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Special Project

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Batting, analytics and data literacy: A triple play

Entered in Education

Objective

SAS is on a mission to empower the next generation with data literacy skills through the SAS Batting Lab. This is an interactive experience that combines AI, computer vision and IoT analytics to help kids improve their baseball and softball swings and their confidence in using data.

The tech-laden batting cage is packed with sensors and cameras to capture a batter’s stance, swing and ball-flight details. Through AI, computer vision and IoT analytics, stance and swing data are analyzed in real time, and feedback and suggestions for improvement are shared via in-cage charts, graphs and visual prompts on its floor and walls.

Batters see how to optimize their weight distribution, hand position, core movements and other factors. The Batting Lab analyzed thousands of swings from elite players – including from North Carolina State University’s baseball and softball teams – to build a model of the optimal swing. It uses this to help guide youth hitters to a better swing.

While The Batting Lab may improve kids’ hitting on the diamond, its most important outcome is to prepare them for the future by giving them the confidence to interact with the data and analytics that run the world around us. This introduction to data and analytics and to the concept of data literacy is The Batting Lab’s true home run.

Strategy

Data literacy will soon be the number one requested job skill. In fact, 85% of executives believe data literacy will become as vital in the future as the ability to use a computer is today. (“Data Literacy: The Upskilling Revolution”) However, 48% of kids today don’t feel their education has given them the confidence and skills needed. (“How to close the data literacy gap to power the future world of work”) SAS is on a mission to empower the next generation with the skills of data literacy through sports.

The Batting Lab is more than just a batting cage where kids can improve their swing; this interactive cage also tells players specific steps to take to improve swings, helping increase confidence throughout the process. To build this AI powered cage, the SAS team analyzed thousands of swings from elite players – including from North Carolina State University’s baseball and softball teams – to build a model of the optimal swing. This data was used to build a hidden Markov model using SAS® Econometrics, creating a 38-dimensional time series model of what an optimal swing looks like for an NCAA Division I player. 

The in-cage data is captured in combination with the hardware in The Batting Lab, including a microphone, cameras, and ball and weight sensors. The sensors and cameras in The Batting Lab collect more than 50,000 data points per swing. In a session of 50 swings, that totals more than 2.5 million data points analyzed.

SAS compares the youth player’s swing to those of elite college players to look for deviations, then delivers real-time feedback on how to improve.  All this data is fed into a simple recommendation system to identify two pieces of feedback for the player. This is the same technology some of our customers are using for applications like detecting flaws in products moving through a manufacturing production line, protecting endangered species, identifying deforestation in rain forests and monitoring cancer progression by analyzing CT scans.

Luis, age 11, who participated in the SAS Batting Lab experience says, “I never thought that data would be my coach.” Data drives the world around us and by preparing kids for how to handle data and ask the right questions, they can be empowered to take on their greatest challenges.

The real success behind the Batting Lab is empowering the next generation with data skills. Lucy Kosturko, Education Programs Manager at SAS notes, “We don’t need these students to grow up to be data scientists. We need them to be data believers. People who believe that if they are going to strategically solve a problem, that data is a component of that.” Students will learn how data fits in their day-to-day lives and the decisions they make. As our world evolves, data is becoming more intertwined in our life, and it is important to equip kids with the tools they need to make data driven decisions.

Results

The Batting Lab was a true effort to combine sports and analytics. And it works! One of the key metrics identified in a successful baseball swing is the player's exit velocity, or how hard the ball is hit. All participants in the SAS Batting Lab saw an improvement in their maximum velocity, some even by 15% within the first six sessions.

Beyond the wow factor of an AI powered batting cage, the goal of the SAS Batting Lab is to empower the next generation with the tools of data literacy. By familiarizing kids with data, we can prepare them for the future by giving them the confidence to interact with the data and analytics that run the world around us.

At the start of the Batting Lab, only 3 out of the 10 kids participating cited having extreme confidence they could accurately read charts and graphs. By the end of the program, 9 out of the 10 kids had extreme confidence to accurately read charts and graphs. While in the batting cage, the participants got to see how their swing translated into thousands of data points in visualizations and charts. Avery, age 11, who participated notes, “Now that I’ve really seen data more, and like, analyzed it, I feel like I can really understand it better than I did at the beginning.” This knocks it out of the park as the kids have data as a foundation to understand how to improve their swing.

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Entrant Company / Organization Name

SAS

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