Baseball’s Rangers seek the analytics advantage with Tableau

Analytics are now ubiquitous in Major League Baseball.

Each team has access to a wealth of data provided by MLB, which uses Google Cloud to power its analytics. Using Statcast, the platform that MLB developed using Google’s analytics capabilities, teams can track every movement of players on the field as well as the movement of the ball from the moment it leaves the pitcher’s hand until a game is over.

It is with Statcast that teams can understand information such as the speed of rotation on a pitch, the path of the bat and the speed of the bat of a swing, and the routes players take to follow a ball when they are on the ground and how fast they cover the ground to make the capture.

So, in an effort to gain an additional competitive advantage, the Texas Rangers use Tableau in addition to what is provided to them by the league to inform players and coaches in real time before, during and after each game.


Tableau, founded in 2003 and based in Seattle, is an analytics provider whose platform is popular for its ability to make complex statistical analysis accessible to everyone through data visualizations. Tableau competes for market share with platforms such as Microsoft Power BI, Qlik, Oracle, and SAS.

And with its ability to communicate complex statistical analysis in easily understandable formats, Rangers are confident that Tableau gives them an edge.

Rangers do their machine learning in R, Python, and Spark, store their data in Google Cloud and AWS, use SQL interfaces to interact with that data, and then use Tableau to communicate the data to players and coaches on the team.

“The competitive advantage is how that information is communicated to stakeholders,” Rangers Major League analyst Randall Pulfer said Wednesday during a breakout session at the 2022 Tableau Conference, the conference hybrid of in-person and virtual provider users.

The competitive advantage lies in how this information is communicated to stakeholders.

Randall PulferMajor League Analyst, Texas Rangers

“If you can’t act on all the information you collect, there’s no point,” he continued. “The goal is to make better decisions, and data and analytics are a way to do that, and we want to give the ultimate decision maker more tools, more insights, to make the most informed decision. possible.”

When statistical analysis beyond conventional measures such as batting average, home runs and runs scored – and wins, ERA and strikeouts for pitchers – began to imposing in baseball at the turn of the 21st century, simply having an analysis department was a significant advantage for teams.

Even when the early years of the 2000s passed and teams such as the Oakland A’s became renowned for their use of analytics – particularly to find value in players that other teams rejected, such as both the book and the movie show it. silver ball – Some baseball clubs still resisted the use of advanced statistics and continued to rely more on traditional scouting methods to assess talent and build rosters.

Today, however, every professional baseball team has an analytics department and uses data to inform their decision making.

That’s why defensive changes deployed to position players not in traditional spots on the pitch, but in areas where each individual hitter hits the ball most often, once rarely used, are now ubiquitous. This is why teams’ best hitters, in the past usually ranked third or fourth in the batting order, now often hit second. This is why pitchers attack certain parts of the strike zone with certain pitches in certain counts depending on the opposing hitter’s strengths and weaknesses.

And that’s why defensive players can now be seen peering into their caps, where they have scouting reports and opposition notes, between pitches.

Achieving competitive advantage through analytics therefore depends on a team’s ability to differentiate itself from what all other teams are doing with analytics.

For the Rangers, their attempt at differentiation is with Tableau, specifically data visualizations using the vendor’s Tableau Desktop and Tableau Server versions and the Tableau mobile app.

“It’s about how we can best communicate, and that’s where Tableau comes in,” Pulfer said.

Cultural component

However, before gaining an advantage with analytics beyond the technology provided by MLB, as with any organization using data to inform decisions, baseball teams need to develop a decision-making culture, according to Pulfer.

They need top-down buy-in, much like a Fortune 500 company does when it first uses analytics to inform business decisions after making decisions on a more ad hoc basis. .

“It goes a long way, when we’re in the clubhouse talking to the players and the coaches, when the manager and the front office executives support what we’re doing,” Pulfer said.

Transparency, availability and consistency are also key to creating a data culture within a baseball team, he continued.

That means data experts and analysts like Pulfer can’t be locked in an office five stories above the clubhouse mulling over the numbers as players and coaches try to digest the reports that the team provides them daily.

Data scientists should be available to answer any questions in meetings and in the clubhouse as to why a player might want to take a certain action, or why a certain action the player took during the night’s game previous – attempting to steal a base in a particular situation, for example – was right or wrong.

And data experts should consistently deliver analytics in the same way so players and coaches can learn about the team’s analytics culture.

“One of the most critical aspects of my job is being available to players and staff,” Pulfer said. “It’s one thing to deploy a good process or a good metric, but it’s another thing to see it through to the end to ensure that the end user understands it and is able to use it.”

Finally, just as any organization should educate its data consumers before implementing a decision-making process with analytics at its core, baseball teams should explain their use of analytics, areas of interest for season and why they think these areas of interest are important. .

“We need to make sure they feel like they are part of the process and educate them about the importance of these numbers and how we think [the numbers] will help their career and help us win more games,” said Pulfer.

Table in action

Rangers use Tableau every day.

A normal game day starts about six hours before the first pitch, or 1 p.m. for a typical 7 p.m. night game. At that time, Pulfer and his team prepare Tableau reports for players and staff based on the previous night’s game and put the reports in lockers for players and coaches to view when they arrive at the venue. baseball stadium.

In addition, analysts make themselves available to answer all questions.

These daily reports – tailored to pitchers and position players depending on their roles – largely only cover previous play and feature data visualizations to make the numbers easier to digest.

“We try to make these reports as simple as possible,” Pulfer said. “The last thing a player wants to do, especially if he may have had a bad game, is look at a report full of numbers. We want the high-level takeaways.”

Two hours later, usually around 3 p.m., meetings are held with different groups of players to go over strategy for the upcoming game – for example, defensive positioning against certain hitters – and review what happened the night before.

Two hours before the first pitch, Pulfer and the rest of the Rangers data analysts prepare materials for players and coaches to integrate into the game, such as reference maps created in Tableau that players can store in their caps to search. the opposing batter quickly. tendencies or the composition of the opposing team with a short note on each player.

MLB allows teams to have iPads in the dugout during games that allow them to view any report at any time, so the reference cards are designed for players and coaches to have on hand to provide a quick reminder.

“It’s fun to create these cards and see them used, hopefully to help us win,” Pulfer said.

After the night’s game, data analysts hold a quick debrief based on data collected throughout the game, but with players and coaches eager to get home, the brief reports created in Tableau just after the end of the game. game are developed so that players can take them home and easily consume them the next morning.

“We’re always trying to find ways to use data to our advantage, and we embody the data-driven culture,” Pulfer said. “We’re always getting better, but every year we get better. It’s easy to complicate things and hard to simplify things, and our goal is to take a huge funnel of data and narrow it down to the key takeaway players we need on the field to perform.”

Too much data in baseball can be dangerous – it’s counterproductive for a player with a baseball coming their way at 100 miles an hour to think about analysis. But by using Tableau, Rangers are able to deliver key data points in a digestible approach that enhances performance rather than hindering it.

“Simplicity is the number one priority,” Pulfer said.

Lance B. Holton