Archive for the 'Data Dump' Category

With the NBA Finals locked up 2-2, it seems like a good time to look at the best Finals performances in our database (which extends back to 1991 for playoff games). The metric of choice is Statistical Plus-Minus, an estimate of the player's contribution to the team's point differential per 100 possessions, using his boxscore stats as inputs. And, as an added twist, I weighted each game of the Finals according to its series leverage (the expected change in series win probability of the game in question relative to the series' overall average per-game change), meaning that performance counts more in the games that contain the most pressure. Here is every player in the dataset who played a minimum of 24 minutes per team game:

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With the Magic, Lakers, and now Celtics being dispatched from the playoffs, I was thinking about whether a down period was necessary for teams that had been at the top for multiple seasons when their run was finally over.

Part of Danny Ainge's rationalization for the Kendrick Perkins-Jeff Green trade was to make the Celtics younger and give the team a solid player in the future. But do (older) mini-dynasties like Boston's ever really have a future? Does a modern NBA team ever successfully rebuild on the fly, or are good years always followed by a transition period of losing? Instead of making any attempt to build a future, should he have just committed to the 2011 team and accepted losing down the road?

Let's go to the data -- every team that went to at least 2 conference finals in 3 years, and their winning percentages in the next 5 years (Y+1, Y+2, ... , Y+5). "Age" is the team's minute-weighted average age in year Y's playoffs. "< .500" and "<.350" are the # of seasons in the next 5 that they posted a a record worse than .500 and .350, respectively. Enjoy: Read the rest of this entry »

A lot of users have been asking for double- and triple-double leaderboards, so I thought I would make some now that we have gamelog data going back to 1986.

Here are the career double-double leaders since then:

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Since we now have boxscore data from the 1985-86 regular season on the site, I thought it'd be fun to look at the top 50 individual single-game performances of that season according to the various "game score" metrics out there. First, here were the top games by John Hollinger's game score:

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Today we have a big data dump thanks to this question from Ifeanyi:

"If the LA Lakers win the rest of their 11 games this season, that'll give them a 24-1 post all-star break record. My question to you is, what is the NBA's all time best record for regular season games played after the break?"

Including 2011 to date, here are the all-time best W-L records after the All-Star break:

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While I'm en route to Boston for the MIT Sloan Sports Analytics Conference, here's a neat question SI's Zach Lowe had regarding the Memphis Grizzlies' defense:

"Memphis has emerged as a top-10 defensive team despite being good at only one of the four factors--forcing turnovers, which they do extremely well. They rank below the league average in eFG (barely below the avg), DRB rate (horrible) and FT/FGA (somewhere in between). I have a feeling it's unusual for a team to rank in the top-10 overall while ranking below the league average in 3 of the 4 defensive factors, but perhaps it's not as unusual as I think it might be."

It is very unusual, in fact. Since 1974, the first year we can compute the Factors, just eleven defenses (including Memphis) have ranked in the top 10 despite being below-average in 3 of 4 Factors. And if we expand it to include either offense or defense, the list contains only 27 teams:

I'll let Zach provide the commentary, so go check out his post at SI's Point Forward blog.

During Chris Bosh's brickfest last night, all I could think of was, "Wow, this is a John Starks-ian performance." Turns out it was even worse, albeit in a much less critical situation than Game 7 of the Finals.

Using offensive statistical plus/minus (OSPM), I put together a list of the most detrimental offensive games in our box score database (this spans 1987-2011 for the regular season, and 1991-2010 for the playoffs). For every game, I calculated the player's OSPM, the team's offensive rating, and what the team's offensive rating would have been had the player turned in a league-average performance. The most detrimental performances were the ones that sucked the most points from a team's offensive rating. I also added one requirement to qualify for the list: the player's offense must have cost his team a win -- i.e., with an average offensive performance from a player in his minutes, they would have outscored the opponent, but instead lost the game.

Let's use Bosh as an example. Last night, Bosh had an OSPM of -15.18, which means for every 100 possessions he was on the floor, he drained more than 15 points away from Miami's offensive rating relative to a league-average performance. Miami's actual offensive rating was 95.3, but if Bosh had just been average, Miami's rating would have been 108.5 -- meaning he cost them 13.16 points of offensive rating over the course of the entire game. Worse yet, Chicago's offensive rating was 99.6, so if Bosh had been average (or even merely below-average), Miami would have won the game. That's why Bosh qualifies for the list, because his poor offense cost his team a win.

Anyway, here are the most detrimental offensive performances in our database (mouse over column headers for descriptions):

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Well, it's (quasi) official now: Carmelo Anthony is a member of the New York Knicks.

Finally, we can put aside the trade speculation and ask the really important questions about the deal. No, I'm not talking about how this shifts the balance of power in the East, or if 'Melo and Amare Stoudemire can coexist in the Big Apple... I'm talking about where Carmelo ranks among all-time players who were traded in the middle of the season.

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The chart on this post about non-passing guards was so popular, I decided to run it for players at all positions (minimum 30 MPG):

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Prompted by some questions in the comments of Monday's post about the playoff predictivity of regular-season W-L vs. elite teams, here's some more raw data on every 2nd-round or later series since the merger:

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