Abstract and forward

If you want to get straight to work, skip the first few chapters and go directly to chapter 5. The work content of this book is all contained in the back half. The first few chapters will familiarize you with the data, we’ll examine the tools we’ll use to explore it, and explain how to contextualize your projects. Then, if you continue reading this chapter, I will explain why I put this project together and what it contains.

This book was primarily conceived as a resource for a young person who wants to work in sports business under an analytics group, strategy function, and to a lesser extent, an I.T. team. These skill sets blend together and complement one another. However, this book could be helpful to almost anyone that wants to get a deeper understanding of how analytics is functionally used in a club setting.

I was once asked by a college professor teaching an analytics course how many analysts we would need in the future. He was speaking in front of his analytics students, and my response was different from what he wanted to hear. We are going to need fewer. I encouraged the students to apply their analytics skills to a discipline such as marketing, I.T., or finance. Technology is rapidly commoditizing analytics work. If you have these skills but work in another field, you can be an incredibly effective manager. From that perspective, anyone working in sports business could benefit from this knowledge. It helps you understand the benefits and limitations of analytics and puts you in the driver’s seat when implementing the strategies you believe will be most effective.

Additionally, this book is partially inspired by a vestigial lament from my youth. When I took a math class, I was always forced to show my work, but the hypocritical writers of textbooks didn’t feel as though this precept applied to them. You were invariably tricked on a test through some algebraic edge case that was entirely new to you. This stuff was formulaic. Just demonstrate how to solve these problems, and I can do the same for all similar problems. The way math used to be taught in school was less about concepts and more about calculation, but there was some modicum of conceptual learning that needed to blend better with contemporary teaching techniques. I want to correct this mistake in a limited way. I want to show you the naked truth. This book is an exposure. I want to show you everything. To that end, it serves four primary purposes:

1. To give you an analytically grounded toolbox that you can build upon
2. To teach you about how a sports team’s business works
3. To demonstrate how to apply this knowledge to real problems to achieve desired outcomes
4. To build a reference manual of solutions to common problems

The first three items of this list are the foundations of your core business strategy. You need experience to put together effective strategies. This text should give you a head-start working with analytically oriented tasks that help support strategy. You won’t be a strategy or analytics expert, but you’ll better understand how to approach many common problems. Analytics (as a field) is an excellent tool for understanding various issues, but it has limits. Keep this quote in mind:

If all you have is a hammer, everything looks like a nail.

This is the famous Law of the Instrument¹. Analytics and data are not the answer to every question. I must assume that many people seem to think this way since it is something that you tend to hear often. Since I am trying to show you how to do this work, we will traverse a lot of very granular material. Due to the more technical nature of that material, it is better suited for people that want to develop specialized skill sets. It is less well suited for people that want to understand the application of the theory.

While technology has democratized analytics, analytics is still a black box to many managers. These people should depend on these tools. Instead, they will often retreat from them. Consider this quote: “Expert Power is influence wielded as a result of expertise, special skill, or knowledge.” (Stephen P. Robbins 2012) Understanding these tools and techniques gives you a degree of expert power. However, as a manager without this knowledge, the idiom “the tail wags the dog” applies. If you don’t understand these concepts but want to use them, you can lose credibility with your employees or look less competent than those you manage.

While you don’t need to know how to script or code to leverage this book, some programming/scripting knowledge will be an enormous benefit. You will want to understand some basic scripting to fully use this text. You will be heavily exposed to it, and I need you to learn to have a working knowledge of it. It is still a necessary prerequisite to work on implementing solutions in this field. The code that you’ll find in this book is written in R (R Core Team 2022). In fact, this entire book was written using R libraries using free software. It was edited using a software called Grammarly². We’ll mostly follow best practices as defined in “Advanced R” (Wickham 2014). While Python has become more prevalent recently, I find R more suitable for non-programmers.

R is excellent in some ways and unusual in others. It has some idiosyncrasies that make it operate differently than many programming languages. The most noticeable difference is in flow control, where for and while loops are avoided in favor of a suite of vectorized functions. These functions have also been expanded and improved by generous developers. If you don’t know what this means, you will learn it, so don’t worry. Our examples will use common constructs when we aren’t penalized on run-time. From a data-science perspective, Python uses many packages duplicating R’s advantages (Pandas and Numpy). You’ll come away with an appreciation for the language whether you want that appreciation or not.

Additionally, I hope to expose you to a lot of reading material and concepts. In fact, all an undergraduate education does is give you a broad cursory knowledge base consisting of facile ideas. You probably didn’t put many of the concepts to use in practice, but you will know things like “If I want to find the area under a curve, I can probably use the Integral.” This is great. It means you can Google through most problems really quickly. The books I mention in the text are ones I have stumbled across while trying to solve problems. I mention them to make your life a little easier. Analytics is too large of a field to know everything. You need to know how to find the answers; others have probably done this for you. Hopefully, you will be introduced to enough concepts to speak to the most critical subjects in these verticals. I’ll make simple references to Wikipedia pages whenever I talk about specific topics that don’t require in-depth information or are out-of-scope. That will be enough to get you started.

Furthermore, I want to teach you a little bit about the main business functions of a professional sports team. Sports is a unique business. Its fortunes are often outside of the control of most of the employees. Your strategies need to reflect this fact. If you think your efforts to sell tickets will be ineffective, why do they? This is where strategy comes into play. If you know the team will be dismantled in a year, how does that change your approach?

We’ll also frame strategy around goals. This means all kinds of different things. To a club, it could mean your plan to achieve a goal of $x valuation. Sports clubs act differently than other assets. Additionally, there has been a rapid proliferation of SPACs designed to invest directly in teams. Valuations are beginning to reach such levels that a single owner may soon be a dinosaur. That will change the way these clubs are run. A club is worth whatever some tech oligarch, hedge-fund managing pirate, real-state heir, company, or consortium wants to pay, and there are thousands of these groups. They are not necessarily worth a discounted cash flow based on revenue.

We aren’t going to cover corporate strategy. We aren’t going to talk about setting up shell companies, owning different parts of the value chain, human resources structure, shady finance and accounting, new business opportunities, and extensions, or the agency agreements that make these businesses function. Instead, we will closely examine the strategy that makes the wheels turn where dollars are exchanged between the club and its fans.

From that perspective, we can create a provisional definition of strategy in this context:

Strategy is the discipline of amplifying revenue-generating efforts, operationalizing improved procedures, consultation on how decisions interact to build cohesive business systems, and longer and shorter-term planning through coordinated and informed decision-making.

That is a deconstructable mouthful, but we don’t want it to be too narrow or broad. We also don’t like to extend platitudes. A definition explains how to think about these problems in this specific context. If you are skeptical of anything you find here, that is good. But please don’t take me at my word. As an analyst, you should demand to be convinced. You’ll have to think actively to do it. This type of work isn’t for the intellectually lazy. You don’t have to understand that the Atkinson cycle ³ makes your car work to be able to drive it. Many analytic techniques can be thought of the same way. You don’t need to understand the underlying mechanisms. You just need to know how to appropriately wield them. This is the gas pedal, this is the brake. An analyst or a strategist is a mechanic for the business systems of a club. If everything always worked, you wouldn’t need them.

The first chapter 1 will cover some essential analytics elements, such as the intersection of information technology. It will also examine the distinction between disciplines such as Business Intelligence and Analytics. We’ll also discuss some technologies that are integrating these disciplines at scale and how these functions will continue to evolve. This chapter helps frame a foundation for the rest of the book.

The ability to leverage analytic techniques is predicated on access to quality data. The second chapter 2 will familiarize you with the data we will use by going through the exercise of creating it. The formats will closely resemble data that we have found in-the-wild. This includes customer data along with standard demographic data formats. We’ll also build a database of ticketing data from the primary and secondary markets to be used in a pricing exercise. We’ll also create some activity data to demonstrate common pitfalls we’ve seen when building sales and marketing plans. This data will be constructed based on an imaginary professional baseball team. Baseball operates differently than other sports because of the high number of games. However, the lessons learned here can be applied to almost any sport. In fact, the lessons in this book can be used for business problems in various industries. Unfortunately, it is a boring chapter. This book isn’t about coding, but we will demonstrate precisely how we do everything we show you. This way, we will pay off a debt my old math teachers owe me.

In chapter 3, we will cover how to explore your data. While B.I. technologies such as Tableau make performing ad hoc analysis relatively easy, writing your analysis in code has enormous advantages. This chapter covers many typical graphs and shows how to build and understand them. It will also demonstrate how to summarize and consolidate data. This is such a prevalent task that it would be easy to ignore it. Using a programming language to manipulate data is so much better than using excel that I can’t express it well enough. R is Excel on military-grade performance-enhancing drugs. While Excel and other spreadsheet programs have their place, after you begin using paradigms found in R, you will avoid them whenever it is convenient. Point-and-click tools sometimes make finding solutions to problems more difficult if you know how to accomplish the same task.

In chapter 4, we will examine how to frame projects. Some basic project management knowledge is valuable, and we’ll cover some of it. This would also be an easy chapter to avoid, but it was essential to include it. It contains some good examples of how to frame a project by asking the right questions. It tries to avoid pedantic MBA speak but definitely covers some of that arena.

In chapter 5, we will demonstrate several methods for building customer segmentation schemes. Consumer segmentation is crucial to an integrated sales, marketing, and research strategy. There are myriad ways to accomplish a practical and helpful segmentation scheme. It is as much an art as it is a science. This chapter will cover some fundamental concepts through a working example to demonstrate one way segmentation might be performed. One of the most essential skills an analyst has in the toolbox is understanding how to deal with missing data. You’ll cover it firsthand here.

In chapter 6, we will cover pricing and forecasting. Pricing is complex, but we will cover how they are computed. Increasingly, pricing exercises are becoming a commodity. This means you may be working little on it directly, but you must understand a few methods prices are decided upon in practice. This chapter also goes deeper into another critical tool that you will use, regression. Regression is the gold standard for estimating numerical data, and understanding some of its complexity is essential. We’ll also cover forecasting in this chapter. Forecasting is also an art and a science. We will cover what forecasts are useful and discuss how to think about them.

Chapter 7 will demonstrate a couple of methods of Lead Scoring. Lead scoring is also fundamental to an integrated sales and marketing strategy. It is an extension of segmentation. Lead scoring can also be slightly controversial. It is a different way to think about going after sales. This chapter will discuss a few commonly used techniques and demonstrate how to build a machine-learning model. It will also illustrate some crucial concepts endemic to the sports marketing world.

As an extension of pricing, we’ll look at promotions in chapter 8. Promotions are a critical marketing component, and there are good and bad ways of looking at them. You also have to make many assumptions when working with marketing. Economics is referred to as “The dismal science.” If Economics is dismal, Marketing is just as dreary but needs more science in both thought and practice. In this chapter, we will also walk through the essential components of a marketing strategy and discuss some of the problems with attributing sales to marketing functions.

Methods for conducting research will be covered in chapter 9. Conducting research is tedious, time-consuming, and often thankless, but it is fundamental to business strategy. Research is also an enormous subject. We’ll examine some valuable techniques that go beyond examining facile attitudinal questions. This chapter will introduce you to some critical concepts if you haven’t conducted formal research. This chapter needs to be longer. It simply glances at enormous subjects such as hypothesis testing and sampling. If you can only take one thing away from this chapter, I want you to know that sampling is critical to do correctly and is always a problem.

Chapter 10 will cover Operations. Operations is a broad topic, and we will discuss some important concepts. Simulation and queuing will be addressed in the context of real problems faced in stadium and ballpark operations. Simulations are the bread-and-butter of operations problems, and you must understand how they work. They are often the best way to understand a system. You’ll enjoy this chapter if you don’t have an operations background and like mathy subjects.

This book can’t be comprehensive. As you have gathered from the preceding paragraphs, this book is heavily concerned with sales and marketing. That is for a good reason. Professional sports teams have high fixed and variable costs and enormous operational leverage locked into payroll. They have a few primary sources of revenue (Ticket sales, Concessions, Retail sales, Media, and Sponsorship). All of these sources are derivative of having fans attend games or watching the games through media outlets. If you are concerned with the fundamentals of your strategy, it has to start with getting your approach to selling and marketing to fans correct. Get the structural parts right. Suppose you or the executives don’t think you are maximizing your opportunities around sales and marketing. In that case, you won’t be able to focus on higher-order projects that prove more valuable in the long or short term.

In addition to what we will cover, Social data, Marketing mix, Retail, Media, staffing, F&B pricing, corporate sponsorship, and operational components of the experience, such as gate entry and parking, all impact revenue and strategy. Furthermore, there could be structural issues throughout the value chain that we need to consider. For instance, a league could have an out-sized influence on your technology stack or even own the digital rights to fans. ⁴ Your strategy must take all of these factors into consideration. Your CRM and technology strategy also has a direct influence on success. From a CRM perspective, we will only touch it tangentially. If we covered every one of these subjects or even went into detail on the ones we cover, this book would be many times longer. However, you will come away from it with an excellent foundation for working in various positions throughout a sports organization.

Finally, this book will quickly become outdated. In many ways, it is already obsolete. The field of analytics has progressed rapidly over the past decade. New technologies (upgrades in hardware and software) make performing specific tasks easier. Amazon Web Services and the Google Cloud Platform offer sophisticated tools for analytics, and I expect much of the low-hanging analytics fruit in sports and other industries to be harvested by these platforms in the coming years. Research uncovers new methods for approaching problems, and higher-order skill sets make specific tasks commodities.

Additionally, consumer behavior makes performing other tasks obsolete. Other factors are entirely out of our control. I hope this text will give you a deeper understanding of the sports industry, and you’ll quickly be able to eclipse what you find here to push our discipline and industry further along.

0.1 Book Liscense

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Just give credit where it is due. Nothing is new, everything is built on those that came before you. We aren’t trying to advance theory here, just to show you how to do some of these things.

0.2 Code Liscense

To the extent possible under law, Justin Watkins has waived all copyright and related or neighboring rights to this work. This work is published from: United States.

Do whatever you want with it.

0.3 Contact Information

Justin Watkins: watkinsjudo@gmail.com