Like any area of analysis, sports analytics can be summarized by the collection of relevant, historical, statistics that pertain to a specific sport, team, game, or upcoming event. Through the collection and analysis of these data points, players, coaches and other staff are better informed to facilitate decision making both during and prior to sporting events. The information collected by analysts could also be beneficial to betting agencies and broadcast teams.
Are There Online Sports Analytics Programs?
Yes, there are a number of online sport analytics degrees. There are many options out there to round out a student's readiness for the sports analytics world, though some of them require a dual focus. However, there are very few programs specifically called Sports Analytics, so choosing the right university and program that is right for you is of utmost importance with regards to preparing for a world in the arena of data as it relate to sports and athletic performance. Sometimes there are degree programs that are focused on sport data analytics.
Consider an online program currently accepting applicants.
|Master||Online Master of Science in Sports Analytics Management
|Certificate||Graduate Certificate in Sports Analytics and Management
What is Sports Analytics?
There are two key types of sports analytics — those that are on-field and off-field. On-field analytics deals with improving the on-field performance of teams and players. It digs into the aspects of game tactics and player health and fitness. Off-field analytics deals with the business side of things like helping a sport organization surface insights that would help increase ticket sales, move merchandise, or improve fan engagement, etc. The bottom line of both aspects, is as usual, the bottom line of profit.
In Depth Review of 6 Top Online Sports Analytics Programs
Arizona State University - Online BS in Sports Business, BS in Business Data Analytics, and MS in Business Analytics
With analytics degrees at the graduate level and the option to pair a sports business bachelors, ASU provides a competitive array of programming. The BS in business data analytics is a 120 credit hour program comprised of 41 courses that extend for just under 8 weeks a piece. For an online program, this track has a high threshold for admissions with freshmen requiring either a 25 ACT score or 1160 SAT score, a class ranking within the top 8% of students as well as a GPA above 3.4. At the graduate level, students will encounter courses in data mining, decision modeling, and data-driven quality management.
Maryville University - BS in Sport Management with Concentration in Sport Data Analytics and MS in Business Data Analytics
This online program is uniquely positioned to prepare its graduates for a career in Sports Analytics with a specific concentration in it. On the pricey end of the tuition spectrum, however, this program comes in at $500 a credit, requiring 128 hours for graduation. Another program-specific detail to Maryville is that the coursework has a built-in partnership with both Rawlings and Game Face, giving students access to real-world experience and corporate level connections in the industry.
University of Mississippi - Online MS in Sport Analytics
Ole Miss' program is an accelerated, one year, online degree program with two emphasis areas – Sport Performance or Sport Business. The online MSSA program is designed to enhance knowledge, skills, and competencies in data acquisition, management, analysis, visualization and interpretation for improving sport performance and sport business. Coursework has a strong emphasis on practical skills in analytics, focusing on measurement and statistical modeling and big data analytics in the sports arena. The program combines academic, practical, and research-based skills to allow students to develop in their selected area. At just $466 per hour and 30 hours of credit to completion, it's one of the more affordable options available at such a recognizable school.
a target="_blank" href="https://www.online.olemiss.edu/mssa/sport-business.html">Website
Indiana University–Purdue University Indianapolis - Online Accelerated B.S/M.S and M.S in Applied Data Science with Concentration in Sports Analytics
There are a few key things that make this program so unique. Beyond a "traditional" online masters degree with a concentration in the sports analytics field, IUPUI also offers an accelerated B.S./M.S. program to earn both your undergraduate and graduate degrees back-to-back and in less time than is typically possible. In addition, while the program itself is online, IUPUI is situated in Indianapolis, the city widely considered the Capitol of Amateur Sports. While it boasts 10 professional sports teams, the city is home to the National Collegiate Athletic Association (NCAA) and the National Federation of State High School Associations. Faculty within this program not only practice in one of the sports analytics hotbeds, they are a combination of masterminds from IU’s Schools of Physical Education, Tourism Management and Informatics and Computing drawing a unique mix of resources for students within this program.
American University - Online M.S. in Sports Analytics and Management
American University prides itself on delivering curriculum that is timely and up-to-date with the latest trends, technology, and news within the predictive data sports landscape. The programming at American is divided into four components which comprise what they call the "Professional Studies Experience." Like many of the programs on this list, you work in a cohort of students that begin and progress through at the same time to foster a collaborative environment and make connections outside the classroom. The four components at American are Core, Electives, Field/Professional, and Capstone. Because AU specifically focuses on coursework that is leading-edge, experiential in learning and that includes hands-on study, they are confident in this program's ability to address employers' needs. Students graduate well-prepared to take a seat at the table with their acquired knowledge and skills that can immediately be applied to real-world situations.
California University of Pennsylvania- Online M.S. in Sport Management with Concentration in Strategic Sport Analysis
Because Cal U's Strategic Sport Analysis concentration falls under a business-forward graduate degree, it primarily focuses on the business and management issues essential to the sports industry. The program touts three key takeaways that students will graduate with the ability to do including analyze the structure of sports teams and determine their potential (or lack thereof) for future success, strategically manage a club or organization using data analysis, and develop a framework to assist in implementing new strategies as well as handling change management. A unique aspect to this degree program is that it requires a 12 credit mentorship program that can take place at the organization of the student's choosing, including a current employer for those students working through the program while maintaining full-time employment.
8 Common Sports Analytics Course Curriculum
Intro to Business Data Analytics
Overview of analytics within a business context including concepts of strategy and operations; overview of concepts like data modeling, the model lifecycle, data mining, Key Performance Indicator metrics, ERP, in-database/memory, data stream, etc.
Intro to Sport Business Data Analytics
This course familiarizes students with the major underpinnings of the sport data analytics space. Often considered an ancillary competency in the analytics space, students learn the importance of soft skills in the analytics industry, like effective communication, framing complex problems correctly, and accurately gauging the success of a solution to a key business problem. Common data manipulation tasks in Microsoft Excel are also learned through real-world sports industry case studies.
Business Data Mining
Building predictive analytics (e.g., SEMMA, KDD), exposure to logistic regression, machine learning and decision tree methods. understanding lift factors, ROC curves, hands-on use of mining software, and business case studies.
Quantitative and Qualitative Research Methods
This is an introduction to design and data collection procedures. Students will learn about the nature and application of qualitative research in sports busines, how to conceptualize qualitative research and to formulate problem statements and research questions, how to design a qualitative research study and about qualitative data collection procedures-observation, interviews, focus group interviews, and collection and use of documents.
Measurement and Evaluation in Sport
This course presents the foundations for making reliable and valid judgments about matters of scientific concern in sport areas. Basic knowledge of measurement and evaluation for designing the various test settings and conducting the evidence-based practice will be covered, and approaches will be presented that enable you to make sound decisions based on empirical data in sport.
Communication and Data Visualization in Sport
Data Visualization aims to improve comprehension, memory, inference, and decision-making as it refers to issues in sport analytics. This course introduces techniques, algorithms and tools for creating effective data visualizations based on principles and techniques from graphic design, visual art, perceptual psychology and cognitive science. Emphasis is placed on the identification of patterns, trends, and differences among data sets. Students will be able to understand the fundamentals of communication and alignment around concepts required for effective data visualization. Students will be able to select and use techniques, algorithms and tools for creating visualization of real-world data. Students will become proficiency in creating static and interactive visualization for data from a variety of disciplines. Students will be able to use data visualization to support decision-making and critical thinking.
Big Data Analytics and Data Management
The explosion of social media and the computerization of every aspect of social and economic activity resulted in creation of large volumes of mostly unstructured data: web logs, videos, speech recordings, photographs, e-mails, Tweets, and similar. In a parallel development, computers keep getting ever more powerful and storage ever cheaper. Today, we have the ability to reliably and cheaply store huge volumes of data, efficiently analyze them, and extract business and socially relevant information.
The key objective of this course is to familiarize the students with most important information technologies used in manipulating, storing, and analyzing big data. We will examine the basic tools for statistical analysis, R and Python, and several machine learning algorithms. The emphasis of the course will be on mastering Spark 2.0 which emerged as the most important big data processing framework. Other topics include: Spark ML (Machine Learning) API and Spark Streaming which allows analysis of data in flight, i.e. in near real time, NoSQL storage solutions exemplified by Cassandra for their critical features, memory resident databases (VoltDB, SciDB) and graph databases (Ne4J).
Students gain the ability to initiate and design highly scalable systems that can accept, store, and analyze large volumes of unstructured data in batch mode and/or real time. Most lectures will be presented using Python examples. Some lectures will use Java and R.
Predictive Analytics in Sport
Advancements in technology and sports have led to the creation of models that can compute probabilities of sports win/loss prospects as well as analyze the performances of individual players. In this course, students compute simple statistics of a prior game, then use correlation to detect statistical relationships between different metrics. The science of rating and ranking is covered in detail, and regression models will be used for estimating a metric from several predictor variables. Predictive models will then be used to compute win/loss probabilities. Topics include: metrics used for team and player evaluation, Sabermetrics, models for win/loss probabilities, regression techniques, player and team performance report generation.
Top 3 Sports Analytics Career Paths
Collegiate or Professional Team or Business Analyst
Statistics have become such a vital part of any sports program because they help teams make sense of collected data and apply it to practical scenarios to increase performance and, ultimately, lead to successful results. Player statistics can be used to make informed decisions about level of performance, game strategies and recruitment options. Off the field, sports analytics can be used to analyze data about such factors as fan-engagement, ticket sales and concession sales in order to make the business run more efficiently and profitably.
Broadcast or Media Analysis
Sports media companies such as ESPN, Fox Sports or Sports Illustrated are increasingly using sports analytics to enhance their sports reporting. While fans will likely be turned off by a strict discussion of statistics, sports analytics can be used to put sporting events and outcomes into perspective and give fans a greater context to appreciate athlete performance or game outcomes. For example, if a team comes from behind to win a game it is exciting, but it is even more interesting if you know that the probability of that outcome was 0.1%. Sports analytics can be used to improve reporting on sports events and engage fans as well as increase entertainment value.
Fitness or Sports Tech. Analysis
Specifically: wearable technology. It has quickly become essential to the world of sport and it requires sports analysis professionals to develop and advance these products. Wearable technologies collect an enormous amount of data. Sports analytics also plays an important role in the development of training technology such as simulators and virtual reality devices for athletes. Sports analysts with exercise science or kinesiology backgrounds may also find work in human performance labs. These labs use specific athlete training data to fine tune performance and increase training efficiency.