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Adopting Data and Analytics to Improve Your Youth Sports Organization, On and Off the Field

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By LeagueApps
July 13, 2021
4 min

In 2003, Michael Lewis’ Moneyball documented the Oakland A’s revolutionary use of analytics in personnel, training and strategy decisions, and forever changed the way we think about baseball. Nearly two decades later, the approach has officially trickled down to youth sports. Competitive youth coaches now employ data to elevate their team’s on-field performance. Savvy club and league organizers use analytics tools to enhance marketing, fundraising, and member retention efforts. Indeed, data-based methods can inform better solutions to a variety of youth sports problems. 

Whether you want to join the revolution, or improve on what you’ve already put in place, here’s a quick and easy how-to guide for using analytics: 

Start with a clear question.

Be as specific as you can about what you’re trying to learn, and what you intend to do with the answer. Here is a sampling of areas that youth sports organizers most often look to explore, and the questions they ask about them:

  • Performance:  What programs and techniques help our players develop their skills?  Which factors are most important in recruiting players?
  • Recruitment: Which marketing channels bring in the most participants? How do we optimize our website to get more sign ups?
  • Retention: Why do players walk away? Do any interventions make them stay?
  • Finances: How can we plan and market an event to maximize ticket sales?  What new programs will further our financial goals?
  • Player experience: How satisfied are players and parents with our programs?  Which coaches and staff members have more satisfied players?
  • Fundraising:  What’s the best way to identify and communicate with donors? How can we best document our achievements for them?
  • Social Impact: Do our players and staff represent the communities we want to serve?  Does participating in our programs improve off-the-field skills?

The scope of these questions may seem far from those that led Oakland to the playoffs, but analytics are being used for a wider range of objectives today. “A few years ago our objective was to win,” said Chad Sunderland, VP of Strategy and Business Consulting for the United States Olympic & Paralympic Committee (USOPC), during LeagueApps’ How to Make Better Data-Driven Decisions seminar. “Now, we are expected to set the standards for safety and the entire athletic experience. We’re using data to raise the bar and hold everyone accountable for making sure that sports culture evolves with the rest of the world.”

Assess your toolbox.

Your existing software suite may well already contain valuable data. For example, LeagueApps’ platform tracks registrations, invoices, transactions, e-commerce, and more. 

When considering new tools, refer to the question you’re trying to answer. Say you want to drill down on coaching efficacy, for example. Surveys, with online tools like SurveyMonkey and Qualtrics, are the best way to understand the player experience, especially when conducted regularly with a consistent set of questions.

Gather the data.

To get the most out of an analytics program, you need to be a digital packrat. You’re looking for unexpected connections, and you won’t find them unless all the relevant information is in one place. Thankfully, accumulating data is now easier than ever. For one thing, the cost of computing power and storage is low. For another, apps have replaced paper for everything from participation data  to stats sheets, so information is in digital form, easily combined and analyzed in several ways:

  • Exporting files: Most systems allow you to export a file, typically in the CSV (comma-separated value) format, which in turn can be imported into a spreadsheet or program. This requires a couple of manual steps whenever you want updated data, but it ensures information from the widest range of sources.
  • Data automation services: Their sole purpose is to move information between other software programs. Take Zapier, which links LeagueApps with hundreds of other products. So, for example, every time a player signs up through LeagueApps, Zapier could create a new entry on your participant list in Google Sheets.
  • Direct API connections: Many services can be linked directly with each other. This is often the best approach because it reduces errors and keeps data fresh.

One important note: Consider the privacy of others as you build your analytics program.  Think through what personal information you actually need, and make sure that all information is kept on a secure system with strictly controlled access. And, always be sure to share your data privacy policy with your members so that everything is by the book. 

Find the patterns.

With your data in an analyzable form, that initial question will lead your investigation. Are you trying to increase player retention? Search for any factors that could be associated with dropping out: skill level, team success, pricing, and more. Sometimes it helps to further segment the issue. Retaining younger players, for example, likely involves factors different than those that keep older kids. These programs will help reveal your answer:

  • Starter analytics programs: Even simple spreadsheet programs like Excel, Google Sheets, and Apple’s Numbers can store significant data, distill statistics and turn data into charts. 
  • Tools that make data analysis easier: There are lots of  general-purpose data analysis programs, including Google Data Studio and Microsoft Power BI. Tableau, in particular, has become popular among data crunchers in business, politics, and sports, allowing the creation of dashboards that monitor an organization’s performance day by day. Its tools also highlight important connections among data points.
  • Specialized tools: Google Analytics does a good job of helping you understand your online presence, showing you how people found your website and what they did there, and measuring the effectiveness of your marketing efforts. It can also incorporate information from thousands of other services. When integrated with LeagueApps, for example, it will tell you how many new registrations a specific social media post or paid advertisement generated. 

 

Don’t stop digging.

Data analytics is rarely a one-and-done process.  Like a scientist, you need to explore a hypothesis until the data tells you a new hypothesis is better, even though that one too will ultimately be superseded. You should think of data analytics as an evergreen initiative: in the same way your athletes need to practice every day to get better, you need to put consistent effort into your analytics program in order to put a better product on the field.