There's a tendency for some in the sports world to hear the word "analytics" and tune out. They might use the old expression, "There's lies, damn lies and statistics" to support their stance. Or, they might just say analytics come from a bunch of nerds that don't understand the game.
Here's an example to help illustrate why that stance is wrong, and why you want to utilize NBA analytics in your life:
On Friday, Kevin Durant joined Kyrie Irving on the sidelines for the Nets due to a shoulder injury. With their MVP sidelined, could the Nets still beat the Magic on Friday night? And by how much? According to Caesars Sportsbook, the Nets were still favored over the Magic by 9.5 points. Should they be?
These type of questions are perfect for the family of Basketball Player Index (BPI) analytics to weigh in on. Unlike many other team- and game-evaluation models, BPI is built from the player up. So, when MVP-caliber players are missing and the team looks entirely different, BPI still has a mechanism to estimate what the team might look like. So, what did BPI say?
