EFFECTS OF OFFENSIVE STRATEGIES ON NFL PERFORMANCE

Introduction Offensive strategies of the National Football League have seemingly shifted towards a “West Coast” style offense, relying more heavily on passing as a means of scoring touchdowns than the more conventional rushing approach. I examine the question of whether adopting the strategy of passing more frequently than rushing resulted in a statistically significant increase in games won from 2006 to 2008. I used Ordinary Least Squares regression analysis to generate an equation estimating the determinants of current regular season wins. Since the Media Exposure variable was not normally distributed, I used a log transformation to normalize the data. Potential determinants of current year wins include team strategy, media exposure, previous year playoff experience and regular season wins, average points per game, conference dummy variables, and variables that reflect whether or not a team has a new coach and stadium.

Equation Wins=ƒ(Media, Prior Playoffs, Rushing %, Points, Prior Wins, Conference, New Stadium)

Variables Dependent VariableCurrent regular season wins over three seasons: 2006-2007, 2007-2008, and 2008-2009. Independent VariablesWins: Number of regular season winsLog Media: Number of times the top four offensive and defensive players were mentioned with first and last name in both Sports Illustrated and Sporting News.Playoffs: Dummy variable indicating whether the team earned a playoff berth the previous seasonPoints: Average points per game in the current seasonPercent Rushing: Rushing yards divided by the sum of rushing and passing yards.Rushing : Number of rushing yards in current season.Passing: Number of passing yards in current season.AFC: Dummy variable indicating whether the team was in the AFC.Stadium: Dummy variable indicating whether the team is playing in a new stadium in the current season.Previous year wins: Number of regular season wins in the previous season

Conclusion Consistent with the original hypothesis, the number of current year wins depends on team strategy. Regression Model A suggests that a ten percent increase in Percent Rushing, or rushing as a percentage of total offensive yards, increases current season wins by nearly one game. As the average team over the three seasons in question dedicated only 35.5% of their offense to rushing, increasing this percentage to 45% was not unheard of in the league. Similarly, Regression Model B implies that 500 additional rushing yards generates approximately one additional regular season win. Conversely, Regression Model C indicates that 500 additional passing yards decreases the number of current season wins by roughly half of a game. Practical application of these variables seems to be backed by logic and readily observable patterns. As strong teams finish a winning game, they tend to rush more in an attempt to burn the clock, while the losing team tends to toss up long passes in a last ditch effort to salvage the game. This strategy will inevitably bring more passing yards to a team even in the event of a loss, while the winning team gains rushing yards and wins. Log Media was statistically significant in all regression models, indicating that the offensive and defensive leaders of a team are turning in noteworthy performances over the course of the season. If media exposure increases by 50 percent, current year wins will increase by approximately 1/3 of a game. Though the coefficients are significant, the economic effects are small. Other results suggest that a team will win approximately 3 more games in the current regular season if the team earned a playoff berth in the previous season. Similarly, four additional points per regular season game translates into approximately 1.2 more current season wins. All regression models indicate that conference affiliation, whether a team is playing in a new stadium, and previous year wins are not significant determinants of current regular season wins. Future studies on this topic should consider expanding the time period and including defensive variables in an attempt to bring further clarity to the subject. However, in light of the findings of this study, it seems entirely plausible to say that a strong running game is essential for most teams even in today’s passer-friendly era.

Trevor Ahbleza Crazy Horse Stanley

Bachelors of Arts, EconomicsAdvisor: Dr. Julianne Treme, PH.D.

Department of

Economics

Variables Description Mean Standard Deviation

Regression Model A

Regression Model B

Regression Model C

LOG Media Number of times top four players appeared in media.

2.839 .963 .60025 (.20348)***

.55704 (.20181)***

.62631 (.21087)***

Playoffs Dummy variable

indicating previous year

playoff appearance

.375 .487 2.5114 (.4616)****

2.60173 (.45507)****

2.50294 (.48076)****

Points Average points per gamein the current season

21.458

4.489 .31949 (.05064)****

.24650 (.04918)****

.38458 (.0669)****

Percent rushing

rushing yards as a

percentage of total offense

.355 .065 9.72321 (2.87889)***

-

-

Rushing yards Number of rushing yards

1,835 346 -

.00190 (.000539)****

-

Passing yards Number of passing yards

3,362 590 - - -.00109 (.00043)**

AFC conference

Dummy

AFC or NFC conference

Dummy variable

.5 .5 -.37840 (.34918)

-.40477 (.34666)

-.42788 (.35799)

New Stadium Dummy

If a new stadium was built within the last year

.03 .175 1.27548 (1.03494)

1.25744 (1.02631)

.96332 (1.05336)

Previous year Wins

Number of wins in the

previous year

8 3.176 .04486 (.06298)

.04805 (.06254)

.04338 (.06504)

Adjusted R^2

-

-

-

.712

.715

.696

Observations Number of observations per variable

96 96 96 96 96

Statistical significance denoted on chart as follows: *= 10%; **= 5%; ***= 1%; ****<.1%.