Category Archives: Expected Scoring Player Profiles

Individual Player Profiles using Expected Scoring and Point Differential

Expected Scoring – Martell Webster (Update)

In early October I began using my Expected Scoring numbers and some preseason statistics to profile some potential breakout players. One of the players we looked at was the Minnesota Timberwolves’ Martell Webster. Webster had a terrific preseason and with the change in scenery from Portland to Minnesota seemed ready to take a huge step forward.

I shared my initial profile of him at the Timberwolves’ site Canis Hoopus. A commenter there, skeptical of my positive outlook on Webster, asked me to revisit his numbers 25 games into the season and see if they looked quite as rosy. So here we are, using Expected Scoring to review and update my assessment of Martell Webster’s scoring efficiency.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Let’s start by looking at some of his traditional numbers. The table below shows his statistics for his last full season in Portland, this preseason and the 1st 25 games of the season.

Webster sat out the first 24 games of this season, recovering from back surgery. While Webster was out Michael Beasley used some dominant scoring performances to firmly entrench himself in the starting small forward position. Wesley Johnson and Corey Brewer have shared minutes at shooting guard which has left Webster fourth in the wing rotation in terms of minutes per game.

His numbers overall are fairly similar to what he did during his last season. However, his shooting percentages are nowhere near what he was making this summer. Webster averaged 12.7 FGA/36 minutes in the preseason. He’s averaging 12.2 in the regular season. Since his shot attempts are basically flat the big dip in his scoring average is all due to the drop in his shooting percentages.

Let’s now take a look at his Expected Scoring numbers. Below is a table showing Webster’s Expected Points, Actual Points and Point Differential for each area of the floor from the last three seasons, this past preseason and through the first 25 games of this season (all numbers are per 40 minutes). I have omitted 2009 as Webster suffered a foot injury and played in only one game. If you prefer a spreadsheet to the embedded table photo, here is the link.

It appears this was a case of me getting a little over-excited about a player’s preseason numbers. While Webster has remained a consistent mid-range jumpshooter he is finishing at a career low rate at the rim. In addition his terrific percentages on 16-23ft. jumpshots and three pointers from the preseason have basically regressed to the league average. Webster still scores at an above expected rate but his per 40 minute point differential is nowhere near the +3.46 he put up in the preseason.

Webster injured his back again on Friday. Although I haven’t heard a solid timetable for his return, it doesn’t sound nearly as serious as the back problems which led him to have surgery this Fall. Still, I have to believe there is room for optimism. His 3PT% is basically at a career low. If he can get healthy and stay on the court consistently it seems likely his shooting from that area would improve and could push his point differential even higher.

One issue that may be affecting his shooting percentages is how he is being utilized by Minnesota. Webster is averaging 1.41 PPP in transition, 1.29 PPP coming off screens, 1.08 PPP as a spot up shooter and 1.57 PPP on cuts to the basket. Those four situations account for 53.4% of the possessions he’s used this season. He’s averaging 0.41 PPP in isolations, 0.70 PPP as a pick and roll ball handler and 0.91 PPP on hand offs. Those three situations account for 29.3% of his possessions used and he has been extremely ineffective in those cases. 20.7% of his three point attempts have come out of those three scenarios and he’s shooting just 18.8% from three in those cases.

Basically, he’s terrific when catching and shooting, finishing opportunities that others have created for him. When he’s asked to use his dribble to create opportunities for himself and teammates he’s not nearly as effective. The problem is that the Timberwolves don’t have a lot of shot creators. Beasley is very much a black hole, Love is a finisher and none of the other wings have much inclination in this regard.

Even with his recent shooting struggles Webster has a better TS% and ORtg than any of the wings he has been competing with for minutes, including Michael Beasley. He is probably the weakest defender of the four, but for a team that ranks in the bottom third of the league in each of the Offensive Four Factors besides Offensive Rebounding, they could probably use a little more efficiency on that side of the ball.

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Expected Scoring – Derrick Rose

We’re moving through the regular season and continuing with our Expected Scoring player profiles. Today we’ll be looking at the Chicago Bulls’ Derrick Rose.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Rose is still very young, nearing the midway point of his third season after playing just one year of college ball. He entered the NBA and was able to contribute at a high level immediately, due to his incredible athleticism. The developmental challenge for Rose has always been to bring his skill level and saavy up to par with his physical attributes.

Rose improved from his first season to his second. After a very successful campaign with USA Basketball this summer at the World Championships in Turkey, expectations were sky high as he entered his third season.  Rose even went so far as to say that he considered himself a legitimate MVP candidate and he hopes other people do to. Rose has been impressive this season; the Bulls have looked extremely sharp and buzz is building for Rose as an MVP contender.

Let’s start by examining some of Rose’s basic statistics for his three seasons and hone in on where exactly the improvement has been which has catapulted him from up-and-comer to legit superstar. Here are his traditional stats (per 40 minutes) from his last two seasons and the 2010-2011 season through 35 games:

The big jumps in production this season have come in his scoring average, assists and three point percentage. I didn’t include it here but his Usage Rate has also jumped from 27.19 last season to 31.04 this year. Most of his other statistics have remained consistent but his turnovers have regressed slightly, somewhat understandable with the increase in his Usage Rate, as has his overall field goal percentage.

An increase in scoring with a decrease in field goal percentage is generally a sign of someone taking more shots but scoring less efficiently. However, the rise in his three point percentage complicates that question somewhat. Let’s delve into this a little deeper by looking at Rose’s Expected Scoring numbers. Below is a table showing Rose’s Expected Points, Actual Points and Point Differential for each area of the floor from the last two seasons and through the first 35 games of this season (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

By these numbers we see that Rose is actually scoring slightly less efficiently than he did last season. His point differential has increased slightly at the rim, on three pointers and on free throws but his declined everywhere else. This has led his overall point differential to drop from 0.82 to 0.53. This is obviously a small decline and he’s still in the positive range, but seems to run counter to the common perception that Rose has taken his offensive performance to another level this season.

Rose’s point differential at the rim has declined but this is actually a function of his shot attempts. His field goal percentage on shots at the rim has been below the league average in each of his three seasons, so by decreasing his shot attempts there he’s actually raised his point differential.

The mid and long-range jumpshot is generally one of the most inefficient shots in the game. For Rose it’s actually been quite a potent weapon the past few seasons. Last season he scored 0.99 more points per 40 than expected on jumpers from 10-23ft. This season he’s scoring 0.13 less points per 40 than expected on shots from the same areas. That’s a decrease of 1.12 points in an area where his ability to score efficiently made him very unique.

A knock on Rose’s game in his first two seasons was his inconsistency on three pointers. This season Rose has seen his three point percentage rise by nearly 8 percentage points and he’s averaging 4.6 attempts per 40 minutes compared to just 0.8 last season. This has brought his point differential on three pointers from a -0.26 to 0.43, a swing of 0.69 points.

Looking at these numbers we see a slight drop in his scoring efficiency this season, but not nearly as large as is implied by the drop in his field goal percentage and the increase in his shot attempts. By increasing his efficiency and frequency with three pointers he’s been able to compensate for the slight drop in his efficiency on mid-range jumpers. This can be seen when we look at his eFG% which is 49.7%, just slightly better than last season’s 49.5%. The scary thing is that he’s in just his third season and has already shown the capability to be an above average scorer from almost every area of the floor. It seems reasonable to expect to see continued growth in his offensive skill set. As that happens he could become a nearly unguardable offensive threat.

One other interesting thing is that this may be one of the rare cases where a team is better off with its star scoring less efficiently. Having the three point shot in his arsenal creates much better spacing for his teammates and allows him driving angles with defenders forcing to close out more aggressively on him. This has helped his playmaking and assist numbers terrificly. Assists are factored into a player’s Individual Offensive Rating and ,despite scoring slightly less efficiently, Rose’s ORtg. has gone from a 106 last season to a 110 this season. This has carried over to his team which has brought last year’s ORtg. of 103.5 to a 105.9 this season.

I am not prepared to offer an opinion on whether he deserves to win the MVP award, but from what I’ve seen so far this season he certainly belongs in the discussion. He’s using more possessions and taking more shots. Despite not producing quite as much as he could with those extra opportunities the diversity Rose has added to his game has made the Bulls much better at the offensive end. What more can a team ask for from it’s star player?

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Expected Scoring – Dwight Howard

We’re moving through the regular season and continuing with our Expected Scoring player profiles. Today we’ll be looking at the Orlando Magic’s Dwight Howard.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

In his time in the NBA Dwight Howard has established himself as a dominating rebounder and shot-blocker. He’s been the NBA’s Defensive Player of the Year the last two seasons and has led the league in rebounds per game in each of the last three seasons. Despite all the individual success for Howard the chink in his armor continues to be his offensive game. More than 54% of his shot attempts have come at the rim in each of the last three seasons. While this would appear to be a strength, the majority of those shots are coming in transition, off cuts, or finishing offensive rebounds. Howard’s inability to consistently create quality shots (and make them) in the post has limited his effectiveness in the playoffs. When this imbalance has been exposed in the postseason teams have been able to slow down the Magic’s perimeter game.

At first glance his statistics for this season would leave you with the impression that little has changed. Here are his traditional stats (per 40 minutes) from his last three seasons and the 2010-2011 season through 7 games:

Howard’s minutes are down slightly, although this is probably due to some combination of a slight increase in fouls and the number of blowout wins Orlando has had so far. His rebounds blocks, steals, turnovers and assists are all relatively flat. The one major difference is a 7 point increase in his per 40 minutes scoring average. Since his FG% and FT% are down slightly the easy answer would seem to be that he is just taking more shots. But is that really the case?

Below is a table showing Howard’s Expected Points, Actual Points and Point Differential for each area of the floor from the last four seasons and through the first 6 games of this season (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

To begin with Howard is attempting a lot more shots and free throws per 40 minutes than he did last season. Last season he averaged 11.7 FGA/40 and 11.5 FTA/40. This season he is averaging 17.1 FGA/40 and 15.6 FTA/40. A surprising thing is that despite a rather large drop in his FG% his Point Differential is just about even. The reason is that he has changed his shot distribution quite a bit. This is reflected in the big jump in his Overall Expected Points.

This season Howard is averaging only 5.3 FGA/40 at the rim, his lowest total in four seasons. Accompanying this decrease, is an increase in shot attempts from other areas. Howard is averaging 7.9 FGA/40 on shots less than 10ft., nearly twice as many as last season. He’s also averaging 2.4 FGA/40 on shots from 10-15ft. which is nearly 5 times as many as last season, and 1.3 FGA/40 on shots from 16-23ft. which is over 6 times as many as last season.

Howard is not just attempting more shots from those areas, he’s also making them at a career high clip. On shots from less than 10ft. Howard is shooting 55.8%, compared to a previous career high of 44.8%. On shots from 10-15ft. Howard is shooting 46.2%, compared to a previous career high of 37.8%. On 16-23ft. jumpers he’s shooting 29.0% down from last year’s 38.0%. However, that percentage comes from making 2 of 7 from that distance this season. He only went of 5 of 13 from that distance all of last year. Clearly he is more confident and comfortable shooting from that range even if he isn’t seeing the results yet.

The last factor that’s important to note is that the percentage of his shots which has been assisted on is down in all three areas closer than 15ft. On shots closer than 10ft. this would seem to indicate that more of his shots are coming on isolations and post-ups, rather then just finishing off cuts and on the pick and roll, a good sign for his offensive growth. The fact that his assist percentage is down on 10-15ft. jumpers may indicate he is a little too eager to show off his new range and taking some contested shots. His FG% may even improve from this area as he becomes more patient, waiting for open jumpers created by his teammates.

Circling back to Expected Points, if Howard is shooting a career high from several areas and still finishing strong at the rim, why is his overall FG% down so far, and why is his overall Point Differential not higher? The answer to his FG% is in his shot distribution. Howard is taking less shots at the rim, where he shoots over 70%, and more mid-range shots, where his shooting is much improved and above average, but not nearly as good as at the rim. A short-sighted fan may look at this decrease in FG% as a negative for the Magic. Anyone with a long-term view should recognize that having Howard be an efficient scorer from multiple spots on the floor will help the Magic in the playoffs, both with individual matchups and creating better spacing and flow for the team’s entire offense.

As far as his Point Differential not reflecting his increased efficiency from the field, we need to look at Howard’s free throw shooting. Howard’s Point Differential is a combined +3.96 on all shots 15ft. and in. This is a great improvement over last year’s +2.12. However, this increase is offset by a 1.61 decline in his Point Differential at the free throw line, down to a career low -3.54. He could pick up an extra 3.54 points per 40 by raising his FT% to the league average of 75.9%. This is extremely unlikely, but what if he just raised it to to last year’s level? Keeping all other things the same, if Howard could raise his FT% to last year’s 59.2% his Point Differential on free throws would rise to a -2.64 and his overall Point Differential would climb to a +0.86, nearly 4 times his career high.

Free throw shooting and the ability to score outside the paint are the two factors which have kept Dwight Howard from scoring at an above expected rate over the course of his career. So far this season he appears to have solved his mid-range scoring issues in a big way. Whether it’s confidence, subtle changes to his shooting form, or moves he picked up training with Hakeem Olajuwon this summer, Howard has posted career scoring numbers over the first seven games from outside the paint. Free throws are a still a problem and likely will continue to be a problem. However, if he can return to his career averages at the line he will be reaching a new plateau of personal overall scoring efficiency. If I was anyone else in the Eastern Conference I’d sure be hoping this was just an abberation!

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Expected Scoring – Glen Davis

We’re moving into the regular season and continuing with our Expected Scoring player profiles. Today we’ll be looking at the Boston Celtics’ Glen Davis.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Over the past three seasons Glen Davis has emerged as a valuable bench contributor for the Boston Celtics. With some very distinct limitations to his skill set and capabilities, Davis has found his niche, providing energy, defense and spot scoring for the C’s. He’s chipped in a few big plays down the stretch in playoff games and has certainly earned his place in Boston’s rotation. The Celtics believed in his abilities to contribute enough that they let equally promising young big man, Leon Powe, leave  before last season (Powe did have a fairly significant injury history).

Even with the increased front-court depth from the additions of Shaq and Jermaine O’Neal, Davis has stepped up his production and has been one of the most consistent and effective offensive threats through three games for the Celtics. Here are his traditional stats (per 40 minutes) from his last three seasons and the 2010-2011 season through 3 games:

Davis’ rebounding, assist and individual defensive numbers have fallen slightly. However, he has been playing solid team defense, as the Celtics’ Defensive Rating is 11.27 points better with Davis on the floor. In addition, he is scoring the ball at a career rate, on career high percentages, all while not turning the ball over once in 86 minutes.

Let’s now break down his scoring efficiency in a little more depth. Below is a table showing Davis’ Expected Points, Actual Points and Point Differential for each area of the floor from the last two seasons and through the first 3 games of this season (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

One of the most obvious differences so far this season has been Davis’ efficiency inside of 10ft. He has never scored at an above expected rate at the rim, but so far this season is scoring 2.95 more points per 40 than expected from that area. Altogether, he has posted a +4.78 Point Differential on shots inside of 10ft.

An interesting paradox in relation to those numbers is his Free Throw Rate and his Blocked Shot Rate. His Blocked Shot Rate (the percentage of his shots which are blocked) has fallen from 17.9% last season, one of the highest in the league, to only10% this season. One would expect this to correlate with an increase in his Free Throw Rate; if his shot isn’t being blocked he is likely drawing and finishing through contact. However, his Free Throw Rate has also fallen from 0.49 to only 0.13 this season.

Looking at his Blocked Shot Rate and Free Throw Rate leads me to believe that he is ending up with a high number of wide open layups, either off offensive rebounds, in transition, or off well executed cuts in the half-court set. Wide open shots like these may not be as freely available throughout the season, would could lead to a decline in his scoring rate at the rim. That being said, he is taking more shots at the rim than he ever has and making them at a much better rate than he ever has. He certainly deserves some credit for making the most of his opportunities with the ball in the paint.

Another area where Davis has seen some significant improvement is on his 16-23ft. jumpshots. Knocking down open mid and long range jumpers was always a piece of his offensive role, but this year he is taking and making more of them than he ever has. Three games is an extremely small sample size and it’s entirely possible that his shooting will tail off, but this is an area where I am more apt to attribute improvement to skill development as opposed to luck.

All together Glen Davis has posted a per 40 minute Point Differential of +5.08 through three games. This represents an astonishing improvement, as last year’s was a -2.25. As Boston’s roster has turned over, Davis has become one of the more senior guys in the team. I’m of course referring to seasons in Boston as opposed to age or NBA experience. This appears to have had a strong positive impact on his confidence. He appears to have developed his offensive skill somewhat and has obviously worked hard to get himself into game shape. Davis’ offensive efficiency will almost certainly flatten out, but everything seems lined up for him to be a positive contributor in terms of offensive efficiency for the first time in his career.

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Expected Scoring – Carl Landry

We’re moving into the regular season and continuing with our Expected Scoring player profiles. Today we’ll be looking at the Sacramento Kings’ Carl Landry.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Landry was a 2nd round gem, discovered by the front office of the Houston Rockets. Despite lacking ideal size for the power forward position, Landry showed himself to be a highly effective scorer and rebounder, using his bruising strength and surprisingly soft touch to beat up on opposing front-lines. After two and a half seasons in Houston, the Rockets sent him to Sacramento as part of the multi-team trade which helped them acquire Kevin Martin. 

Landry arrived in Sacramento with the promise of more minutes and touches, hoping to fill their rather large post scoring void. It took a little while to adjust in Sacramento, but he finished the season strong. Over this summer the Kings acquired Samuel Dalembert from Philadelphia and drafted DeMarcus Cousins from the University of Kentucky. Pairing these two with Landry and Jason Thompson starts to make the Kings frontcourt look a little crowded. That being said Landry has been playing 32.3 minutes per game so far this season and has been earning every minute of playing time with his production on the floor. 

Here are his traditional stats (per 40 minutes) from his last two seasons (2010 was split between Sacramento and Houston) and the 2010-2011 season through 3 games:

With the Kings’ additional big men, Landry has been playing less with his back to the basket and pushing out as more of a face up power forward this season. This clearly shows in his rebounding, assist and turnover numbers. However, he is still scoring at a strong rate with a terrific FG%.

Let’s now break down his scoring efficiency in a little more depth. Below is a table showing Landry’s Expected Points, Actual Points and Point Differential for each area of the floor from the last two seasons and through the first 3 games of this season (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

The first thing that jumps out is what a terrific finisher Landry is at the rim. He has scored at least 1 point per 40 minutes more than expected on shots at the rim in the last two seasons, and the pattern has continued so far this season. The other thing worth noting is how Landry’s point differential on mid and long-range jumpshots has increased steadily since the beginning of 2010 in Houston. Through three games Landry is averaging 2.56 more points per 40 than expected on jumpshots from 10-23ft. While the high rate at which he is making these shots will likely level out of the course of the season, the steady improvement over the last year is cause for optimism.

As exciting as the increase in his jumpshooting has been, the steady decline in his Point Differential on free throws is just as troubling. He certainly has the potential to be better, as he was a consistent 80% free throw shooter in Houston. Figuring out his issues there can really help him maximize his scoring efficiency potential.

Landry has consistently been an efficient scorer, posting a Point Differential of nearly 2.0 for each of his full or part seasons in Houston. Through three games this season his overall Point Differential is a terrific 2.64. However, I worry that his early success with his jumpshot this season may be reinforcing some bad habits.

His jumpshooting efficiency will likely level off this season, but his ability as an above average scorer at the rim should remain at it’s very high level. The problem is that he’s progressively moving away from the rim and taking a far higher percentage of his shots away from the basket. Landry never averaged more than 2.8 FGA/40 on 16-23ft. jumpshots in Houston. During his time in Sacramento last season he averaged 5.1 FGA/40 on 16-23ft. jumpshots, and this season he is averaging an astonishing 8.2 FGA/40 from that distance. Landry averaged roughly 7.2 FGA/40 at the rim in Houston, so far this season that number is down to 4.5. In addition, his free throw rate has fallen from 0.46 during his last full season in Houston to 0.26 so far this season.

It is terrific to see a young player develop and I applaud Landry for finding a way to be efficient in diversifying his offensive game. That being said, I hope he doesn’t lose sight of what earned him a roster spot and significant minutes in the first place, his ability to score tough points in the paint. With Cousins, Dalembert and Thompson, the Kings may not need his post scoring in the same way they did in the past. However, I would hope the Kings’ coaching staff will work to instill in Landry an honest assessment of his abilities. When the inevitable shooting slump comes, I hope they can provide the right feedback and create opportunities for him to get back into the paint.

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Expected Scoring – Hedo Turkoglu

We are continuing with our preseason Expected Scoring player profiles. Today we’ll be looking at the Phoenix Suns’ Hedo Turkoglu.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Turkoglu’s career has been in a free-fall since he and the Orlando Magic lost in the 2009 Finals to the Los Angeles Lakers. That summer Turkoglu left as a free agent for Toronto. He never fit in the offense, struggled with injuries, and left the team, the fans and himself eager to part ways. This summer Turkoglu was traded and became a member of the Phoenix Suns.

Joining the Suns was going to require some adjustment on Turkoglu’s part. In Orlando, Turkoglu frequently filled the role of primary ball-handler, spending a lot of time creating shots for himself and his teammates in the pick and roll. In Toronto, he was asked to spend more time playing off the ball and struggled. The situation seems like it will only be exacerbated in Phoenix with Steve Nash and Goran Dragic playing point guard. Each side was optimistic after the trade, but things do not look rosy after Turkoglu’s performance in the preseason. Here are his traditional stats (per 40 minutes) from his last season in Orlando, his one season in Toronto, and the 2010-2011 preseason:

There are a few positives here. Turkoglu will likely spend a lot of time at power forward for Phoenix, and he seems to have embraced this to some extent, rebounding at a career high rate. He also has shown some defensive effort in the preseason, blocking shots and stealing the ball at rate much higher than his career average.

That being said, Turkoglu’s shooting numbers have been atrocious. With FG and 3PT percentages hovering around 30%, Turkoglu is clearly not meeting expectations in Phoenix. He is being asked to contribute primarily as a scorer and shooter as opposed, to creator and he has struggled mightily.

Let’s now break down his scoring efficiency, or lack there of, in a little more depth. Below is a table showing Turkoglu’s Expected Points, Actual Points and Point Differential for each area of the floor from the last three seasons and through this preseason (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

Turkoglu is actually scoring at an above expected rate at the rim in the preseason with Phoenix. This is about the only bright spot so far in his time with the Suns. The shots that are going to be most available to Turkoglu in Phoenix are jumpshots and in the preseason he was absolutely miserable shooting jumpers. On all shots from 10ft. and out, Turkoglu is scoring 3.81 less points per 40 than expected. Even with his above average scoring at the rim and on free throws, he still scored 2.72 less points per 40 than expected.

Another piece of bad news for the Suns is that his terrible scoring efficiency numbers in the preseason don’t seem that out of character for him. In only one of his last four seasons has he posted a positive overall Point Differential. He shoots a lot 3PTs, and generally scores at an above expected rate but not by a large margin. Over the last four seasons he has never posted a positive point differential on 16-23ft. jumpers.

Chances are his scoring efficiency will even out over the course of the season. His Point Differential on 3PTs will likely be close to zero or a slight positive. However, his Point Differential on shots close to the basket will likely drop and also end up being closer to zero. The fact remains that it is difficult to imagine him providing efficient scoring overall.

It seems the Suns looked at his skill set, and thought they could reduce some parts (ball handling, shot creation) while their system would increase his efficiency in others (shooting, scoring). Thus far Turkoglu has shown nothing to indicate his ability to be successful in a complimentary role centered primarily around knocking down outside shots. The good news for the Suns is that they have plenty of roster flexibility, and several other players who can step in and fill those minutes effectively. The bad news is that Turkoglu is under contract for another four seasons, at a rough total of 45 million. It behooves both sides to continue to try to make the best of this situation, but come February the Suns might need to be looking for a trade partner to take on Turkoglu.

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Filed under Expected Scoring Player Profiles, NBA, Phoenix Suns, Statistical Analysis

Expected Scoring – Michael Beasley

We are continuing with our preseason Expected Scoring player profiles. Today we’ll be looking at the Minnesota Timberwolves’ Michael Beasley. I ended up looking at Beasley after reading an excellent post about his potential at Canis Hoopus: Beasley Needs To Be A 10-10-10 Player. I’m also working on a post for later today looking at the 10-10-10 idea in a little more depth.

If you’ve missed my other posts on the subject, Expected Points uses a player’s FGA from each area of the floor and multiplies it by the average number of points scored on that type of shot to come up with an Expected Point total from that area. The Expected Point total can than be compared to the actual number of points a player scored from that area to arrive at a Point Differential. This point differential is an expression of how a player shot compared to the league average, but I like that the comparison is drawn with actual point totals.  The average values of shots by location that I use (At Rim – 1.208, <10ft. – 0.856, 10-15ft. – 0.783, 16-23ft. – 0.801, 3PT – 1.081, FT – 0.759) were calculated by Albert Lyu of ThinkBlueCrew.

Beasley’s story is well known. He was one of the most dominant college players in recent memory. He entered the NBA with a mix of power forward and small forward attributes and a reputation for being immature and unfocused on and off the court. This reputation was reinforced with several drug related incidents, a stint in rehab last summer, and disappointing production on the court. Beasley was traded to Minnesota this summer as part of Miami’s cap clearing efforts. David Kahn and the Timberwolves were hoping that a change of scenery and a new system could put his considerable offensive talents to better use. Let’s take a look at what the Timberwolves got and might expect to get from Beasley this season. Here are his traditional stats (per 40 minutes) from his two seasons in Miami and the 2010-2011 preseason thus far (6 games):

His first two seasons in Miami were fairly similar statistically. He saw a drop off in his scoring, likely connected to the 13 point drop in his 3PT%. Other than that there was not much progression or regression in his stats. With Minnesota, Beasley has seen a fairly large increase in his scoring output. However, his FG% and FT% have both dropped by nearly 4 points, so the scoring increase comes mostly from the fact that he is averaging 21.6 FGA/40 as opposed to 17.9 FGA/40 last season in Miami. His rebounding numbers have fallen off and his turnovers have jumped to a ludicrous level. Some of this may come from the fact that he is playing a lot more small forward than he did in Miami, as well as learning a new offensive system, the notoriously complex triangle offense.

Let’s now break down his scoring efficiency, or lack there of, in a little more depth. Below is a table showing Beasley’s Expected Points, Actual Points and Point Differential for each area of the floor from the last two seasons and through the first 6 games of this preseason (all numbers are per 40 minutes). If you prefer a spreadsheet to the embedded table photo, here is the link.

As with his first two seasons in the league, what Beasley has provided thus far has been somewhat of a mixed bag. Beasley has shown a steady increase in his efficiency at the rim, going from scoring 0.52 points less than expected per 40 minutes as a rookie, to scoring 0.60 points more than expected per 40 minutes in Minnesota. His 3PT shooting his rebounded after last year’s disaster to a respectable level, moving him back to a positive Point Differential from that area.

Despite those positives Beasley has continued to shoot himself in the foot with his horrible efficiency in the mid-range game. Beasley is scoring slightly above expected on shots from 10-15ft. but is scoring WAY below expected on shots <10ft. and 16-23ft., with a negative differential of over 1.00 points per 40 from each area. Combined, he is scoring 1.77 points per 40 less than expected on all shots that aren’t taken at the rim or from behind the three-point line. Last season his Point Differentials from those three areas were each negative and combined to have him score 0.61 points per 40 less than expected on those shots.

The most frustrating thing is his seeming lack of awareness of this weakness in his game. Last season 61% of his shots came from those three areas combined (<10ft, 10-15ft., 16-23ft.) on which he scored 0.61 points per 40 less than expected. Thus far in the preseason he is taking 66% of his shots from those three areas and scoring 1.77 points per 40 less than expected. It’s not that Beasley isn’t capable of being a consistent jumpshooter, he shot 46% on 16-23ft. jumpers as a rookie. The problem is that he is far to willing to settle for these shots and teams are happy to let him, contesting the shot on the way up.

Beasley’s XPts at the rim have gone down in each of his first two seasons, and have continued their downward trend thus far in the preseason. The inverse has happened with his XPts on 3PTs. This means Beasley has fallen into a pattern of taking less shots at the rim and moving them out beyond the 3PT arc. Again, Beasley is a capable 3PT shooter, but his prowess from distance is nothing compared to what he can do close to the basket.

As Beasley enters his 3rd season in the NBA, obscurity and irrelevance threaten to envelop him, likely for the first time in his life. In my humble opinion, the solution is a drastic adjustment in his shot selection. Begin each game attacking the rim. Develop a reputation for attacking the rim. The contested jumpers will still be there when the shot clock is running down. Beasley does not and should not bear sole responsibility for making this change. It is incumbent upon the Minnesota coaching staff to help him make this change with coaching, cajoling and adjustments to their offensive schemes. Beasley can be a tremendous asset for the Timberwolves, but only if they can work with him to maximize his talents for their benefit.

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Filed under Expected Scoring Player Profiles, Minnesota Timberwolves, NBA, Statistical Analysis