857142858
-Cameron Ward,Washington State,159.8,14,3,1,16.666666666666664
-Gunnar Watson,Troy,144.8,11,0,0,17.857142857142858
-Grayson McCall,Coastal Carolina,143.9,8,1,0,12.5
-Haynes King,Georgia Tech,155.4,16,2,1,12.5
-Grant Wilson,Old Dominion,134.8,7,1,0,12.5
-Chandler Rogers,North Texas,155.8,12,3,0,12.5
-Carter Bradley,South Alabama,149.2,11,1,0,12.5
-Jordan Travis,Florida State,154.1,13,4,1,25.0
-Shedeur Sanders,Colorado,160.3,21,3,1,14.285714285714285
-Dante Moore,UCLA,129.8,10,0,1,16.666666666666664
-DeQuan Finn,Toledo,149.3,12,4,0,21.428571428571427
-Seth Henigan,Memphis,144.7,13,3,0,16.666666666666664
-Joey Aguilar,Appalachian State,144.5,14,1,0,12.5
-Brayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,12.5
-Taulia Tagovailoa,Maryland,146.0,16,4,1,17.857142857142858
-K.J. Jefferson,Arkansas,148.9,14,1,1,7.142857142857142
-Garrett Shrader,Syracuse,135.5,8,6,1,14.285714285714285
-Dylan Hopkins,New Mexico,130.4,7,1,0,8.333333333333332
-Ashton Daniels,Stanford,139.6,7,0,1,8.333333333333332
-Noah Fifita,Arizona,156.7,8,0,1,14.285714285714285
-Max Johnson,Texas A&M,133.5,7,1,1,14.285714285714285
-Jacob Zeno,UAB,148.3,12,4,0,7.142857142857142
-Will Rogers,Mississippi State,138.7,10,0,1,12.5
-Thomas Castellanos,Boston College,135.5,10,7,1,12.5
-Preston Stone,SMU,137.6,14,1,0,16.666666666666664
-Mikey Keene,Fresno State,147.7,15,0,0,21.428571428571427
-Byrum Brown,South Florida,133.9,12,7,0,10.714285714285714
-Chevan Cordeiro,San Jose State,130.4,8,3,0,7.142857142857142
-Donovan Smith,Houston,144.5,13,4,1,12.5
-Phil Jurkovec,Pitt,124.6,6,1,1,8.333333333333332
-Brayden Schager,Hawaii,137.8,17,1,0,7.142857142857142
-Luke Altmyer,Illinois,127.7,8,3,1,10.714285714285714
-Cam Fancher,Marshall,135.0,7,2,0,16.666666666666664
-Will Howard,Kansas State,130.6,9,6,1,16.666666666666664
-Mitch Griffis,Wake Forest,129.8,9,0,1,12.5
-Riley Leonard,Duke,129.8,3,4,1,20.833333333333336
-Nicholas Vattiato,Middle Tennessee State,137.4,11,2,0,7.142857142857142
-Rocco Becht,Iowa State,134.4,12,2,1,14.285714285714285
-Devin Leary,Kentucky,130.2,14,1,1,17.857142857142858
-Emory Jones,Cincinnati,131.2,11,3,1,8.333333333333332
-Tayven Jackson,Indiana,118.3,2,1,1,8.333333333333332
-Rocky Lombardi,Northern Illinois,123.4,6,2,0,10.714285714285714
-Kyron Drones,Virginia Tech,128.3,6,4,1,10.714285714285714
-Taylen Green,Boise State,116.1,5,4,0,10.714285714285714
-Jack Turner,Louisiana Tech,121.1,5,2,0,9.375
-Jalen Mayden,San Diego State,125.1,6,3,0,10.714285714285714
-Joe Milton,Tennessee,133.6,10,3,1,20.833333333333336
-Drew Allar,Penn State,145.3,12,3,1,25.0
-Kurtis Rourke,Ohio,131.7,8,2,0,17.857142857142858
-Ta'Quan Roberson,Connecticut,131.6,7,1,0,4.166666666666666
-Austin Reed,Western Kentucky,134.2,14,3,0,16.666666666666664
-Noah Kim,Michigan State,119.0,6,0,1,8.333333333333332
-Andrew Peasley,Wyoming,141.6,12,4,0,17.857142857142858
-Michael Alaimo,Kent State,111.2,2,1,0,3.571428571428571
-Hudson Card,Purdue,121.1,7,3,1,7.142857142857142
-Heinrich Haarberg,Nebraska,116.9,4,3,1,12.5
-Davis Brin,Georgia Southern,130.3,12,1,0,16.666666666666664
-Cade Klubnik,Clemson,135.4,11,3,1,16.666666666666664
-Gavin Wimsatt,Rutgers,114.2,7,4,1,17.857142857142858
-E.J. Warner,Temple,121.3,12,0,0,7.142857142857142
-Jase Bauer,Central Michigan,112.2,4,7,0,14.285714285714285
-Payton Thorne,Auburn,118.6,4,2,1,12.5
-Billy Wiles,Southern Mississippi,112.7,7,1,0,4.166666666666666
-Tanner Mordecai,Wisconsin,118.8,3,4,1,16.666666666666664
-Alan Bowman,Oklahoma State,112.6,4,1,1,16.666666666666664
-Brennan Armstrong,North Carolina State,112.5,5,3,1,14.285714285714285
-Daniel Richardson,Florida Atlantic,121.7,5,0,0,12.5
-Jiya Wright,Louisiana-Monroe,114.1,6,1,0,8.333333333333332
-Athan Kaliakmanis,Minnesota,110.8,6,2,1,12.5
-Keegan Shoemaker,Sam Houston,116.2,6,0,0,0.0
-Austin Smith,Eastern Michigan,114.5,6,1,0,14.285714285714285
-Ben Bryant,Northwestern,115.9,6,2,1,12.5
+Jayden Daniels,LSU,197.7,22,4,1,9.996470516382256
+Michael Penix Jr.,Washington,189.9,20,0,1,22.69695237105186
+J.J. McCarthy,Michigan,195.9,14,3,1,21.270050538343227
+Jalen Milroe,Alabama,174.7,11,5,1,13.570723302000426
+Timmy Mcclain,UCF,177.7,9,1,1,1.6849078341013826
+Kaidon Salter,Liberty,175.6,14,6,0,12.20981023988543
+Caleb Williams,USC,187.0,23,6,1,8.420336946119777
+Jaxson Dart,Ole Miss,167.8,12,4,1,17.703387784662432
+Diego Pavia,New Mexico State,167.0,14,2,0,0.7450503077325233
+Kyle McCord,Ohio State,165.9,11,0,1,26.14413878407365
+Dillon Gabriel,Oklahoma,178.2,16,5,1,27.715560317738326
+Brady Cook,Missouri,168.7,14,4,1,16.729790617545717
+Tyler Van Dyke,Miami (FL),171.8,16,1,1,5.311439268232076
+Cardell Williams,Tulsa,151.6,8,3,0,2.171415441176471
+Quinn Ewers,Texas,163.8,11,5,1,20.75175441116404
+Brett Gabbert,Miami (OH),162.9,14,2,0,3.920146548570542
+Jordan McCloud,James Madison,168.1,14,2,0,19.975142045454543
+Carson Beck,Georgia,163.8,12,3,1,15.485074626865671
+Jack Plummer,Louisville,153.2,13,1,1,12.010369640535282
+Sam Hartman,Notre Dame,166.9,18,2,1,15.199267174586778
+Drake Maye,North Carolina,159.1,12,4,1,21.284646674865197
+JT Daniels,Rice,157.4,15,0,0,1.0250516408591794
+Spencer Rattler,South Carolina,163.3,11,2,1,1.2742037978468896
+D.J. Uiagalelei,Oregon State,158.9,15,5,1,14.987510612382634
+Keyone Jenkins,Florida International,133.5,5,4,0,0.618658613936305
+Garrett Greene,West Virginia,143.7,6,5,1,5.763090676883778
+Zeon Chriss,Louisiana,159.7,7,5,0,2.5762195121951215
+TJ Finley,Texas State,160.5,14,3,0,3.075065664479112
+Bo Nix,Oregon,178.2,17,1,1,10.974942044357128
+Cooper Legas,Utah State,159.7,13,0,0,1.8086380318333217
+Darren Grainger,Georgia State,154.4,8,5,0,9.702508336771178
+Graham Mertz,Florida,163.7,12,2,1,5.004320683556366
+Cameron Ward,Washington State,159.8,14,3,1,6.126747240028489
+Gunnar Watson,Troy,144.8,11,0,0,9.012728683930499
+Grayson McCall,Coastal Carolina,143.9,8,1,0,2.9700185403318238
+Haynes King,Georgia Tech,155.4,16,2,1,2.6717275943396226
+Grant Wilson,Old Dominion,134.8,7,1,0,1.1267314721369597
+Chandler Rogers,North Texas,155.8,12,3,0,0.9459459459459462
+Carter Bradley,South Alabama,149.2,11,1,0,2.035137287621359
+Jordan Travis,Florida State,154.1,13,4,1,23.00141752921983
+Jayden Maiava,UNLV,140.3,5,1,0,6.340255400405775
+Shedeur Sanders,Colorado,160.3,21,3,1,3.3095043052368793
+Dante Moore,UCLA,129.8,10,0,1,9.983896940418676
+DeQuan Finn,Toledo,149.3,12,4,0,3.4537886646609453
+Seth Henigan,Memphis,144.7,13,3,0,5.452094625112917
+Joey Aguilar,Appalachian State,144.5,14,1,0,1.9296139171269242
+Brayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,1.4417531718569778
+Taulia Tagovailoa,Maryland,146.0,16,4,1,4.004389579822285
+K.J. Jefferson,Arkansas,148.9,14,1,1,0.541213949654249
+Garrett Shrader,Syracuse,135.5,8,6,1,3.591105011169142
+Dylan Hopkins,New Mexico,130.4,7,1,0,0.298408819083788
+Ashton Daniels,Stanford,139.6,7,0,1,0.7859639513429152
+Chandler Morris,TCU,144.6,12,3,1,3.7084461597614493
+Noah Fifita,Arizona,156.7,8,0,1,3.4744936096058257
+Max Johnson,Texas A&M,133.5,7,1,1,3.307061073261007
+Jacob Zeno,UAB,148.3,12,4,0,0.40883006949742523
+Will Rogers,Mississippi State,138.7,10,0,1,1.602176870748299
+Thomas Castellanos,Boston College,135.5,10,7,1,2.5212681708644276
+Preston Stone,SMU,137.6,14,1,0,3.484857682635864
+Mikey Keene,Fresno State,147.7,15,0,0,4.465065626028063
+Byrum Brown,South Florida,133.9,12,7,0,1.4834943682158241
+Chevan Cordeiro,San Jose State,130.4,8,3,0,0.43959378759469797
+Donovan Smith,Houston,144.5,13,4,1,1.3569846082089552
+Phil Jurkovec,Pitt,124.6,6,1,1,0.5460516122693451
+Brayden Schager,Hawaii,137.8,17,1,0,0.3126073895065902
+Luke Altmyer,Illinois,127.7,8,3,1,1.8241426642919532
+Cam Fancher,Marshall,135.0,7,2,0,4.750060178127255
+Will Howard,Kansas State,130.6,9,6,1,7.379528677010535
+Mitch Griffis,Wake Forest,129.8,9,0,1,1.4392148740192017
+Riley Leonard,Duke,129.8,3,4,1,16.525516391324228
+Nicholas Vattiato,Middle Tennessee State,137.4,11,2,0,0.4310847491706042
+Rocco Becht,Iowa State,134.4,12,2,1,5.310806554517334
+Devin Leary,Kentucky,130.2,14,1,1,5.820780693229675
+Emory Jones,Cincinnati,131.2,11,3,1,0.8282001201923075
+Tayven Jackson,Indiana,118.3,2,1,1,0.6737526165150155
+Kedon Slovis,Brigham Young,128.1,10,3,1,2.71911029486787
+Rocky Lombardi,Northern Illinois,123.4,6,2,0,1.1935816216927155
+Kyron Drones,Virginia Tech,128.3,6,4,1,1.3726528468543207
+Taylen Green,Boise State,116.1,5,4,0,1.4237558654926838
+Jack Turner,Louisiana Tech,121.1,5,2,0,0.3865979381443298
+Jalen Mayden,San Diego State,125.1,6,3,0,1.5487259992754496
+Joe Milton,Tennessee,133.6,10,3,1,10.950425091911764
+Drew Allar,Penn State,145.3,12,3,1,24.810970139689864
+Kurtis Rourke,Ohio,131.7,8,2,0,3.418116014878859
+Ta'Quan Roberson,Connecticut,131.6,7,1,0,0.07637773686890442
+Austin Reed,Western Kentucky,134.2,14,3,0,4.995477883931683
+Noah Kim,Michigan State,119.0,6,0,1,0.9758874520779282
+Andrew Peasley,Wyoming,141.6,12,4,0,9.107826346139213
+Michael Alaimo,Kent State,111.2,2,1,0,0.035410592808551994
+Hudson Card,Purdue,121.1,7,3,1,0.5990409401488118
+Heinrich Haarberg,Nebraska,116.9,4,3,1,2.2462277091906726
+Davis Brin,Georgia Southern,130.3,12,1,0,3.1488850344069195
+Cade Klubnik,Clemson,135.4,11,3,1,8.347862188230616
+Gavin Wimsatt,Rutgers,114.2,7,4,1,6.405312421763326
+E.J. Warner,Temple,121.3,12,0,0,0.21086421327107283
+Jase Bauer,Central Michigan,112.2,4,7,0,2.099125364431487
+Payton Thorne,Auburn,118.6,4,2,1,2.153921072839992
+Billy Wiles,Southern Mississippi,112.7,7,1,0,0.08553542818445446
+Tanner Mordecai,Wisconsin,118.8,3,4,1,6.393294608234562
+Alan Bowman,Oklahoma State,112.6,4,1,1,6.270821085635898
+Brennan Armstrong,North Carolina State,112.5,5,3,1,4.095803331129478
+Daniel Richardson,Florida Atlantic,121.7,5,0,0,2.0897284533648164
+Jiya Wright,Louisiana-Monroe,114.1,6,1,0,0.45108611448337194
+Athan Kaliakmanis,Minnesota,110.8,6,2,1,3.5997308612440193
+Austin Smith,Eastern Michigan,114.5,6,1,0,1.1695764438716405
+Ben Bryant,Northwestern,115.9,6,2,1,2.9203424043062203
 Brendon Lewis,Nevada,102.4,2,3,0,0.0
-Cole Snyder,Buffalo,116.7,11,1,0,7.142857142857142
-Alex Flinn,East Carolina,85.5,1,0,0,4.166666666666666
+Cole Snyder,Buffalo,116.7,11,1,0,0.3553316852262804
+Alex Flinn,East Carolina,85.5,1,0,0,0.07646706398007125
diff --git a/docs/app.json b/docs/app.json
index 9f2f019..4a58148 100644
--- a/docs/app.json
+++ b/docs/app.json
@@ -1 +1 @@
-[{"name": "app.py", "content": "from shiny import App, ui, render\nimport pandas as pd\nimport numpy as np\nimport pickle\nimport statsmodels.api as sm\nfrom shinywidgets import output_widget, render_widget\nimport plotly.express as px\nfrom pathlib import Path\n\nmodel_path = Path(__file__).parent / \"heisman_model.pkl\"\nmodel_data_path = Path(__file__).parent / \"Model_Data.csv\"\nweekly_data_path = Path(__file__).parent / \"Weekly_Data.csv\"\n\nmodel = pickle.load(open(model_path, 'rb'))\n################### Historical #########################\nmodel_data = pd.read_csv(model_data_path).reset_index(drop = True)\n\npredict_data =  model_data[['Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']]\npredict_data = sm.tools.add_constant(predict_data)\npredict_data['Prediction'] = model.predict(predict_data)\npredict_data = predict_data['Prediction']\n\nmodel_data = pd.merge(model_data, predict_data, left_index=True, right_index=True)\nmodel_data['CPI'] = model_data['CPI'].round(2)\nmodel_data['Prediction'] = model_data['Prediction'].round(2)\n\n################### Current #########################\ncurrent_df = pd.read_csv(weekly_data_path).reset_index(drop = True)\n\ncurrent_predict_df =  current_df[['Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']]\ncurrent_predict_df = sm.tools.add_constant(current_predict_df)\ncurrent_predict_df['Projected Voting Points'] = model.predict(current_predict_df)\ncurrent_predict_df = current_predict_df['Projected Voting Points']\n\ncurrent_df = pd.merge(current_df, current_predict_df, left_index=True, right_index=True)\ncurrent_df['CPI'] = current_df['CPI'].round(2)\ncurrent_df['Projected Voting Points'] = current_df['Projected Voting Points'].round(2)\n\n\n# Part 1: ui ----\napp_ui = ui.page_fluid(\n    ui.navset_tab(\n        ui.nav(\"Model Details\", \n           \n        ui.markdown(\n            \"\"\"\n            # So how does this model work anyway?\n            This is a project that I spent the summer of 2020 on in my free time.\n            <br />\n\n            Simply put, the model aims to predict the finals standings in Heisman voting for quarterbacks\n            specifically. This is mostly because it is difficult to come up with a sample of metrics that apply\n            to the different positions across college football.\n            <br />\n\n            The model itself is a linear regression with voting points as a response, and individual and team\n            statitistics as the predictors. The model is built with training data from the 2006 to 2018 seasons.\n            <br />\n\n            The model is made up of the following 5 predictors;\n            <br />\n            \n            **Passer Rating** : Passer efficency rating as according to pro-football-reference.com.\n            <br />\n\n            **Passing TDs** : Number of passing touchdowns thrown by a quarterback.\n            <br />\n\n            **Rushing TDs** : Number of rushing touchdowns ran by a quarterback.\n            <br />\n\n            **Power 5 Indicator** : A binary value of 0 or 1. Set equal to 1, \n            if the quarterback's team plays in a power 5 conference. Otherwise 0. Notre Dame is the only independent team \n            to receive a power 5 label.\n            <br />\n\n            **CPI** : A team strength of record metric involving the winning percentages of opponents. More details \n            of the metric can be found at www.cpiratings.com/about.html.\n            \"\"\"\n        )\n               ),\n        ui.nav(\"Past Model Results\", \n           \n        ui.input_select(\"model_year\", \"Model Year\", model_data['Year'].tolist()),\n        ui.output_table(\"historical_data\")\n               ),\n\n    ui.nav(\"Current Model Results\", \n           \n        ui.output_table(\"current_data\")\n               ),\n    \n    ui.nav(\"What If\", \n           \n        ui.input_numeric(\"what_if_QBR\", \"Passer Rating\", value=0.0),\n        ui.input_numeric(\"what_if_pass_TD\", \"Passing TDs\", value=0),\n        ui.input_numeric(\"what_if_rush_TD\", \"Rushing TDs\", value=0),\n        ui.input_radio_buttons(\"what_if_power_5\", \"Power 5 Conference\",  {1 : \"Yes\", 0: \"No\"}),\n        ui.input_numeric(\"what_if_CPI\", \"CPI\", value=0.0),\n        ui.output_text(\"what_if_analysis\")\n               ),\n    \n    ui.nav(\"Scatter\",\n           ui.div(\n           output_widget(\"my_widget\")\n           )\n           )\n    )\n)\n\n\n\n\n# Part 2: server ----\ndef server(input, output, session):\n\n    @output\n    @render.table\n    def historical_data():\n\n        result_df = model_data[model_data['Year'] == int(input.model_year())]\n\n        result_df['Actual_Rank'] = result_df['points_won'].rank(ascending = False).astype('int')\n        result_df['Predicted_Rank'] = result_df['Prediction'].rank(ascending = False).astype('int')\n\n        result_cols = ['Player', 'School', 'Actual_Rank', 'Predicted_Rank', 'Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']\n        result_df = result_df[result_cols]\n\n        return result_df\n    \n    @output\n    @render.table\n    def current_data():\n\n        result_df = current_df\n\n        result_df = result_df.sort_values(by = 'Projected Voting Points', ascending = False)\n        result_df = result_df.reset_index(drop = True)\n        result_df['Rank'] = result_df.index + 1\n        result_cols = ['Rank', 'Player', 'School', 'Projected Voting Points', 'Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']\n        result_df = result_df[result_cols]\n\n        return result_df\n    \n    @output\n    @render.text\n    def what_if_analysis():\n\n        what_if_df = pd.DataFrame({\n            'Passing_Rate' : [float(input.what_if_QBR())],\n            'Passing_TD' : [int(input.what_if_pass_TD())],\n            'Rushing_TD' : [int(input.what_if_rush_TD())],\n            'Power5' : [int(input.what_if_power_5())],\n            'CPI' : [float(input.what_if_CPI())]\n        })\n\n        what_if_df = sm.tools.add_constant(what_if_df, has_constant='add')\n\n        what_if_df['Prediction'] = model.predict(what_if_df)\n\n        result = what_if_df.iloc[0]['Prediction']\n        result = result.round(2)\n\n        return f\"A player with these statistics would have {result} projected voting points.\"\n    \n    @output\n    @render_widget\n    def my_widget():\n        fig = px.scatter(\n            model_data, x=\"Year\", y=\"Prediction\",\n            hover_data=['Player']\n        )\n        return fig\n\n# Combine into a shiny app.\n# Note that the variable must be \"app\".\napp = App(app_ui, server)", "type": "text"}, {"name": "Model_Data.csv", "content": "Player,School,Year,points_won,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI\nTroy Smith,Ohio State,2006,2540,161.9,30,1,1,15.013680174870936\nBrady Quinn,Notre Dame,2006,782,146.7,37,2,1,8.231919146738909\nColt Brennan,Hawaii,2006,202,186.0,58,5,0,6.365435540069685\nTim Tebow,Florida,2007,1957,172.5,32,23,1,7.987912822160973\nColt Brennan,Hawaii,2007,632,159.8,38,8,0,7.5994759572849\nChase Daniel,Missouri,2007,425,147.9,33,4,1,11.748104548755686\nDennis Dixon,Oregon,2007,178,161.2,20,9,1,6.540100800550993\nPat White,West Virginia,2007,150,151.4,14,14,0,11.379512110196254\nMatt Ryan,Boston College,2007,63,127.0,31,2,1,8.768469146897912\nSam Bradford,Oklahoma,2008,1726,180.8,50,5,1,15.05704821146074\nColt McCoy,Texas,2008,1604,173.8,34,11,1,18.946208112380297\nTim Tebow,Florida,2008,1575,172.4,30,12,1,19.409963559776127\nGraham Harrell,Texas Tech,2008,213,160.0,45,6,1,13.05053009399466\nPat White,West Virginia,2008,19,142.3,21,8,0,6.385230641176652\nNate Davis,Ball State,2008,10,157.0,26,5,0,6.050702467936028\nColt McCoy,Texas,2009,1145,147.4,27,3,1,16.18331903502398\nTim Tebow,Florida,2009,390,164.2,21,14,1,18.51486090299109\nKellen Moore,Boise State,2009,100,161.7,39,1,0,14.46082921027991\nCase Keenum,Houston,2009,37,154.8,44,4,0,4.218052997436561\nCam Newton,Auburn,2010,2263,182.0,30,20,1,23.86780983482786\nAndrew Luck,Stanford,2010,1079,170.2,32,3,1,13.946308906421848\nKellen Moore,Boise State,2010,635,182.6,35,1,0,12.802241937566109\nDenard Robinson,Michigan,2010,84,149.6,18,14,1,3.2478886059804224\nRyan Mallett,Arkansas,2010,41,163.6,32,4,1,10.82973394387262\nColin Kaepernick,Nevada,2010,31,150.5,21,20,0,11.384387560083765\nAndy Dalton,TCU,2010,30,166.5,27,6,0,14.944350584507326\nRobert Griffin III,Baylor,2011,1687,189.5,37,10,1,10.316157413813375\nAndrew Luck,Stanford,2011,1407,169.7,37,2,1,9.667409405228565\nMatt Barkley,USC,2011,153,161.2,39,2,1,9.562203977574791\nCase Keenum,Houston,2011,123,174.0,48,3,0,11.420863535280626\nKellen Moore,Boise State,2011,90,175.2,43,0,0,12.265954369362133\nRussell Wilson,Wisconsin,2011,52,191.8,33,6,1,8.281890427937858\nJohnny Manziel,Texas A&M,2012,2029,155.3,26,21,1,15.754760156860875\nCollin Klein,Kansas State,2012,894,149.2,16,23,1,11.817693133497077\nBraxton Miller,Ohio State,2012,144,140.5,15,13,1,15.169148199200322\nJordan Lynch,Northern Illinois,2012,52,144.9,25,19,0,6.92703223246081\nJameis Winston,Florida State,2013,2205,184.8,40,4,1,19.32052650022246\nA.J. McCarron,Alabama,2013,704,167.2,28,0,1,11.90196866646686\nJordan Lynch,Northern Illinois,2013,558,138.4,24,23,0,7.111211920283987\nJohnny Manziel,Texas A&M,2013,421,172.9,37,9,1,8.051361094960829\nBryce Petty,Baylor,2013,127,174.3,32,14,1,11.402244928532845\nDerek Carr,Fresno State,2013,107,156.3,50,2,0,7.156147448813237\nBraxton Miller,Ohio State,2013,91,158.1,24,12,1,10.39338163747249\nMarcus Mariota,Oregon,2014,2534,181.7,42,15,1,16.12744333111277\nTrevone Boykin,TCU,2014,218,145.9,33,8,1,13.076626318134918\nJ.T. Barrett,Ohio State,2014,78,169.8,34,11,1,20.0747422358138\nJameis Winston,Florida State,2014,51,145.5,25,3,1,18.46103191334333\nDak Prescott,Mississippi State,2014,21,151.7,27,14,1,9.456126458240307\nDeshaun Watson,Clemson,2015,1165,156.3,35,12,1,19.16167854243615\nBaker Mayfield,Oklahoma,2015,334,173.3,36,7,1,12.740224517380366\nKeenan Reynolds,Navy,2015,180,162.1,8,24,0,10.128862442591032\nConnor Cook,Michigan State,2015,13,136.6,24,0,1,14.713371407886711\nLamar Jackson,Louisville,2016,2144,148.8,30,21,1,5.608782090662399\nDeshaun Watson,Clemson,2016,1524,151.1,41,9,1,23.78005620893973\nBaker Mayfield,Oklahoma,2016,361,196.4,40,6,1,11.25001891558911\nJake Browning,Washington,2016,182,167.5,43,4,1,12.923870541835983\nBaker Mayfield,Oklahoma,2017,2398,198.9,43,5,1,11.183099131224177\nLamar Jackson,Louisville,2017,793,146.6,27,18,1,3.9226957076095994\nMason Rudolph,Oklahoma State,2017,56,170.6,37,10,1,6.425405376500221\nMcKenzie Milton,UCF,2017,54,179.3,37,8,0,19.08379077956817\nKyler Murray,Oklahoma,2018,2167,199.2,42,12,1,12.942861869472573\nTua Tagovailoa,Alabama,2018,1871,199.4,43,5,1,20.688097541235337\nDwayne Haskins,Ohio State,2018,783,174.1,50,4,1,13.097950650643533\nWill Grier,West Virginia,2018,126,175.5,37,3,1,5.5749718367802\nGardner Minshew,Washington State,2018,122,147.6,38,4,1,10.593990104817577\nMcKenzie Milton,UCF,2018,39,161.0,25,9,0,11.842688493982308\nJoe Burrow,LSU,2019,2608,202.0,60,5,1,27.81090580974389\nJalen Hurts,Oklahoma,2019,762,191.2,32,20,1,11.86131918185052\nJustin Fields,Ohio State,2019,747,181.4,41,10,1,19.03510596761913\nTrevor Lawrence,Clemson,2019,88,166.7,36,9,1,17.71916867557893\n", "type": "text"}, {"name": "Weekly_Data.csv", "content": "Player,School,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI\nJayden Daniels,LSU,197.7,22,4,1,17.857142857142858\nMichael Penix Jr.,Washington,189.9,20,0,1,25.0\nJ.J. McCarthy,Michigan,195.9,14,3,1,25.0\nJalen Milroe,Alabama,174.7,11,5,1,21.428571428571427\nTimmy Mcclain,UCF,177.7,9,1,1,12.5\nKaidon Salter,Liberty,175.6,14,6,0,25.0\nCaleb Williams,USC,187.0,23,6,1,21.428571428571427\nJaxson Dart,Ole Miss,167.8,12,4,1,20.833333333333336\nDiego Pavia,New Mexico State,167.0,14,2,0,14.285714285714285\nKyle McCord,Ohio State,165.9,11,0,1,25.0\nDillon Gabriel,Oklahoma,178.2,16,5,1,25.0\nBrady Cook,Missouri,168.7,14,4,1,21.428571428571427\nTyler Van Dyke,Miami (FL),171.8,16,1,1,16.666666666666664\nCardell Williams,Tulsa,151.6,8,3,0,12.5\nQuinn Ewers,Texas,163.8,11,5,1,20.833333333333336\nBrett Gabbert,Miami (OH),162.9,14,2,0,21.428571428571427\nJordan McCloud,James Madison,168.1,14,2,0,25.0\nCarson Beck,Georgia,163.8,12,3,1,25.0\nJack Plummer,Louisville,153.2,13,1,1,21.428571428571427\nSam Hartman,Notre Dame,166.9,18,2,1,18.75\nDrake Maye,North Carolina,159.1,12,4,1,25.0\nJT Daniels,Rice,157.4,15,0,0,12.5\nSpencer Rattler,South Carolina,163.3,11,2,1,8.333333333333332\nD.J. Uiagalelei,Oregon State,158.9,15,5,1,21.428571428571427\nKeyone Jenkins,Florida International,133.5,5,4,0,10.714285714285714\nGarrett Greene,West Virginia,143.7,6,5,1,16.666666666666664\nZeon Chriss,Louisiana,159.7,7,5,0,16.666666666666664\nTJ Finley,Texas State,160.5,14,3,0,17.857142857142858\nBo Nix,Oregon,178.2,17,1,1,20.833333333333336\nCooper Legas,Utah State,159.7,13,0,0,10.714285714285714\nDarren Grainger,Georgia State,154.4,8,5,0,20.833333333333336\nGraham Mertz,Florida,163.7,12,2,1,17.857142857142858\nCameron Ward,Washington State,159.8,14,3,1,16.666666666666664\nGunnar Watson,Troy,144.8,11,0,0,17.857142857142858\nGrayson McCall,Coastal Carolina,143.9,8,1,0,12.5\nHaynes King,Georgia Tech,155.4,16,2,1,12.5\nGrant Wilson,Old Dominion,134.8,7,1,0,12.5\nChandler Rogers,North Texas,155.8,12,3,0,12.5\nCarter Bradley,South Alabama,149.2,11,1,0,12.5\nJordan Travis,Florida State,154.1,13,4,1,25.0\nShedeur Sanders,Colorado,160.3,21,3,1,14.285714285714285\nDante Moore,UCLA,129.8,10,0,1,16.666666666666664\nDeQuan Finn,Toledo,149.3,12,4,0,21.428571428571427\nSeth Henigan,Memphis,144.7,13,3,0,16.666666666666664\nJoey Aguilar,Appalachian State,144.5,14,1,0,12.5\nBrayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,12.5\nTaulia Tagovailoa,Maryland,146.0,16,4,1,17.857142857142858\nK.J. Jefferson,Arkansas,148.9,14,1,1,7.142857142857142\nGarrett Shrader,Syracuse,135.5,8,6,1,14.285714285714285\nDylan Hopkins,New Mexico,130.4,7,1,0,8.333333333333332\nAshton Daniels,Stanford,139.6,7,0,1,8.333333333333332\nNoah Fifita,Arizona,156.7,8,0,1,14.285714285714285\nMax Johnson,Texas A&M,133.5,7,1,1,14.285714285714285\nJacob Zeno,UAB,148.3,12,4,0,7.142857142857142\nWill Rogers,Mississippi State,138.7,10,0,1,12.5\nThomas Castellanos,Boston College,135.5,10,7,1,12.5\nPreston Stone,SMU,137.6,14,1,0,16.666666666666664\nMikey Keene,Fresno State,147.7,15,0,0,21.428571428571427\nByrum Brown,South Florida,133.9,12,7,0,10.714285714285714\nChevan Cordeiro,San Jose State,130.4,8,3,0,7.142857142857142\nDonovan Smith,Houston,144.5,13,4,1,12.5\nPhil Jurkovec,Pitt,124.6,6,1,1,8.333333333333332\nBrayden Schager,Hawaii,137.8,17,1,0,7.142857142857142\nLuke Altmyer,Illinois,127.7,8,3,1,10.714285714285714\nCam Fancher,Marshall,135.0,7,2,0,16.666666666666664\nWill Howard,Kansas State,130.6,9,6,1,16.666666666666664\nMitch Griffis,Wake Forest,129.8,9,0,1,12.5\nRiley Leonard,Duke,129.8,3,4,1,20.833333333333336\nNicholas Vattiato,Middle Tennessee State,137.4,11,2,0,7.142857142857142\nRocco Becht,Iowa State,134.4,12,2,1,14.285714285714285\nDevin Leary,Kentucky,130.2,14,1,1,17.857142857142858\nEmory Jones,Cincinnati,131.2,11,3,1,8.333333333333332\nTayven Jackson,Indiana,118.3,2,1,1,8.333333333333332\nRocky Lombardi,Northern Illinois,123.4,6,2,0,10.714285714285714\nKyron Drones,Virginia Tech,128.3,6,4,1,10.714285714285714\nTaylen Green,Boise State,116.1,5,4,0,10.714285714285714\nJack Turner,Louisiana Tech,121.1,5,2,0,9.375\nJalen Mayden,San Diego State,125.1,6,3,0,10.714285714285714\nJoe Milton,Tennessee,133.6,10,3,1,20.833333333333336\nDrew Allar,Penn State,145.3,12,3,1,25.0\nKurtis Rourke,Ohio,131.7,8,2,0,17.857142857142858\nTa'Quan Roberson,Connecticut,131.6,7,1,0,4.166666666666666\nAustin Reed,Western Kentucky,134.2,14,3,0,16.666666666666664\nNoah Kim,Michigan State,119.0,6,0,1,8.333333333333332\nAndrew Peasley,Wyoming,141.6,12,4,0,17.857142857142858\nMichael Alaimo,Kent State,111.2,2,1,0,3.571428571428571\nHudson Card,Purdue,121.1,7,3,1,7.142857142857142\nHeinrich Haarberg,Nebraska,116.9,4,3,1,12.5\nDavis Brin,Georgia Southern,130.3,12,1,0,16.666666666666664\nCade Klubnik,Clemson,135.4,11,3,1,16.666666666666664\nGavin Wimsatt,Rutgers,114.2,7,4,1,17.857142857142858\nE.J. Warner,Temple,121.3,12,0,0,7.142857142857142\nJase Bauer,Central Michigan,112.2,4,7,0,14.285714285714285\nPayton Thorne,Auburn,118.6,4,2,1,12.5\nBilly Wiles,Southern Mississippi,112.7,7,1,0,4.166666666666666\nTanner Mordecai,Wisconsin,118.8,3,4,1,16.666666666666664\nAlan Bowman,Oklahoma State,112.6,4,1,1,16.666666666666664\nBrennan Armstrong,North Carolina State,112.5,5,3,1,14.285714285714285\nDaniel Richardson,Florida Atlantic,121.7,5,0,0,12.5\nJiya Wright,Louisiana-Monroe,114.1,6,1,0,8.333333333333332\nAthan Kaliakmanis,Minnesota,110.8,6,2,1,12.5\nKeegan Shoemaker,Sam Houston,116.2,6,0,0,0.0\nAustin Smith,Eastern Michigan,114.5,6,1,0,14.285714285714285\nBen Bryant,Northwestern,115.9,6,2,1,12.5\nBrendon Lewis,Nevada,102.4,2,3,0,0.0\nCole Snyder,Buffalo,116.7,11,1,0,7.142857142857142\nAlex Flinn,East Carolina,85.5,1,0,0,4.166666666666666\n", "type": "text"}, {"name": "heisman_model.pkl", "content": "gASVGDsAAAAAAACMI3N0YXRzbW9kZWxzLnJlZ3Jlc3Npb24ubGluZWFyX21vZGVslIwYUmVncmVzc2lvblJlc3VsdHNXcmFwcGVylJOUKYGUfZQojAhfcmVzdWx0c5RoAIwKT0xTUmVzdWx0c5STlCmBlH2UKIwGcGFyYW1zlIwVbnVtcHkuY29yZS5tdWx0aWFycmF5lIwMX3JlY29uc3RydWN0lJOUjAVudW1weZSMB25kYXJyYXmUk5RLAIWUQwFilIeUUpQoSwFLBoWUaA6MBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMwEKe0LLHUqMCBOhzYBe0mQE+UaKKMZTRAprDxtdCxRkCRWmqPTkOBQC5Ah5baiUVAlHSUYowFbW9kZWyUaACMA09MU5STlCmBlH2UKIwHd2VpZ2h0c5RoDWgQSwCFlGgSh5RSlChLAUtChZRoGolCEAIAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwP5R0lGKMBGRhdGGUjBVzdGF0c21vZGVscy5iYXNlLmRhdGGUjApQYW5kYXNEYXRhlJOUKYGUfZQojApvcmlnX2VuZG9nlIwRcGFuZGFzLmNvcmUuZnJhbWWUjAlEYXRhRnJhbWWUk5QpgZR9lCiMBF9tZ3KUjB5wYW5kYXMuY29yZS5pbnRlcm5hbHMubWFuYWdlcnOUjAxCbG9ja01hbmFnZXKUk5SMFnBhbmRhcy5fbGlicy5pbnRlcm5hbHOUjA9fdW5waWNrbGVfYmxvY2uUk5RoDWgQSwCFlGgSh5RSlChLAUsBS0KGlGgXjAJpOJSJiIeUUpQoSwNoG05OTkr/////Sv////9LAHSUYolCEAIAAOwJAAAAAAAADgMAAAAAAADKAAAAAAAAAKUHAAAAAAAAeAIAAAAAAACpAQAAAAAAALIAAAAAAAAAlgAAAAAAAAA/AAAAAAAAAL4GAAAAAAAARAYAAAAAAAAnBgAAAAAAANUAAAAAAAAAEwAAAAAAAAAKAAAAAAAAAHkEAAAAAAAAhgEAAAAAAABkAAAAAAAAACUAAAAAAAAA1wgAAAAAAAA3BAAAAAAAAHsCAAAAAAAAVAAAAAAAAAApAAAAAAAAAB8AAAAAAAAAHgAAAAAAAACXBgAAAAAAAH8FAAAAAAAAmQAAAAAAAAB7AAAAAAAAAFoAAAAAAAAANAAAAAAAAADtBwAAAAAAAH4DAAAAAAAAkAAAAAAAAAA0AAAAAAAAAJ0IAAAAAAAAwAIAAAAAAAAuAgAAAAAAAKUBAAAAAAAAfwAAAAAAAABrAAAAAAAAAFsAAAAAAAAA5gkAAAAAAADaAAAAAAAAAE4AAAAAAAAAMwAAAAAAAAAVAAAAAAAAAI0EAAAAAAAATgEAAAAAAAC0AAAAAAAAAA0AAAAAAAAAYAgAAAAAAAD0BQAAAAAAAGkBAAAAAAAAtgAAAAAAAABeCQAAAAAAABkDAAAAAAAAOAAAAAAAAAA2AAAAAAAAAHcIAAAAAAAATwcAAAAAAAAPAwAAAAAAAH4AAAAAAAAAegAAAAAAAAAnAAAAAAAAAJR0lGKMCGJ1aWx0aW5zlIwFc2xpY2WUk5RLAEsBSwGHlFKUSwKHlFKUhZRdlCiMGHBhbmRhcy5jb3JlLmluZGV4ZXMuYmFzZZSMCl9uZXdfSW5kZXiUk5RoUYwFSW5kZXiUk5R9lChoK2gNaBBLAIWUaBKHlFKUKEsBSwGFlGgXjAJPOJSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0s/dJRiiV2UjApwb2ludHNfd29ulGF0lGKMBG5hbWWUTnWGlFKUaFOMG3BhbmRhcy5jb3JlLmluZGV4ZXMubnVtZXJpY5SMCkludDY0SW5kZXiUk5R9lChoK2gNaBBLAIWUaBKHlFKUKEsBS0KFlGhEiUIQAgAAAAAAAAAAAAABAAAAAAAAAAIAAAAAAAAAAwAAAAAAAAAEAAAAAAAAAAUAAAAAAAAABgAAAAAAAAAHAAAAAAAAAAgAAAAAAAAACQAAAAAAAAAKAAAAAAAAAAsAAAAAAAAADAAAAAAAAAANAAAAAAAAAA4AAAAAAAAADwAAAAAAAAAQAAAAAAAAABEAAAAAAAAAEgAAAAAAAAATAAAAAAAAABQAAAAAAAAAFQAAAAAAAAAWAAAAAAAAABcAAAAAAAAAGAAAAAAAAAAZAAAAAAAAABoAAAAAAAAAGwAAAAAAAAAcAAAAAAAAAB0AAAAAAAAAHgAAAAAAAAAfAAAAAAAAACAAAAAAAAAAIQAAAAAAAAAiAAAAAAAAACMAAAAAAAAAJAAAAAAAAAAlAAAAAAAAACYAAAAAAAAAJwAAAAAAAAAoAAAAAAAAACkAAAAAAAAAKgAAAAAAAAArAAAAAAAAACwAAAAAAAAALQAAAAAAAAAuAAAAAAAAAC8AAAAAAAAAMAAAAAAAAAAxAAAAAAAAADIAAAAAAAAAMwAAAAAAAAA0AAAAAAAAADUAAAAAAAAANgAAAAAAAAA3AAAAAAAAADgAAAAAAAAAOQAAAAAAAAA6AAAAAAAAADsAAAAAAAAAPAAAAAAAAAA9AAAAAAAAAD4AAAAAAAAAPwAAAAAAAABAAAAAAAAAAEEAAAAAAAAAlHSUYmhjTnWGlFKUZYaUUpSMBF90eXCUjAlkYXRhZnJhbWWUjAlfbWV0YWRhdGGUXZSMBWF0dHJzlH2UjAZfZmxhZ3OUfZSMF2FsbG93c19kdXBsaWNhdGVfbGFiZWxzlIhzdWKMCW9yaWdfZXhvZ5RoNCmBlH2UKGg3aDpoPWgNaBBLAIWUaBKHlFKUKEsBSwNLQoaUaBqJQjAGAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D/NzMzMzDxkQGZmZmZmVmJAAAAAAABAZ0AAAAAAAJBlQJqZmZmZ+WNAzczMzMx8YkBmZmZmZiZkQM3MzMzM7GJAAAAAAADAX0CamZmZmZlmQJqZmZmZuWVAzczMzMyMZUAAAAAAAABkQJqZmZmZyWFAAAAAAACgY0DNzMzMzGxiQGZmZmZmhmRAZmZmZmY2ZECamZmZmVljQAAAAAAAwGZAZmZmZmZGZUAzMzMzM9NmQDMzMzMzs2JAMzMzMzNzZEAAAAAAANBiQAAAAAAA0GRAAAAAAACwZ0BmZmZmZjZlQGZmZmZmJmRAAAAAAADAZUBmZmZmZuZlQJqZmZmZ+WdAmpmZmZlpY0BmZmZmZqZiQAAAAAAAkGFAzczMzMwcYkCamZmZmRlnQGZmZmZm5mRAzczMzMxMYUDNzMzMzJxlQJqZmZmZyWVAmpmZmZmJY0AzMzMzM8NjQGZmZmZmtmZAzczMzMw8YkCamZmZmTllQAAAAAAAMGJAZmZmZmb2YkCamZmZmYljQJqZmZmZqWVAMzMzMzNDZEAzMzMzMxNhQJqZmZmZmWJAMzMzMzPjYkDNzMzMzIxoQAAAAAAA8GRAzczMzMzcaEAzMzMzM1NiQDMzMzMzU2VAmpmZmZlpZkBmZmZmZuZoQM3MzMzM7GhAMzMzMzPDZUAAAAAAAPBlQDMzMzMzc2JAAAAAAAAgZEA1WX8WAQcuQKMePRu+diBA4pT1uzR2GUD56zlrn/MfQJYbfQbdZR5A/ck1jwd/J0DGoysvECkaQC11S2lPwiZAt9K7yXSJIUDRCVVsNR0uQB7i4bE68jJAS8oxX/NoM0B8V5oU3xkqQFUVteZ5ihlAaXIGWeszGECLKQz/7S4wQPRVlOzNgzJAL2NmzvHrLECjI/NISd8QQJq7C8ko3jdAoP3ZmYLkK0D4pop0v5opQEPlfQWt+wlAxaAy49KoJUAXGT9yzsQmQLzVeOuB4y1Aym5xYt+hJEC+/4CvtlUjQM26IjPZHyNA7TfgbHvXJkD/Rs0rK4goQNsYMvFTkCBAJBVc7G+CL0BCEaWsqKInQEB8v5eaVi5AOAcD8Ee1G0Dx9FMGDlIzQNr7SNbOzSdAKi6iieFxHEB6SV4ATBogQJQPGgzzzSZA2QboHeWfHEAilWdRackkQP84SyCgIDBAA86UkDsnKkBAc6JOIhM0QM84/i8GdjJAAfc5aInpIkBsOtTDYykzQC6xO7X+eilA6jgRQvpBJEDAjGUEP20tQF0kh5JkbxZAGXCCw7HHN0BYrLN6AoAmQMHYRY8F2SlAVRFZK79dJkATvoJJrmEPQK5xjnedsxlAnvMBUHMVM0BsD3zKvuIpQFQQFCknsDRAlEVyliYyKkA4XsxqxUwWQJ+tlHgfMCVAML3E3XSvJ0CUdJRiaA1oEEsAhZRoEoeUUpQoSwFLA4WUaESJQxgAAAAAAAAAAAEAAAAAAAAABQAAAAAAAACUdJRiSwKHlFKUaD1oDWgQSwCFlGgSh5RSlChLAUsDS0KGlGhEiUIwBgAAHgAAAAAAAAAlAAAAAAAAADoAAAAAAAAAIAAAAAAAAAAmAAAAAAAAACEAAAAAAAAAFAAAAAAAAAAOAAAAAAAAAB8AAAAAAAAAMgAAAAAAAAAiAAAAAAAAAB4AAAAAAAAALQAAAAAAAAAVAAAAAAAAABoAAAAAAAAAGwAAAAAAAAAVAAAAAAAAACcAAAAAAAAALAAAAAAAAAAeAAAAAAAAACAAAAAAAAAAIwAAAAAAAAASAAAAAAAAACAAAAAAAAAAFQAAAAAAAAAbAAAAAAAAACUAAAAAAAAAJQAAAAAAAAAnAAAAAAAAADAAAAAAAAAAKwAAAAAAAAAhAAAAAAAAABoAAAAAAAAAEAAAAAAAAAAPAAAAAAAAABkAAAAAAAAAKAAAAAAAAAAcAAAAAAAAABgAAAAAAAAAJQAAAAAAAAAgAAAAAAAAADIAAAAAAAAAGAAAAAAAAAAqAAAAAAAAACEAAAAAAAAAIgAAAAAAAAAZAAAAAAAAABsAAAAAAAAAIwAAAAAAAAAkAAAAAAAAAAgAAAAAAAAAGAAAAAAAAAAeAAAAAAAAACkAAAAAAAAAKAAAAAAAAAArAAAAAAAAACsAAAAAAAAAGwAAAAAAAAAlAAAAAAAAACUAAAAAAAAAKgAAAAAAAAArAAAAAAAAADIAAAAAAAAAJQAAAAAAAAAmAAAAAAAAABkAAAAAAAAAAQAAAAAAAAACAAAAAAAAAAUAAAAAAAAAFwAAAAAAAAAIAAAAAAAAAAQAAAAAAAAACQAAAAAAAAAOAAAAAAAAAAIAAAAAAAAABQAAAAAAAAALAAAAAAAAAAwAAAAAAAAABgAAAAAAAAAIAAAAAAAAAAUAAAAAAAAAAwAAAAAAAAAOAAAAAAAAAAEAAAAAAAAABAAAAAAAAAAUAAAAAAAAAAMAAAAAAAAAAQAAAAAAAAAOAAAAAAAAAAQAAAAAAAAAFAAAAAAAAAAGAAAAAAAAAAoAAAAAAAAAAgAAAAAAAAACAAAAAAAAAAMAAAAAAAAAAAAAAAAAAAAGAAAAAAAAABUAAAAAAAAAFwAAAAAAAAANAAAAAAAAABMAAAAAAAAABAAAAAAAAAAAAAAAAAAAABcAAAAAAAAACQAAAAAAAAAOAAAAAAAAAAIAAAAAAAAADAAAAAAAAAAPAAAAAAAAAAgAAAAAAAAACwAAAAAAAAADAAAAAAAAAA4AAAAAAAAADAAAAAAAAAAHAAAAAAAAABgAAAAAAAAAAAAAAAAAAAAVAAAAAAAAAAkAAAAAAAAABgAAAAAAAAAEAAAAAAAAAAUAAAAAAAAAEgAAAAAAAAAKAAAAAAAAAAgAAAAAAAAADAAAAAAAAAAFAAAAAAAAAAQAAAAAAAAAAwAAAAAAAAAEAAAAAAAAAAkAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAlHSUYmhKSwJLBUsBh5RSlEsCh5RSlIaUXZQoaFNoVX2UKGgraA1oEEsAhZRoEoeUUpQoSwFLBoWUaF2JXZQojAVjb25zdJSMDFBhc3NpbmdfUmF0ZZSMClBhc3NpbmdfVESUjApSdXNoaW5nX1RElIwGUG93ZXI1lIwDQ1BJlGV0lGJoY051hpRSlGhTaGh9lChoK2hsaGNOdYaUUpRlhpRSlGh0aHVodmh3aHh9lGh6fZRofIhzdWKMBWVuZG9nlGgNaBBLAIWUaBKHlFKUKEsBS0KFlGhEiUIQAgAA7AkAAAAAAAAOAwAAAAAAAMoAAAAAAAAApQcAAAAAAAB4AgAAAAAAAKkBAAAAAAAAsgAAAAAAAACWAAAAAAAAAD8AAAAAAAAAvgYAAAAAAABEBgAAAAAAACcGAAAAAAAA1QAAAAAAAAATAAAAAAAAAAoAAAAAAAAAeQQAAAAAAACGAQAAAAAAAGQAAAAAAAAAJQAAAAAAAADXCAAAAAAAADcEAAAAAAAAewIAAAAAAABUAAAAAAAAACkAAAAAAAAAHwAAAAAAAAAeAAAAAAAAAJcGAAAAAAAAfwUAAAAAAACZAAAAAAAAAHsAAAAAAAAAWgAAAAAAAAA0AAAAAAAAAO0HAAAAAAAAfgMAAAAAAACQAAAAAAAAADQAAAAAAAAAnQgAAAAAAADAAgAAAAAAAC4CAAAAAAAApQEAAAAAAAB/AAAAAAAAAGsAAAAAAAAAWwAAAAAAAADmCQAAAAAAANoAAAAAAAAATgAAAAAAAAAzAAAAAAAAABUAAAAAAAAAjQQAAAAAAABOAQAAAAAAALQAAAAAAAAADQAAAAAAAABgCAAAAAAAAPQFAAAAAAAAaQEAAAAAAAC2AAAAAAAAAF4JAAAAAAAAGQMAAAAAAAA4AAAAAAAAADYAAAAAAAAAdwgAAAAAAABPBwAAAAAAAA8DAAAAAAAAfgAAAAAAAAB6AAAAAAAAACcAAAAAAAAAlHSUYowEZXhvZ5RoDWgQSwCFlGgSh5RSlChLAUtCSwaGlGgaiEJgDAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/zczMzMw8ZEBmZmZmZlZiQAAAAAAAQGdAAAAAAACQZUCamZmZmfljQM3MzMzMfGJAZmZmZmYmZEDNzMzMzOxiQAAAAAAAwF9AmpmZmZmZZkCamZmZmbllQM3MzMzMjGVAAAAAAAAAZECamZmZmclhQAAAAAAAoGNAzczMzMxsYkBmZmZmZoZkQGZmZmZmNmRAmpmZmZlZY0AAAAAAAMBmQGZmZmZmRmVAMzMzMzPTZkAzMzMzM7NiQDMzMzMzc2RAAAAAAADQYkAAAAAAANBkQAAAAAAAsGdAZmZmZmY2ZUBmZmZmZiZkQAAAAAAAwGVAZmZmZmbmZUCamZmZmflnQJqZmZmZaWNAZmZmZmamYkAAAAAAAJBhQM3MzMzMHGJAmpmZmZkZZ0BmZmZmZuZkQM3MzMzMTGFAzczMzMycZUCamZmZmcllQJqZmZmZiWNAMzMzMzPDY0BmZmZmZrZmQM3MzMzMPGJAmpmZmZk5ZUAAAAAAADBiQGZmZmZm9mJAmpmZmZmJY0CamZmZmallQDMzMzMzQ2RAMzMzMzMTYUCamZmZmZliQDMzMzMz42JAzczMzMyMaEAAAAAAAPBkQM3MzMzM3GhAMzMzMzNTYkAzMzMzM1NlQJqZmZmZaWZAZmZmZmbmaEDNzMzMzOxoQDMzMzMzw2VAAAAAAADwZUAzMzMzM3NiQAAAAAAAIGRAAAAAAAAAPkAAAAAAAIBCQAAAAAAAAE1AAAAAAAAAQEAAAAAAAABDQAAAAAAAgEBAAAAAAAAANEAAAAAAAAAsQAAAAAAAAD9AAAAAAAAASUAAAAAAAABBQAAAAAAAAD5AAAAAAACARkAAAAAAAAA1QAAAAAAAADpAAAAAAAAAO0AAAAAAAAA1QAAAAAAAgENAAAAAAAAARkAAAAAAAAA+QAAAAAAAAEBAAAAAAACAQUAAAAAAAAAyQAAAAAAAAEBAAAAAAAAANUAAAAAAAAA7QAAAAAAAgEJAAAAAAACAQkAAAAAAAIBDQAAAAAAAAEhAAAAAAACARUAAAAAAAIBAQAAAAAAAADpAAAAAAAAAMEAAAAAAAAAuQAAAAAAAADlAAAAAAAAAREAAAAAAAAA8QAAAAAAAADhAAAAAAACAQkAAAAAAAABAQAAAAAAAAElAAAAAAAAAOEAAAAAAAABFQAAAAAAAgEBAAAAAAAAAQUAAAAAAAAA5QAAAAAAAADtAAAAAAACAQUAAAAAAAABCQAAAAAAAACBAAAAAAAAAOEAAAAAAAAA+QAAAAAAAgERAAAAAAAAAREAAAAAAAIBFQAAAAAAAgEVAAAAAAAAAO0AAAAAAAIBCQAAAAAAAgEJAAAAAAAAARUAAAAAAAIBFQAAAAAAAAElAAAAAAACAQkAAAAAAAABDQAAAAAAAADlAAAAAAAAA8D8AAAAAAAAAQAAAAAAAABRAAAAAAAAAN0AAAAAAAAAgQAAAAAAAABBAAAAAAAAAIkAAAAAAAAAsQAAAAAAAAABAAAAAAAAAFEAAAAAAAAAmQAAAAAAAAChAAAAAAAAAGEAAAAAAAAAgQAAAAAAAABRAAAAAAAAACEAAAAAAAAAsQAAAAAAAAPA/AAAAAAAAEEAAAAAAAAA0QAAAAAAAAAhAAAAAAAAA8D8AAAAAAAAsQAAAAAAAABBAAAAAAAAANEAAAAAAAAAYQAAAAAAAACRAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAAhAAAAAAAAAAAAAAAAAAAAYQAAAAAAAADVAAAAAAAAAN0AAAAAAAAAqQAAAAAAAADNAAAAAAAAAEEAAAAAAAAAAAAAAAAAAADdAAAAAAAAAIkAAAAAAAAAsQAAAAAAAAABAAAAAAAAAKEAAAAAAAAAuQAAAAAAAACBAAAAAAAAAJkAAAAAAAAAIQAAAAAAAACxAAAAAAAAAKEAAAAAAAAAcQAAAAAAAADhAAAAAAAAAAAAAAAAAAAA1QAAAAAAAACJAAAAAAAAAGEAAAAAAAAAQQAAAAAAAABRAAAAAAAAAMkAAAAAAAAAkQAAAAAAAACBAAAAAAAAAKEAAAAAAAAAUQAAAAAAAABBAAAAAAAAACEAAAAAAAAAQQAAAAAAAACJAAAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAAAAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAAAAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAAANVl/FgEHLkCjHj0bvnYgQOKU9bs0dhlA+es5a5/zH0CWG30G3WUeQP3JNY8HfydAxqMrLxApGkAtdUtpT8ImQLfSu8l0iSFA0QlVbDUdLkAe4uGxOvIyQEvKMV/zaDNAfFeaFN8ZKkBVFbXmeYoZQGlyBlnrMxhAiykM/+0uMED0VZTszYMyQC9jZs7x6yxAoyPzSEnfEECauwvJKN43QKD92ZmC5CtA+KaKdL+aKUBD5X0FrfsJQMWgMuPSqCVAFxk/cs7EJkC81XjrgeMtQMpucWLfoSRAvv+Ar7ZVI0DNuiIz2R8jQO034Gx71yZA/0bNKyuIKEDbGDLxU5AgQCQVXOxvgi9AQhGlrKiiJ0BAfL+XmlYuQDgHA/BHtRtA8fRTBg5SM0Da+0jWzs0nQCouoonhcRxAekleAEwaIECUDxoM880mQNkG6B3lnxxAIpVnUWnJJED/OEsgoCAwQAPOlJA7JypAQHOiTiITNEDPOP4vBnYyQAH3OWiJ6SJAbDrUw2MpM0AusTu1/nopQOo4EUL6QSRAwIxlBD9tLUBdJIeSZG8WQBlwgsOxxzdAWKyzegKAJkDB2EWPBdkpQFURWSu/XSZAE76CSa5hD0CucY53nbMZQJ7zAVBzFTNAbA98yr7iKUBUEBQpJ7A0QJRFcpYmMipAOF7MasVMFkCfrZR4HzAlQDC9xN10rydAlHSUYowJY29uc3RfaWR4lEsAjAprX2NvbnN0YW50lEsBjAZfY2FjaGWUfZR1Ymi/SwFot2i6aLBos4wKX2RhdGFfYXR0cpRdlChot2iwjAlkYXRhLmV4b2eUjApkYXRhLmVuZG9nlIwPZGF0YS5vcmlnX2VuZG9nlIwOZGF0YS5vcmlnX2V4b2eUjApwaW52X3dleG9nlIwGd2VuZG9nlIwFd2V4b2eUaCRljApfaW5pdF9rZXlzlF2UaMpoumjJaLOMBG5vYnOUR0BQgAAAAAAAjAlfZGZfbW9kZWyUR0AUAAAAAAAAjAlfZGZfcmVzaWSUaAuMBnNjYWxhcpSTlGgaQwgAAAAAAABOQJSGlFKUjARyYW5rlGjRaERDCAYAAAAAAAAAlIaUUpRoyGgNaBBLAIWUaBKHlFKUKEsBSwZLQoaUaBqJQmAMAABXkfiCQGOyP5oxtjp+qs0/v5nEOB1YwL+uVqUDEc7Dv62jsseM6LU/klxuGr7FyT81vivqZkSSP56A2/6Ffbg/ARthEHni2j9GFyrK0H+7vxhLHPMuFbm/WVsvBPiluL//4u9E7pi2P//u30I0380/PHjMCndRvD8yl72xLcrJPwQb2ehQeqS/3CngutRauz/RbqkpLJ7FP3YFRzFzhc6/iA3zMSsLlL9yA2VBjTq8v0k6Ni+qf7o/PanvShdLpT8Uyix5Cy+1P2x1BPvUtIQ/zpE+zBNQz79JJqSohXIUv8E/y+ARxLY/f4/dOTVair8wjfMDQPiQv5BHS+ryHdC/qjw4vXdokz8SJxNnyfqqP4UqbKcC6cg/jHEQLlFzwz+k4EwOFWXEv6EmzcnUf5U/GJfO9p67yD9brKTFX1Gyv57qevqvXr+/hGm7kohhxj8lVLR6dbyjPyOZHgvc2ce/wM7zrxl0yT8XlhUR6Zatv1PVgU7Yx8s/AkDUhOXOuD9IxPUcxQizP8KdTDHRA7G/rxIw/CgRtL8JjFkq4J/UPxIhSCIVl7c/UHu7ZZKewz8YTAfT0FjSv0nUbUpcHJU/bfT+5GNG079ubhR23CrAP6xgg0PRkqu/0RN0brkYvb+KR0wKuRvWv7DEs2n1p9O/Spy6IkF2ob/0s5+PTFGwv8En0OhBQMs/e2d2sZNUpz/iiJDm0rMhPyYXCHwnVFe/BMAetwSMLT/gr9dQhEdAP464QvwfST2/I7q6NwhQVL8ogQVBI6JSP/Vypwv5WkA/gxGBdG5nZb+BspOmTbYgv3vZKVJARi8/rZS1MYyTOj//q4j2MMVWv1uRcP4gEjq/RJh7K/PSQT+6j5BfA/JPv7HRvNvunj4/T/LGhrPFQL8H8/ula3lRv+vZ54sX60Y/kQ0g7lacRT9fwYWUr/xbPymJJ8uczDU/cpAotRvuLj+uDrOsH6c5vxNZfpHMKUg/g1srZg0CXj/n080zl+g9P4Bg8Ny4iTy/hmd6KeXEIr/2z/TPZWk9P7WNcB3jgWU/2kEQeFSfSr/8D1I2h7I0v3WiIPdnm0q/01M71IOPTr+oGV0U5LxMP/eQXB/vtU8/4XzthuhdWb+XF/5QputCPzbUsS4vQkk/nL1nAvNxWb8OlYULrVQrP6uiYudxIy8/+e7zPy+UWr8xbDJK36Mlv21Rr/0a3VG/LT9qkxkcRL+DYH5vHbVWv5NB0UVLlkA/DZ3+88seWz+Tpq+o08FXv8GjtIAg0FK/Fia9sAeAZL99jI/zsWViP01fBNrEbEC/y1+iVJ5TYj93qBKvyshMv+5nd+buqTw/U8Ft1ua0RT82WZk0z3ZgP9aw//QJr1w/F7ui6TEvQr9nd9Qw+L1SP2EescPQxlq/8WjckeS+QD+K5ASPKexhv0mEK5Hwc1Q/TD9eBxQedD+gXrFWhuNbPzvsljx3RVo/Ju+tS6rgPD8SxbVmfzJwv0yhC7RGA2+/o2yqIh4eUj+6utMPqmRqP6bLaaYJcis/N3asY8fIRr8dLUjDp2dtP4G5qr7LPmK/iJt+lwMAZb/tQv0gxDBXv21cl+kY02O/Ss4td56qQz+flIpZS0doP+JX8fkTpzE/wl2eWUB0X7+Vhu3g+qlkv1YKPRxgBWa/wcfXU3PDVL9dXQtLCEI0v0Qs6RzTrGS/y5oI+/jISL9f2gW+soxGv6sfWhpW4EU/h49k5QuEZT++OsR8Hno5P5ujf1TKVmm/BS+lYjYAVD+qh0ZD20tSv/IlPWE4D2W/kplzRewhUT9jUxBp5jMyv1GzRNRYc22/7FiQjwNUYT+h9DHWK5Y5P8vl5wG39CK/0YQgIRMUcj/xN5GqtYVbv48MJ6i7RmY/eIfhv24yWD98aQzfZ6pDP+s4sichP12/9Sy4guBoJz9PWkmRa2tiP3Hwl3nnTSe/LsEsLX/ccr/MEQ+SdAthv6bwvyPPkmU/fv1Nnj73cD9P1dwsXI1Tv83JYDt5OV8/j2UYNHpJRr8NyKrwxuZTP5WbWIUu4Uc/G+RqC5ZFCz/9KejSGtA+PxA8I5yzBDe/9EQXUPvbbD++wm04789SvzlD51V8OGA/KldNOjnkYb/Yo9QovEZxv/mSypYhbGC/jRg8vWskYz8rV+GSSKl5P70O/AadSUY/hrM42pgXXb+/oG1os2RlvzAkthkmY0y/1Qn+QketZL+fYl8VFm9SP6u32lET71I/19LFprc/TT8HkzOTDH1UP9moAmpgB2K/pfWNkFLiab8tmAd00y9rv5fshyclKDM/KeVr2UhSY78wvihCznD3PurJhhcfxHI/4X3H34jpab80d/mfKidwv1LztTMddjO/4wfBeaPiZL+oEfo0dp1sP3W3y4KGn2S/dlLdQf1VPj9UQvJla41mv4c3G3zQ2mC/xVd370dnFr88OfBc6Qllv+q0l0YG62O/v52zFE8mdD+eopYO7ipwP7b862sP2Ea/A8CBtbW1bz9jbHDtmsRWv8VMN2zFE3a/FQqmRjvpdz9KGJZMwmU/P25tA3N76V8/MB1C6oFbND9Ls8lTRZMevwDKvuYe1nE/+GWgNt0EMj8b6ZOej8hVP+FSAAfZYG2/NakXf4gSWz9F+pHCnxpkP0EjqSMzSkK/9Gl1wi1OYz+DGDaq47R0v0JEzknkEXc/ELXtqFrTZD+WGKMuT6RRvwU1h5KWZTm/4geRL8gRUb+5MUs85GxtP3SoL0ZSP1A/gEzPCEotJj8qxR8k7/phP2Rip203z0i/0M0+CvSESj+PC/PNJ0llv4qFdmXC1Em/h5/68wmQVr++pJeuV+eRPxDE5I2zSqA/iuZzzZkuqr/UCdH9W9qcP2nWiRig86m/PnAkx1WqmT95eaQ9NbmgPyk3E8NZTa2/vylTcoDyoD+cBY1a/jOPP5kqb9jdQ4E/w4PmrNhQfz+eVRz3G86VP95PpXgF26e/+K2cXV5VqL/JlpKf0lWRP199+YgMmoQ/8P2C6VEusL9Yr/gv5lOmv6RsNHOt5mC/ZRhO2x7Wkj+61Mfz9Qywv7UcvzgYZ6Q/pJbHX4l3mT96a5OUAlitv5L01wJdp7C/i7bMeG0Qlz9at03gxxKbPyx9iyXmVZw/cUNqJts7rr9LeW+6OhGvv1kQ+w95v5o/pMc1VlJUkD8RsPY2TUOYP1jK2H3wdZM/Kucgrb7AqL84oZUkrvd7P7I/lrCkI5c/UiwLgS+hqL986b8AE2edP9a2spVZnpY/uaKWqZUZqb/HtDmh43qaP4xBp2zuzYk/3GJUH3M4lz/xvydRG/p7P+0J5ek/f4o/GNUIjm75nD91Uy3OJ6iEPxL/oO5XmZQ/erQHOKsMrb+AMlSKWYWVPxCONhVqJaI/mxh1/xTbYz9TUHx6frCUP9dYpMbVMZU/G/VNYP6YlD/T47VZBeujPzSSOpKfWaA/sEwKeLX7sr9zARoxJeiQP0FMwqMWB2U/9zm2owkolD/S/CEP0wOhP0coas+y8Zs/BqQiGyYirr9EL2eqbPFXP4IDJIN6C2S/+j57ZjDIar/3Ccy9RHBtvwcEXWht21m/KZMz5eec8T7aGA+hi1B0vw6gWlNheU8/wrh8CGlqU794U2AJHydWP04w00/+O3E/2mHTupd1cj9fIayNos5LP30choY+02G/BBKbFcm/ab86oU91TEppP0nWEabkaHA/fOWBy7ikaj8bfMc9/W5uvw/XCPuU734/adti9buZNj+nmF+0ccVGP+otHH3kZnu/24EungbpWb8oOte4XDtYPxVAVzSj3Gg/AWLIMOa8aL8N87486sFlv4d3pkwg4mG/mapybUJyRz95TjMKtDBQPzR252zGRXS/sxp73LhuZz+6Muz8Lj0Rv13AZJV3/WQ/Vfgb+A4bV7+hbCwYIthvP3AApZ/du1S/JW+yE/34Sr99HSyjzEVvv2Xu/Oqydle/U9WdQTWCV7+KEeHZrjJbvzGafkCrPmE/3bZXYQdsVD/W8q5RZJh1P8k1rCT2t3M/OSnLSobaXb9JkAuiSSx2P3PL22/fFj2/XEHkS8TQP78i1UEQhXxjPx4apeobK3G//71vhskFgz/sk6fwIUFmv6m7a7poiCk/Ys8Y5OUZZ79uvnAkBLF2vzukR/l683O/G1sfSjIHeD9pMUWLD/ZVv5wkXMF0YnE/Cq1b/A9XLj8GWYGGA5R4v6gRR/0rtES/kz7gGa8ZUT+UdJRijBVub3JtYWxpemVkX2Nvdl9wYXJhbXOUaA1oEEsAhZRoEoeUUpQoSwFLBksGhpRoGolCIAEAAFvm+cfX1fo/wCfTQL6hhL/0IsVePJVbP9UAwXk+DXe/heF/3TI8kr/bfYMeuFEZv8An00C+oYS/ts81rj5XFj8DzuOlULYWv7NLF93YGAK/ZP4DBW86H78okTBkVy4Nv/QixV48lVs/A87jpVC2Fr+IQ+7g4m00P56NdzKEkio/xcDb+li96z6w0bK0N4gEP9UAwXk+DXe/s0sX3dgYAr+ejXcyhJIqP4PUnVE7xj8/U0xpbBrIB7+ZD7sGEqgAP4Xhf90yPJK/ZP4DBW86H7/FwNv6WL3rPlNMaWwayAe/KT3Soi70tD/eImoYMSVev9t9gx64URm/KJEwZFcuDb+w0bK0N4gEP5kPuwYSqAA/3iJqGDElXr/lKGdXGHNIP5R0lGKMFXdleG9nX3Npbmd1bGFyX3ZhbHVlc5RoDWgQSwCFlGgSh5RSlChLAUsGhZRoGolDMEQlIp+vc5VAiKBU3d9MU0BP57MDrW9EQM87sc4DakJAoohiZUX9C0BR6Cod/7ToP5R0lGJ1Ymi/SwFowl2UjA5fZGF0YV9pbl9jYWNoZZRdlCiMDGZpdHRlZHZhbHVlc5SMBXJlc2lklIwGd3Jlc2lklGVo32jijAZfdXNlX3SUiGjAfZSMFl93ZXhvZ19zaW5ndWxhcl92YWx1ZXOUaOmMCGRmX21vZGVslEdAFAAAAAAAAIwIZGZfcmVzaWSUaNSMCGNvdl90eXBllIwJbm9ucm9idXN0lIwIY292X2t3ZHOUfZSMC2Rlc2NyaXB0aW9ulIxXU3RhbmRhcmQgRXJyb3JzIGFzc3VtZSB0aGF0IHRoZSBjb3ZhcmlhbmNlIG1hdHJpeCBvZiB0aGUgZXJyb3JzIGlzIGNvcnJlY3RseSBzcGVjaWZpZWQulHN1YowHX19kb2NfX5RY3QMAAAogICAgUmVzdWx0cyBjbGFzcyBmb3IgZm9yIGFuIE9MUyBtb2RlbC4KCiAgICBQYXJhbWV0ZXJzCiAgICAtLS0tLS0tLS0tCiAgICBtb2RlbCA6IFJlZ3Jlc3Npb25Nb2RlbAogICAgICAgIFRoZSByZWdyZXNzaW9uIG1vZGVsIGluc3RhbmNlLgogICAgcGFyYW1zIDogbmRhcnJheQogICAgICAgIFRoZSBlc3RpbWF0ZWQgcGFyYW1ldGVycy4KICAgIG5vcm1hbGl6ZWRfY292X3BhcmFtcyA6IG5kYXJyYXkKICAgICAgICBUaGUgbm9ybWFsaXplZCBjb3ZhcmlhbmNlIHBhcmFtZXRlcnMuCiAgICBzY2FsZSA6IGZsb2F0CiAgICAgICAgVGhlIGVzdGltYXRlZCBzY2FsZSBvZiB0aGUgcmVzaWR1YWxzLgogICAgY292X3R5cGUgOiBzdHIKICAgICAgICBUaGUgY292YXJpYW5jZSBlc3RpbWF0b3IgdXNlZCBpbiB0aGUgcmVzdWx0cy4KICAgIGNvdl9rd2RzIDogZGljdAogICAgICAgIEFkZGl0aW9uYWwga2V5d29yZHMgdXNlZCBpbiB0aGUgY292YXJpYW5jZSBzcGVjaWZpY2F0aW9uLgogICAgdXNlX3QgOiBib29sCiAgICAgICAgRmxhZyBpbmRpY2F0aW5nIHRvIHVzZSB0aGUgU3R1ZGVudCdzIHQgaW4gaW5mZXJlbmNlLgogICAgKiprd2FyZ3MKICAgICAgICBBZGRpdGlvbmFsIGtleXdvcmQgYXJndW1lbnRzIHVzZWQgdG8gaW5pdGlhbGl6ZSB0aGUgcmVzdWx0cy4KCiAgICBTZWUgQWxzbwogICAgLS0tLS0tLS0KICAgIFJlZ3Jlc3Npb25SZXN1bHRzCiAgICAgICAgUmVzdWx0cyBzdG9yZSBmb3IgV0xTIGFuZCBHTFcgbW9kZWxzLgoKICAgIE5vdGVzCiAgICAtLS0tLQogICAgTW9zdCBvZiB0aGUgbWV0aG9kcyBhbmQgYXR0cmlidXRlcyBhcmUgaW5oZXJpdGVkIGZyb20gUmVncmVzc2lvblJlc3VsdHMuCiAgICBUaGUgc3BlY2lhbCBtZXRob2RzIHRoYXQgYXJlIG9ubHkgYXZhaWxhYmxlIGZvciBPTFMgYXJlOgoKICAgIC0gZ2V0X2luZmx1ZW5jZQogICAgLSBvdXRsaWVyX3Rlc3QKICAgIC0gZWxfdGVzdAogICAgLSBjb25mX2ludF9lbAogICAglHViLg==", "type": "binary"}]
\ No newline at end of file
+[{"name": "app.py", "content": "from shiny import App, ui, render\nimport pandas as pd\nimport numpy as np\nimport pickle\nimport statsmodels.api as sm\nfrom shinywidgets import output_widget, render_widget\nimport plotly.express as px\nfrom pathlib import Path\n\nmodel_path = Path(__file__).parent / \"heisman_model.pkl\"\nmodel_data_path = Path(__file__).parent / \"Model_Data.csv\"\nweekly_data_path = Path(__file__).parent / \"Weekly_Data.csv\"\n\nmodel = pickle.load(open(model_path, 'rb'))\n################### Historical #########################\nmodel_data = pd.read_csv(model_data_path).reset_index(drop = True)\n\npredict_data =  model_data[['Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']]\npredict_data = sm.tools.add_constant(predict_data)\npredict_data['Prediction'] = model.predict(predict_data)\npredict_data = predict_data['Prediction']\n\nmodel_data = pd.merge(model_data, predict_data, left_index=True, right_index=True)\nmodel_data['CPI'] = model_data['CPI'].round(2)\nmodel_data['Prediction'] = model_data['Prediction'].round(2)\n\n################### Current #########################\ncurrent_df = pd.read_csv(weekly_data_path).reset_index(drop = True)\n\ncurrent_predict_df =  current_df[['Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']]\ncurrent_predict_df = sm.tools.add_constant(current_predict_df)\ncurrent_predict_df['Projected Voting Points'] = model.predict(current_predict_df)\ncurrent_predict_df = current_predict_df['Projected Voting Points']\n\ncurrent_df = pd.merge(current_df, current_predict_df, left_index=True, right_index=True)\ncurrent_df['CPI'] = current_df['CPI'].round(2)\ncurrent_df['Projected Voting Points'] = current_df['Projected Voting Points'].round(2)\n\n\n# Part 1: ui ----\napp_ui = ui.page_fluid(\n    ui.navset_tab(\n        ui.nav(\"Model Details\", \n           \n        ui.markdown(\n            \"\"\"\n            # So how does this model work anyway?\n            This is a project that I spent the summer of 2020 on in my free time.\n            <br />\n\n            Simply put, the model aims to predict the finals standings in Heisman voting for quarterbacks\n            specifically. This is mostly because it is difficult to come up with a sample of metrics that apply\n            to the different positions across college football.\n            <br />\n\n            The model itself is a linear regression with voting points as a response, and individual and team\n            statitistics as the predictors. The model is built with training data from the 2006 to 2018 seasons.\n            <br />\n\n            The model is made up of the following 5 predictors;\n            <br />\n            \n            **Passer Rating** : Passer efficency rating as according to pro-football-reference.com.\n            <br />\n\n            **Passing TDs** : Number of passing touchdowns thrown by a quarterback.\n            <br />\n\n            **Rushing TDs** : Number of rushing touchdowns ran by a quarterback.\n            <br />\n\n            **Power 5 Indicator** : A binary value of 0 or 1. Set equal to 1, \n            if the quarterback's team plays in a power 5 conference. Otherwise 0. Notre Dame is the only independent team \n            to receive a power 5 label.\n            <br />\n\n            **CPI** : A team strength of record metric involving the winning percentages of opponents. More details \n            of the metric can be found at www.cpiratings.com/about.html.\n            \"\"\"\n        )\n               ),\n        ui.nav(\"Past Model Results\", \n           \n        ui.input_select(\"model_year\", \"Model Year\", model_data['Year'].tolist()),\n        ui.output_table(\"historical_data\")\n               ),\n\n    ui.nav(\"Current Model Results\", \n           \n        ui.output_table(\"current_data\")\n               ),\n    \n    ui.nav(\"What If\", \n           \n        ui.input_numeric(\"what_if_QBR\", \"Passer Rating\", value=0.0),\n        ui.input_numeric(\"what_if_pass_TD\", \"Passing TDs\", value=0),\n        ui.input_numeric(\"what_if_rush_TD\", \"Rushing TDs\", value=0),\n        ui.input_radio_buttons(\"what_if_power_5\", \"Power 5 Conference\",  {1 : \"Yes\", 0: \"No\"}),\n        ui.input_numeric(\"what_if_CPI\", \"CPI\", value=0.0),\n        ui.output_text(\"what_if_analysis\")\n               ),\n    \n    ui.nav(\"Scatter\",\n           ui.div(\n           output_widget(\"my_widget\")\n           )\n           )\n    )\n)\n\n\n\n\n# Part 2: server ----\ndef server(input, output, session):\n\n    @output\n    @render.table\n    def historical_data():\n\n        result_df = model_data[model_data['Year'] == int(input.model_year())]\n\n        result_df['Actual_Rank'] = result_df['points_won'].rank(ascending = False).astype('int')\n        result_df['Predicted_Rank'] = result_df['Prediction'].rank(ascending = False).astype('int')\n\n        result_cols = ['Player', 'School', 'Actual_Rank', 'Predicted_Rank', 'Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']\n        result_df = result_df[result_cols]\n\n        return result_df\n    \n    @output\n    @render.table\n    def current_data():\n\n        result_df = current_df\n\n        result_df = result_df.sort_values(by = 'Projected Voting Points', ascending = False)\n        result_df = result_df.reset_index(drop = True)\n        result_df['Rank'] = result_df.index + 1\n        result_cols = ['Rank', 'Player', 'School', 'Projected Voting Points', 'Passing_Rate', 'Passing_TD', 'Rushing_TD', 'Power5', 'CPI']\n        result_df = result_df[result_cols]\n\n        return result_df\n    \n    @output\n    @render.text\n    def what_if_analysis():\n\n        what_if_df = pd.DataFrame({\n            'Passing_Rate' : [float(input.what_if_QBR())],\n            'Passing_TD' : [int(input.what_if_pass_TD())],\n            'Rushing_TD' : [int(input.what_if_rush_TD())],\n            'Power5' : [int(input.what_if_power_5())],\n            'CPI' : [float(input.what_if_CPI())]\n        })\n\n        what_if_df = sm.tools.add_constant(what_if_df, has_constant='add')\n\n        what_if_df['Prediction'] = model.predict(what_if_df)\n\n        result = what_if_df.iloc[0]['Prediction']\n        result = result.round(2)\n\n        return f\"A player with these statistics would have {result} projected voting points.\"\n    \n    @output\n    @render_widget\n    def my_widget():\n        fig = px.scatter(\n            model_data, x=\"Year\", y=\"Prediction\",\n            hover_data=['Player']\n        )\n        return fig\n\n# Combine into a shiny app.\n# Note that the variable must be \"app\".\napp = App(app_ui, server)", "type": "text"}, {"name": "Model_Data.csv", "content": "Player,School,Year,points_won,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI\nTroy Smith,Ohio State,2006,2540,161.9,30,1,1,15.013680174870936\nBrady Quinn,Notre Dame,2006,782,146.7,37,2,1,8.231919146738909\nColt Brennan,Hawaii,2006,202,186.0,58,5,0,6.365435540069685\nTim Tebow,Florida,2007,1957,172.5,32,23,1,7.987912822160973\nColt Brennan,Hawaii,2007,632,159.8,38,8,0,7.5994759572849\nChase Daniel,Missouri,2007,425,147.9,33,4,1,11.748104548755686\nDennis Dixon,Oregon,2007,178,161.2,20,9,1,6.540100800550993\nPat White,West Virginia,2007,150,151.4,14,14,0,11.379512110196254\nMatt Ryan,Boston College,2007,63,127.0,31,2,1,8.768469146897912\nSam Bradford,Oklahoma,2008,1726,180.8,50,5,1,15.05704821146074\nColt McCoy,Texas,2008,1604,173.8,34,11,1,18.946208112380297\nTim Tebow,Florida,2008,1575,172.4,30,12,1,19.409963559776127\nGraham Harrell,Texas Tech,2008,213,160.0,45,6,1,13.05053009399466\nPat White,West Virginia,2008,19,142.3,21,8,0,6.385230641176652\nNate Davis,Ball State,2008,10,157.0,26,5,0,6.050702467936028\nColt McCoy,Texas,2009,1145,147.4,27,3,1,16.18331903502398\nTim Tebow,Florida,2009,390,164.2,21,14,1,18.51486090299109\nKellen Moore,Boise State,2009,100,161.7,39,1,0,14.46082921027991\nCase Keenum,Houston,2009,37,154.8,44,4,0,4.218052997436561\nCam Newton,Auburn,2010,2263,182.0,30,20,1,23.86780983482786\nAndrew Luck,Stanford,2010,1079,170.2,32,3,1,13.946308906421848\nKellen Moore,Boise State,2010,635,182.6,35,1,0,12.802241937566109\nDenard Robinson,Michigan,2010,84,149.6,18,14,1,3.2478886059804224\nRyan Mallett,Arkansas,2010,41,163.6,32,4,1,10.82973394387262\nColin Kaepernick,Nevada,2010,31,150.5,21,20,0,11.384387560083765\nAndy Dalton,TCU,2010,30,166.5,27,6,0,14.944350584507326\nRobert Griffin III,Baylor,2011,1687,189.5,37,10,1,10.316157413813375\nAndrew Luck,Stanford,2011,1407,169.7,37,2,1,9.667409405228565\nMatt Barkley,USC,2011,153,161.2,39,2,1,9.562203977574791\nCase Keenum,Houston,2011,123,174.0,48,3,0,11.420863535280626\nKellen Moore,Boise State,2011,90,175.2,43,0,0,12.265954369362133\nRussell Wilson,Wisconsin,2011,52,191.8,33,6,1,8.281890427937858\nJohnny Manziel,Texas A&M,2012,2029,155.3,26,21,1,15.754760156860875\nCollin Klein,Kansas State,2012,894,149.2,16,23,1,11.817693133497077\nBraxton Miller,Ohio State,2012,144,140.5,15,13,1,15.169148199200322\nJordan Lynch,Northern Illinois,2012,52,144.9,25,19,0,6.92703223246081\nJameis Winston,Florida State,2013,2205,184.8,40,4,1,19.32052650022246\nA.J. McCarron,Alabama,2013,704,167.2,28,0,1,11.90196866646686\nJordan Lynch,Northern Illinois,2013,558,138.4,24,23,0,7.111211920283987\nJohnny Manziel,Texas A&M,2013,421,172.9,37,9,1,8.051361094960829\nBryce Petty,Baylor,2013,127,174.3,32,14,1,11.402244928532845\nDerek Carr,Fresno State,2013,107,156.3,50,2,0,7.156147448813237\nBraxton Miller,Ohio State,2013,91,158.1,24,12,1,10.39338163747249\nMarcus Mariota,Oregon,2014,2534,181.7,42,15,1,16.12744333111277\nTrevone Boykin,TCU,2014,218,145.9,33,8,1,13.076626318134918\nJ.T. Barrett,Ohio State,2014,78,169.8,34,11,1,20.0747422358138\nJameis Winston,Florida State,2014,51,145.5,25,3,1,18.46103191334333\nDak Prescott,Mississippi State,2014,21,151.7,27,14,1,9.456126458240307\nDeshaun Watson,Clemson,2015,1165,156.3,35,12,1,19.16167854243615\nBaker Mayfield,Oklahoma,2015,334,173.3,36,7,1,12.740224517380366\nKeenan Reynolds,Navy,2015,180,162.1,8,24,0,10.128862442591032\nConnor Cook,Michigan State,2015,13,136.6,24,0,1,14.713371407886711\nLamar Jackson,Louisville,2016,2144,148.8,30,21,1,5.608782090662399\nDeshaun Watson,Clemson,2016,1524,151.1,41,9,1,23.78005620893973\nBaker Mayfield,Oklahoma,2016,361,196.4,40,6,1,11.25001891558911\nJake Browning,Washington,2016,182,167.5,43,4,1,12.923870541835983\nBaker Mayfield,Oklahoma,2017,2398,198.9,43,5,1,11.183099131224177\nLamar Jackson,Louisville,2017,793,146.6,27,18,1,3.9226957076095994\nMason Rudolph,Oklahoma State,2017,56,170.6,37,10,1,6.425405376500221\nMcKenzie Milton,UCF,2017,54,179.3,37,8,0,19.08379077956817\nKyler Murray,Oklahoma,2018,2167,199.2,42,12,1,12.942861869472573\nTua Tagovailoa,Alabama,2018,1871,199.4,43,5,1,20.688097541235337\nDwayne Haskins,Ohio State,2018,783,174.1,50,4,1,13.097950650643533\nWill Grier,West Virginia,2018,126,175.5,37,3,1,5.5749718367802\nGardner Minshew,Washington State,2018,122,147.6,38,4,1,10.593990104817577\nMcKenzie Milton,UCF,2018,39,161.0,25,9,0,11.842688493982308\nJoe Burrow,LSU,2019,2608,202.0,60,5,1,27.81090580974389\nJalen Hurts,Oklahoma,2019,762,191.2,32,20,1,11.86131918185052\nJustin Fields,Ohio State,2019,747,181.4,41,10,1,19.03510596761913\nTrevor Lawrence,Clemson,2019,88,166.7,36,9,1,17.71916867557893\n", "type": "text"}, {"name": "Weekly_Data.csv", "content": "Player,School,Passing_Rate,Passing_TD,Rushing_TD,Power5,CPI\nJayden Daniels,LSU,197.7,22,4,1,9.996470516382256\nMichael Penix Jr.,Washington,189.9,20,0,1,22.69695237105186\nJ.J. McCarthy,Michigan,195.9,14,3,1,21.270050538343227\nJalen Milroe,Alabama,174.7,11,5,1,13.570723302000426\nTimmy Mcclain,UCF,177.7,9,1,1,1.6849078341013826\nKaidon Salter,Liberty,175.6,14,6,0,12.20981023988543\nCaleb Williams,USC,187.0,23,6,1,8.420336946119777\nJaxson Dart,Ole Miss,167.8,12,4,1,17.703387784662432\nDiego Pavia,New Mexico State,167.0,14,2,0,0.7450503077325233\nKyle McCord,Ohio State,165.9,11,0,1,26.14413878407365\nDillon Gabriel,Oklahoma,178.2,16,5,1,27.715560317738326\nBrady Cook,Missouri,168.7,14,4,1,16.729790617545717\nTyler Van Dyke,Miami (FL),171.8,16,1,1,5.311439268232076\nCardell Williams,Tulsa,151.6,8,3,0,2.171415441176471\nQuinn Ewers,Texas,163.8,11,5,1,20.75175441116404\nBrett Gabbert,Miami (OH),162.9,14,2,0,3.920146548570542\nJordan McCloud,James Madison,168.1,14,2,0,19.975142045454543\nCarson Beck,Georgia,163.8,12,3,1,15.485074626865671\nJack Plummer,Louisville,153.2,13,1,1,12.010369640535282\nSam Hartman,Notre Dame,166.9,18,2,1,15.199267174586778\nDrake Maye,North Carolina,159.1,12,4,1,21.284646674865197\nJT Daniels,Rice,157.4,15,0,0,1.0250516408591794\nSpencer Rattler,South Carolina,163.3,11,2,1,1.2742037978468896\nD.J. Uiagalelei,Oregon State,158.9,15,5,1,14.987510612382634\nKeyone Jenkins,Florida International,133.5,5,4,0,0.618658613936305\nGarrett Greene,West Virginia,143.7,6,5,1,5.763090676883778\nZeon Chriss,Louisiana,159.7,7,5,0,2.5762195121951215\nTJ Finley,Texas State,160.5,14,3,0,3.075065664479112\nBo Nix,Oregon,178.2,17,1,1,10.974942044357128\nCooper Legas,Utah State,159.7,13,0,0,1.8086380318333217\nDarren Grainger,Georgia State,154.4,8,5,0,9.702508336771178\nGraham Mertz,Florida,163.7,12,2,1,5.004320683556366\nCameron Ward,Washington State,159.8,14,3,1,6.126747240028489\nGunnar Watson,Troy,144.8,11,0,0,9.012728683930499\nGrayson McCall,Coastal Carolina,143.9,8,1,0,2.9700185403318238\nHaynes King,Georgia Tech,155.4,16,2,1,2.6717275943396226\nGrant Wilson,Old Dominion,134.8,7,1,0,1.1267314721369597\nChandler Rogers,North Texas,155.8,12,3,0,0.9459459459459462\nCarter Bradley,South Alabama,149.2,11,1,0,2.035137287621359\nJordan Travis,Florida State,154.1,13,4,1,23.00141752921983\nJayden Maiava,UNLV,140.3,5,1,0,6.340255400405775\nShedeur Sanders,Colorado,160.3,21,3,1,3.3095043052368793\nDante Moore,UCLA,129.8,10,0,1,9.983896940418676\nDeQuan Finn,Toledo,149.3,12,4,0,3.4537886646609453\nSeth Henigan,Memphis,144.7,13,3,0,5.452094625112917\nJoey Aguilar,Appalachian State,144.5,14,1,0,1.9296139171269242\nBrayden Fowler-Nicolosi,Colorado State,137.7,14,1,0,1.4417531718569778\nTaulia Tagovailoa,Maryland,146.0,16,4,1,4.004389579822285\nK.J. Jefferson,Arkansas,148.9,14,1,1,0.541213949654249\nGarrett Shrader,Syracuse,135.5,8,6,1,3.591105011169142\nDylan Hopkins,New Mexico,130.4,7,1,0,0.298408819083788\nAshton Daniels,Stanford,139.6,7,0,1,0.7859639513429152\nChandler Morris,TCU,144.6,12,3,1,3.7084461597614493\nNoah Fifita,Arizona,156.7,8,0,1,3.4744936096058257\nMax Johnson,Texas A&M,133.5,7,1,1,3.307061073261007\nJacob Zeno,UAB,148.3,12,4,0,0.40883006949742523\nWill Rogers,Mississippi State,138.7,10,0,1,1.602176870748299\nThomas Castellanos,Boston College,135.5,10,7,1,2.5212681708644276\nPreston Stone,SMU,137.6,14,1,0,3.484857682635864\nMikey Keene,Fresno State,147.7,15,0,0,4.465065626028063\nByrum Brown,South Florida,133.9,12,7,0,1.4834943682158241\nChevan Cordeiro,San Jose State,130.4,8,3,0,0.43959378759469797\nDonovan Smith,Houston,144.5,13,4,1,1.3569846082089552\nPhil Jurkovec,Pitt,124.6,6,1,1,0.5460516122693451\nBrayden Schager,Hawaii,137.8,17,1,0,0.3126073895065902\nLuke Altmyer,Illinois,127.7,8,3,1,1.8241426642919532\nCam Fancher,Marshall,135.0,7,2,0,4.750060178127255\nWill Howard,Kansas State,130.6,9,6,1,7.379528677010535\nMitch Griffis,Wake Forest,129.8,9,0,1,1.4392148740192017\nRiley Leonard,Duke,129.8,3,4,1,16.525516391324228\nNicholas Vattiato,Middle Tennessee State,137.4,11,2,0,0.4310847491706042\nRocco Becht,Iowa State,134.4,12,2,1,5.310806554517334\nDevin Leary,Kentucky,130.2,14,1,1,5.820780693229675\nEmory Jones,Cincinnati,131.2,11,3,1,0.8282001201923075\nTayven Jackson,Indiana,118.3,2,1,1,0.6737526165150155\nKedon Slovis,Brigham Young,128.1,10,3,1,2.71911029486787\nRocky Lombardi,Northern Illinois,123.4,6,2,0,1.1935816216927155\nKyron Drones,Virginia Tech,128.3,6,4,1,1.3726528468543207\nTaylen Green,Boise State,116.1,5,4,0,1.4237558654926838\nJack Turner,Louisiana Tech,121.1,5,2,0,0.3865979381443298\nJalen Mayden,San Diego State,125.1,6,3,0,1.5487259992754496\nJoe Milton,Tennessee,133.6,10,3,1,10.950425091911764\nDrew Allar,Penn State,145.3,12,3,1,24.810970139689864\nKurtis Rourke,Ohio,131.7,8,2,0,3.418116014878859\nTa'Quan Roberson,Connecticut,131.6,7,1,0,0.07637773686890442\nAustin Reed,Western Kentucky,134.2,14,3,0,4.995477883931683\nNoah Kim,Michigan State,119.0,6,0,1,0.9758874520779282\nAndrew Peasley,Wyoming,141.6,12,4,0,9.107826346139213\nMichael Alaimo,Kent State,111.2,2,1,0,0.035410592808551994\nHudson Card,Purdue,121.1,7,3,1,0.5990409401488118\nHeinrich Haarberg,Nebraska,116.9,4,3,1,2.2462277091906726\nDavis Brin,Georgia Southern,130.3,12,1,0,3.1488850344069195\nCade Klubnik,Clemson,135.4,11,3,1,8.347862188230616\nGavin Wimsatt,Rutgers,114.2,7,4,1,6.405312421763326\nE.J. Warner,Temple,121.3,12,0,0,0.21086421327107283\nJase Bauer,Central Michigan,112.2,4,7,0,2.099125364431487\nPayton Thorne,Auburn,118.6,4,2,1,2.153921072839992\nBilly Wiles,Southern Mississippi,112.7,7,1,0,0.08553542818445446\nTanner Mordecai,Wisconsin,118.8,3,4,1,6.393294608234562\nAlan Bowman,Oklahoma State,112.6,4,1,1,6.270821085635898\nBrennan Armstrong,North Carolina State,112.5,5,3,1,4.095803331129478\nDaniel Richardson,Florida Atlantic,121.7,5,0,0,2.0897284533648164\nJiya Wright,Louisiana-Monroe,114.1,6,1,0,0.45108611448337194\nAthan Kaliakmanis,Minnesota,110.8,6,2,1,3.5997308612440193\nAustin Smith,Eastern Michigan,114.5,6,1,0,1.1695764438716405\nBen Bryant,Northwestern,115.9,6,2,1,2.9203424043062203\nBrendon Lewis,Nevada,102.4,2,3,0,0.0\nCole Snyder,Buffalo,116.7,11,1,0,0.3553316852262804\nAlex Flinn,East Carolina,85.5,1,0,0,0.07646706398007125\n", "type": "text"}, {"name": "heisman_model.pkl", "content": "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", "type": "binary"}]
\ No newline at end of file
diff --git a/heisman_project/heisman_model/Data_Cleaning/__pycache__/model_data_clean.cpython-39.pyc b/heisman_project/heisman_model/Data_Cleaning/__pycache__/model_data_clean.cpython-39.pyc
index 8629ff9..3cf8da4 100644
Binary files a/heisman_project/heisman_model/Data_Cleaning/__pycache__/model_data_clean.cpython-39.pyc and b/heisman_project/heisman_model/Data_Cleaning/__pycache__/model_data_clean.cpython-39.pyc differ
diff --git a/heisman_project/heisman_model/Data_Wrangling/__pycache__/CPI_Ratings.cpython-39.pyc b/heisman_project/heisman_model/Data_Wrangling/__pycache__/CPI_Ratings.cpython-39.pyc
index 89488a7..56de998 100644
Binary files a/heisman_project/heisman_model/Data_Wrangling/__pycache__/CPI_Ratings.cpython-39.pyc and b/heisman_project/heisman_model/Data_Wrangling/__pycache__/CPI_Ratings.cpython-39.pyc differ
diff --git a/heisman_project/heisman_model/Data_Wrangling/__pycache__/Get_Weekly_Win_Percent.cpython-39.pyc b/heisman_project/heisman_model/Data_Wrangling/__pycache__/Get_Weekly_Win_Percent.cpython-39.pyc
index 22c2967..8d709d0 100644
Binary files a/heisman_project/heisman_model/Data_Wrangling/__pycache__/Get_Weekly_Win_Percent.cpython-39.pyc and b/heisman_project/heisman_model/Data_Wrangling/__pycache__/Get_Weekly_Win_Percent.cpython-39.pyc differ
diff --git a/heisman_project/heisman_model/Data_Wrangling/__pycache__/Quarterback_Stats.cpython-39.pyc b/heisman_project/heisman_model/Data_Wrangling/__pycache__/Quarterback_Stats.cpython-39.pyc
index 065d3d3..5979ea4 100644
Binary files a/heisman_project/heisman_model/Data_Wrangling/__pycache__/Quarterback_Stats.cpython-39.pyc and b/heisman_project/heisman_model/Data_Wrangling/__pycache__/Quarterback_Stats.cpython-39.pyc differ
diff --git a/heisman_project/heisman_model/__pycache__/__init__.cpython-39.pyc b/heisman_project/heisman_model/__pycache__/__init__.cpython-39.pyc
index f3dc7ca..7e7c916 100644
Binary files a/heisman_project/heisman_model/__pycache__/__init__.cpython-39.pyc and b/heisman_project/heisman_model/__pycache__/__init__.cpython-39.pyc differ