How the Toronto Raptors Operate as the NBA’s Most Data-driven Team


Based on his interviews with different layers of the team organization, our expert contributor, Brian Jackson, research director at Info-Tech Research Group, discusses how the NBA team Toronto Raptors have embraced data-driven insights and used them to define their on-court strategy.

Toronto Raptors head coach Nick Nurse stands on the court at the OVO Athletic Centre, dwarfed by the 120-foot custom LG video screen on the wall behind him, with 448 panels weighing 6,000 lbs. Shining three times as bright as any home TV screen, there’s no missing the new and dominant addition to the NBA team’s practice facility owned by Maple Leaf Sports and Entertainment (MLSE).

Originally the plan was to use the board to playback video, showing players game footage to highlight teaching moments the coaches wanted to focus on. But that idea was quickly surpassed by the opportunity to surface custom analytics insights. One such data point is the feedback provided by Noah Basketball’s Shooting System. 

“We’ve been using Noah for a number of years and it always just went into the data bank. We had to go find it, pull it off the computer, print it out, and show it to a player,” Nurse says. “Everyone’s moving pretty fast around here during the season, so it’s nice to get immediate teaching up there.”

The Noah shooting analytics are provided by video cameras placed above the rim and on the back wall of the court. Using cognitive vision technology, it gives immediate feedback on a shot’s arc, depth, and horizontal position in relation to the center of the net. A computer voice issues verbal cues after a ball contacts the hoop, allowing a player to adjust their shot to start hitting the net instead of the rim. 

It’s just one example of the way the Toronto Raptors have embraced a data-driven culture as an organization from top to bottom. The 2019 NBA champions were one of the first six teams in the league to adopt SportsVU’s cognitive vision analytics system when it became available in 2013. The system pushed the number of data points generated per game from about 1,000 to around 1 million. Teams had the option of receiving the raw data from the vendor and running it through their own code, an opportunity MLSE saw as a competitive differentiator. It’s since created a Digital Labs team at MLSE that’s operated like a technology company within MLSE. The data analytics practice has informed team strategy from on-court performance to player acquisition and even produced a new head coach for the organization’s basketball team in the NBA G League, a developmental minor league.

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Digital Labs Team Operates as a Tech Company within MLSE

MLSE’s digital labs team is entering its fifth season. Its staff of 100 employees is composed of software engineers, product designers, product managers, data scientists, and technical operators, says Christian Magsisi, vice-president of venue and digital technology. The in-house analytics team builds specific data models to support the Raptors ambition to repeat as champions. 

“All the way from making sure that a specific player is achieving the results that they’re looking for and showing that through data, or finding opportunities for the coaching staff. This is the manifestation of it in real life,” he says as he points up at the gigantic video board. “Our ultimate goal with the coaches was to be able to take what was on emails or in a report and sometimes even in text message and actually implement it into practice.”

MLSE believes it’s unique in how it built technology into its practice facility. Beyond shot analytics, data insights can reveal other on-court insights. SportsVU provides information about how players are positioned on each play, not only in terms of their own body but compared to other players on the court. The result is new data points that can help a coach determine how to defend an opponent’s on-court tactics, or even provide specific advice to a player on how to defend in a specific area of the court. 

Raptors forward Thaddeus Young is bought into analytics, both on the court and in business. Young’s venture capital firm, Reform Ventures, is invested in Shoot 360, a basketball training experience that provides players with immediate feedback on their shot mechanics using a custom digital setup. At the OVO center, he spoke about the feedback from Noah’s shooting system. 

“It helps a lot. As professional basketball players we all want to be better shooters right? Like Steph Curry or Klay Thompson,” he says. “This is one of the reasons why you have some guys that get better at shooting. Because they get a chance to see all the data, all the different analytics.”

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From Analytics Specialist to Head Coach

Eric Khoury helped the Toronto Raptors develop their analytics approach from its inception, joining the team in 2012. With his background studying fluid dynamics as a mechanical engineer, he realized the SportsVU approach of updating player position on the court 25 times per second held similarities to his field of study. It was his Eureka moment when he had a chance to pursue a career in basketball, his passion. 

“I was looking into different aerospace engineering jobs, but this sounded a lot more fun,” he says. 

Khoury turned an internship into a full-time position and eventually became an assistant coach with the Raptors. This season, he’s taking on the head coach role with the Raptors 905 team. As far as he knows, no one else has emerged from an NBA team’s analytics practice to land a head coaching position. He hopes his background can give him a unique perspective in separating the signals from the noise when it comes to winning games. For example, even if the team pulls out a win in one game, if it’s because players were making statistically unlikely shots, it’s important to understand that it won’t be sustainable to string a winning streak together.

There are lessons to take away from the Raptors’ success with analytics for organizations across all industries, the coach says. 

“You have to be really curious about what you want to analyze,” Khoury says. “A data provider might not know the right questions to ask, and knowing the right questions to ask and having the ability to dive into that data is really important.” 

He also advises to focus on data cleaning. Pre-processing data is a priority at MLSE to ensure the data is consistent with reality. Throwing away garbage data that is clearly in error is necessary before you can plumb data for insights. 

MLSE’s team taps into cloud services to help support its data insights pipeline. Rather than maintaining infrastructure, they partner with Amazon Web Services (AWS). Amazon Rekognition provides support for cognitive vision analysis from video, and Amazon Kinesis provides video processing. That allows MLSE’s team to focus on creating value around the differentiation of their data models to help players and coaches. 

The data practice is just one example of MLSE’s digital pipeline that it uses to enhance its operations on the court and for fan experience. MLSE chief technology and digital officer, Humza Teherany, says it all starts with having meaningful conversations about driving business goals and figuring out how technology can be used in the most impactful way.

“Our first goal in the entire buildup of the digital labs organization has been to support MLSE and all of our teams,” he says. “We like to do things first. We leverage our own technology to make things better for our fans and for our teams to complete and find incremental advantages where possible.” 

This season, the Raptors have delivered a couple of firsts. The first head coach of a G League team to come out of an analytics background. The first 120-foot video board towering above an NBA team’s practice court. 

For coach Nurse, those innovations drive the team’s competitive effort. “There’s got to be a better way, to teach better, where (players) can learn faster, where they can do things better for themselves.” 

For MLSE, the hope is that being first in analytics will deliver a second championship in the seasons ahead. 

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