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The NBA Advanced Statistics Thread: #SwagEffect

post #1 of 744
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JPEG Pro

The all encompassing thread for anything to do with NBA advanced statistics.

Resources:
nba.com/stats
nba.com/advancedstats/
Basketball-Reference
HoopData
82games
Vorped
nbawowy
Wages of Wins
NBA Geek
hoops stats
Synergy
statitudes
The Mikan Drill
Vantage Sports
Hickory-High
Sports Club Stats
Team Rankings
Advanced Statistics Calculator

Remember, we don't watch games. We just analyze box scores.

Edit:

A good starting point for those interested.
Quote:
The Evolution of NBA Stats

kobe-stats-overview-690.png

Every year, the NBA is getting smarter. Front offices, coaches, players and fans around the league are all learning more about the game by embracing analytics on some level. More than ever, we know which shots are good shots, which players can make their teams better without scoring, and the value of efficiency.

Now, we're taking another step forward with the relaunch of NBA.com/stats, a massive tool which will allow you to learn more about the league's teams and players, and see if the numbers back up what you see with your eyes.

If you're new to the advanced stats movement, we're here to catch you up. And the best place to begin is with pace, efficiency and the four factors.

Pace

Advanced stats on the team level really start with the acknowledgement of pace. Different teams play at different speeds and numbers should reflect that. So instead of measuring team offense or defense by the number of points scored or allowed per game, we look at them on a per-possession basis, putting every team on a level playing field.

For example, opponents of the Brooklyn Nets score just 94.7 points per game, the fifth-lowest mark in the league. But that number is more about the pace that the Nets play at than how good they are defensively.

The Nets and their opponents average just 90.5 possessions per 48 minutes, the slowest pace in the league. And that number helps keep their opponent points down. On a per-possession basis, the Nets actually rank 17th defensively.

In the same vein, the Nets are a better offensive team than their per-game numbers indicate. On a per-game basis, they score the 20th most points in the league. But when you adjust for pace, they have the 12th most efficient offense.

This is important, because when two teams play each other, they're going to each get the ball an equal number of times (give or take an extra possession or two, depending on how the ends of quarters go) and numbers that aren't pace-adjusted are kind of worthless.

Efficiency and the four factors

Sometimes, you'll hear a broadcaster reference field goal percentage as a way to measure how effective an offense or defense is. But that doesn't tell the whole story either.

For example, the Atlanta Hawks are a very good shooting team (sixth best in the league). But they also also turn the ball over too often, don't get to the free throw line much, and fail to grab many offensive rebounds. Overall, the Hawks rank 15th offensively.

Per-game numbers and standard field goal percentage both lack a lot of context. Offensive and defensive efficiency, however, are tidy numbers that tell you exactly how good teams are on either end of the floor.

To make efficiency resemble standard stats somewhat, we look at points scored or allowed per 100 possessions. And the formulas are simple...

Offensive efficiency (OffRtg) = 100 x (Points / Possessions)

Defensive efficiency (DefRtg) = 100 x (Opponent points / Opponent possessions)

Possessions do not necessarily end with a shot attempt. An offensive rebound extends a possession, which doesn't end until the other team gets the ball.

The number of possessions a team has over the course of a game (or the season, or a stretch of games) is estimated using standard boxscore stats and the following formula:

Possessions = FGA + (0.44 x FTA) + TO - OReb

At the All-Star break, the Miami Heat have been the best offensive team in the league, scoring 110.4 points per 100 possessions. The Indiana Pacers have been the best defensive team in the league, allowing just 95.9.

As noted in the paragraph about the Hawks above, there are four factors that affect efficiency on either end of the floor: Shooting, rebounding, turnovers and free throw rate. And if you truly want to be a strong offensive team, you have to be good at more than one of the four.

Here's how they break down.

Shooting (effective field goal percentage)

Effective field goal percentage (EFG%) is a better number than standard field goal percentage, because it takes the added value of a 3-pointer into account.

Here's the formula: EFG% = (FGM + (0.5 * 3PM)) / FGA

And here's an example of why EFG% is a better number than standard FG%:


Team A gets the ball 10 times, shoots 10 2-point shots, and makes five of them. So they had a field goal percentage of 50.0 percent and scored 10 points on those 10 shots.

Team B gets the ball 10 times, shoots 3-for-5 from 2-point range and 2-for-5 from 3-point range. They also had a field goal percentage of 50.0 percent, but scored 12 points on those 10 shots.

Team A's effective field goal percentage was 50,0 percent. Team B's was 60 percent.

At the All-Star break, the Heat are the best shooting team in the league, with an effective field goal percentage of 54.6 percent. The Pacers have the lowest opponent EFG%: 44.8 percent.

Rebounding

Instead of looking at rebounds per game, we want to look at rebounding percentage, because other factors (how well a team or its opponent shoots and how often they turn it over) can affect raw rebounding numbers.

Here are our simple formulas on the team level:

Offensive rebounding percentage (OREB%) = Offensive rebounds / (Offensive rebounds + Opponent defensive rebounds)

Defensive rebounding percentage (DREB%) = Defensive rebounds / (Defensive rebounds + Opponent offensive rebounds)

And here's an example of how rebounding percentage can affect efficiency...

Team A gets the ball 10 times, shoots 10 2-point shots, makes five of them, and doesn't rebound any of the misses. So they scored 10 points on their 10 possessions.

Team B gets the ball 10 times, shoots 10 initial 2-point shots and makes only four of the 10. But Team B rebounds two of their six initial misses and follows them each up with a 2-point make.

So both teams shot 50 percent (whether you're looking at standard or effective field goal percentage). Team A shot 5-for-10 and Team B shot 6-for-12. But Team B was more efficient, scoring 12 points on its 10 possessions, while Team A scored just 10.

Team A had an offensive rebounding percentage (OREB%) of 0.0 percent, because they grabbed zero of the five available offensive boards. Team B had an OREB% of 33.3 percent, because they grabbed two of the six available offensive boards.

At the All-Star break, the Memphis Grizzlies are the best offensive rebounding team in the league, grabbing 32.0 percent of available offensive boards. And the New York Knicks are the best defensive rebounding team in the league, allowing their opponents to grab only 24.8 percent of available offensive rebounds.

Turnovers

You can't score if you aren't able to actually get a shot. Turnovers are obviously critical, because they wipe out an offensive possession entirely.

Here's your turnover rate example...

Team A gets the ball 10 times, doesn't turn the ball over at all, and, once again, goes 5-for-10 on 2-point shots with no offensive rebounds.

Team B gets the ball 10 times, turns the ball over twice, and shoots 4-for-8 on 2-point shots, without any offensive rebounds.

Again, both teams shot 50 percent (FG% or EFG%). But Team A was more efficient, because it scored 10 points on its 10 possessions, while Team B scored just eight.

Team A had a turnover rate (TmTOV%) - turnovers per 100 possessions - of 0.0. Team B had a turnover rate of 20.0.

At the All-Star break, the Knicks have done the best job of taking care of the ball, committing just 12.6 turnovers per 100 possessions. And the Los Angeles Clippers lead the league by forcing 17.7 turnovers per 100 possessions.

Free throws

Simply, a trip to the line for two free throws is worth more than a shot from the field. On average, two free throws are worth 1.56 points (because the league shoots 75.3 percent from the line), while a shot from the field is worth 0.99 (because the league-average EFG% is 49.3 percent).

One more time: Team A gets the ball 10 times and shoots 5-for-10 on 2-point shots, with no turnovers, offensive rebounds or free throws.

Team B gets the ball 10 times, shots 4-for-8 on 2-point shots, but gets fouled on two other attempts and shoots 3-for-4 from the free throw line.

Once more, both teams shot 50 percent (FG% or EFG%). But Team B was more efficient, scoring 11 points on its 10 possessions, while Team A scored just 10.

Free throw rate (FTA rate) is measured by a simple formula: FTA/FGA. Team A had a FTA Rate of .000 (0/10). Team B had a free throw rate of .500 (4/glasses.gif.

At the All-Star break, the Oklahoma City Thunder lead the league in free throw rate, attempting 34 free throws for every 100 field goal attempts. The San Antonio Spurs do the best job of keeping their opponents off the line. Their opponents have attempted just 23 free throws per 100 field goal attempts.

So those are the basics of team efficiency. And as we evaluate players, we need to look beyond their boxscore stats and focus on how they affect their team's success on either end of the floor.

We'll do just that in another story.
Link
Edited by PMatic - 10/25/13 at 1:51pm
post #2 of 744
Thread Starter 
The MIT Sloan Sports Analytics Conference (SSAC) starts tomorrow and runs through Saturday.

Here's a link to all the research papers being presented.
post #3 of 744
What is the joy y'all get out of this? Not hating just curious.

I understand the idea of advanced stats and what not, but do people really analyze this stuff all the time?
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"In Northeast Ohio, nothing is given. Everything is earned. You work for what you have. I'm ready to accept the challenge. I'm coming home"
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O-H-I-O

CAVALIERS - INDIANS - BROWNS - BUCKEYES


"In Northeast Ohio, nothing is given. Everything is earned. You work for what you have. I'm ready to accept the challenge. I'm coming home"
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post #4 of 744
I think it's just a different way of looking at the game.

Production, efficiency, etc....
post #5 of 744
Thread Starter 
Quote:
Originally Posted by FinallyFamous View Post

What is the joy y'all get out of this? Not hating just curious.

I understand the idea of advanced stats and what not, but do people really analyze this stuff all the time?
I look at it like this, if you love the NBA, why not get as much information about it as possible?
post #6 of 744
Quote:
Originally Posted by PMatic View Post

I look at it like this, if you love the NBA, why not get as much information about it as possible?

I gotchu
O-H-I-O

CAVALIERS - INDIANS - BROWNS - BUCKEYES


"In Northeast Ohio, nothing is given. Everything is earned. You work for what you have. I'm ready to accept the challenge. I'm coming home"
Reply
O-H-I-O

CAVALIERS - INDIANS - BROWNS - BUCKEYES


"In Northeast Ohio, nothing is given. Everything is earned. You work for what you have. I'm ready to accept the challenge. I'm coming home"
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post #7 of 744
SLOWLY getting into advanced stats....still won't watch Moneyball tho laugh.gif

I love this site below:

Wages of Wins

pimp.gif

(Good thread, P)
post #8 of 744
Quote:
Originally Posted by FinallyFamous View Post

What is the joy y'all get out of this? Not hating just curious.

I understand the idea of advanced stats and what not, but do people really analyze this stuff all the time?

For me its all about having as much information and insight into the game as possible. Its aslo a huge help when it comes to discussions. I'd rather a mountain of stats get posted than someone use cliche phrases like "he willed it in" or "this team wanted it more"

San Antonio Spurs: MCMXCIX, MMIII, MMV, MMVII, MMXIV


I Never Cried When _____ Died, But I Definitely Will When Hov Does
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San Antonio Spurs: MCMXCIX, MMIII, MMV, MMVII, MMXIV


I Never Cried When _____ Died, But I Definitely Will When Hov Does
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post #9 of 744
I'm fascinated by the new sportvu cameras that hang in a few of the arenas and track and record every player's movement

"The technology was originally developed to track missiles. Now, SportVU systems hang from the catwalks of 10 NBA arenas, tiny webcams that silently track each player as they shoot, pass, and run across the court, recording each and every move 25 times a second. SportVU can tell you not just Kevin Durant’s shooting average, but his shooting average after dribbling one vs. two times, or his shooting average with a defender three feet away vs. five feet away. SportVU can actually consider both factors at once, plus take into account who passed him the ball, how many minutes he’d been on the court, and how many miles he’d run that game already."
http://www.fastcodesign.com/1670059/moneyball-20-how-missile-tracking-cameras-are-remaking-the-nba

I like the heat maps they create off the info, here's durant's shooting percentage on contested shots from various spots on the floor


and here's just a graphic of # of shots from various spots


it's less about number crunching and more about quantifying (and thereby gathering the information that allows you to improve) player and team effectiveness
you have to take advantage of this lifetime because when you die, you're dead for a long time
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you have to take advantage of this lifetime because when you die, you're dead for a long time
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post #10 of 744
Thread Starter 
Quote:
Stephen Curry Lights Up The Garden

Golden State guard Stephen Curry was on fire Wednesday night in New York, scoring a career-high 54 points with 11 3-pointers in the Warriors' 109-105 loss to the Knicks.

Curry's shot chart vs. New York

shotchart-curry-130227-500.jpg



Notes on Curry's performance vs. New York
  • Curry's 54 points is the most points scored by any player in the NBA this season, surpassing Kevin Durant's 52-point performance vs. Dallas on Jan. 18.
  • Curry's 54 points eclipsed his previous career high of 42 points (@Portland 04/14/10) and is the most points by a Warrior since Purvis Short scored 59 vs. New Jersey on Nov. 17, 1984.
  • The last player to score 54 in a game was Deron Williams, who had 57 on March 3, 2012 against the Bobcats. Like Curry, Williams' career-high came on the road.
  • Curry set a new franchise record with 11 3-pointers made. He fell just one 3-pointer shy of the all-time NBA record of 12 in game, held by Kobe Bryant and Donyell Marshall.
  • Curry hit all three of his corner threes, while going 8-of-10 on above the break threes.
  • Curry did more than score, as he also led the Warriors in assists (7) and tied for the team-high in rebounds (6, with Festus Ezeli).
  • Curry became the first visiting player to score 50 points at Madison Square Garden since LeBron James in 2009.
  • Curry scored the most points in NBA history for a player with 10+ 3PTM. The previous record was held by Ray Allen with 47 points in '01-02.
  • According to the Elias Sports Bureau, only Wilt Chamberlain and Rick Barry scored more points in a loss to the Knicks than Stephen Curry did on Wednesday.
  • Curry couldn't get a shot off in the final minute. His final field-goal attempt came with the game tied at 105 and 1:28 to play, but it was blocked by Raymond Felton. The Knicks would score the final four points of the game to secure the 109-105 win.

More from this game
  • Other than Curry, the Warriors starting lineup combined to score only 13 points on 6-22 (21.4%) shooting. The Warriors had two players other than Curry reach double figures -- Jarrett Jack (14) and Carl Landry (15) -- with both coming off the bench.
  • Tyson Chandler set a new career high with 28 rebounds (including 13 in the first quarter alone) for the Knicks. He grabbed 36.8% of available rebounds while he was on the floor. His previous career high came in 2007 against the Memphis Grizzlies.
  • Carmelo Anthony scored a team-high 35 points, while J.R. Smith had 26, including six 3-pointers and the bucket that put the Knicks up for good with 1:10 to play.
  • Curry's 54-point performance came on the second night of a back-to-back against Eastern Conference division leaders. Take a look at Curry's numbers from the two games combined.

Curry's shot chart from the past two games (@ Indiana, @ New York)

shotchart-curry-2gms-130227-500.jpg



Notes on Curry's last two games
  • Curry's 92 points in consecutive games is the most since Kobe Bryant had 97 back in February of 2009.
  • Despite Curry's tremendous shooting performances over the last two nights, the Warriors lost both games, to the Central-leading Pacers and the Atlantic-leading Knicks, respectively.
  • Curry had a plus/minus of -16 during the two games.
Link
post #11 of 744
Quote:
Originally Posted by PMatic View Post

Quote:
Curry had a plus/minus of -16 during the two games.
Link

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San Antonio Spurs: MCMXCIX, MMIII, MMV, MMVII, MMXIV


I Never Cried When _____ Died, But I Definitely Will When Hov Does
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San Antonio Spurs: MCMXCIX, MMIII, MMV, MMVII, MMXIV


I Never Cried When _____ Died, But I Definitely Will When Hov Does
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post #12 of 744
How far away do you guys think we are from having Synergy or another service become like it available for cheap or maybe even free? If they don't do it themselves, I'd have to imagine somebody else will come along and try to open the floodgates. (Although I dont know what type of licence they have with the NBA)
post #13 of 744
Thread Starter 
Quote:
Originally Posted by Al3xis View Post

How far away do you guys think we are from having Synergy or another service become like it available for cheap or maybe even free? If they don't do it themselves, I'd have to imagine somebody else will come along and try to open the floodgates. (Although I dont know what type of licence they have with the NBA)
I read recently NBA.com/stats will be using videos soon. I'm not sure it'll be as thorough as Synergy though.

At least Synergy allows one to check the stats for free.
post #14 of 744
Quote:
Originally Posted by FinallyFamous View Post

What is the joy y'all get out of this? Not hating just curious.

I understand the idea of advanced stats and what not, but do people really analyze this stuff all the time?
Being educated.

Looking at numbers.

I personally LOVE numbers, so it is fun.

Best paper last year to me (that I need to study for hooping) is , "Where do all the rebounds go."

http://courtvisionanalytics.com/where-do-rebounds-go/
post #15 of 744
Synergy pimp.gif

There's no excuse for an NBA player about their craft not to use it
post #16 of 744
Quote:
Originally Posted by Al3xis View Post

How far away do you guys think we are from having Synergy or another service become like it available for cheap or maybe even free? If they don't do it themselves, I'd have to imagine somebody else will come along and try to open the floodgates. (Although I dont know what type of licence they have with the NBA)
There is a $30 fee to see a modified version of Synergy. Well it was like that a few years ago. I haven't used it because the stream is always choppy on my PC.
post #17 of 744
Thread Starter 
Quote:
Revisiting Lin vs. Felton decision

From the standpoint of the New York Knicks, hoping to justify their decision to let Jeremy Linleave in free agency and replace him at point guard with Raymond Felton, this season couldn't have started any better. Felton was excellent during the month of November as the Knicks got off to a surprising start, while Lin struggled to find his place next to James Harden with the Houston Rockets.

Some three months later, it's worth revisiting the Lin decision. Felton's success, like his team's, has proved fleeting. Meanwhile, the Rockets and Lin are one of the league's hottest teams.

Misleading month
You remember November, right? President Barack Obama had just been re-elected, Manti Te'o was merely a linebacker in contention for the Heisman, and the Knicks were one of the NBA's best teams. Behind a flurry of 3-pointers and a smaller lineup with Carmelo Anthonyat power forward, New York started the season 14-4. The Knicks capped that stretch with their second win over the Miami Heat and marked themselves as serious contenders in the Eastern Conference.

New York's backcourt of Felton and fellow newcomer Jason Kidd played a major role in the fast start. Felton made 40 percent of his 3s in November while averaging 14.6 points and 6.7 assists. Kidd was even better beyond the arc at nearly 49 percent. As a team, the Knicks shot 41.6 percent from 3-point range, powering the league's best offensive rating in the month.

Everyone said the shooting couldn't last, and it didn't. Since Dec. 1, New York has shot exactly the league average (35.8 percent) on 3-pointers. Felton, at 31.4 percent, has been even worse. The Knicks are still a very good offensive team, ranking sixth in points per possession from December onward, but not the juggernaut they once were.



At the same time, as the chart shows, the Rockets were making the opposite transformation, with Lin as one of the leaders. As Houston has figured out how to utilize both Harden and Lin, the Rockets' offense has gone from solidly above average in November to elite. Lin's own statistics, as measured by wins above replacement, have seen a similar boost.

Knicks finding their level
The Knicks, it turns out, are who we thought they were. Since peaking at 14-4, they have consistently played at about a 45-win pace -- matching preseason expectations. Project that out through the rest of the schedule and New York figures to finish somewhere around 49 wins, which should be good for third in the East.

Fears that the crosstown rival Brooklyn Nets will come back to win the Atlantic Division are probably overstated. While the Nets have climbed within two games in the standings, their point differential is barely better than .500, suggesting they're likely to regress somewhat the rest of the way. The same is true of the Atlanta Hawks, who sit fifth, leaving only theChicago Bulls with a healthy Derrick Rose as a serious threat to the Knicks' top-three seed.

Felton, it turns out, is also who we thought he was -- not quite as bad as he looked during his disastrous 2011-12 campaign in Portland, but not as good as he played during his first half-season in New York or the opening month this season. As much as Felton's playmaking and his ability to generate steals have helped the Knicks, he has had a tough time scoring efficiently since the 3s stopped falling. Felton is making just 42.4 percent of his 2-point attempts and has seen his true shooting percentage slip to 47.5 percent -- far worse than the league average of 53.2 percent.

Moving beyond Linsanity
For both the Knicks and Lin himself, Linsanity has become a distant memory. Gone are the headlines, the screaming fans and the incredible numbers Lin posted as the Knicks' go-to player last February. Instead of getting Linsanity, the Rockets ended up with Jeremy Lin, developing point guard.

Playing next to Harden, Lin isn't the focal point of the Houston offense the way he was during the stretch that made him a household name. However, he has defied critics by showing the ability to thrive in that smaller role. In part, that's because of the adjustments made by the Rockets' coaching staff. It also reflects Lin's 3-point shooting regressing to the mean. After shooting 26.3 percent from downtown in November, Lin is at 34.4 percent since, making him something of a threat when opponents leave him open.

The funny thing is Lin's 2012-13 stat line is relatively similar in many ways to what he did last year in New York. His effective field goal percentage, for example, is an identical .478. The difference in Lin's offense is entirely a matter of volume. He's down from using 28.1 percent of the Knicks' plays to 20 percent of Houston's, putting him precisely at the typical figure, and his assist rate has dropped by almost a third. Lin's overall performance, All-Star caliber in 2011-12's limited sample, is slightly below league average this season. That's a more sustainable level of play.

Looking ahead
Lin's ability to coexist with Harden, who doesn't use as many plays as Anthony but tends to dominate the ball to a greater extent, leads naturally to the question of whether Lin could have fit into an Anthony-centric offense at Madison Square Garden.

There are advantages to Lin's current situation. Houston's fast pace, and the sheer number of pick-and-rolls the Rockets run as the basis of their offense, give him more opportunity to play in space than he might have had in New York. Still, it's not clear that Felton is any better fit for the Knicks than Lin would have been. According to mySynergySports.com, the two players have been about equally effective on spot-up opportunities, with Lin averaging 0.91 points per shot to Felton's 0.95. Surprisingly, Lin is a much more frequent spot-up shooter.

We're also comparing these players as they are now, not as they will be at the end of the three-year contract Houston gave Lin. While Felton, 28, is likely to be about the same player at that point if not take a slight step backward, the 24-year-old Lin still has room to grow as an outside shooter and playmaker.

The Knicks won the early rounds of the Lin versus Felton decision. If Lin already has pulled even, however, there may be no question who the better choice was in a couple of years.
Link
post #18 of 744
Saw this last week


The Dwight Effect: A New Ensemble of Interior Defense Analytics for the NBA


Major nerd alert, but I thought some of the data was interesting.


EDIT: just saw PMatic posted a link to all the papers. so my bad for the repeat.
Edited by MaxElite - 2/28/13 at 8:44am
post #19 of 744
Thread Starter 
Quote:
How the NBA’s love for advanced stats has slowed our understanding of the game.

This weekend, many of the NBA’s sharpest minds will gather at the Sloan Sports Analytics Conference, an increasingly splashy affair held each year by MIT, and now sponsored by ESPN. They’ve come a long way. Just over a decade ago, several of the most prominent among them first gathered in a much humbler spot: a Yahoo Groups message board called “APBR Analysis,” for the Association of Professional Basketball Researchers. In the very first post, on Feb. 10, 2001 at 10:32 p.m., a former Cal Tech hoopster turned statistics Ph.D. named Dean Oliver laid out an ambitious agenda of 12 issues. “To start off the group, I think that it is most appropriate to identify some of the outstanding questions in basketball,” he wrote. Some questions were practical. “Does Hack-a-Shaq work?” “Why has Charlotte had such a good record without Derrick Coleman in the lineup and a mediocre one with him in?” Others were more theoretical. “What additional statistics could be taken to improve individual defensive evaluation?”

Oliver and his cohorts on the message board wrestled with these questions and countless others, logging on at all hours to debate the relative merits of Allen Iverson or how best to calculate a new metric called usage rate. Long before Moneyball author Michael Lewis wrote a New York Times Magazine cover story on the topic, the board wondered why Shane Battier had such a positive impact on his teams despite not appearing to be all that good at basketball. The message board was a veritable think tank. “You could tell that this was a place where there was going to be a serious level of discussion about NBA statistics,” says Kevin Pelton, who would become one of the original writers for Basketball Prospectus. “It was literally the only place in the world it was happening.”

The NBA establishment quickly took notice. Oliver, who published the seminal Basketball on Paper in 2003, seven months after Moneyball hit stores, was hired full time by the Seattle Supersonics in 2004. Another frequenter of the board, John Hollinger, was hired the following year by ESPN—and recently became a vice president of basketball operations for the Memphis Grizzlies. Hollinger’s ESPN gig was filled by Pelton, who, after making his name at Basketball Prospectus did a consulting stint with the Indiana Pacers’ front office. Roland Beech, who created the popular website 82games, was hired by the Dallas Mavericks in 2009 as director of basketball analytics. (His boss, Mark Cuban, is regularly one of the biggest names at the Sloan conference.)

As soon as each statistician joined an NBA squad, sharing in public became off-limits—and so, gradually, the think tank closed shop. What were the teams paying for, after all, if their new stat gurus were just posting their ideas online for the other 29 franchises to read? This has had a paradoxical result: Because NBA teams embraced advanced stats so quickly, progress on basketball analytics has actually slowed down. The top minds are now all working in silos, not only unable to collaborate but actually competing against each other.

Major League Baseball teams were hidebound enough to ignore Bill James and sabermetrics for a full quarter century—as a result, he and others hashed out ideas out in open, public forums. By the time MLB executives finally embraced advanced baseball statistics, the movement was fully formed. But advanced basketball stats were just getting started when NBA teams tuned in. And though many of those teams are now collecting the kind of data that outsiders can only dream of, they lack the manpower to fully harness it. Certainly there have been advances: Teams’ internal stats generally blow away what’s available publicly. But they haven’t come as fast as they otherwise might have. And we, as fans, don’t understand the game as well as we could.

Dean Oliver estimates that between 22 and 24 NBA teams currently employ some form of analytics, with about one-half that number seriously incorporating their findings into the team’s approach to the game. Most analytics departments are small, which makes it hard to tell when your research is headed down the wrong path, says Aaron Barzilai, a former MIT player who started the site BasketballValue before joining the Philadelphia 76ers in November as their Director of Basketball Analytics. “You often just don’t have a ton of feedback on how you’re doing, especially if you’re one person on a team by yourself,” he says. And asking for help isn’t an option. Desperate for any competitive advantage, NBA teams guard their data—and whatever conclusions they draw from it—with about the same paranoia as a government official sitting on bomb codes. When asked how many analysts he employs, Houston Rockets General Manager Daryl Morey, the first stats acolyte to be hired to run a franchise, replies, “It’s not something we talk about.”

Fans have lost out in the bargain, too, with the newest ideas mostly staying locked up inside team offices. Just glancing at the homepages of leading advanced stat sites makes it clear they’re not getting enough love—BasketballValue and 82games both look like they were designed by a 14-year-old sometime in 1998. Barzilai hasn’t updated the numbers on his site since the Sixers hired him, and while the stats 82games remain current, Beech stopped posting articles there when he joined the Mavericks. Hollinger’s analysis, too, has now disappeared behind the league’s veil. NBA.com just launched a much prettier stats portal, complete with advanced metrics—but what’s on the site pales in comparison to what’s available behind closed doors.

Oliver, now back out of the league and working for ESPN, says that he’s particularly frustrated by the lack of headway that’s been made on one of the first problems he posed on the Yahoo message board: What new metrics could be created to quantify individual defensive performance? The last decade has seen tremendous progress in understanding the offensive side of the floor, but defense—where players must constantly rotate and cover for each other—presents a much knottier problem. Oliver believes that technology is providing the raw data to solve it, but all those NBA stat gurus working in isolation against each other aren’t close to cracking the code.

Where is that raw data coming from? Cameras that weigh about a pound and can fit in the palm of your hand. They’re provided by STATS, the global information behemoth, as part of its SportVU program, and they currently hang in the rafters belonging to 15 different NBA franchises, six per arena. They record everything: How far and how fast a player runs during the game, how many dribbles he takes when he has the ball, where he shoots from, the arc of his shot, whom he’s passing to, whom he’s not passing to, the spots where he get his rebounds, the spots where others get his rebounds. It’s endless. For each second of game play, the SportVU cameras capture the location on the court of the ball and each player 25 times, according to Brian Kopp, a VP at STATS. “You have 1 million data records per game.”

STATS acquired SportVU in 2008 from an Israeli company that had originally designed it for soccer. This is the system’s third year in the NBA since being recalibrated for basketball. STATS charges teams from $75,000 to $100,000 per season for SportVU, and the program has grown in that time from four initial teams to now half the league. The result is one of the largest and richest data sets not just in sports, but in the world.

Kirk Goldsberry, a visiting scholar at the Harvard Center for Geographic Analysis who also uses spatial mapping to analyze the NBA for Grantland and on his blog, Court Vision, is one of the few civilians who’s been granted access to any of the SportVU data. He’s working with another Harvard professor, statistician Luke Bornn, and four Harvard and MIT Ph.D. students in a semester-long project to break some of it down. “We look at that data and we say this isn’t just good data, this is the best space-time data,” Goldsberry says. “It’s just an incredible amount of information, regardless of whether it’s about NBA or anything else … There’s very few people who have ever seen any data like this.”

If six people from Harvard and MIT have their hands full with SportVU, you can only imagine how teams in the NBA are dealing with it. STATS provides standard reports to help teams understand the information, but those only scratch at the surface of what’s possible. “I’d like to think we’re ahead,” Morey says, “but it is a whole new overwhelming amount of data. You need to take a different approach to it and I don’t think anyone has the killer app there—the thing that comes out of that data that gives someone a very significant edge.”
Many, including Oliver, believe the killer app is hiding in there somewhere. The challenge is that there’s so much information, it’s easy to get lost. “It’s like saying you’re going to Wal-Mart or Ikea to get something,” offers Tommy Sheppard, the Washington Wizards vice president of basketball administration. “You better know what you want, or you’re going to walk out with a ton of ****.” That each franchise is working alone—and against each other—compounds the problem. Goldsberry describes it as 30 “micro-CIAs,” all racing against each other to “procure actionable intelligence out of these haystacks of vast data.”

Which brings us back to that lingering question from Oliver’s first post on the Yahoo Message board: How to measure defense? Traditional measures—like blocks, steals, and rebounds—fail to account for the full context of each play, but SportVU can provide a more complete picture. “We can say, OK, when Roy Hibbert is near an offensive player, A) they don’t even tend to challenge him very much, and B) when they do, their field goal percentage is really low if he’s within three feet of the shot,” Goldsberry says. “And then you can look at somebody like David Lee—when he’s within three feet of a shot, those numbers are much higher.” The paper Goldsberry submitted (along with co-author Eric Weiss) to this year’s Sloan conference expands on that idea, using SportVU to quantify which NBA big men are best not only at defending shots close to the basket, but deterring those shots from being taken in the first place. When it comes to analyzing SportVU data, though, the authors note that their “paper’s methods only represent a small first step.”

In theory, the Sloan conference is where all these analysts now gather to learn from each other. But they’re no longer working together, as they once did on that Yahoo message board. Daryl Morey admits that, from an academic perspective, it would be fun to drop the iron curtain dividing all of the franchises so that everybody could work in unison to hash out what’s probably the greatest data challenge in the history of sports. “Maybe someday when we all get fired we could get together, but right now our jobs are to win for our teams, so we focus on that,” he says. “Our businesses aren’t for the public domain. Knowledge in general will slow down, but hopefully knowledge that gives us an edge will not.”
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post #20 of 744
^
Great read.

I've been playing with the SAP stuff on NBA.com going thru old game logs of Magic Johnson and copying them down. Sadly, I'm finding issues with the information. Some of the totals are not adding up as they should be. To me, that's dicey when you have all that info and some are wrong, what the hell man? I found a game when Magic had like 18 points, 15 assists, 6-7 rebounds, and it says he played 6 minutes that game. laugh.gif That has to be some kind of record. So I tried to think logically, ok, it was probably 36 minutes and just a typo, add the 30 minutes, and his season total is still off from what his season stats show. mean.gif

In another season I found his points off by 1-2, his assists off by 1, his free throw makes and attempts both off, and one other stat I'm forgetting.

So now I'm a little worried about what they are entering in as their information. I think they are still working on it tho, because his game logs from like 85 and earlier are incomplete still.


I'm not all the way on board with you all yet, but I'm starting to lean and if I ever do fall, I have to give the credit to Osh, Proshares and PMatic. I hate all 3 of you. laugh.gif
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post #21 of 744
Quote:
What is the joy y'all get out of this? Not hating just curious.
I like to find new ways of proving myself right.
post #22 of 744
I hate this time of the year because there is TOO MUCH to read. I always get behind mean.gif
post #23 of 744
Thread Starter 
Follow @SloanSportsConf for live updates from SSAC.
post #24 of 744
Quote:
Originally Posted by PMatic View Post

Follow @SloanSportsConf for live updates from SSAC.

Whoever is running this twitter is tweeting too much

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post #25 of 744
Anybody up and following? Some good stuff being discussed right now.
post #26 of 744
Quote:
Originally Posted by DCAllAmerican View Post

Anybody up and following? Some good stuff being discussed right now.
I've been looking at the twitter, where else should I be?
San Antonio Spurs: MCMXCIX, MMIII, MMV, MMVII, MMXIV


I Never Cried When _____ Died, But I Definitely Will When Hov Does
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post #27 of 744
Follow Henry Abbot on TrueHoop : @TrueHoop

Also, True Hoop will post recaps/articles

http://espn.go.com/blog/truehoop
post #28 of 744
Thread Starter 
Quote:
10 NBA questions still to solve

When the NBA's analytics community gathers Friday in Boston for the first day of the annualMIT Sloan Sports Analytics Conference, it does so with the intent of expanding its knowledge of the game it loves. In that spirit, this seems like an appropriate time to consider the most important questions statistical analysis can help shed light on in basketball -- and give a progress report on where we stand in attempting to answer them.

My inspiration is the German mathematician David Hilbert. In 1900, at the dawn of the new century, Hilbert set forth 23 problems for the field of mathematics to solve in the next 100 years.

Hilbert's problems were translated to baseball by Keith Woolner in Baseball Prospectus at the start of this century, and Insider contributor Aaron Schatz published a list of football's Hilbert problems in the Journal of Quantitative Analysis in Sports, but no one has set forth such a list in basketball.

Until now.

Ten of Hilbert's 23 problems are now considered "resolved;" because of the nature of basketball analysis, I don't think we can ever solve any of the problems I present, but with more data and research, we can improve our understanding of them. While Hilbert came up with 23 problems and Jay-Z famously had 99, I settled on 10 important topics.


1. Which better describes player value -- individual stats or team impact?

When it comes to player evaluation, there are two schools. There are stats derived from the box score -- such as player efficiency rating, my WARP, Basketball-Reference.com's win shares and Wages of Wins' wins produced -- and plus-minus statistics. The problem with plus-minus is that it tends to be highly variable from season to season, but the advanced techniques and multiple seasons utilized by regularized adjusted plus-minus have allowed it to predict future team performance nearly as well as the best box score stats.

Ultimately, the answer probably isn't one or the other but a combination of both methods, since they measure slightly different things. Eventually, adding data from SportVU's optical tracking, such as screens and shot defense, could get us closer to measuring the value of players who don't make an impact on the box score.

2. How do basketball players age?

One of the most important discoveries of sabermetrics was that the peak age for baseball players was much younger than conventional wisdom held. For the most part, basketball research has found a similar prime to baseball, with a peak age around 27. However, the answer depends on the metric of choice because different skills age differently; players grab fewer offensive rebounds from the time they enter the league but shoot more accurately. Defense might peak latest of all because of the importance of experience. The continued success of this generation's veterans, such asKobe Bryant and Tim Duncan, also is forcing us to rethink how players decline in their 30s.


3. What is the best way to develop young players?

If there's one criticism fans always have of their favorite team's coach, it's that he doesn't give young players enough minutes. The assumption here is that time on the court is the only way for NBA players to develop, which makes sense intuitively but has never been demonstrated statistically, at least not publicly. This is one area in which future research could have a major impact on how teams play.


4. How do players' roles on offense affect their efficiency?

Usage versus efficiency is the fundamental question for rating offense, and it explains much of the difference among various rating systems (PER heavily rewards usage, while wins produced doesn't value it at all, and WARP falls somewhere in between). This has huge implications when it comes to comparing volume scorers with role players. Because players tend to shoot more when they have favorable matchups, it's impossible to use game-to-game performance to measure how much trade-off there is between using more plays and efficiency. The best study, done by Houston Rockets analyst Eli Witus, looked at the performance of various lineups and found a change of 1.25 points of offensive rating for each percent of usage rate above or below league average. But that's not true for every player; stars such as Bryant are able to take more shots without much hit in terms of efficiency, while specialists such as Tyson Chandler are very sensitive to changes in their role.


5. How much effect do players have on their teammates' statistics?

The notion that stars "make their teammates better" is probably as old as basketball. Now that we can track performance by players depending on their teammates, it has become statistically demonstrable. Elite passers and high scorers improve their teammates' efficiency by setting up easier shots. Teammates also are extremely important on the defensive glass, where elite rebounders tend to take some rebounds from teammates who would have gotten them otherwise.


6. Do per-minute (or per-play) stats translate across changes in playing time?

Few contentions of the statistical community are more divisive than the new conventional wisdom that players are best measured on a per-minute basis (or, better yet, per play to account for pace). Again, it's difficult to separate players forced into bigger roles from those earning more minutes with their improved play. John Hollinger attempted to do that in Pro Basketball Prospectus 2002-03 by looking at players who moved up due to injury. My follow-up with Tom Ziller on Ballhype.com showed players actually improving with additional minutes, but there's still room for additional research on players going from, say, 20 minutes per game to 35.


7. What role does coaching play in the success of teams and players?

Measuring coaching might be the last frontier for analytics. Dave Berri found in "Stumbling on Wins" that coaches show little difference in developing players. Of course, this is just one aspect of coaching. Including coaches as a sixth player in adjusted plus-minus calculations backed up the conventional wisdom that coaches have more impact at the defensive end. However, we've yet to make any real inroads in measuring late-game strategy or evaluating how well coaches put together lineups.


8. How do statistics translate from other leagues to the NBA?

Sabermetricians tackled minor league translations early on in their development. Adjusting college stats for the pros is trickier because of the wide differences in strength of schedule, changes in player roles and the importance of age in development. Still, my NCAA translations have proved reasonably accurate when it comes to predicting first-year performance, and adding in age helps account for long-term potential. Hollinger and I have found translating European stats even more reliable, and D-League stats can be translated to the NBA as well.


9. What is the market value for player performance?

Converting player value into dollar figures is another topic that surely has gotten more attention inside front offices than in the public sphere. We touched on this topic recently in Per Diem, but there's plenty more to explore. It's unclear whether value and salary are linear, for example, or how the new collective bargaining agreement has affected teams' willingness to spend in free agency. Stay tuned.


10. How do we best predict the outcome of games or series?

Lastly, there's the matter of evaluating teams. At the most basic level, we know point differential predicts performance going forward better than win-loss record. Other factors muddy the water. Are recent results more predictive than those from early in the season? And how do we deal with teams such as Denver and Utah that consistently display significant home/road splits because they play at altitude? When it comes to picking playoff series, head-to-head results show some value above and beyond overall level of play. Also,rest is better than rust, although the magnitude of the difference is relatively small.

Of course, there are many more questions besides these that statistical analysis can help answer, some of which will be addressed by the papers presented this weekend during the Sloan conference. Still, even these 10 problems will give statistical analysts plenty to work on in years to come.
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post #29 of 744
Thread Starter 


Edit:

Edited by PMatic - 3/2/13 at 11:40am
post #30 of 744
More articles? nerd.gif
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