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If you've been following the blog recently, I've developed a way to convert a player's Basketball on Paper stats to a Statistical Plus/Minus estimate. I'll spare you the gory details (which you can read about at the bottom of this page), and simply say that this version of SPM is less biased toward any one position and captures defense better than the original edition, making it the superior SPM in my opinion (although, as always, I'm certainly open to critiques).
Which players excel against the best defenses, and which ones get their numbers by feasting on the weakest Ds?
To answer those questions, here's the latest installment of a series I started in 2009 and continued in 2010... The concept is simple: I rate each team defensively using the BBR Rankings formula (including regular-season and playoff games), then track how well each player performed offensively against opponents of varying defensive quality.
Quick mailbag for Nick, who asked how many games in each season (since 1999) featured at least 1 team playing its second game in two nights:
1999: 392 of 725 (54.1%)
2000: 494 of 1189 (41.5%)
2001: 481 of 1189 (40.5%)
2002: 504 of 1189 (42.4%)
2003: 487 of 1189 (41.0%)
2004: 475 of 1189 (39.9%)
2005: 500 of 1230 (40.7%)
2006: 474 of 1230 (38.5%)
2007: 486 of 1230 (39.5%)
2008: 483 of 1230 (39.3%)
2009: 471 of 1230 (38.3%)
2010: 490 of 1230 (39.8%)
2011: 497 of 1230 (40.4%)
Hopefully the 2011-12 lockout will resolve quickly, so we don't have to have back-to-backs in 54% of games like in 1999 (and the 102.2 league offensive rating that came with it).
It's unfortunate that this is coming out after his retirement, but here's a National Geographic special about Yao Ming's impact as a basketball ambassador:
It was announced yesterday that NBA 2K12 will feature Larry Bird and Magic Johnson as cover athletes, in addition to a return from the GOAT himself. In retrospect, last year's game was hands down the best sports title of the year (with far more replay value than MLB: The Show), so expectations are justifiably high for 2K12. Zach speculates about how 2K will integrate Bird and Magic into game modes similar to last year's Jordan Challenge, and dreams up challenge lists for the two legends.
One parting thought from Harper: With the added emphasis on Magic, Larry, and Michael, will we see a Dream Team mode in NBA 2K12? If so, this game could be just what hoops fans need to survive the lockout in one piece.
Here's a great post at TrueHoop by Zach Harper, about NBATV's lockout programming schedule.
Oddly enough, one of the few silver linings of the labor dispute has been the fact that NBATV can't show any current players. Why? Because in the scramble to fill airtime, we've been treated to a number of classic games with great historical players.
A few weeks ago, it was Michael Jordan & Karl Malone. Last week, Bill Walton and Charles Barkley. And just last night, we got to watch Larry Bird's 50 greatest moments, a Celtics-Bulls game from 1981 (Artis Gilmore!), and Game 4 of the 1984 Finals. It was because of the lockout... and it was great. Since I don't have ESPN Classic, I've probably watched more old NBA games in the past 3 weeks than I had in the previous 3 years.
I'm sure that if NBATV had its choice, it would show nothing but the usual offseason talking-head commentary about free agency and the like, but for now I'm actually enjoying the absence of that. Who needs Dirk & LeBron when you have Magic & Larry?
As a follow-up to this afternoon's list of the Top 593 Players of 2012, here's a positional breakdown for the 452 players who played at least 1 game in 2011:
Watching one of the NFL Network's "Top 100 Players of 2011" shows this weekend, I was inspired to create a similar list for the NBA using APBRmetric stats. But why stop at 100? Instead, I ranked all 593 players who played at least 1 NBA game since 2008-09.
Here's a quick-n-dirty study I ran this morning... The idea is this:
Some stats seem to be more correlated with a player's role than his actual skill. Take a player out of the role, plug another similar player in, the new player produces just like the old one (and the old one can't "take the stats with him" to his new destination).
How can we quantify this, though? Well, let's identify players whose circumstances changed. I took every team since 1978 and assigned its players to 10 "roles" -- primary PG, backup PG, primary SG, etc. -- based on my detailed position file and where the players ranked on the team in terms of minutes played. I then isolated every player in that sample who:
Played at least 500 minutes in back-to-back seasons
Was between age 24 and 34 in back-to-back seasons (to filter out potential aging effects)
Moved to a new "role"
Was replacing a player who played >= 500 MP in the role and was between age 24 and 34 the previous season
This leaves us with 1,866 player-seasons to look at. For each of those, I need to know which predicts the player's performance in Year Y better -- his own stats from Year Y-1, or the Year Y-1 stats of the player whose role he took?