IT’S TIME FOR A REFRESH ON HOW WE VIEW ANALYTICS
The last three NBA playoffs have been difficult for analytics absolutists across the basketball world.
In 2018 the Rockets missed 27 straight threes and even still, refused to question their strategy en route to a devastating game seven loss to the Golden State Warriors. Then, last season, Kawhi Leonard mid-ranged the Raptors past the analytic gods in Milwaukee and all the way to a championship.
Finally, this past season, the biggest question mark on the Lakers was shooting. We as a basketball community wondered if their role players could do enough to get them there despite what the numbers would suggest.
What unfolded, was inexplicable performances from Rajon Rondo, Markieff Morris, Kentavious Caldwell-Pope and shockingly, Dwight Howard. If you looked at the numbers in the regular year, what happened in the postseason would’ve seemed impossible and yet, it did.
As baseball has learned in their analytic shift, when you go all-in on the numbers, over the course of a massive sample size it’s going to favour you tremendously. Unfortunately in a playoff series, where a couple of matchups here and there can decide everything, all of a sudden those analytically dominant pieces aren’t so dominant.
Take a look at Milwaukee who once again underperformed. By the numbers, their team was actually quite a bit better this season than last. When playoff basketball came around though, they struggled without Malcolm Brogdon due to their lack of offensive creation.
Over the course of 82 games, Brogdon’s absence was hardly felt. As the series with Miami tightened though, and the Bucks needed a proven ball-handler, their cupboard was empty.
Players like Eric Bledsoe and George Hill have become famous as playoff disappointers and supposed outliers due to their poor performances consistently when it matters most. The truth is though, players like Bledsoe and Hill are common across sports and defy what the numbers may tell you.
Similar to how guys like Rondo and Morris stepped up out of nowhere, players can also do the opposite and fail repeatedly when it’s least expected.
Now I’m not some descendant from the Charles Barkley school of analytics are useless but, at this point, it’s time to acknowledge the obvious: in basketball, you can’t just build your teams exclusively in the spreadsheet.
The spreadsheet may say Hill for example is a much better option to shoot a big three over a career 32.8% shooter like Rondo and yet, I would imagine no one who reads this would take Bledsoe.
Teams need to be built with analytics as a guide but at the end of the day, it’s important to remember who the name is behind the spreadsheet.
Much like how Kawhi is allowed to take mid-range shots because his points per possession when he does dictates his abilities, we need to find a way of measuring dudes who you trust versus dudes who you don’t when it matters most.
Sure it’s great to win 60 games on the backs of the Bledsoe’s and Hill’s of the world but, time and again in league history, we see massive performances from the unlikeliest sources.
By name and statistical achievement, for example, Robert Horry was a good role player. Somehow though, whenever his team needed it, Horry possessed an impossible knack for always making the biggest plays. That wouldn’t show up on the traditional analytics sites but who cares?
The Horry’s of the world have rings for a reason. Similarly, Rondo and Morris became deadeye shooters in the playoffs. I can’t explain it and neither can you because that’s the beauty of the sport, the unexplainable.
Until we find a way to marry the analytics with the unexplainable, we will continue to have disappointments like the Rockets and Bucks of recent vintage, no matter what the formulas may tell you.
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