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Does signing a high priced player make a MLB team more profitable? By: Brad Tuffy and Lynn Kilduff
No salary cap in MLB. NHL cap $56.8 million NBA cap $57.7 million NFL cap $128 million 16 of the top 50 highest paid athletes are baseball players Basketball, Football, Hockey, Boxing, Racing, Golf Background
Large difference between highest and lowest spending teams. 2009 New York Yankees payroll: $201.5 million 2009 Florida Marlins payroll: $36.8 million Baseball has an exciting offseason GM bidding wars Hot stove reports Trades to unload expensive contracts Hypothesis: spending money on high priced players makes a team more profitable Background cont…
162 game season April until October Longer careers It’s America’s pastime New York and Boston found success 2009 Yankees: $201.5 million 2007 Red Sox: $146.7 million Reasons
LA Dodgers Traded for Manny Ramirez in 08. Total attendance in 2009 3,761,669 NY Yankees 5 top paid players in MLB. (Jeter, Rodriguez, Texiera, Sabathia) Total attendance in 2009 3,719,358 Philadelphia Phillies Traded for Cliff Lee and signed Pedro Martinez in 2009 Total attendance in 2009 3,600,693 Oakland A’s Traded away Matt Holliday in 09 and released Jason Giambi in 09. Total attendance in 2009 1,408,783 Ticket Sales
Phillies acquired Pedro Martinez in July 2009. Pedro Martinez is a former CY Young award winner with an impressive resume. On August 12th 2009 Pedro Martinez made his first start for the Phillies. Comcast Sports Net achieved record setting ratings during this baseball game. Most watched program on television in the Philadelphia market during this time slot. Philadelphia
Season long average Nielsen rating was 7.1 and for this game the overall rating was 11.1 at times hitting over 13. The ratings associated with these high profile players drive up ratings in turn driving up what TV networks can charge for advertising. The end result means a bigger television deal for the baseball team. Philadelphia
Target Audience – MLB Fans Sampling Plan – decided to target specific sites baseball fans frequent Summary of respondents – 37 fans Administration – MLB.com, ESPN.com Potential Sources of error – disgruntled fans, proud fans (won’t really admit the truth) Data Collection
Survey Questions Q01: Who is your favorite baseball team? Yankees 9 -Mets 4 Phillies 7 -Cubs 3 Dodgers 3 Q02: How excited would you be if you team signed such a player?
Survey Questions Q03: Would you want to view more games on TV if your favorite team signed such a player? Q04: Would you want to attend more games live?
Survey Questions Q05: Is your favorite team available in your area without a TV package? Q06: If your favorite team is not available in your TV market without the MLB TV package, would you purchase it if your team signed such a player?
Survey Questions Q07:What would you buy more of if your team signed such a player?
Survey Questions Q08: How much do you agree with the following statements?
Survey Questions Q09: If you knew such a player was making his first start on the field for your favorite team, would you tune in? Q10: What would intrigue you most about such a player on your favorite team?
The results from the hypotheses tests showed us that most fans will view more games on TV both overall and when such a player debuts. This supports our original hypothesis. Surprisingly the results for live attendance showed us that most fans will not attend more games if such a player is signed. This does not support our original hypothesis and would definitely not help the profitability of a baseball team. Reporting
Collect more results to get a more accurate picture. In the future it would make sense to start collecting this information at the beginning of the baseball season and continue the study for the entire season. This could be useful information for a baseball organization considering the signing of such a player. Reporting
Is there a relationship between a fan’s level of excitement over a player and the likelihood they will spend more money on the team (watch TV, live games, more merchandise)? Null: There is no relationship between excitement level and likelihood to spend money. Alt: There is a relationship between excitement level and excitement level. Multiple R: .8155 R Squared: 66.5% Adjusted R Squared: 63.4% Standard Error: .5034 Significance: .000000056 Regression Analysis
Multiple R: .8145 R Squared: 66.4% Adjusted R Squared: 64.4% Standard Error: .4967 Significance: .00000000089 P Values Watch TV: .00448 Buy More Merchandise: .0000001 Take Out “Attend Live Games”
Scale used for “excitement” 1=Very excited 2=More excited than usual 3=No more excited than usual 4=Less excited Intercept: 3.03 Watch TV: -.62 Buy More Merchandise: -1.13 Person who would watch more TV and buy more merchandise is 1.28 (close to very excited). Reporting