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A Statistical Analysis of NFL Quarterback Rating Variables

Listed author(s):
  • Stimel Derek

    (Menlo College)

Using data from NFL seasons 1960-2007, we examine the quarterback rating and the four variables of which it consists: average yards per attempt, completion percentage, interception percentage, and touchdown percentage. We test for structural breaks in the means and standard deviations of each variable. The analysis finds evidence that there are structural breaks in the series likely associated with rule changes designed to promote the passing game and the implementation of the salary cap. The break test results as a whole suggest that comparisons of quarterbacks from different regimes are inappropriate unless the regime differences are taken into account. There appears to have been a simultaneous improvement in quarterback performance and reduction in volatility suggestive of the idea that the relative difference between above average and average quarterbacks has been reduced. Using graph theory and the information gleamed from structural break tests, we examine the causal relationships among the four quarterback rating variables over the most recent stable period, which is 2000-2007. The causal analysis shows that completion percentage is commonly caused by interception percentage and average yards per attempt over the course of a season. Also, touchdown percentage causes average yards per attempt. We suggest possible explanations of the findings and suggest avenues for future research.

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Article provided by De Gruyter in its journal Journal of Quantitative Analysis in Sports.

Volume (Year): 5 (2009)
Issue (Month): 2 (May)
Pages: 1-26

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Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:2:n:1
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References listed on IDEAS
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  1. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  2. Ruxandra Prodan, 2004. "Potential Pitfalls in Determining Multiple Structural Changes with an Application to Purchasing Power Parity," Econometric Society 2004 North American Summer Meetings 90, Econometric Society.
  3. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
  4. Hoover, Kevin D., 2003. "Some causal lessons from macroeconomics," Journal of Econometrics, Elsevier, vol. 112(1), pages 121-125, January.
  5. Hoover, Kevin D & Sheffrin, Steven M, 1992. "Causation, Spending, and Taxes: Sand in the Sandbox or Tax Collector for the Welfare State?," American Economic Review, American Economic Association, vol. 82(1), pages 225-248, March.
  6. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
  7. Hoover, Kevin D., 2005. "Automatic Inference Of The Contemporaneous Causal Order Of A System Of Equations," Econometric Theory, Cambridge University Press, vol. 21(01), pages 69-77, February.
  8. Hoover, Kevin D & Siegler, Mark V, 2000. "Taxing and Spending in the Long View: The Causal Structure of US Fiscal Policy, 1791-1913," Oxford Economic Papers, Oxford University Press, vol. 52(4), pages 745-773, October.
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