4/6/2023 0 Comments Badger basketballThey held Ohio State scoreless for 6 and a half minutes. Refusing to go quietly into the night, the Badgers started clawing their way back. In the midst of this exciting comeback, it was mentioned by the TV announcers that the largest comeback in the Big Ten tourney was a 16-point Ohio State comeback against Nebraska in 2014. The final 10 minutes were some of the most inspired basketball Wisconsin has played all season. The last 10 minutes were a completely different story. The first 30 minutes of the game was anything but that. I’ve always thought of Wisconsin basketball as gritty and tenacious. Wisconsin basketball tried to make magical history With 11:03 left in the game, Ohio State made a lay-up that stretched their lead back to 22 points. Their 18 first-half points were the second-lowest first-half output of the season (they only scored 16 in their last loss to Illinois). Down by as much as 27 points, the Badgers could not have played any worse. It looked like the team thought so too.įor the first 28 minutes of their game against Ohio State, Wisconsin basketball seemed apathetic. The Big Ten announcers stated before the game that Wisconsin’s coach, Greg Gard, thought that UW had done enough to get an at-large bid come Sunday. In a game that many thought Wisconsin needed to win in order to get into the NCAA tournament, the Badgers were surprisingly blase for the first 3/4 of the game. Wisconsin basketball seemed disinterested In a game that many had written off after the first 12 minutes, the Badgers mounted a furious comeback that ultimately fell short. The y-axis in this graph represents the percentage weight of the score that gets applied to an overall team ranking.Wisconsin basketball dropped their opening round game of the Big Ten tourney to Ohio State, losing 65-57. You can see that the area under the curve gets smaller both as the rating for a commit decreases and as the number of total commits for a school increases. This standard deviation creates a bell curve with an inflection point near the average number of players recruited per team.īelow is a graphical representation of how our formula works. Readers familiar with the Gaussian distribution formula will note that we use a varying value for σ based on the standard deviation for the total number of commits between schools for the given sport. This formula ensures that all commits contribute at least some value to the team's score without heavily rewarding teams that have several more commitments than others. You can think of a team's point score as being the sum of ratings of all the team's commits where the best recruit is worth 100% of his rating value, the second best recruit is worth nearly 100% of his rating value, down to the last recruit who is worth a small fraction of his rating value. In order to create the most comprehensive Team Recruiting Ranking without any notion of bias, 247Sports Team Recruiting Ranking is solely based on the 247Sports Composite Rating.Įach recruit is weighted in the rankings according to a Gaussian distribution formula (a bell curve), where a team's best recruit is worth the most points. Where c is a specific team's total number of commits and R n is the 247Sports Composite Rating of the nth-best commit times 100.
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