Probability
I don’t think there’s a supercomputer or mathematician alive capable of accurately calculating the true probability behind situations like the one we found ourselves in last night.
Sure, there’s the basic logic:
• Your team shoots X% from the line.
• Their team shoots Y%.
• There’s Z seconds on the clock.
From there, you model the outcomes of fouling vs. defending and get a mathematical edge.
But in reality? The variables are way too layered for that approach to hold water every time. Let me explain why last night was one of those moments where the math breaks down:
1. Jokic Was on the Bench
The best player in the world wasn’t even on the floor. That changes everything about expected offensive output.
2. Inbounding The Ball
Whatever your inbounds data says over the years, it doesn’t account for who is inbounding. Giddey had a higher probability of successfully getting the ball to Shai—our best free throw shooter.
3. Risk of a Shooting Foul
Fouling too late = risk of a three-shot foul or even a four-point play. That’s a massive shift in win probability and one that’s hard to quantify ahead of time.
4. Risk of Fouling Too Early
If you foul 90 feet from the basket, you guarantee no shooting foul—but you also risk leaving too much time on the clock and needing to win the game at the line twice. That exchange introduces a complex risk cycle.
5. Who You Can Foul
Aaron Gordon, for example, might look like the right guy to foul based on career free throw stats. But he’s clearly improved—put a gym in his house and revamped his shot. Career stats don’t account for offseason development.
Bottom line:
Sometimes the situation is too complex for a model to capture. I’m pro-analytics. I studied probability in business school. I trust math when I bet on sports. And for a 47-year-old, I probably lean on analytics more than most in my age group.
But in this case?
I’m with the defense. Just get the stop and win the damn game.