Math Madness 4: Aftermath

Last night, the University of Kentucky men’s basketball team defeated Kansas University 67-59 to claim the school’s 8th NCAA Championship, just as I predicted about two seconds before tip-off. The point difference with 1:32 left was just 5 points. So, we can debate whether it was a close contest overall, even though the point differential was much larger for most of the game. As far as predictions go, it appears that I am either marginally clever or lucky1.

How did the Kentucky Wildcats pull off the win?

Neither team played with particular efficiency on offense. Their shot selection distributions tended to look like those of average teams, especially in their choice to shoot two point jump shots. As we talked about last night, shooting two point jump shots is correlated with losing.
Continue reading “Math Madness 4: Aftermath”

Math Madness #3: Jump Shots and Expectation

For those of you who do not embrace, much less embody, stereotypical geek indifference to athletics, you may have noticed that it is NCAA basketball tournament time. In fact, the final game between the Kansas and Kentucky is just about to tip-off. Living in the UK, I haven’t watched much college basketball this season, but I’m picking Kentucky in a close one.

Let me tell you why. Continue reading “Math Madness #3: Jump Shots and Expectation”

Math Madness #2: The “Jinx” & The “Choke”

During their 2009 game against Villanova, Duke guard John Scheyer was getting ready to take his fifth foul shot of the game. He’d made all four previous attempts. Announcer Verne Lundquist made reference to Scheyer’s high career free throw success rate (86%). Scheyer missed the shot, causing Lundquist to publicly flagellate himself for jinxing Scheyer.

Scheyer was one of the best foul shooters to ever play for Duke (3rd best). An 86% success rate is so high that we expect Scheyer to make any given free throw. Yet, at the moment of Lundquist’s apology, Scheyer was 4 for 5 (80%) from the line. Even over that small sample set, his short term 80% success rate was effectively identical to his career rate of 86%.

Verne didn’t jinx Scheyer. He just made a statement that, by chance, happened to coincide with a normal, probabilistic event. Superstitions get started that way. Continue reading “Math Madness #2: The “Jinx” & The “Choke””

Math Madness #1: The Upset

It is conventional wisdom that every sensible bracket includes one and only one #12 seed upset over the #5 seed.  Is getting the #12 seed the basketball equivalent of a +8 sword with double damage against the undead?  If we look at the historical frequency of upsets in the round of 64 compared to the difference in seed[1], we see that the probability of upset decreases linearly as the difference in seed between the two teams increases (r2=0.96).

Continue reading “Math Madness #1: The Upset”

%d bloggers like this: