Archive for the 'Statgeekery' Category

Today I wanted to tackle the question of "team talent" -- which team has the most, and which team wins the most with the least? Unfortunately, there's no real way to quantify "raw talent" in a sense of "what is Player X's basketball potential right now?" The best you could do is to look at past years and regress to the mean for a projection, which we did a lot over the past offseason when attempting to predict player performance in 2009-10. But that's a different way to define "talent" than I wanted to look at here -- that method assumes a player has at least shown some flashes of potential in the past, upon which you can base future expectations. But about players who are still considered prospects despite having done nothing at the NBA level? In cases like that, I suppose the only way to really capture "talent" is to use draft position as a proxy, since draft decisions are made on the basis of raw talent the majority of the time. So who are the teams right now with the best collection of talent, based on where their players were drafted?

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Here's a question that's sure to spark debate: Which NBA teams have the most loyal fans?

Well, to answer that, first you have to define how you want to measure "loyalty" in a fan base. I think we'd all agree that it's easy to come out and support the team when they're winning, but what about making the trip to the arena and dropping x amount of cash to see a demonstrably lousy team lose again and again? Irrational or not, a lot of sports fans would call that kind of behavior the mark of a true die-hard, the kind of rooter against whom we all measure our own love for our favorite teams. Obviously, this is an oversimplification -- you can fervently support a team without necessarily going to games, especially if you're not living in the same area as that team -- but the assumption remains that a team's support "at home" will track with their fandom "abroad", that the two are strongly correlated. Maybe this isn't true, but for our purposes here it's a lot easier to track attendance than it is to go out and poll people in Nevada about their support for the Lakers. So we'll go with arena attendance as a proxy for team support.

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If you didn't catch it the first time around (since I know all of you read the PFR Blog now that I occasionally post over there), I highly recommend that you check out this series of posts that Doug Drinen wrote about various computer ranking systems and the methods behind them:

A very simple ranking system (If you ever wondered where the ubiquitous SRS comes from, this is it)
Another ranking system
Another rating system: maximum likelihood

That last link is the topic I wanted to talk about today.

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Last week, I attempted to replicate an old Bill James study on high-peak (since people apparently don't like the word "peaky") vs. consistent pitching aces, adapting it to basketball. The goal was to see whether a team would expect to win more championships over a 20-year span with a guy whose peak was fast and meteoric -- but whose decline was just as abrupt and total -- or a guy whose career slowly built to become a solid star, never contending for MVP but performing at a high level for a long time. To accomplish this, I took real-world data and built a composite player for each type of All-Star, each with the same number of career Win Shares, and then ran a Monte Carlo simulation of 10,000 careers, tallying how many times each player won a title when surrounded by average teammates. The results were that the consistent player won a ring slightly more often in his career, which contradicted James' findings in baseball, but the # of rings/season for each type was so negligibly different that there was an advantage of just 0.011 championships per 20-year career for Mr. Consistency, not enough to make any difference for real players.

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Recently I was reading Bill James' 1994 book The Politics of Glory, about the baseball hall of fame, and he devoted a chapter to the debate of Don Drysdale vs. Milt Pappas. If you're unfamiliar with the players, all you need to know is that Pappas and Drysdale had virtually identical won-loss records (209-166 for Drysdale, 209-164 for Pappas), Drysdale had an ERA+ of 121 vs. Pappas' 110, and Drysdale was inducted into the Hall of Fame with 78.4% of the vote in 1984 after 10 years on the ballot (never receiving less than 21% of the vote), while Pappas received 1.2% of the vote in 1979 and dropped off the ballot forever.

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Required reading material:

Who Are the “Inner-Circle” Hall of Famers? (Part I – Intro to Method)
Inner-Circle Hall of Famers: 1950s/1960s
Inner-Circle Hall of Famers: 1970s
Inner-Circle Hall of Famers: 1980s
Inner-Circle Hall of Famers: 1990s

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Required reading material:

Who Are the “Inner-Circle” Hall of Famers? (Part I – Intro to Method)
Inner-Circle Hall of Famers: 1950s/1960s
Inner-Circle Hall of Famers: 1970s
Inner-Circle Hall of Famers: 1980s

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Required reading material:

Who Are the “Inner-Circle” Hall of Famers? (Part I – Intro to Method)
Inner-Circle Hall of Famers: 1950s/1960s
Inner-Circle Hall of Famers: 1970s

Read the rest of this entry »

Required reading material:

Who Are the “Inner-Circle” Hall of Famers? (Part I – Intro to Method)
Inner-Circle Hall of Famers: 1950s/1960s

Read the rest of this entry »

Per the methodology outlined here, I now present your Inner-Circle Hall of Famers from the 1950s and 1960s... But first, remember the rules: the player had to play 10 years combined in the NBA or ABA (with 1 exception, which I'll explain below) and had to rank as one of the 4 best players of their decade in terms of both "media" and "stats" points. By popular demand, I dropped the requirement that a player had to win a championship to be included in the "Inner Circle", instead requiring them to be the best player on an NBA Finalist. This small change allows for the inclusion of players like Elgin Baylor, a legitimate legend who did not technically win a title despite coming extraordinarily close on a number of occasions. Also, be forewarned that I gerrymandered the "decades" slightly to include the highest possible % of the top 20 overall players by 10-year percentage scores, so in this edition Bill Russell is listed in the 1950s even though the majority of his years came in the 60s, in order to include Baylor in the 1960s. This happened two times in the process: once in the 80s/90s, and once here, with Russell/Baylor.

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