Do MLB giveaways and special events influence attendance?

Do MLB giveaways and special events influence attendance?
by Kirk Wakefield – October 2018

Forbes reported before the 2018 season started that clubs planned over 1800 special event promotions, including about 28 giveaways per team on average. The Cardinals (49), Dodgers (42), and Cubs (41) all topped 40 giveaways. The Marlins (11), Athletics (14), and Diamondbacks (15) were the least giving. If you’re already seeing a pattern, you may be onto something.

Not everyone follows MLB attendance with the same passion as I do. I’ve been tracking and analyzing MLB attendance trends decade by decade since 1990. In the 1990s and early 2000s, it was the rash of new stadiums drawing fans to the game. As we move into the current decade, the strongest predictor of attendance is the presence of star players (represented by total payroll) and the fact that each new year brings overall lower attendance. Winning has always been important, but always behind star power and stadium-related factors (including capacity). Ticket prices, as we’ll see shortly, rarely influence annual attendance. Instead, we can reliably predict next year’s prices based on this year’s attendance.

What about giveaways and special events?

We don’t have historical, annual data on the number of giveaways and special events offered by team. But, thanks to Forbes, we have them for 2018.

It’s not enough to ask, “Are more giveaways and special events correlated with attendance?” You must account for anything else that might influence attendance. Thankfully we did this for you.

To explain average attendance (right) we include the following factors for each team:

  1. Total payroll in dollars
  2. Won/loss percentage
  3. Stadium capacity
  4. Special Events
  5. Giveaways
  6. Population/Franchise Index 1
  • Fan Cost Index (see Team Marketing)
  • Park factors: Runs scored; Home runs

 

The results

We can explain 91.3% of the variance in attendance with these factors. If you think that is high, you are correct. We rarely explain over 90% of anything. If you’d like to play with the data yourself, click here to download. 2

We numbered the factors above for a reason. They represent, in order, those factors with the most influence on attendance. Total payroll (B = .411), winning (B = .328), and size of the stadium (B = .313; i.e., bigger stadiums like the Yankees and Dodgers) each strongly predict average attendance.

Special events (B = .224) and giveaways (B = .198) significantly influence attendance (p < .05). But, not so fast. We took a deeper dive on the relationship of giveaways on attendance. The relationship is not linear.


As most readers likely guessed, what we see is the classic sideways-S curve of a cubic function. Ok, maybe you don’t hit these kinds of curves very well. But, you can see from the graph that teams offering few giveaways (e.g., Marlins and A’s) fared poorly.  As teams offer 10-20 giveaways, attendance increases. However, the dip in the curve shows a good many teams with 20-40 giveaways actually decrease in attendance. This is bad.

What is good? Going all out. The teams offering 40 or more fared very well. This finding is consistent with the philosophy of making the big even bigger. Rather than using promotions only to shore up lousy games, make the big game weekends too big to ignore. The spillover excitement offers a windfall to attendance overall.

What is better? More giveaways and special events give fans more reasons to go. Without, you’re just selling baseball. With, you’re selling entertainment. Want baseball fans to bring less motivated family members and friends? Give them a reason. Many reasons.

The unconvinced are saying, well, those are the Dodgers, Cubs and Cardinals. They have bigger or better stadiums, or winning teams, or maybe bigger markets. We accounted for all of that, remember? These numbers don’t lie. The number of giveaways explain or predict attendance (apart from everything else), and the effect increases at an increasing rate.

Conclusion

The results also show that special events significantly increase attendance. Teams like the Padres (172), Brewers (136), and Royals (126) benefitted from these appeals to different market segments to increase attendance above what it would have been without them. We can argue those with the fewest special events (Red Sox, Mets & Yankees) didn’t need them because of the other factors going in their favor. What might they have done with them?

Finally, it’s always interesting to note the cost of going to the game doesn’t influence average attendance. Neither did any of the park factors, like runs scored or home runs. The total market size and inter-city rivalries help attendance, but just as it has from 1990-2015, it is the least (although significant) effect.

 

  1. The PFI accounts for larger markets + total major league franchises in the DMA. The New York teams lead the way with the largest population and the most (9) major league teams.
  2. To get 91.3% R-Squared you need to include the quadratic and cubic functions for giveaways.

How to get started using Big Data in sports

How to get started using Big Data in sports
by Aaron LeValley – April 2015

Big data requires strategy

“Big data” is no longer just a buzz phrase or a passing fad. According to a W.P. Carey School of Business study at Arizona State University, the amount of data accessible for businesses is growing exponentially, with the amount of data doubling every 1.2 years.  Having a plan for this amount of data is no longer a way to generate a competitive advantage, it’s a necessity.

Bobby-Whitson-Headshot
Bobby Whitson

Bobby Whitson, Partner at SSB Consulting Group, summed it up nicely when I chatted with him recently about the growth of big data in sports. “Without an effective data warehouse and management strategy, sports teams will continue to struggle to manage data efficiently, and more importantly, make data actionable.  Big data should be a focus of every team; from generating revenue to creating better fan understanding and engagement.”

charlie
Charlie Sung Shin

It may seem overwhelming when approaching this project, but with a few steps, you can help your organization step in to the future. According to Charlie Sung Shin, Senior Director, Strategic Planning – CRM & Analytics at Major League Soccer, “Developing a big data strategy is a journey and it’s not just about implementing new technology or integrating a customer database. The strategy needs to support and continuously be aligned with your organization’s overall goal.”

How teams can get started with big data

So where do you begin? Here are a few steps which may help you and your organization adopt a big data project.

  1. Establish Objectives.
    1. Meet with your constituents to address short, mid and long-term goals.
    2. Example Goals
      1. Short-Term: How can I use this data to grow revenue for a ticket promotion?
      2. Mid-Term: How can I create a better profile of my customer through all of the data feeds we have?
      3. Long-term: How can we use the data to identify trends to generate more revenue or increase efficiency is aspects of our business?
  2. Identify key data sources.
    1. What are all the sources of data you have, transactional & non-transactional?
    2. Which of these data sources are most important for your objectives?
      • Don’t be afraid to not incorporate some data sources from the start. It’s a process and can be taken in steps.
    3. Data source examples include: Ticketing, Email, Social Media, Website, Surveys, Loyalty, Merchandise, Concessions
  3. Analytical Models / Dashboard.
    1. Aggregating the data alone doesn’t get your team anywhere. Remember (or figure out how) to identify what types of dashboards or statistical models are needed to reach your goals/objectives.
    2. Models/Dashboards examples include: Projecting Single Game Sales, Lead Scoring, Retention Risk Modeling
  4. Identify a partner.
    1. Many sports teams and organizations don’t have the staffing to do this on their own. Make sure you find the partner that fits your needs, be it strategic, technical or other.
    2. Some partners may include: SSB, Teradata, Hadoop, AXS, or SAS

The work doesn’t end there, but if you start with these 4 steps, you’ll be well on your way to bringing your organization to a new level.