HoopsHype: No team is shooting or making fewer three-pointers than the Knicks

Good article by Bryan Kalbrosky.

Only the Golden State Warriors have a better catch-and-shoot field goal percentage this season. New York is shooting 38.7 percent from downtown when taking catch-and-shoot three-pointers, which ranks Top 5 in the East.

But they rank last in the East (16.6) for attempts per game. They have not found a true spot-up shooter on their roster, as they have run this play type (15.3 percent) fewer than any other team in their conference.

Last season, this is something they relied on from 6-foot-8 forward Lance Thomas. In fact, most of his offense (53.2 percent frequency) came from this play type. Mindaugas Kuzminskas, who they recently waived, was also a spot-up shooter (35.9 percent frequency) for the Knicks.

The article also quotes Hornacek as noting that this needs to change, and yet….

Triángulo: José Calderón’s Value to the Knicks

After the dust settled on the trade with Dallas, and the unfamiliar high of receiving draft picks simmered down, one slightly unnerving reality kicked in: the length (three years) and cost ($22.21M) remaining on José Calderón’s contract, and the hearty bite into New York’s desired 2015 cap space. Though shipping Tyson Chandler and his expiring deal) back to Texas and extraditing the oleaginous mutta that is Raymond Felton netted the team a handful of assets, it seemed puzzling that the Knicks would be willing to accept the multiyear baggage attached to a guard approaching his 33rd birthday.

How difficult would it be to flip Calderón down the line? How does this affect Carmelo Anthony’s free agency? How would Calderón gel as part of the triangle offense?

These are all legitimate questions, though not before doing your due diligence on exactly what the scruffy Spaniard could bring to the Garden fold.

Calderón, whose 2013-14 season was his first and only with the Mavericks, boasts an elite shooting touch. A career 41.1% shooter from the outside, he ranked seventh in the league last season for made three-pointers, but finished fourth in 3PT%. His shooting numbers are insane across the board. He has eclipsed the 59.0 percent plateau for True Shooting in six of his nine seasons, and even enjoyed a 68-game run in 2009 where he converted 98.1% of his attempts at the charity stripe. Simply put, it’s very, very tough to find a level of sustained shooting excellence that is on a par with what José Calderón has produced throughout his nine seasons.

As a starter for 81 of the Mavs’ regular season games, he was a major factor in Dallas cobbling together an offense that tied as the second most efficient in the league. Granted, Calderón was flanked by the two-headed, Dirk-and-Carlisle offensive juggernaut, but his role in orchestrating the attack shouldn’t be dismissed. The Mavs’ scoring engine churned out 108.6 points per 100 possessions in nearly 2,500 minutes with Calderón on the floor, per NBA.com.

Dallas plugged Calderón alongside a ball-dominant, high usage guard in Monta Ellis, and the undersized duo (somewhat unexpectedly) proved to be a blessing for the Mavs’ offense. It’s hard to hide more than one player on the opposite end of the floor, however, and the move didn’t auger well for the team’s defense. For fans who grew tired of the Knicks’ switch-heavy, chaotic scramble of a defense last season, with Calderón on board, you might want to avert your eyes. Calderón is many things, though a league-average level defender is not one of them.

The Knicks’ self-inflicted anarchy under Mike Woodson’s scheme created headaches all season long. Calderón, on the other hand, has historically struggled to negotiate even a half-decent pick, and is too often found wandering in no man’s land on defensive possessions.

A quick glance at the stats and you might think Calderón is a respectable defender in pick-and-roll situations. He managed to rank in the top one-hundred defenders when guarding the ball-handler. In comparison, Raymond Felton came in at no. 205, allowing opponents to score on40.6% of his defensive stands, per Synergy Sports. Calderón’s opponents scored on 37.1% of their screen-and-roll plays, far from a humiliating mark. But it would be remiss not to consider the secondary effects of the Spaniard’s approach on the defensive end, where the bulk of the problems emerge.

The above example shows Calderón neither fighting over nor slipping under the Varejão screen, instead feigning activity and freeing Kyrie Irving for the regulation twenty-two footer. It’s a troubling bit of apathy on defense, but not exactly a criminal offense.

Calderón’s flaws are most exposed when the opponent is able to initiate a hint of ball movement, zipping the ball across the perimeter, and sending him into a tailspin. Here, moments after the Pelicans had swung the ball from one side of the floor to the other, and Calderón encounters a screen from Greg Stiemsma, he is visibly pointing for teammates to make a last ditch recovery on his opponent, Brian Roberts:

Again, elementary picks like this weren’t the worst outcome for Dallas. Things started to get a little nightmarish when the opposing point guard wasn’t necessarily the person to put up the shot attempt. A screen, a pass, another pass, and maybe another action, and you’ll get this:

This only highlights the closing moments of the possession, with the shot clock winding down. After a brief switch was forced earlier in the play, and Ellis was sucked over from the weakside on Jimmy Butler’s baseline drive, Calderón is caught ball watching at the top of the key, allowing Mike Dunleavy to break loose for the corner three. Plays like this constitute the less-than-ideal notion of having Calderón deployed as the “primary” defender on spot-up shooters.

Even if only due to his own absent-mindedness and curious positioning, Calderón cops the brunt of these defensive mishaps on the stat sheet. Nearly a third of his defensive plays resulted in covering spot-up gunslingers and, as Dallas quickly learned, it’s a slippery slope straight to scoreboard damage from that point on. According to Synergy, opposing players drilled 43.5% of their long range attempts with Calderón as the primary defender, contributing to his season average of 1.09 points per possession allowed.

Trotting out Calderón with anything but a defensive stalwart by his side is a major gamble, and one that can only be micromanaged in the most extraordinary of circumstances, a la with Dirk in tow. But before you pound your head to the desk at the prospect of one, two, or three seasons of this caliber of backcourt defense, take a moment to understand why an organization like the Mavericks would be willing to doll out a pricy, four-year deal to a player of this mold.

Last season in particular, Calderón was lethal on the perimeter. Scorching hot. He nailed almost two and a half triples per contest, shooting 44.9% on 425 total attempts. As futile as it seemed having Calderón within a five mile radius of opposing wings, he can dazzle with his own deadly jumper. Crack open an extra inch or two of space by setting a high screen, and he will gleefully fire away.

Check the film of José and Dirk running the pick-and-roll, and you will likely find yourself drooling at the thought of him doing with same with Melo (provided that Anthony re-signs). The threat of a capable shooter and/or stretch four fanning out onto the wing or popping out to the top of the key, with armed and readied shooting hands, poses a scary threat to the defense. That’s a choice that nobody wants to have to make–wrestle over to try to corral Calderón, or scurry away to a tough crossmatching scenario.

Few teams are going to be willing to punt on the opportunity to cover Calderón with the knowledge that he comfortably splashed 46.6% of his three-point attempts as the setup man in pick-and-rolls. Of course, shooting–if used correctly–creates bonus opportunities, leaves opponents scattered, and opens avenues that maybe you never even knew existed.

Part of the reason why the Mavericks were able to get away (for the most part) with the Calderón-Ellis tandem was what happened when teams deliberately looked to shun the screen-and-roll situations. What’s the best way to deal with above defensive dilemma? Avoid it altogether? Perhaps, but then you’re faced with the problem of tossing too many eggs into one ball-stopping basket.

Ellis’ slashing game shouldered a decent load for Dallas, and Calderón was one of the primary beneficiaries. With the Spanish veteran, though, it doesn’t even require a stream of high voltage hurls into the paint to free him up on the outside. He connected on 45.9% of his catch-and-shoot attempts from distance, courtesy of NBA.com. A basic action, balancing of the floor, and another draw card or two in the lineup is a tantalizing recipe for unchaining Calderón around the arc.

Tim Hardaway Jr.’s trigger happy hands are streaky, useful tools from time to time, but the transition from guards who were either not willing (Prigioni), able (Felton), or confident (Shumpert) to launch from beyond the arc to heavier minutes for the deadly Calderón is an overdue adjustment. That change, in the shadow of the triangle offense, figures to be smooth.

Calderón only has to look as far as, say, his new head coach Derek Fisher for inspiration on how to yield sharp shooting as a weapon within the parameters of the triangle. Having the team’s new point guard outside the arc, with Carmelo Anthony–again, in the event that he stays–or another agile frontcourt player functioning through the “pinch post” role would be a nice start. It’s not worth delving too deeply into the mechanics of Calderón in the triangle until the makings of the supporting cast are a little clearer, suffice to say that he is the model lead guard to slot into the system with Anthony either on the block, or cutting from the weakside.

He was also one of the premier protectors of the ball among all point guards last season, turning it over on just 11.7% of his possessions, an invaluable commodity in a system that’s based on fluid passing and well spaced quarters. Calderón deserves to be viewed as more than just a cap-clogging relic, and his serious defensive weaknesses can be skewed and lessened with the aid of a cohesive system. He is, for now, the Knicks’ starting point guard, and if you’re itching to see him clad in blue and orange, it’d be worthwhile watching him suit up for Spain in the FIBA World Cup (in September).

It’s also worth mentioning that he does have some serious mileage on his legs (almost 19,000 minutes, including playoffs), and–depending on your belief in the real plus-minus measurement–you could argue that he finished 2013-14, defensively, as one of the ten worst players in the league that spene any time at the point guard position. Calderón’s contract is more palatable than some have suggested, given the current market for perimeter players with a jumper of his caliber, and the showpieces of his skillset (vision, passing, shooting) should fare well with age.

Trading Tyson Chandler brought a close to one “era,” (for lack of a better term), and reaped a basket of returning goodies. Rather than panning his inclusion in the deal, it may yet prove easier to shade José Calderón as one of the chief assets gained in the move that began a welcome changing of the guard.

The Melozoic Era, Statistically Speaking

When it comes to the Melo trade, there’s probably one thing everyone can agree on: the on-court results are a mixed bag. A thrilling win over Miami, blowout wins over New Orleans and Utah and a tough road loss to the Magic, but also a pair of embarrassing defeats to Cleveland and the latest stinkers against Dallas and Indiana.

At 6-6, the Knicks of the Melozoic Era (kudos to Jim Cavan for coining the phrase) have a worse record than the previous version. Subjectively, they’re disjointed and inconsistent. They’re not sharing the ball. They clamp down on D… except when they don’t. Is it a few problems, or a lot of them?

As usual,  the numbers clear up the picture.

Pace Rank Offensive Efficiency Rank Defensive Efficiency Rank
Pre-Melo Knicks 98.7 2 107.6 9 107.1 24
Melozoic Knicks 97.0 7 111.5 1 110.0 30

As Mike D’Antoni has modified his beloved SSOL scheme, the Knicks have turned – ironically – into a parody of a Mike D’Antoni team: all O, no D.

Some common complaints are unwarranted. The Knicks may or may not be uglier to watch, or more selfish, but there’s not much to complain about when they have the ball. Since the trade, their offense is the best in the league.

On the other end of the court – peeeeee-uw.  I can hear it now:  “Can you imagine how bad they’d be without DPOY candidate Jared Jeffries?”

The picture is muddied by Chauncey Billups missing five of the 12 games, but if anything a healthy Billups should make the trends stronger. Billups is one of the most efficient offensive players in the league, but the Knicks D isn’t much helped by his taking minutes from Toney Douglas.

None of this is shocking, but the effect has been more dramatic than most expected. Were Chandler, Gallinari and Felton that good on the defensive side? Is Melo that bad? Is it just a lack of practice time?

Quibble if you must over whether Renaldo Balkman deserves some burn, but D’Antoni has already thrown solid minutes to Jeffries and even Anthony Carter. It’s hard to envision big improvements through different personnel. A healthy Ronny Turiaf would help, but unless the Knicks find something to reverse their defensive collapse, the first round playoff series is likely to be short.

A note on the details: as I started doing the math, I discovered that different sources count posssessions differently, which – obviously – affects the efficiency numbers. I went with posession totals from Hoopdata, which gave me final calculations almost identical to ESPN and John Hollinger. That let me compare apples to apples in the rankings. If you see a slight difference – a tenth of a percentage point or two – blame it on the possession data. Here’s a game-by-game chart: Knicks 2010-2011 game log . You can see how bizarre an outlier was our latest Miami win.

Answering Thomas B.’s Questions

Thomas B. Said:
Maybe you and I are not looking at the same stats when it comes to Denver’s defense.

Denver gives up 104 per game, that is good for 25th place in the NBA, that means only 5 teams give up more points. They only score 2.4 more points than their opponents, which is good for 10th place in the NBA.

Three teams score more points per game than Denver and none of those teams allow as many points as Denver….

Mike K. (KnickerBlogger) Said:

By points per possession allowed, Denver is 6th….

Thomas B. Said:
So does that mean Denver is actually a good defensive team? What would happen to the Knicks if they played at Denver’s pace? Would they give up 110 per because they now give the other team more chances to score?

1. So does that mean Denver is actually a good defensive team?

Up to this point, the Nuggets have allowed an average of 105.2 points for every 100 possessions. So yes, Denver is a good defensive team despite allowing the 6th most points per game in the league. I don’t want to get into the specifics, because I think A Layman’s Guide to Advanced NBA Statistics does a good job at it. I’ll just say, a team’s pace can affect the amount of points scored or allowed per game, so points per game isn’t a good measure of a team’s quality.

2. What would happen to the Knicks if they played at Denver’s pace?

Most likely Eddy Curry would have a heart attack and Zach Randolph would stop running back on defense altogether.

3. Would they give up 110 per because they now give the other team more chances to score?

Up to this point in the season, the Knicks have allowed 112.5 points per 100 possessions, they’ve averaged 89.4 possessions per game, and they’ve allowed 100.4 pts/g. In other words, they’re the worst defensive teams in the league (30th), but since they play at a slightly slow pace they’re only the 20th worst team on defense. So what if they played at Denver’s pace?

The Nuggets average 97.9 possessions per game, the most in the league. By simple arithmetic the Knicks would allow an average of 110.1 points per game if they played at that pace (97.9*112.5/100). That mark would be 5 points per game worse than the Nuggets are currently averaging now. It would easily be the worst in the league, more than the Warriors 107.1.

Colley Rankings 12/5/2008

Last year I unveiled OTTER, an objective team ranking system. It had two parts, a pre-season predictive team aspect and a in season aspect. Unfortunately I’ve decided to put part one on hold for now. I’d like to find a better way to predict performance from season to season.

However I’m still able to publish the second part which is team rankings based on the Colley Matrix. Dr. Colley invented this method of ranking teams by looking at only the results of games. That is each game is valued by strength of opponent. This ranking has a single advantage over other systems, in that it “sees” every single game played. I’ve modified Dr. Colley’s method slightly, accounting for home field advantage.

Team Rank SOS W L
Boston 0.886 8.9 14 2
Orlando 0.879 12.3 16 4
San Antonio 0.825 9.5 15 3
Phoenix 0.803 10.1 14 4
Detroit 0.731 9.4 12 5
Utah 0.729 10.8 13 6
Dallas 0.697 9.9 12 6
New Orleans 0.694 9.9 12 6
L.A. Lakers 0.655 11.1 10 8
Houston 0.635 11.7 9 9
Golden State 0.628 10.4 9 8
Cleveland 0.622 12.6 9 10
Denver 0.603 9.1 11 7
Toronto 0.599 10 10 8
New Jersey 0.575 10.5 9 9
Milwaukee 0.574 9.3 8 8
Washington 0.555 10 8 9
Indiana 0.535 10.7 9 10
Sacramento 0.519 10.4 7 10
Atlanta 0.483 9.7 7 10
Portland 0.476 11.5 6 12
L.A. Clippers 0.439 8.9 6 10
New York 0.438 9.9 5 11
Memphis 0.436 9.8 6 11
Charlotte 0.417 8.5 6 10
Philadelphia 0.397 10 5 12
Miami 0.392 11 4 13
Chicago 0.368 8.8 4 11
Seattle 0.295 10.9 3 15
Minnesota 0.262 9.7 2 14

As for the results: early on it looks like the East has caught up to the West. Not only has the rebuilt Celtics taken the top spot over the usual suspects in the West, but the Orlando Magic is right behind them. The results are a bit shocking, since Phoenix beat Orlando twice this year, but it seems that Orlando has faced one of the toughest schedules so far. The Suns are about league average with respect to their opponent strength. Additionally from this data it seems that the Cavs have been hurt by their schedule, while the Nuggets might have received a bit of an advantage.

A Layman’s Guide to Advanced NBA Statistics

This guide is intended for those that are interested in modern basketball statistics. In order to make it more accessible, I’ve decided to forgo the formulas and numbers. At times both fans and journalists alike struggle to use stats when it comes to basketball. Often enough, their interpretation is inadequate because they don’t have the right stats to explain what is happening on the court. Even worse is when stats are used improperly to arrive at the wrong conclusion.

Over the past few years basketball statisticians have learned a lot about the game. While most of it is based on the same stats you would see in boxscores, the findings go far beyond traditional stats. Evaluation on the team level is the most reliable aspect of basketball statistical analysis. In other words, we’re very sure what factors lead a team to victory. Although statisticians aren’t exactly sure how player stats equates to wins, there are many ways to better evaluate individuals than the classical stats.

Team Stats

What You Need to Know
When looking at team stats it’s important to understand that some teams play faster than others which skews their per game stats. Faster paced teams will get more chances to score per game, solely because they have more opportunities. It’s similar to two NFL RBs, both with 1000 yards rushing, but one had 300 attempts and the other only 200 attempts. In this case it’s not enough to know the totals, instead you have to account for the difference in the number of opportunities. The same applies for team stats.

So in lieu of viewing how a team performs per game, we calculate how a team does per possession. What’s a possession? A possession ends when a team gives the ball to the other team, usually through a score, a turnover, or a missed shot recovered by the defense. By using points per possession, we’re looking at how many points a team scores when they have the ball on offense. This is called offensive efficiency or offensive rating, and is measured in points per 100 possessions. Basically offensive efficiency answers the question “if this team had the ball 100 times, how many points would it score?” Similarly we can rate defenses by calculating how many points a team allows per possession, called defensive efficiency or defensive rating.

But it doesn’t stop there. We can break down what aspects of the game contributes to those rankings. Offense (or defense) is broken down into 4 crucial factors: shooting, turnovers, rebounding, and free throws. Shooting is by far the most important factor and is best measured by eFG% which is a better version of FG% (see “Shooting” below). Next come turnovers and rebounding which are about equal to each other, but less valuable than shooting percentage. Like points, turnovers are measured per possession (how many times you cough the ball up when you have it). Rebounding is measured by percentage of missed shots recovered. This is so teams that shoot poorly (have lots of misses to recover) are judged on an even platform with teams that can shoot. Last and least is free throw shooting. This is measured by free throw shots made per shot attempt.

In 50 Words or Less
Throw away points per game for team stats. Instead use offensive efficiency (or defensive efficiency), which is basically how many points a team would score in 100 possessions. Team stats are broken in four factors: shooting, rebounding, turnovers, and free throws. You can find these stats on basketball-reference (search for “Points Per 100 Possessions” and “Four Factors” on the team pages) and my stat site.

Examples Why
In 2006, Portland ranked 18th in points allowed per game, which means they should have been slightly worse than average. However they finished a paltry 21-61 that year. Their defense wasn’t adequately measured by points allowed per game, because they played at the league’s third slowest pace. Ranked by defensive efficiency they were 29th, which would make their 21 win season more understandable. Of course there’s the 1991 Denver Nuggets.

More Please
Dean Oliver (Points Per Possessions): http://www.rawbw.com/~deano/helpscrn/rtgs.html
Dean Oliver (Four Factors): http://www.rawbw.com/~deano/articles/20040601_roboscout.htm
Kevin Pelton: http://www.nba.com/sonics/news/factors050127.html
Basketball-Reference: http://www.basketball-reference.com/about/factors.html

Player Stats

What You Need to Know
Without a doubt per minute stats are more important that per game stats. This is because per minute stats makes valid comparisons between players of varying minutes. Using per game stats in the NBA is like using hits/game in MLB. In 2007 Michael Young averaged 1.29 hits/game to David Ortiz’ 1.22, but Young’s batting average was only .315 to Ortiz’ .332. Young had more hits because he had more at bats (639 to 549), not because he was a better contact hitter. Similarly you might find that one basketball player has better per game stats, but if he had more minutes then the comparison is invalid. Only per minute stats will clarify which player is truly better in a category.

The common notation for per-minute stats is using per 40 minute stats. This is because it’s easier to visualize 2.3 blk/40 min instead of 0.0575 blk/min. Measuring basketball stats per 40 minutes is similar to measuring earned runs per 9 IP in baseball (ERA). One thing to note, unlike ERA in baseball, basketball players’ per-minute stats stay the same despite their playing time. So while baseball relievers have lower ERAs than starters, the same is not true in basketball. Additionally this doesn’t mean a player should play 40 minutes, just as using ERA doesn’t mean that a pitcher should pitch a full 9 innings. It’s just a fair way to compare players.

In 50 Words or Less
Throw out a player’s per game stats, and look at per-minute stats instead. Per minute stats are usually measured per 40 minutes. Study, after study, after study shows a player’s per minute production to stay the same despite how many minutes they play. You can find them at basketball-reference for historical data, or my stat page for the current season.

Examples Why
Some examples of players that had good per minute numbers, but poor per game numbers due to a lack of playing time: Ben Wallace, Jermaine O’Neal, Gerald Wallace, and Michael Redd. Throw in a point guard, and that’s a pretty good team.

More Please
Kevin Pelton’s Stat Primer: http://www.nba.com/sonics/news/stats101.html
The Basketball Notebook’s Primer: http://basketballnotebook.blogspot.com/2005/12/basketball-notebook-stats-primer.html


Another stat that should be replaced is FG%. Why? Field goal percentage doesn’t account for the scoring bonus in a three point shot, which is a lower percentage shot. Sharp shooter Kyle Korver’s career FG% (as of 2007) is a lowly 41.3%. If FG% rates a good shooter like Korver so poorly, then it’s obviously not a good stat to use. So replace FG% with eFG% (effective field goal percentage), which compensates for the extra point in a three point shot. Korver’s eFG% is a more robust 53.6%.

But eFG% isn’t the only statistic used to measure a shooter. True Shooting Percentage (TS%) accounts not only for three pointers, but free throws made as well. For instance a player that hits a layup, gets fouled, and hits the extra point is more valuable than the guy that just sinks a jumper. To compare players with respect to their total scoring contribution, this is the stat to use.

In 50 Words or Less
Field goal percentage (FG%) should be replaced by eFG% or TS%. Effective field goal percentage (eFG%) compensates properly for three pointers, while true shooting percentage (TS%) compensates for three pointers and free throws.

Examples Why
Well I used Kyle Korver above, but otherwise you can look at any player that takes a large amount of three pointers or gets (and converts) a lot of free throws. Players like Kevin Martin, Jason Kapono, Manu Ginobili, and Shawn Marion come to mind as players who are misrepresented by FG%.

More please
Kevin Pelton’s Stat Primer: http://www.nba.com/sonics/news/stats101.html
The Basketball Notebook’s Primer: http://basketballnotebook.blogspot.com/2005/12/basketball-notebook-stats-primer.html

Overall Player Value

As I mentioned earlier, it’s not exactly clear exactly how to calculate a player’s worth. However there are 3 main stats that have attempted to give a single number to represent a player’s total contribution. The first and most prevalent is Player Efficiency Rating (PER). Created by John Hollinger, it attempts to take add up the good things, subtract the bad things, and account for team pace and minutes played. It’s normalized to 15, which means the average player in the league scores a 15 PER. The league’s best players are around 30, while the worst are in the single digits. Following Hollinger is economist Dave Berri (and friends) who came up with Wins Produced and it’s cousin Win Score. Unlike Hollinger who chose his equation, Berri and co. statistically derived what factors went into Wins Produced.

But both stats have their weaknesses. According to Wins Produces, PER tends to overrate players that score a lot of points, but do so inefficiently (poor shooting numbers). Meanwhile PER says that Wins Produced overrate strong rebounders that score infrequently. Additionally since they both rely on box score stats, neither captures actions that occur outside of the stat sheet. For instance Bruce Bowen plays tough defense and forces Kobe Bryant to take a bad shot that Tim Duncan rebounds. The stat sheet will record Duncan’s rebound and Kobe’s missed shot, but Bowen doesn’t get any credit for his defense.

One stat that does capture Bowen’s effort is plus/minus stats. Currently kept by Roland Beech, +/- comes in a few different flavors. Among the most popular are offensive and defensive +/-, which measure how a team does with the player on the court. Also Roland Rating and net +/- attempt to evaluate a player’s value. However plus/minus doesn’t just capture than the individual effort, it captures the value of his teammates as well. When Bowen and Duncan prevent the Lakers from scoring not only do they get credit for the effort, everyone else on the court gets the credit as well.

In 50 Words or Less
Trying to create a player’s total worth using a single number isn’t highly reliable. But if you need to use one, you can try PER, Wins Produced, or +/-. Each has their strengths & weaknesses and are only good to begin a discussion, not end one.

Examples Why
The biggest hole in statstical analysis is defensive stats. Blocks, rebounds, and steals aren’t enough to tell the whole story on what happens on defense. Players who excel in this area of the court usually have strong defensive +/-, like Bruce Bowen (-9.6). However these numbers tend to fluctuate based on the strength of the team. A player that spends a lot of time on the court with strong defensive players will have their defensive +/- inflated.

More please
Kevin Pelton’s Stat Primer: http://www.nba.com/sonics/news/stats101.html
What is PER?: http://sports.espn.go.com/nba/columns/story?id=2850240
Dave Berri’s Site: http://dberri.wordpress.com/2006/05/21/simple-models-of-player-performance/
Roland Rating: http://www.82games.com/rolandratings0405.htm
Adjusted +/-: http://www.82games.com/ilardi1.htm
Online & Downloadable +/- stats: http://basketballvalue.com/index.php

Using Stats to Gauge Player Ability

Let’s assume you’re the GM of an NBA franchise. It’s the offseason and you need to sign a free agent center. You have three options.

Player A 24 11.7 10.9 0.7 1.5 1.5 1.6
Player B 24 9.8 8.2 0.4 0.5 2.2 1.8
Player C 25 4.8 8.0 0.9 0.8 0.8 1.6

If these are the only stats we have, then it’s clear. Player A is a superior scorer and rebounder, and his defensive stats are about as good as the other two. On the other hand, Player C is a feeble scorer and the worst rebounder of the three. Player B is twice as good a scorer than C, and slightly better in rebounding and shot blocking. I would rank them Player A, Player B, then Player C.

Now what if your options were these three players:

Player A 24 13.5 12.5 0.8 1.7 1.8 1.8
Player B 24 12.6 10.5 0.6 0.6 2.8 2.2
Player C 25 8.0 13.3 1.5 1.4 1.4 2.7

In this example Player C is the best choice. He is superior to the others in 4 categories: rebounds, blocks, steals, and turnovers. Meanwhile Player B sinks to the bottom of the list, being too turnover prone and the worst rebounder of the three. This time I would rank them Player C, Player A, and Player B.

Now what if I revealed that the players in the first table are the same as the ones in the second table? How is it that a player can have two entirely different set of stats? Simple, the first table is the players’ per game stats, while the second is their per 40 minute stats. The stats changed so much from the first table to the next because per game stats are proportional to the number of minutes a player receives. And in this example, the players played varying amounts of minutes. Player A averaged 34.7 min/g, Player B 31.2 min/g, and Player C 24.1 min/g.

Playing time in the NBA is dependent on a few different factors. For younger players their talent, draft position, contract size, pre-draft hype, team depth, coach’s tendency, team record, and sneaker deal may alter their court time. A #2 overall pick playing for a rebuilding team with little depth (LaMarcus Aldridge) will see more playing time than a #4 pick playing for a playoff team with ample forwards/centers (Tyrus Thomas). Since per-game stats are proportional to playing time, and playing time is based on many different factors, then it makes sense that per-game stats are capturing some factors other than a player’s ability. In other words when Aldridge had more rebounds per game (5.0 rpg) last year than Thomas (3.7 rpg) it’s not due to Aldridge’s skill on the glass, but rather his higher draft position, team depth, team record, et al.

If we want to judge a player based on their talent alone, then we need to isolate a player’s talent from the rest of those variables. And that’s what per minute stats do. Once we remove a player’s minutes from his stats, then all the factors that go into playing time are removed as well. Per minute stats aren’t dependent on draft position, contract size, pre-draft hype, team depth, coach’s tendency, team record, or sneaker deal. When compared to per game stats, per minute stats come much closer to capturing a player’s ability.

Getting back at our tables above, it’s clear that Player C was hindered by his lack of playing time. Hence why he appeared to be inferior when using per game stats. But when we accounted for this lack of playing time with per minute stats, Player C was clearly superior to the other two. Player C, also known as Ben Wallace, would receive major minutes the next year in Detroit and win the first of his 4 Defensive Player of the Year award the season after. Player A, Dale Davis, was a fine player for 14 seasons, but was never considered great. Michael Olowokandi, Player B, never amounted to the hype of being the #1 overall pick, and despite being a year younger than Wallace, is barely holding on to his NBA career.

In the end, per game stats was unable to distinguish the perennial All Star (Ben Wallace) from the solid pro or the first round bust (Michael Olowokandi). However per minute stats identified the players correctly from most to least talented. Using per minute stats to compare players eliminates many of the unwanted factors that go into per game stats. Like sneaker contracts.


  • Why do we use per 40 minutes stats? Ben Wallace averaged 2.3blk/40 and he also averaged 0.072blk/min. It’s easier to visualize 2.3 blocks instead of 0.072 blocks. You could use any number instead of 40, but we use 40 since it has become the most commonplace.
  • Using per 40 minute stats isn’t an endorsement for the player to receive that many minutes. Nor should you use per 40 minute stats for one player, and per game stats for another. (And yes I mention this because I’ve seen people do it).
  • You could use more advanced metrics than per-minute stats, but per minute stats are easily calculated and widely circulated.
  • Don’t think that per minute stats hold up over increased minutes? Check this out:

    I did a small study using player-seasons from 1978-2004. To be included in the study, a player had to (a) see an increase of at least 50% in minutes per game from one season to the next and (b) play at least 41 games in each season. These criteria gave me 465 player-seasons. In 346 of these seasons (74.41%), the player’s PER increased with an increase in playing time.

    And this:

    No, increased minutes do not seem to lead to decreased efficiency. In fact, the data indicates increased minutes lead to? increased efficiency. More than 70% of the players in the study (there were 251 in total) saw their PER (which is, by definition, a per-minute summary statistic) increase with the increase in minutes. Players whose minutes per game increased by five saw an average change of +1.38 in their PER.

    And then this:

    Players who receive 10 or more minutes per game are likely to keep the same per minute stats no matter what the increase in playing time is. Therefore per minute stats remains far superior to per game stats in terms of comparing and evaluating players.