My Eli Manning article from last week pulled no punches against the New York Giants quarterback, dissecting both his statistics and his game film and finding him lacking in both areas. For further clarification, I wanted to explain why I weighed his statistics regarding negative plays so much more heavily than I weighed his statistics regarding positive plays.
Manning’s positive plays ranked close to the top of the league, but the frequency with which he threw interceptions was the deciding factor in my conclusion that he was unworthy of being discussed as one of the top 100 players in the league. The reason for this is that turnovers absolutely kill teams because they take away a chance for the team to score, AND they give the opposing team an extra chance to score.
About a year ago, I performed a mathematical investigation into the significance of turnovers in the NFL, using each statistics from every team in the league over a period of ten years. While it’s a no-brainer that turnovers are bad, I aimed to discover the extent to which they inhibited a team’s chances of winning. The results were rather shocking. The investigation revealed an equation that, given no information other than a team’s turnover differential, could predict a team’s win-loss record correctly within one standard deviation an astounding 70 percent of the time.
For those of you who like both math and football, please read the investigation and enjoy it. For those of you who like football but not math, have no fear. While the process used to derive the formulas was mildly complex, the results are presented in a manner that allows readers without an extensive mathematical background to see the impact of turnovers as well. If you have any questions about the study that you’d like for me to clarify or explain, feel free to comment on this post or send me an email.
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Hank Koebler is an NFL Writer and On-Air Personality. Hank's work as a journalist has been widely published and he's received numerous citations for his NFL coverage. You may email Hank @ firstname.lastname@example.org or follow him on Twitter @HankKoebler