When you picture a GM, you probably think of an old former player turned front office guy using his playing experience and knowledge of the game piecing together a team with the monetary and regulatory contraints at hand.. More realistically, the picture in your head is the plot line from Michael Lewis’ Moneyball. Brad Pitt and Jonah Hill throwing names onto a magnetic white board based on who gets on base the most, not based on home runs or strike outs or a gut feeling.
Depends on the team, but GMs in baseball are using feel for the game and advanced analytics together, and the natural rules of baseball facilitate easy stat collection, analysis, and interpretation. Football has a similarly rigid structure that makes comparing offensive and defensive breakdowns more complex but still easy enough to see little change in the types of statistics being gathered.
The NBA is a different story. Fast paced games, players constantly switching defensive and offensive assignments and roles. While it’s easy to track how many assists, turnovers, or points a player scores in a single game, it’s not so easy to track player efficiency like QBR does for football or WAR does for baseball. Or a certain player’s efficiency breakdown by who they are guarded by, who’s on the court, and where his teammates are playing. This is where SAP comes in. Founded by five former IBM employees in 1972, System Analysis and Program Development (SAP) uses various softwares to process and analyze data to an unparalleled level. At the Hashtag Sports Benchmark for Fan Engagement Conference in New York City, Ryan Somers of SAP presented on how they push their NBA partnership beyond the box score statistics and help teams and front offices, providing over 4.5 quadrillion different statistics last season alone.
Stephen A. Smith isn’t the only person using stats to push a narrative (although does he really even use stats to be honest). According to Somers, “it’s no longer enough to just have an opinion. Fans actually have to have the stats to back it up when discussing the NBA. Everyone’s an expert, and with the stats that SAP publishes for the NBA, fans are getting smarter and smarter.” Fans are so smart that come the fourth quarter of any NBA game, Twitter becomes a yelling match and often the GM of the losing team is the scape goat.
Masai Ujiri has done substantial damage to his reputation in this town today. And started the clock ticking on his own tenure.
— Damien Cox (@DamoSpin) May 11, 2018
Never understood why people applaud Masai Ujiri like he's some messiah lol. Can't draft, bad trades, desperate acquistions, coach fired. Bottom line, he sucks. #Raptors
— Mark Bowman (@musichead_mark) July 18, 2018
While maybe 10 years ago fans would complain without reasonable justification, SAP provides the numbers that help the average individual become the next NBA top analyst for ESPN. This past NBA season, SAP went a step further even.
What happened if all those Twitter fans were offered the chance to decide who was the most impactful player of the 2019 NBA Finals? Somers argued for VanVleet, citing his defensive value on the court and when matched up against Steph Curry. Every other NBA analyst could say a different name and provide equally insightful evidence. SAP, in their partnership with the NBA and NBATV, produced a show to determine the average fan’s ability to judge players on a meaningful level – the level at which each fan criticizes on a daily basis for performing inadequately. A classic case of “let’s see how you like it,” except with the added bonus of actually getting an interview with various league execs if you win. From there, GM School was born.
Today’s GMs still use stats like Player Efficiency Rating, an inherently advanced stat in its own right, points per game, minutes per game, defensive rating, and more. Many GMs like Danny Ainge are former players using a combination of statistics and experience to perform their jobs. At the end of the day, however, the NBA is moving towards a more analytical platform where playing experience is an important part of the job, but not as much at the forefront. “Take the Raptors for example,” Somers noted. “They signed Siakim at an annual average of $1.5 million yet he outproduced players on the All-NBA 1st and 2nd teams throughout the playoffs.” Siakim is a perfect example of GMs using advanced analytics and strategies like heat maps, offensive efficiency on fast breaks, and defensive win shares.
So is there really a total adoption of the Moneyball concept, or is it just the effect of a new generation with different habits? Either way, SAP is the bridge leading general managers and front offices towards a new era of justifying the next max contract for someone like Siakim or even D’Angelo Russel. Whether it’s a super fan looking to win an argument or a front office guy trying to find the most valuable six man, SAP has the data to revolutionize the NBA going forward.