Tag Archives: Daryl Morey

The Seattle Scientists — an alternative to the New Orleans Mess

You all know by now — the New Orleans Mess tried to trade Chris Paul to the Lakers (involving the Rockets as well), but the other owners, who jointly own the Mess, stepped in and blocked the trade. The trade has quickly become an argument about the small market/big market dichotomy in the NBA. My brother Conor sent me a standard response from Matthew Yglesias at Slate. Yglesias argues that artificially preserving the talent on small market teams is misguided:

It’s not clear to me why they don’t just eliminate this New Orleans franchise. Everyone knows there are too many NBA teams. Nobody wants to own this team, nobody wants to play for it, and there’s no a priori reason to believe an NBA franchise in New Orleans could ever be financially viable.

Yglesias and many others feel that the Mess and maybe a few more teams should be “liquidated” and “replaced” in some way. Ideally, they could be moved to a big market, where the financial returns to winning seem higher. However, eliminating and moving teams is bad press. I also think that keeping teams Continue reading


Pythagorean expectations, Pythagenports, and Pythagenpats – a bunch of mumbo jumbo

It seems like everywhere you turn in sports statistics, someone is talking about Pythagorean expectations. The Pythagorean expectation is a formula created by Bill James to estimate team quality in baseball, with runs scored and runs allowed as inputs. Proponents argue that luck plays a big part in close games, making point totals a better measure of team quality than wins. The formula is

Pythagorean = Runs scored^/ (Runs scored^c + Runs allowed^c),

where c is some exponent (usually greater than one) that can be calibrated. This kinda looks like the old Pythagorean formula from grade school (hence the name), though not really. The Pythagorean rises (at a decreasing rate) as you score more and drops (at a decreasing rate) as your opponents score more. In other words, the Pythagorean rewards teams for blowouts and punishes them for getting spanked, since these scoring outcomes may reflect team quality. If you score the same amount as your opponents, your Pythagorean is 0.5. The max is one and the min is zero, like a winning percentage. “Pythagorean wins” are given by the Pythagorean multiplied by the number of games.

Over time, this formula has been exported to basketball and football, and probably other sports. My buddy Adrian the Canadian sent me this week’s DVOA update at Football Outsiders, in which Aaron Schatz informs us that Football Outsiders has upgraded from the Pythagorean expectation to the “Pythagenport,” and Baseball Prospectus (the original Pythagenporters) has moved on to the Pythagenpat! These are identical to the Pythagorean, but allow the exponent c to depend on the number of runs scored and/or the teams involved.

Maybe this sounds reasonable to you, but these formulas make my head hurt. The Pythagenport even gets a logarithm involved. Where do these crazy functional forms come from? The intuition for these stats is simple: Continue reading