Tiago Splitter didn't think much about analytics when he played. It was hardly an option.

Now, just nine games into his head coaching career with the Chicago Bulls, he admits that it is baked into the day-to-day of the job.

"When I played, I didn't pay much attention to analytics," Splitter told Roundtable. "Also, the league was a little bit different. We didn’t have that much numbers back then."

Splitter, a seven-year NBA vet, began his professional career in Spain in 1999. After several years in the top Spanish league, the Liga ACB, a 23-year-old Splitter declared for the 2007 NBA Draft and was selected in the first round by the San Antonio Spurs.

He finally came to the U.S. to join the Spurs in 2010 and had five production seasons there including an NBA title in 2013-14. Learning under legendary head coach Gregg Popovich and Hall of Fame big man Tim Duncan, analytics were not a part of the equation.

It wasn't until he transitioned to coaching following his retirement in 2018 that this came to the forefront.

"But when I started to coach, especially in Brooklyn when I was with Kenny Atkinson, I learned a lot about that," he explained. "How to be effective, how to use the numbers, what type of numbers you really should be paying attention to, sample size, all that stuff."

Atkinson is one of the most analytically forward thinkers in the NBA. Last season, as head coach of the Cleveland Cavaliers, he infamously used expected score to declare that "analytically" his team had won two out of the first three games despite being down 3-0 to the eventual champion New York Knicks.

But Splitter, who spent five years with the Nets as a pro scout and then a player development coach, knows that there is more to it than just what the metrics say.

“There is a balance of everything. Yes, we like good shots, shots that have good PPP (points per possesion), but I know that players also need to shoot the ball from different spots. The other team is thinking that as well, so they’re gonna give you the worst PPP shots in the game... Especially in playoff games, when you go to the scouts, the only shot they’re gonna give you is the worst PPP in the court. So, you’ve got to be able to make those shots."

Splitter's background both as a player and scout clearly informs his approach to analytics as a tool to support the player based on their needs, rather than a way to identify traits that fit a certain style of play that is favorable for the models. To explain it, he leaned on an example of an NBA great and top five scorer of all time that has thrived for close to 20 years, through different eras of the league.

"It’s a balance, especially with development, you’ve got to figure out what kind of shot a certain player can develop throughout their career. If you tell Kevin Durant since he got to the league he cannot shoot at mid-range, I don’t think that’s smart," he explained.

"You’ve got to see, develop where he can go, and I think every individual, every player is different. We try to assess what they’re good at and go from there.”

For Splitter and his staff, the first step is to identify, or scout a player's skillset on an individual. Once they know what he can and can't do, it's their job to develop this skillset, sometimes leveraging advanced analytics to do so. In other words: if it can help, great. Otherwise, development on an individual level is the priority.

"We use it. It’s not our rule, but sometimes, when you have a lot of those 50-50 decisions to make, you try to use the numbers to support your decision.”