Last Updated on March 31, 2022
Sports Analytics Degree – How to Become a Sports Data Analyst
“In the same way the industrial revolution changed the world forever, I believe people will look back at this time and think the same thing. The data explosion is truly phenomenal. If you were to take all the data that has been created since the beginning of the world and put it into a giant warehouse, 90% of what is in that warehouse has been created in the last 24 months. And the rate of new data creation is still exponentially expanding!”Dr. Darin White, Center for Sports Analytics at Samford University
When the best selling book Moneyball by Michael Lewis was turned into a feature film years ago, the concept of sports analytics was formally introduced to popular culture. Back in 2003 when the book was published, many teams didn’t employ a single sports data analyst. Today, every professional sports organization employs a team of sports data analysts. Sports analytics has experienced significant growth in recent years. It is a large and growing business and the success of teams that have invested heavily in analytics has validated the entire industry.
Sports Analytics by the numbers:
- This is a quickly expanding field in which growth through 2022 is predicted to be at 27 percent. [source]
- A sport statistician’s median pay in 2019 was $92,030 per year ($44.25/hr.). [source]
Why is Sports Analytics so Important?
In today’s world, data analytics affect the sports industry in many ways. Sports teams use analytics to find the best talent available and build championship-caliber teams. Teams also apply sport science analytics to optimize the output of their players in the form of training, nutrition, and load management.
On the business side of sports, where fan engagement, advertising and partnerships have become invaluable drivers of revenue, data analytics play an even more important role. In an interview with Sports Degrees Online, Dr. Ted Hayduk from New York University highlighted that,
“…in reality, for every analyst looking at ‘on field’ outcomes, there are probably three to five analysts in the business strategy or marketing verticals. And, generally speaking, these two groups don’t speak to each other because they are concerned with very different outcomes.”
It is important for sports analytics graduates to keep this in mind – that it is extremely valuable to understand the fundamentals of sports analytics both ‘on field’ and in the business world. The marketability for sports data analysts who are versatile problem solvers promises to be exceptionally strong for years to come.
How a Sports Analytics Degree Can Help Launch Your Career
There is no question that data analytics will be a crucial part of the future of both sports and business. For students who are eyeing a career anywhere in the sports industry, the best way to future-proof your education is by building a foundation in data science and analytics.
Kieran Kelliher – who is VP of Finance for the Chicago Bulls and an adjunct professor at Northwestern University – recently spoke with Sports Degrees Online about trends in the sports industry,
“I look at where growth is right now in sports and it’s heavily in sports analytics. Not only on the sports side, but especially on the business side. Seeking customer insights, deep dives into data. How can we collect and analyze data to deliver a more tailored or customized product or element of the service? That relies on a degree of skill that doesn’t just naturally grow up inside a sports team. A lot of these organizations are going outside to get someone who has data analytics experience and is really good with statistics.”[source]
Dan Matheson, the former director of baseball operations for the New York Yankees, interviewed with Sports Degrees Online and had this to say on the future of sports analytics:
“I think you are going to see continued growth in the use of analytics as an important element of the decision making process, in all areas of sports. Analytics gets a lot of attention on the player personnel side, on the field and on the court but analytics will play a big role in all aspects of an organization from sponsorship deals to social media and game presentation.”[source]
Earning a Sports Analytics Degree – even if it is just a concentration area, or a minor to complement a business or sport management degree – provides applicants with a distinct advantage over other candidates for virtually any position. Companies and teams are literally drowning in all kinds of data, so any candidate that can help them create a plan for how to derive value from their data would have a significant advantage. Candidates who have a Sports Analytics Master’s Degree – who know how to approach a wide range of problems in a professional manner – will be highly sought after for many years to come.
Sports Analytics Fundamentals – What to Expect from a Sports Analytics Degree
Any Sports Analytics Degree must include a foundation in both statistics and data analytics. There may be more than a few students and young professionals out there who are interested in sports analytics, but may be nervous that their math skills or coding skills may not be strong enough.
Math and statistics are important in sports analytics, but maybe not in the way you are thinking. Sports Degrees Online asked Dr. Ted Hayduk from NYU about the importance of mathematics when pursuing a career in sports analytics. He pointed out that statistics is subtly different than pure mathematics, which is filled with calculations and memorization of formulas. In many cases, working with statistics in sports analytics is more conceptual. An important point to consider when working with models and statistics is that “A lot of the models in analytics are really just middle school applied math like linear algebra and matrix algebra, but on steroids.”
When asked about how important strong math skills are to study sports analytics, Professor Darin White explained it this way:
“Yes, [math skills] are important. But when we say math, we aren’t talking calculus, geometry and trigonometry. We are talking about statistics, which is a different type of math. I know a lot of students who were not very good when they did advanced calculus but once they got into stats, they really flourished. It’s a very different kind of math than what you would take in high school. There you will take algebra, calculus, geometry and trigonometry. Some students in high school might have the chance to take a class in statistics, but certainly not everyone.[source]
I ask two questions all the time to high school students applying to our undergraduate program – I want to know 1) how well they did in the statistics class, and 2) did they enjoy it. Because that’s what you are going to be doing all day every day. You are going to be running statistical analysis, regression, ANOVA and correlation data. A lot of people do like stats. Those who don’t like the other math subjects thrive in statistics because they feel like they can see the relationship to the real world easier.
In addition to understanding the fundamentals of statistics, coding programs that can process large data sets in a variety of ways are another key part of sports analytics. Professor Hayduk also shares some advice on specific coding skill sets that he expects to be an important part of a future in this industry:
“Coding languages such as R and Python are more flexible and thus allow the analyst to complete a wider array of tasks integral to the data science process (and to complete them more seamlessly). Also, as part of the data science toolkit, future practitioners in sport will likely need to be familiar with more advanced modeling techniques related to machine learning (ML), artificial intelligence (AI), and deep learning (DL).Ted Hayduk, Statistical Modeling and Sports Business Analytics
Dr. Hayduk continues to explain that the understanding of the AI/ML/DL process “aim to aid computers improve their execution of certain tasks by constantly incorporating new information.” [Source]
Beyond knowing which questions to ask and having the tools to answer them using huge sets of data, there are two other key aspects in which sports analytics professionals must be fluent. The first is the ability to communicate results. Dr. Hayduk explains,
“The final stage of the data analysis process involves disseminating findings and communicating about the results. This represents a special challenge for data science because it often involves distilling very complex concepts and methodologies into palatable, clear insights. Furthermore, being able to relate the tactical findings of the analysis to the larger strategic implications it generates is a unique skill in and of itself.Ted Hayduk, Statistical Modeling and Sports Business Analytics
The second key skill set – which is related to the first – is the ability to understand how the data might be visualized so that it can be easily and instantly expressed to a diverse group of people. Again, Dr. Hayduk explains,
“In order to clarify and effectively communicate the results of an analytics project, analysts will need to become familiar with various data visualization techniques and programs. Data visualization refers to the process of presenting complex relationships in ways that are visually informative and thus palatable to someone unfamiliar with the technicalities of the analysis. A well-made data visualization tool can make the difference between other stakeholders accurately interpreting the results of a project or not.Ted Hayduk, Statistical Modeling and Sports Business Analytics
Understanding the Stories That the Numbers are Trying to Tell
But how is one to understand how to turn specific data trends into precise action plans that will positively affect a team or company? Well, that requires deep understanding of the business or the sport that you are working on.
If finding solutions hidden in data was a simple endeavor, it would not be such a big deal. This is where the real magic lies.
In the previous section, Professor Hayduk outlined how sports analytics uses statistics, coding programs, and visualization to turn troves of meaningless data into useful actionable items for decision makers to use. But before that process can start, the sports analytics team must determine what they are trying to find and where they might find it.
On the business side of sports analytics, data analysts must understand how revenue generation works before they can even begin to approach using data sets to gain valuable insights. Professor Darin White, Director of the Center for Sports Analytics and Professor at Samford University, explains,
“It’s one thing to not know how to do predictive analytics and how to use programs like Tableau, R, and SPSS – you have to have that, and understand that – but you also have to understand how to take that data and put it in a format that business decision-makers can use to make important business decisions. So you need to have knowledge of the business side of the industry and what would be a valuable insight… You may be looking at the most unbelievable insight ever, but you don’t understand it because you don’t know the industry. Or, you may be thinking “Wow, if I could find that it would be really valuable” but in reality, it’s not that valuable. So really understanding how the industry works and how the business side of the industry works, and how revenue generation works is important.[Source]
The Path to Becoming a Successful Sports Data Analyst
Get yourself acquainted with the field
It is a complicated and interesting field that requires knowledge of data science, statistics, and for many a passion for sports. In the current age of the internet, there is a wealth of knowledge out in the world. As you are job searching, studying, or preparing your portfolio, set time aside to read articles or blogs regularly, listen to podcasts, or even check out some books from your local library (or purchase them). Some great titles are…
- Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football by Wayne Winston.
- Trading Bases: How a Wall Street Trader Made a Fortune Betting on Baseball by Joe Peta.
- Moneyball: The Art of Winning an Unfair Game by Michael Lewis.
- Basketball on Paper by Dean Oliver
- Chasing Perfection: A Behind-the-Scenes Look at the High-Stakes Game of Creating an NBA Champion by Andy Glockner
- Betaball: How Silicon Valley and Science Built One of the Greatest Basketball Teams in History by Erik Malinowski
- A Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos
- The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman
- Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths
Landing the First Job in Sports Analytics
With a relevant degree in hand, the next logical step for many would be to get hired. What is the best way forward?
- Create a portfolio. There is an incredible amount of publicly available data that you can use to start your first project. This will help to get you familiar with different software and tools that you would need to use on the job, and it can be very helpful to have a goal to work towards, and then figure things out as you go. While this may lead to a feeling of spinning your wheels and not making progress as fast as you would like, just remember that every day working on the project is time well spent. A project that is in the works is a great talking point as you are meeting analysts in the industry. A completed project is an even better talking point.
- Publish Something! Share your knowledge and projects with the world. Social Media has become increasingly important for job seekers. Consistently sharing articles that are interesting, and sharing your own projects and reports will help build your brand and gain credibility in the field. Again, Professor Darin White explains, “You have to build your brand. You have to be intentional about building your brand as a rising sports industry executive. This can be done by internships, writing and publishing content, including on our blog or website, and making your resume stand out. Anything you can do to build that brand.” [source]. If you have a project you are proud of, reach out to media publications, sports blogs, sports radio shows, professional teams, and see if they are interested in your analysis. The worst thing that could happen is they said no, and the best thing that could happen is you could get paid for your work, gain exposure, and maybe even land a job.
- Leverage Your Network! This is a competitive industry with a lot of people willing to work for low wages or even for free to get their foot in the door. If you are in the financial position to do the same, it could very well pay off in the long run. There are conferences around the country related to sports analysis. Perhaps the most famous is the MIT Sloan Sports Analytics Conference. This is an excellent opportunity to meet like-minded people and grow your professional network. Many times conferences post featured speakers, sponsors, and in some cases attendees. It is wise to comb through this list and make it a point to try and speak with people from organizations which you are interested in working with. While this is not the best time to hand out your resume, it could be a very good time to make a first introduction, grab their contact information and follow up at a later point in time. If you are comfortable you can offer to provide your services for free if they have any projects they need help with.
- Further Schooling. If you have gone through the motions of learning some of the tools of the trade and could use more professional instruction, then think about the return on investment of time and money. Ultimately it is up to the applicant how they will build up their resume with the education, portfolio, and experience. However, a certification or degree in data science or statistics can go a long way in providing you with a solid foundation for your career as well as keeping the momentum going of building your projects and portfolio.
Sports Analytics Jobs – What to Expect
Professional organizations depend on their sports analytics teams to produce insights on a wide range of projects. As such, there are three different Sports Analytics applications. They are:
- Sports Business Analytics
- ‘On Field’ or ‘Moneyball’ Sports Analytics, and
- Sport and Exercise Performance Analytics
While there is some overlap between these disciplines, each requires a different academic foundation in order to know what you are looking for within the data. Let’s look closer at what each area involves
Sports Business Analytics
As Professor Ted Hayduk noted at the top of this guide, “for every analyst looking at ‘on field’ outcomes, there are probably three to five analysts in the business strategy or marketing verticals.” Because the business side of Sports Analytics has so many emerging opportunities, a business foundation is a wise career move.
During the game, organizations, sponsors, and partners gather troves of data about how effective each of their in-game components are at engaging their fans, both in the stadium, at home, and on social media. They will be monitoring things like sales of concessions and merchandise, how many fans are using in-game apps for fantasy statistics, and any other traffic that they hope to drive. Professor Darin White explains how professional teams try to leverage the data that they collect,
“Sports teams are buried in data on the business side of the organization. We’ll take ticketing data, social media data and help teams better determine how they can drive revenue from that data. How can they make better business decisions based on that data? That’s one part of it.
Another part is focusing on the sponsorship side. As you probably know this is an exploding channel in the marketing world. It’s in the seventy billion dollar range just for North America in terms of total sponsorship spends each year. We also find they work quite a bit with brands like Coca Cola, Chick-Fil-A, Transamerica, Phillips 66 and on and on. There are so many brands out there that leverage sports property so you have to achieve their marketing objectives as well. [Sports Data Analysts] help those brands understand the value they are actually getting from those partnerships.[source]
Anyone who has seen professional sporting events – whether it be an NBA game, and eSports tournament, an MMA match, or the World Cup – is confronted with messaging from sponsors and partners who are vying for your attention. As Professor White explains, data analytics weigh heavily into the decisions that those companies make, and there are a wide variety of objectives that they might be hoping to achieve.
“The market objective and the business objective of the brand is going to be different in almost every situation. Some are looking for awareness, others are looking to get into the consideration set. When you’re hungry and it’s lunch time and there’s three restaurants, you want to make sure your restaurant pops into their mind. Sponsorship is a great way for that to happen.”[Source]
Another related aspect of business analytics relates to the high value that many sporting event attendees represent to sponsors. Professor John Grady of the University of South Carolina, who recently spoke with Sports Degrees Online, explains,
“if you are a season ticket holder of an NBA team, [for example], you likely have enough disposable income to be a luxury car owner or a high-end watch consumer. Those customer profiles start to mesh together pretty nicely. So having that user data is quite valuable in sport.[source]
This is a significant benefit for high profile, official sponsors who are keen to get the attention of valuable customers.
‘On Field’ or ‘Moneyball’ Sports Analytics
In recent years, professional organizations have poured an incredible amount of time and resources into assembling winning teams, and a significant part of team building strategy is informed by analytics. Sports analytics is used by the scouting and player development departments to help the front office assemble the most competitive team each season.
‘On Field’ Sports Data Analysts work to find competitive advantages through scouting players using advanced statistics or metrics. They must have an incredible depth of knowledge and nuance about the sport(s) that they are working on. Without knowing exactly where to look and what to look for, it is not possible to find the knowledges hidden in the data. As sports analyst and freelance author Sam Gregory wrote a few years back,
“You need to understand the sport, what the problems that the sport presents are, how data can be used to approach these problems and how to communicate all of this in a succinct and easy to understand manner.”Sam Gregory, [source]
The job market for ‘On Field’ Sports Data Analysts varies a great deal. Some sports already have very advanced analytics departments, while other sports have hardly gotten started. Professor Darin White of Samford University explains, “baseball is much more advanced whereas a sport like soccer is more in the developmental stage. We are still trying to figure out the things we need to be measuring that are meaningful.”
Professor White continues,
“I think it’s going to mature. If you look at baseball, for example, your typical pro team now has several dozen analytical executives that work for [professional teams] like the Braves, Marlins or whoever. You have a pretty large analytic staff whereas the NBA, pro soccer or NHL, the numbers are much smaller. Those numbers are about ten to fifteen years behind when it comes to analytics.[Source]
I think what you’ll find in the next ten years or so, those other sports are going to pick up the pace and do more hiring. Analytics are going to become more a part of the equation in a lot of those areas.”
Sport and Exercise Analytics Careers
Tom Brady leading the league in passing at 44 years old. LeBron James still in his prime after 20 years in the NBA. What do these legends have in common? Both are religious about the care they invest in their bodies, and the results speak for themselves.
The field of Sport Science is becoming a more important field than ever. With the proliferation of wearable technology, there is more data than ever to analyze from players throughout each game. Sport Science is a multi-disciplinary field that is a synthesis of fitness regimens, nutrition, post-training treatment, and biometrics. The more we understand about the body, the better we become at helping athletes reach new levels of potential.
Sport Science is also an important discipline for injury prevention and recovery. By helping athletes understand how injuries occur – and the ways that this risk can be minimized – sport and exercise analytics has become an incredibly important tool for coaches and trainers.
Professor Kristof Kipp, Director of the Sports and Exercise Analytics program at Marquette University, recently spoke with Sports Degrees Online about how this field is poised for growth:
“The amount of data that we collect and generate will also just continue to increase, so I think an understanding of data science methods, how to analyze, or visualize, or appropriately collect data will become more and more valuable. Wearable devices will probably become even more ubiquitous as well. We’ve just seen a proliferation of wearables, such as power meters for running, and all other sorts that provide you with very, very detailed information about how your body is doing or functioning at the moment. Knowing how those wearables work and what kind of data they provide – so we can make assessments as to the validity and the reliability of that data – is very important.”[source]
Students seeking careers in Sport and Exercise Science need a background in areas such as kinesiology, exercise science, health and human performance, or biomechanics to understand the human body and how it moves. From this knowledge foundation, students then learn data science and research methods that help them approach complex questions.
Since the early returns on investment have been so convincing, expect career opportunities for Sport and Exercise Data Analysts to grow significantly in the years to come. Again, Professor Kristof Kipp,
“There’s been an increase in jobs at the professional sports level and within professional sports organizations who are looking for people with specific sports analytics qualifications. In the US, we don’t have as many professional or industry academia partnerships, but if you go to places like Australia, it is more common to have partnerships between academia and industry or organizations. There are also biomechanics labs that are associated with orthopedic practices where they’re offering fee-for-service testing, injury screenings, and biomechanical or post-op assessments. We’ve had quite a few of our students not go into academia and go into those positions, which are pretty exciting. They get paid well and some of them get to travel a lot as well.”[source]
Sports Analytics and Legal Sports Betting
Looking at the growth of fantasy sports and how quickly many states have legalized gambling since New Jersey broke the barrier in 2018, there is no question that these industries are poised for considerable growth. For anyone who has watched any professional sports programming in 2022 – whether it be pre-game shows or the product itself – simply looking at how many many ads and sponsorships FanDuel and DraftKings are investing in is telling. This is a huge industry, and it is only getting bigger.
As states across the US continue to legalize sports gambling, it certainly seems like the negative stigma that has often been associated with gambling is starting to fade throughout popular culture around the world. All of this while the cost of technologies, data storage, and computer modeling have been decreasing, helping sports analytics companies boost their margins has left the job market trying to keep up with the incredible wave of demand for sports data analysts.
There are teams of sports data analysts overseeing all of the algorithms which produce the gaming odds. As this industry continues to grow, so will the demand for Sports Analytics professionals at these companies.
The demand for data analysts continues to grow across the board, including in the sports industry. With that said, the future growth of positions will vary considerably from sport to sport. Professor Darin White, who recently spoke with Sports Degrees Online, explains, “When you look at NBA, NFL and MLS teams – they are just now hiring their first folks in analytics in the business or sports side, whereas the MLB teams already have full blown analytics departments.”
Sports Data Analysts work for Sports Marketing Agencies, Professional Teams, Professional Leagues, Collegiate Teams, Collegiate Teams, Collegiate Leagues, Sports Analytics Firms, Media Outlets, and Tech Firms.
According to ZipRecruiter, the average annual Sports Analytics salary is $93,119.
Technically, no degree is required to be a sports data analyst. Anyone with extensive experience using R and/or Python will have a good foundation from which to contribute to a team. With that said, the coursework that comprises a sports analytics degree – from data driven decision making to data visualization and communication, understanding how wearable technology collects data, etc. are all essential to the job.
If you are passionate about solving problems related to sports, and you enjoy diving into statistics to determine what stories lie within, a career in sports analytics could be a dream profession. Learning how to use both R and Python programming languages will provide you with the tools to solve a wide range of exciting problems using data, and with average salaries approaching six figures, the future of the field is very bright.