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Analytic Versus Non-Analytic Decision Makers And Their Effect On Win Percentage After In-Season Player Acquisitions, Kenneth Adam Siemers, Xin Gao Mr., Tyler Armijo, Brandon Lovette
Analytic Versus Non-Analytic Decision Makers And Their Effect On Win Percentage After In-Season Player Acquisitions, Kenneth Adam Siemers, Xin Gao Mr., Tyler Armijo, Brandon Lovette
Creative Activity and Research Day - CARD
This paper examines whether teams with winning records that employ analytic decision makers see a higher increase in win percentage after in-season player acquisitions versus teams that employ non-analytic decision makers. This was accomplished through analyzing the in-season player acquisition data from the MLB and NBA over the last four completed seasons through descriptive and inferential statistics. There was not a significant difference between the two groups in average win percentage after total acquisitions, trades, or signings. Using inferential tests we found no statistical significance between the type of decision maker, and the difference in win percentage after an acquisition.
What Does It Take? Deciphering Performance Indicators Of Nfl Running Backs Through The Examination Of Collegiate Performance And Nfl Combine Results, Colin W. Weaver, Kevin L. Hindenach, Zach A. Vos, Antonio De Moss Jr.
What Does It Take? Deciphering Performance Indicators Of Nfl Running Backs Through The Examination Of Collegiate Performance And Nfl Combine Results, Colin W. Weaver, Kevin L. Hindenach, Zach A. Vos, Antonio De Moss Jr.
Creative Activity and Research Day - CARD
This research uses a linear regression model to investigate the relationship between prospective NFL running backs’ NCAA FBS football statistics, NFL Combine measureables, and realized performance in the NFL as evaluated by Pro Football Focus. We observe 435 player-seasons from 2007-2014. The model suggests that collegiate conference affiliation, collegiate touchdowns, and NFL team passing strength are positively associated with NFL running back performance at statistically significant levels. Conference affiliation has the most substantial effect. NFL talent evaluators must appreciate that context is king when evaluating potential, and that pure stats are only a small piece of the puzzle.