Salt City Hoops » Analytics http://saltcityhoops.com The ESPN TrueHoop Utah Jazz Site Tue, 16 Sep 2014 23:12:43 +0000 en-US hourly 1 http://wordpress.org/?v=4.0 The ESPN TrueHoop Utah Jazz Site Salt City Hoops no The ESPN TrueHoop Utah Jazz Site Salt City Hoops » Analytics http://saltcityhoops.com/wp-content/plugins/powerpress/rss_default.jpg http://saltcityhoops.com/category/analytics/ Pump the Clutch: Utah’s Late-Game Issues http://saltcityhoops.com/pump-the-clutch-utahs-late-game-issues/ http://saltcityhoops.com/pump-the-clutch-utahs-late-game-issues/#comments Mon, 08 Sep 2014 18:09:32 +0000 http://saltcityhoops.com/?p=12763 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Photo by Melissa Majchrzak/NBAE via Getty Images

Photo by Melissa Majchrzak/NBAE via Getty Images

August has come and gone, and there is much rejoicing. Never mind the nearly two months to go until regular season basketball played – September offers light at the end of the tunnel. FIBA competition, training camp before the month is out; I’m in game mode, and don’t try and tell me differently.

When the Jazz do eventually take the court, they’ll have plenty to work on. A group that was behind in a number of areas last season will also be adjusting to a new coaching staff, and while the long term picture here shows great promise, it’s a big change nonetheless for a young roster getting even younger. The defensive side of the ball in general will of course be a targeted area following a league-worst efficiency figure in 2013-14, and Utah will hope Quin Snyder and his staff can stabilize an unbalanced defensive culture. There were issues everywhere, but one that stands out upon further review is opponents’ performance near the end of close games.

Already sieve-like defensively, the Jazz were even more porous during the “clutch” portions of games. Their per-100-possessions figure for the year was 109.1, narrowly below Milwaukee for 30th in the league. But in the final five minutes of games with the Jazz trailing or leading by five points or fewer, they plummeted even further to 124.0 points allowed per-100, per NBA.com. This was just a hair more stingy than the league-worst Minnesota Timberwolves (124.3), of dubious infamy for their frequent late-game meltdowns. Utah was solid to begin the year in this area before spiraling out of control:

And a look at an individual breakdown of the seven roster members playing somewhat regular minutes in the clutch:

The numbers are anything but encouraging across the board, both on a team and individual level. Much has already been said and written regarding the general defensive ineptitude often present in Utah last season – what elements of “crunch time” affected the Jazz to an even greater extent?

To be sure, there are several factors here working against Utah that are mostly or completely out of their control. For starters, a mandatory caveat about sample size applies, although 146 total clutch minutes is certainly enough to draw basic conclusions from. It’s also important to remember that the exact thresholds we’re using are somewhat arbitrary, and could vary, perhaps greatly, using different minutes or scoring benchmarks for many teams. That said, the Jazz ranked at or near the bottom of the league in nearly all similar iterations, and the numbers clearly support a team that was markedly worse defensively during these periods.

Other explanations involve uncontrollable elements that Utah will nonetheless expect to improve in future years. The relative youth and inexperience of the majority of the roster surely played a role in their late-game issues, and the team’s key players should develop more poise as they become more familiar with crunch time scenarios. It’s also fair to note that opponents will almost always have their best players on the floor during these periods, a not-insignificant fact that likely skews the numbers to a degree. But the Jazz should also have their best players on the court, and as they begin hitting their athletic primes they’ll be expected to go blow-for-blow with the best the league has to offer.

More tangible and controllable explanations were similarly varied. The above player chart listed turnovers-per-48 in the final column; Burke, Burks and Williams all showed notable per-minute increases in their turnovers during clutch periods, and a team turnover ratio (turnovers per-100-possessions) that was roughly middle of the pack for the year became the second-worst in the league during crunch time behind only Sacramento. This isn’t a defensive stat, of course, but it has a direct effect on that end of the court; turnovers mean extra defensive possessions, and live-ball turnovers in particular can create advantageous situations for opponents. The Jazz also allowed a league-high 42.2 percent from beyond the arc, with a sizeable gap of nearly four percent between them and next-worst Minnesota.

The Jazz also sent their opponents to the line at an advanced rate in the clutch. Utah allowed 48.7 attempts at the stripe per-48, over double a 23.6 figure for the entire season. This isn’t quite as insane a jump as it may seem on the surface; intentional fouls at the end of games skew this average across the league, and the Jazz aren’t the only team who saw a huge increase. But they allowed the third-highest total during clutch minutes, well up from a middle-of-the-pack overall finish. And to compound the issue, they were fouling excellent free-throw shooters – opponents sank a higher percentage of clutch freebies than any other team in the league. As with the overall picture, Kanter is likely the worst offender here, committing 10.4 personal fouls per-48 in the clutch, double his normal figure. Favors was also more jumpy than usual, fouling 7.6 times per-48, a near-150-percent increase.

A look through the game action itself doesn’t reveal a whole lot that hasn’t already been dissected as far as the Jazz defense last season, but the issues were even more prevalent and frequent. The team struggled badly to form a unified identity, acting too often as individual pieces and lacking the sort of trust necessary to work as a unit. There was certainly a noticeable uptick in effort level, one small silver lining going forward, but it was mostly badly directed, as evidenced by certain elements above like foul rate.

Inexperience showed through, and perhaps most worrying of any element within this piece is the way this seemed to intensify as the year went on rather than the other way around. The hope going forward is that this reflects on the outgoing coaching staff more than the players themselves. This isn’t unrealistic, and Utah showed real promise on the other side of the ball during these clutch periods as well – they increased their offensive rating to 114.2, the seventh-best mark in the league (best of non-playoff teams) and nearly a 14-point boost on their overall mark. Hayward and Burke were especially effective offensive weapons, each drastically upping their efficiency in the clutch, and Favors wasn’t far behind.

The foundation is there for a core that can get buckets when it counts, and more experience together along with a more focused defensive scheme could eventually see them become a formidable overall unit down the stretch in close games. The turnaround defensively has to start this year; another stalled campaign on this front will be cause for concern regardless of surrounding circumstance. But expect it to be a point of emphasis, along with all things defense, as the new season begins to take shape.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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The NBA’s Goaltending Leaders http://saltcityhoops.com/the-nbas-goaltending-leaders/ http://saltcityhoops.com/the-nbas-goaltending-leaders/#comments Tue, 19 Aug 2014 05:43:16 +0000 http://saltcityhoops.com/?p=12584 Author information
Andy Larsen
Andy Larsen
Andy Larsen is the Managing Editor of Salt City Hoops, the ESPN TrueHoop affiliate for the Utah Jazz. He also hosts a radio show and podcast every week on ESPN700 AM in Salt Lake City.
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Serge Ibaka blocks Matt Barnes' layup during this season's NBA playoffs. But how often does he goaltend?

Serge Ibaka goes for the block on Tony Parker’s shot during this year’s NBA playoffs. But how often does Ibaka goaltend? (Photo by Chris Covatta/Getty Images)

Goaltending is awesome.

Basketball players have an unfortunate choice: they can sky above the rim and forcefully reject a shot in a direction of their choosing, or they can meekly hope a shot misses so they may gather the rebound. The former is a remarkable feat limited to only the most athletic and genetically gifted of humans, an artistic feat of animal expression. The latter is a game delay while gravity takes its course. Unfortunately, the rules have chosen to punish goaltending. Lame.

But which players are the most likely to break the goaltending rules? To find out, I used a play-by-play database of the 2013-14 NBA season, acquired using APBRForums’ user kpascual’s NBAscrape Python tool. Essentially, this tool goes to the play-by-play section of every NBA game on NBA.com, and saves the contents to a database to use for whatever kind of basketball analysis you want, including a lot of stuff that wouldn’t be available in the box score. Today, we’re looking at goaltends, because they’re awesome.

In the 2013-14 NBA season, 758 offensive and defensive goaltends took place, or an average of 0.616 goaltends per NBA game. Below is the list of all of the NBA players with more than 10.

Total Goaltend Leaders, 2013-14 season.

Total Goaltending Leaders, 2013-14 season.

We have a tie! Serge Ibaka and Andre Drummond are co-champions of the goaltend, going above and slightly-too-far beyond to protect their team’s rim. While they were often caught, both players had big moments last season during missed goaltending calls. Ibaka had several high-profile goaltends-turned-blocks in the NBA Playoffs (including this one), while Drummond somehow escaped being punished for this:

Both Plumlee brothers finish amongst the top group, and Jazzman Derrick Favors barely makes the list. What about offensive goaltending alone?

2013-14 Offensive Goaltending leaders

2013-14 Offensive Goaltending Leaders

Drummond and Ibaka again top this list, showing that goaltending violations are probably reflective of eagerness, rather than an innate desire to protect the rim. Here’s the list of defensive goaltending leaders:

2013-14 Defensive Goaltending leaders.

2013-14 Defensive Goaltending leaders

At the top: Ibaka and Drummond, but Dwight Howard also goaltends on D quite frequently too. Since this is a Utah Jazz site, I’ll include all of the Utah Jazz’s goaltends last season:

2013-14 Utah Jazz Goaltending

2013-14 Utah Jazz Goaltending

Sadly, the Jazz didn’t go for the style points while losing, goaltending just 23 times last season, an average of only .28 goaltends per game.

If you’d like to look up your favorite team or player’s goaltending data, don’t fret. The whole 2013-14 season of goaltending data is available for download here on Salt City Hoops.

Author information

Andy Larsen
Andy Larsen
Andy Larsen is the Managing Editor of Salt City Hoops, the ESPN TrueHoop affiliate for the Utah Jazz. He also hosts a radio show and podcast every week on ESPN700 AM in Salt Lake City.
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TeamSPACE and the Jazz’s “Core Five” http://saltcityhoops.com/teamspace-and-the-jazzs-core-five/ http://saltcityhoops.com/teamspace-and-the-jazzs-core-five/#comments Fri, 15 Aug 2014 19:07:09 +0000 http://saltcityhoops.com/?p=12559 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Earlier in the week, I spent some time breaking down last year’s Jazz starting (and most-used) lineup using shooting data expertly compiled by Matt D’Anna of Nylon Calculus – how the five-man unit as a whole as well as individuals within it functioned in terms of their shot selection, frequency, and effectiveness. Continuing the nerd-out today, we’ll turn an eye toward the future pieces within the franchise. How did Utah’s “Core Five” lineup stack up from Matt’s TeamSPACE perspective last year? The lineup played 122 minutes together over 24 different games, per NBA.com, so they don’t have as large a sample to draw on as the starters from last year, but such a sample is still easily large enough (214 FGA) to draw conclusions from. Here’s the chart:

Jazz1314core5

The TeamSPACE chart for Burke/Burks/Hayward/Favors/Kanter.

And just for the purposes of convenient contrasting, here’s the chart I used earlier in the week for last year’s starters:

Jazz most-used lineup: Burke/Hayward/Jefferson/Williams/Favors in 13-14

Jazz most-used lineup: Burke/Hayward/Jefferson/Williams/Favors in 13-14

The Not-So-Good:

We’ll begin with the areas that still need work this time around, in part to mix things up and in part because, despite a still-flawed chart for the core youngsters, I think there are a few more areas of promise to highlight here. These are mostly individual areas, though – on the team level, it’s likely this chart showcases even less overall direction and efficiency than that of the starters. Smaller, somewhat isolated splotches are even more frequent, particularly those in the longer midrange areas.

The “in-between” areas, between at-the-hoop looks and midrange, are far too populated with clusters. These shots aren’t necessarily bad from time to time, but in larger groups generally tend to indicate either frequently rebuffed driving attempts or rushed shots after rebounds and at the end of the shot clock. Perhaps worst of all, though, is the way their activity from beyond the arc was so staggered and inconsistent – the group certainly has work to do in terms of spreading the floor and finding the areas that will best stretch defenses. Of nine Utah lineups with over 100 total minutes last year, this one shot the second-fewest three-point attempts and had the fewest makes.

Of course, much of this is entirely understandable. This unit had no members over the age of 24, had never played together before Trey Burke’s debut, and certainly wasn’t helped much by Ty Corbin’s refusal to start or play them many sustained minutes throughout the year. It’s easy to see how that translates into a lack of in-depth understanding from each player of their individual role within the lineup, and it’s a big part of why there’s so much visible overlapping between guys. But there are positives to glean for multiple individuals within the chart (more below).

The Good:

After all the flack his shooting has taken from myself and basically the entire known basketball world these last few months, you bet Gordon Hayward gets the first mention here. His chart within the core five group last year, while still far from ideal given the role Utah wants to see him in long term, was a major improvement over the performance he put forth as part of the starting unit. Barely visible in much of the halfcourt with the starters despite his nominal “first option” title, Hayward’s red clusters appear in a far more prevalent way with the rest of the youngsters – and with better results, as well. Per nbawowy.com, Hayward had an Effective Field-Goal Percentage of 47.4 with the starters, a figure that skyrocketed to 55.3 when he played with the core unit. Gordon is far too spread out in an overall sense, but his increased activity with this lineup showcases a comfort level and sense of responsibility that will prove vital as the team works its way up to contender status. It’d be nice to see him move some of those longer midrange shots back beyond the arc, but of course spacing plays a big role here and often isn’t under his control.

Alec Burks also receives a mostly positive grade here, though like both Burke and Hayward his selection is somewhat all over the place. Burks did rank in the top third of guards for “In the Paint (Non-RA)” percentage, but a slightly sub-40-percent figure from there again has me wishing he’d eliminate some of those in-between looks. That said, he was likely the best of the three guards at somewhat clustering his locations. I’ve talked before about his off-the-bounce game being notably more effective when going to his right hand, and either defenses noticed also or Alec wasn’t doing a good enough job getting to those spots – larger clusters to his left side would likely be better served if they were going to his stronger hand. But overall, he seems to be grasping his role reasonably, loading up from distance and in close while hopefully limiting his midrange to more of a secondary option going forward.

I was surprised to see such little activity from Kanter, the de facto shooter at the big position within this lineup. In particular, the (shooter’s) left baseline is noticeably bare of jumpers from the big Turk, despite it being easily his most common and most effective jump-shooting area over the full season. Whether this speaks to positioning issues with Favors, opportunity issues given the three guards, or something else entirely, I’d expect Enes to make himself more known within these sort of lineups this season, particularly if his midrange game continues the solid upward trajectory it’s followed thus far in his career. But outside this, he’s doing what he should – sticking to shots in his office by the hoop, with a few selective splotches from midrange to complement it. Favors and Burke don’t show too many marked departures from their performances with the starting lineup, so many of the same talking points apply for them.

As a unit, while the entire picture likely isn’t as pretty as we might like, to my eye there’s plenty of promise. Hayward and Burks are clearly comfortable with their young peers, and both are reaching an age where shot selection refinement is a common addition to a player’s game. The group is almost insanely young, and a fairly large amount of improvement across the board, particularly from Burke as he enters his sophomore season, isn’t out of the question whatsoever. They’ll be a lock to well exceed their total minutes last year barring major injury, likely in more sustained periods where they can really nail down the chemistry aspect. And of course, all five have another year of experience under their belts, a heralded player development staff newly on board, and a new scheme within which to operate. Can’t wait to team back up with Matt and take a look at their progress as the season takes shape.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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TeamSPACE and the 13-14 Jazz, Part 1 http://saltcityhoops.com/teamspace-and-the-13-14-jazz-part-1/ http://saltcityhoops.com/teamspace-and-the-13-14-jazz-part-1/#comments Mon, 11 Aug 2014 19:08:38 +0000 http://saltcityhoops.com/?p=12485 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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The NBA may take the summer off, particularly the typically dead month of August, but nerdiness has no “season”, so neither do I. Last week I used this space to look at some contextualized elements of last season for the Jazz through the lens of SportVU tracking data, namely their shooting prowess (or lack thereof), passing and elements of rebounding. The week before, I used shot charts created by my Nylon Calculus colleague Austin Clemens to accentuate individual shooting and shot selection among vital Jazz pieces going forward.

In keeping with the theme of breaking down last season with a keen eye toward next, today I’ll be highlighting another remarkable project pioneered by a Nylon Calculus writer, Matt D’Anna. The data is affectionately referred to as TeamSPACE – an extrapolation of Austin’s excellent charts focused not on individuals, but rather on entire five-man units during their periods on the floor together over a given season. Before I say anything further, check out an example in the form of last year’s New York Knicks:

San Antonio Spurs 2013-14 TeamSPACE

New York Knicks 2013-14 TeamSPACE

Matt used the Knicks as part of his inaugural TeamSPACE introduction, where you can also find more detail on his methodology. In a nutshell, though, it’s easy enough to decipher; each player within a given lineup is marked with a color in the lower right corner, and said colors correspond to their shot clusters on the court. Again, these are shots taken only while this particular five-man unit shares the floor. One extra nugget is the presence of weighted values for made shots over missed ones – clusters are primarily based on volume of attempts from the given areas, but Matt included slightly heavier weights for makes as compared to misses, so a player who chucks away repeatedly from an area they never connect from will show a lighter cluster there, or even in extreme cases perhaps no cluster at all.

Today will be Part 1 of my investigation of Jazz shooting within lineups last season, where I’ll break down data from their most frequently-used lineup of Burke-Hayward-Jefferson-Williams-Favors. Let’s take a look at the chart:

Jazz most-used lineup: Burke/Hayward/Jefferson/Williams/Favors in 13-14

Jazz most-used lineup: Burke/Hayward/Jefferson/Williams/Favors in 13-14

The Good:

Part of what makes Matt’s work so interesting is that we can gauge both team and player context from the same visualization without sacrificing quality in either. Utah’s chart from last year is a prime example – within this lineup, Marvin Williams obviously stands out. Outside the Restricted Area (where all teams naturally clump up), he has the largest and most concentrated clusters of shots, particularly from beyond the 3-point arc. He has very few random blotches outside his preferred shooting areas, save for a few clusters from midrange that were frequently one-dribble step-ins after a close-out to the 3-point line from a defender. This type of clumping is almost always desirable, an indication that a player has identified his strongest areas and is taking steps to get to them regularly within the offense (more on this in a little).

Richard Jefferson was another positive through this lens, even more selective than Williams and rarely shooting from anywhere but beyond the arc or at the rim with this lineup. Derrick Favors also showed glimpses of range from the right block baseline up to free-throw line extended, but spread-out clusters here indicate that he hasn’t quite found a “sweet spot” or two to lean on, something he’ll need to work on if he wants to continue expanding his game away from the basket. And while I wish I could say more positive things about the guards’ showing here, the only major plus for Burke and Hayward was that the latter at least kept his chucking to some of the same general areas.

The Not-As-Good:

This shouldn’t surprise anyone by now, so I’ll just say it: This form of shot chart is just as ugly as any other metric we’ve attempted to analyze Jazz shooting with. I talked a couple paragraphs above about concentrated clustering being almost universally positive within this context, and Utah’s visualization displays nearly the exact opposite. Compare their chart above, for example, to last year’s NBA champion Spurs:

San Antonio Spurs 2013-14 TeamSPACE

San Antonio Spurs 2013-14 TeamSPACE

Obviously, comparing Utah’s performance to a legendary offense is foolish in a vacuum, but in this case it helps partially illustrate some of the issues they had shooting the ball and as an overall offense. Look at how much more spread out the Jazz were in their shot selection, and just how beautifully concentrated San Antonio’s individual clusters were within each player’s preferred zone. Kawhi Leonard, he of multi-talented Finals MVP-winning pedigree, was the only starter with even slightly varied clusters, and you might say he had an OK year last year – no one is complaining about his variety. And outside Leonard, it’s the embodiment of a team that knows their roles: Tony Parker and Tim Duncan handle the midrange, Danny Green bombs away from the wings and the corners, and Thiago Splitter cleans up and shoots almost exclusively near the hoop. There are slight exceptions likely born of player tendencies within the group, but this is a squad with pieces who know exactly what their roles are and remain constantly within them.

Contrast that with the Jazz and the picture is pretty ugly, especially as far as future pieces within last year’s starting lineup go. Favors, as I mentioned above, was valiant in attempting to extend his range, but he needs to take those little clumps and parlay them into larger ones in more concentrated areas. And though my readers must think I hate them after these last few weeks (I don’t), Burke and Hayward were very disappointing here, the former in particular. Trey’s clusters are littered all over the court, clumping heavily only near the basket. Hayward was a tad more selective, but still has splotches in several places and not even a sniff of one or two “go-to” areas.

As a team, these results are especially worrisome within a starting lineup designed by then-coach Ty Corbin specifically to improve Utah’s spacing after a dreadful shooting start. Some of it is certainly age, role and lack of experience – Williams and Jefferson are both veterans, and thus have had more time in the league to define their offensive games. But these factors aside, these are still professional basketball players, and both Burke and Hayward count basketball IQ as a positive element in their respective scouting reports. That neither was able to find any semblance of a niche for themselves even among improved spacing can’t be entirely overlooked, and should be one of new head coach Quin Snyder’s first priorities when instilling his system.

Like many elements of a disappointing year in 2013-14, there’s tons of context at play here. This is only a single lineup, albeit far and away Utah’s most-used, and they weren’t exactly playing within a solid offensive system. Also, while the young guards certainly need improvement, a refining of their offensive games is far from out of the question; Burke still has at least a two-year cushion before such a chart would incite truly ominous alarm bells, and the fact that “Hayward was outside his optimal role!” has been repeated ad nauseam doesn’t make it any less true. The NBA is fun in part because ugly situations can turn around so quickly, and despite several decidedly negative elements and their lingering stench, the Jazz have positioned themselves well to undergo just such a reversal should a couple chips fall their way.

Stay tuned later this week for Part 2 of my examination of last year’s Jazz using Matt D’Anna’s TeamSPACE visualization, when I’ll look at Utah’s “Core Five” lineup and forecast their prospects for the upcoming season both as individuals and as a unit.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Jazz 2013-14 SportVU Snapshot http://saltcityhoops.com/jazz-2013-14-sportvu-snapshot/ http://saltcityhoops.com/jazz-2013-14-sportvu-snapshot/#comments Fri, 01 Aug 2014 22:05:04 +0000 http://saltcityhoops.com/?p=12412 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Photo by Melissa Majchrzak/NBAE via Getty Images

Photo by Melissa Majchrzak/NBAE via Getty Images

As I mentioned in my piece last week, I’m lucky enough to count myself a writer for Nylon Calculus, the new analytics arm of Hardwood Paroxysm (under the Sports Illustrated/Fansided banner). Several of my colleagues are supremely gifted data scrapers and manipulators, and are doing simply remarkable things with extrapolations of publicly-available data.

One bit of scraping I’m eternally grateful for has been done by NC writer Darryl Blackport, with some assistance in compiling from Krishna Narsu. Most of you who read me regularly will remember my frequent references to SportVU player and team data available publicly on NBA.com, but they’re not the only bits of such information on the site. Perhaps slightly less well-known in last year’s public roll-out were Player Tracking Box Scores – game by game only, but with several bits of data that aren’t available within the season-long database, and several others that allow for extrapolation if laid out over the full season. And extrapolate Darryl did: he scraped every individual box score, compiling season-long statistics by both team and player that expound on the data already available. And while I obviously can’t share any full databases, I want to highlight a few bits and pieces I found relevant within a Jazz context, using both Darryl’s extrapolations and other bits of publicly-listed data. Keep in mind these are snapshots, not anything remotely comprehensive, but they still have some interesting implications.

Shooting:

The Jazz had a plethora of issues shooting the ball last season, a fact that’s easily attainable without any sort of advanced information. They spent time in the early parts of the year flirting with all-time levels of awfulness from the floor before smoothing things out to simply bad, finishing the year in the league’s bottom third for both effective field-goal percentage and true shooting percentage. SportVU box score data gives us some further insights: they track contested shots versus uncontested ones, one of the snippets of info that doesn’t appear on their publicly-housed yearlong stats. Now, the distance-only aspect of this differentiation means they need to be taken with grains of salt, particularly contested numbers – the closer to the hoop a shot is taken, the higher the chances become that said shot was “contested” under these guidelines given defenses’ proclivity for placing themselves in that area, up to the point where nearly every non-fast-break layup attempt (even those with no true challenge, essentially 90-95 percent shots for NBA players) will fall under the “contested” label.

That said, tracking the other end of the spectrum, or “uncontested” shots, can provide us with less noisy data. These shots can’t be convoluted by the possibility of non-challenges, because challenges simply aren’t possible with no defender within four feet. Accordingly, again excepting breakaway layups and dunks, such shots will trend heavily toward open jumpers, and therefore can be of some use.

As far as the Jazz went here last year, the picture wasn’t pretty. Utah ranked 29th in the NBA for uncontested field-goal percentage at just 40.7 percent, over 7 percent below Miami’s league-leading mark and mere tenths of a point above tanktastic Philadelphia. Again, these aren’t perfectly contextualized numbers, but they seem to match up decently with team success overall: 12 of the league’s 16 playoff teams were in the top half for uncontested percentage, meaning just four fell in the bottom 15, and vice versa. The top five teams for this category, in order, were Miami, San Antonio, Dallas, Oklahoma City and Phoenix, all of whom were in the top eight league-wide for per-possession offensive efficiency.

He’s been piled on unfairly by some in Jazzland recently, but unfortunately Trey Burke comes in as the worst offender here for Utah’s rotation players. He shot just 38.4 percent on 477 uncontested attempts – this was a top-40 attempt number for the entire league, and of these 40, only Josh Smith shot a worse percentage. Gordon Hayward was nearly as inefficient, posting the ninth-most uncontested attempts league-wide and converting at just over 40 percent, only three spots ahead of Burke among this same top 40 for attempts. Easily best among Jazz regulars was Enes Kanter at just over 46 percent, but the Jazz had only four players (Kanter, Gobert, Evans, and Jefferson) over the league average of almost exactly 43 percent. It speaks to an overall lack of jump-shooting prowess on the roster last season, and Utah will hope the additions of sharpshooters Steve Novak and Rodney Hood can boost things somewhat along with rejuvenated shooting years from Burke and Hayward, among others.

Passing:

One element that could be involved in some of the still-present traces of noise in the above numbers involves another we can snapshot, in this case assists and assists per opportunity. This isn’t exclusively a box score tracking stat, but SportVU tracks “assist opportunities”, or passes by a player followed by a field-goal attempt which, if made, would result in an assist for the passer. Inserting a simple formula, we can find each team’s assist-per-opportunity, which is really a measure of two things: how well a team shoots the ball after passes, and how good those passes are in the first place.

The Jazz ranked dead last for assists-per-opportunity last year, and also dead last in a similar category, assists per total passes. Though there were a few more exceptions than the uncontested shooting numbers above, the top of the lists for both these areas mostly included top-10 offenses and vice versa. Quantifying what portion of Utah’s showing here is shooting skill versus bad passing is impossible given the information available currently, but I unfortunately lean toward the former – passing accurately has much more room for error and is intuitively far less integral than shooting. Not to beat a dead horse, but the Jazz just weren’t good shooters last year from any viewpoint, and it’s even possible that their miserable early season showing was closer to reality than the slight improvement their overall offensive efficiency seemed to indicate later in the year.

Rebounding:

One area the Jazz stacked up well in was team rebounding, per SportVU’s rebound chance stats, defined as any time a player is within 3.5 feet of an available rebound. Utah ranked eighth for defensive rebounds per chance (62.6 percent) and ninth for offensive rebounds per chance (54.5 percent). The defensive number is of particular importance seeing as they gave up the second-fewest total misses in the league, and a failure to rebound at such a good rate would have sunk their already-league-worst defense to even further depths.

Within the roster, Hayward and Burke both get credit here – Hayward was the top rotation player for Utah, snagging 68 percent of his available boards, while Burke trailed just him and Diante Garrett, grabbing 62.5 percent. These elements can help compensate some for deficiencies in other areas, and the Jazz will surely be pleased at placing 13 roster members last season, including eight rotation players, over the league average of 57.8 percent.

Again, these are just a few small pieces in the massive jigsaw puzzle that is player tracking data and its potential extrapolations. Like absolutely everything in this league, they must be analyzed in proper context and through an unbiased lens to be of optimal use, and here’s hoping the amount of data available makes this process easier and more detail-rich in future years.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Focusing on FTr: Alec Burks and Trey Burke http://saltcityhoops.com/focusing-on-ftr-alec-burks-and-trey-burke/ http://saltcityhoops.com/focusing-on-ftr-alec-burks-and-trey-burke/#comments Tue, 29 Jul 2014 18:30:48 +0000 http://saltcityhoops.com/?p=12363 Author information
Laura Thompson
Laura Thompson
I grew up in California, but have been a Jazz fan pretty much since I was in diapers; I went to Karl Malone's basketball camp when I was 11 and I flew up to Utah in 1997 to go to Game 3 of the Finals. After graduating from BYU in 2008, I moved back to California to work in Marketing and have been doing that for the last five years. My favorite things in life are the Utah Jazz, basketball, food (whether cooking or consumption of), reading, church, black Labs, and the beach (though hopefully not in that order).
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Rocky Widner - NBAE via Getty Images

Rocky Widner – NBAE via Getty Images

I was looking at some stats for the team, and what stood out to me was the discrepancy between Trey Burke’s free-throw rate (.126) and Alec Burks’ (.449). Burks has a FTr better than 3.5x that of Burke’s. I don’t mean to harp on Burke entirely on this one, but I think noticing the discrepancy illustrates both what makes Alec Burks unique—and potentially elite in one area—and how improvement in this area could elevate a young-and-improving Trey Burke from a below-average starting point guard (according to Hollinger’s PER ratings, he’s 52 of 71) to what could be an average to above-average starting point guard.

 

Rk Player Age MP PER TS% eFG% FTr 3PAr ORB% DRB% TRB% AST% STL% TOV% USG%
1 Gordon Hayward 23 2800 16.2 .520 .454 .369 .271 2.5 14.0 8.0 24.1 2.1 15.0 23.1
2 Trey Burke 21 2262 12.6 .473 .442 .126 .375 1.8 9.0 5.3 29.4 1.0 12.2 21.8
3 Richard Jefferson 33 2213 11.8 .573 .544 .248 .460 0.9 10.8 5.7 9.6 1.3 11.5 16.9
4 Derrick Favors 22 2201 19.0 .556 .522 .380 .001 10.1 23.7 16.7 7.3 1.8 12.9 20.8
5 Alec Burks 22 2193 15.8 .547 .487 .449 .172 3.0 10.7 6.8 16.9 1.7 13.0 23.9
6 Enes Kanter 21 2138 15.6 .523 .491 .239 .001 11.6 20.9 16.1 6.4 0.7 13.3 23.3
7 Marvin Williams 27 1674 14.0 .540 .519 .139 .445 5.5 17.9 11.5 7.7 1.7 8.7 16.7
8 Jeremy Evans 26 1209 16.2 .549 .527 .226 .006 11.1 18.7 14.8 6.1 1.8 9.9 15.3
9 Diante Garrett 25 1048 7.1 .459 .449 .045 .362 1.2 9.8 5.3 17.6 2.1 21.7 15.1
Provided by Basketball-Reference.com: View Original Table
Generated 7/27/2014.

 

So let’s look at some numbers and comparisons and see where each player stands.

One of the things that was so tantalizing about Alec Burks’ game his rookie season was his ability to get to the line—a skill very few rookies have to that degree. His FTr in his first season was .401, which was third on the team that year behind Enes Kanter (.445) and Derrick Favors (.436).

 

Season Age Tm Lg Pos G MP PER TS% eFG% FTr
2011-12 20 UTA NBA SG 59 939 14.0 .506 .450 .401
2012-13 21 UTA NBA SG 64 1137 11.5 .507 .463 .332
2013-14 22 UTA NBA SG 78 2193 15.8 .547 .487 .449
Career NBA 201 4269 14.2 .528 .473 .409
Provided by Basketball-Reference.com: View Original Table
Generated 7/29/2014.

 

How did that FTr compare to other rookies in previous years? I was curious what superstars had as their FTr their rookie seasons: Burks’ .401 FTr was higher than Carmelo Anthony, Anthony Davis, Kevin Durant, and LeBron James. Of the superstars I looked through, only Kevin Love had a higher FTr than Alec Burks in his rookie season.

 

Rk Player Season Age G MP PER TS% eFG% FTr
1 Carmelo Anthony 2003-04 19 82 2995 17.6 .509 .449 .358
2 Alec Burks 2011-12 20 59 939 14.0 .506 .450 .401
3 Anthony Davis 2012-13 19 64 1846 21.7 .559 .516 .333
4 Kevin Durant 2007-08 19 80 2768 15.8 .519 .451 .328
5 LeBron James 2003-04 19 79 3122 18.3 .488 .438 .308
6 Kevin Love 2008-09 20 81 2048 18.3 .538 .461 .488
Provided by Basketball-Reference.com: View Original Table
Generated 7/27/2014.

 

Interestingly, Burks’ FTr dipped to a mere-mortal .332 in his sophomore season, possibly because opposing teams knew more what to expect, and also possibly because he was sometimes tasked at the PG position.  But that doesn’t explain how he was able to increase his FTr in his third season to an incredible .449. Given the improvement he made in his game last season, I’m intrigued to see what his FTr will be in 2014. With a new-and-improved offensive system and better spacing, will Burks be given the green line to attack the rim with reckless abandon? Burks has an elite skill in his ability to get to the line; what if he became the best in league in that area?

So what about Trey Burke? He had a very solid season for a rookie point guard, especially considering he broke his index finger in the preseason. We saw how much better the team was with him running the show instead of JLIII or Tinsley. We saw how careful he was with the ball (very low turnover rate). We saw how clutch he could be. But looking at his stats, his FTr is incredibly low. If he were a poor free-throw shooter, that might be a more understandable statistic, but given that he shot 90.3% from the line last year, why not attack the basket a bit more and make the opposing team pay for it by sinking the free throws?

 

Rk Player Season Age G MP PER TS% eFG% FTr 3PAr
1 Trey Burke 2013-14 21 70 2262 12.6 .473 .442 .126 .375
2 Stephen Curry 2013-14 25 78 2846 24.1 .610 .566 .252 .445
3 Goran Dragic 2013-14 27 76 2668 21.4 .604 .561 .381 .274
4 Tony Parker 2013-14 31 68 1997 18.9 .555 .513 .266 .073
5 Chris Paul 2013-14 28 62 2171 25.9 .580 .511 .397 .244
6 Russell Westbrook 2013-14 25 46 1412 24.7 .545 .480 .370 .271
Provided by Basketball-Reference.com: View Original Table
Generated 7/29/2014.

 

Admittedly, the numbers above compare Trey’s rookie season numbers to star point guard’s numbers. But I think it’s instructive to show how much an increase in FTr and TS% (which will be bumped up by an increased FTr assuming his FT% stays stellar) could go a long way in helping Trey become a much better point guard. Chris Paul, someone to whom Trey was (unfairly) compared before entering the league, has a similar build and speed to Trey, but has learned how to use his body, how to use angles, and how to use his craftiness in order to get to the line, at more than three times the rate as Burke. Steph Curry has a FTr exactly twice that of Burke, while shooting almost nearly as well from the line (88.5%). What’s impressive about that is Curry takes nearly eight three pointers a game; he spends a lot of his time outside the arc, yet still gets to the line a decent amount. Dragic also went to the line at a rate three times that of Burke, which also helped contribute to his excellent TS% (60.4%). Of the star point guards here, Tony Parker had the lowest FTr at .266, which is still more than twice that of Trey’s. Russell Westbrook, considered a top point guard by Hollinger’s PER, had a FTr nearly three times that of Burke.

This is one area in which Trey could improve pretty quickly and fairly easily. He has the handle, he has enough speed and a quick-enough first step; I’ll be interested if he can develop a craftiness and some hesitation moves, a la Chris Paul, that enable to him to throw defenders off just a split second, enough to get them to foul him. Even though it’s nitpicking one stat, I think it’s one stat which, if improved, can dramatically improve other areas of his game. And with a new coach and a new offensive system, I think it’s very possible.

Author information

Laura Thompson
Laura Thompson
I grew up in California, but have been a Jazz fan pretty much since I was in diapers; I went to Karl Malone's basketball camp when I was 11 and I flew up to Utah in 1997 to go to Game 3 of the Finals. After graduating from BYU in 2008, I moved back to California to work in Marketing and have been doing that for the last five years. My favorite things in life are the Utah Jazz, basketball, food (whether cooking or consumption of), reading, church, black Labs, and the beach (though hopefully not in that order).
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Examining Utah Jazz Shot Charts http://saltcityhoops.com/examining-jazz-shot-charts/ http://saltcityhoops.com/examining-jazz-shot-charts/#comments Fri, 25 Jul 2014 18:18:32 +0000 http://saltcityhoops.com/?p=12350 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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In today’s media-savvy basketball world, there are a number of methods available to analysts like myself to evaluate players, teams, lineups and everything in between. As part of our natural human tendency, in many cases we gravitate toward more comprehensive measures, particularly in terms of individual player analysis; metrics like PER or Win Shares were created in this vein, an attempt to quantify an all-encompassing view of a player’s statistical contributions within a single number.

Frequently, though, we require more context.

With this in mind, let’s take a small bite from the proverbial Jazz analytics pie. Last week, the recently-launched Nylon Calculus (the new analytics arm of Hardwood Paroxysm under the Sports Illustrated banner, for which I am also a contributor) debuted a remarkable advancement in shot chart data from my colleague Austin Clemens. Those who enjoy pieces from Kirk Goldsberry on Grantland are in heaven, as NC now hosts the capability for anyone and everyone to create very similarly-styled shot charts for any player in the league, dating all the way back to the 1996-97 season. Let’s look at Gordon Hayward’s chart from last season as an example:

As the legend at the bottom explains, colors by area reflect the player’s field-goal percentage from that area compared to league average for the given year – red is better, blue is worse. The size of the cubes reflect the frequency of shots from each location, and printed numbers inside certain cubes reflect actual field-goal percentage from that area rather than percentage compared to league average.

Got it? Good. Now let’s apply it to our Jazz. What follows is a look at several of Utah’s more important pieces through the lens of Austin’s charts, with bits of relevant context to further paint the picture. Because I already took a detailed look at Hayward for NC last week, he’ll be left out.

Trey Burke:

This particular set of glasses isn’t too rosy as far as Trey was concerned in his rookie season. Of particular worry to me isn’t necessarily the amount of blue in his chart, but rather how spread out it all is. Burke was chucking from everywhere, despite being efficient compared with his peers in only a few areas of the court – as he develops, Jazz fans will hope he identifies his strongest areas and works to generate higher volume from them while eliminating some of the fluff from his selection. His work from midrange was scattered, though he was solid from both the left and right elbow, a promising sign going forward for his off-the-bounce game coming out of the pick-and-roll. His strange side-to-side disparity, particularly from the baseline midrange and corner 3’s, is likely a result of variance within a small sample – he attempted just 24 corner 3’s from the left and 15 from the right, per NBA.com, so just a few makes or misses would swing his percentages here in a large way.

Most worrying were his percentages from the high-emphasis areas in today’s NBA, at the rim and from deep. Trey hoisted 293 non-corner 3’s last year, shooting just 32.8 percent on them, and apart from a couple small clusters had virtually no reliable areas as a distance threat. Utah’s generally poor spacing certainly contributed to a degree, but it’s also not as though he was forced to take high-volume stepbacks or off-the-bounce triples – over 82 percent of his non-corner makes were assisted. Things were equally grim at the basket, where Burke simply wasn’t efficient finishing against NBA length. This isn’t uncommon for young guards, but given his general lack of explosiveness it may be a concern for Trey throughout his career, and he’ll surely be spending time this offseason working on angles and shielding the ball more effectively. As he moves forward with his career, much like many of his young teammates, expect his selectivity and accuracy to improve as he becomes more comfortable with the pro game in all aspects.

Alec Burks:

Like his similarly-named backcourt counterpart, Burks needs to improve his selection a bit, though not to nearly the same degree. Part of this is his time in the league already, as he’s developed in this area significantly from his first couple years. I wrote back in February about, among other things, his divisive splits from the left and right sides, and Austin’s chart only reinforces this idea – he’s significantly better going to his right than his left. This is an exploitable tendency for smart defenses until he can smooth it out somewhat, but credit to Alec for emphasizing his right more often, as shown by the larger clusters there.

The reversal of this trend around the basket is likely representative of his strong athleticism and cutting, as well as an ability to finish through contact even on his weaker side:

He’ll want to improve on his stronger hand here, but on the surface this seems far easier for a player with his kind of physical ability than rapidly improving his weaker side. But overall, especially given Utah’s numerous offensive issues last year, fans should be quite encouraged with Burks’ chart, particularly if he continues to improve from deep.

Derrick Favors:

Favors has the easiest chart to dissect, by a decent amount. Like Burks, he reined in some of his lesser efficiency shots from the previous year, in particular basically eliminating shots outside 16 feet (he took just 57 all year). I’ve discussed his jump-shooting in this space before, and while it continues to make small strides over previous years, it’s likely Derrick’s largest obstacle as a player going forward. He’s a strong finisher around the rim and will continue to be given his athleticism, but a leap in his midrange efficiency, and particularly an evening out of both his attempts and accuracy from each side of the block, could be the element that really pushes him into borderline star territory at his position. The upcoming couple years will be huge in this regard for Favors, who can well exceed the value of his recent contract extension and put himself in position for a big raise down the line if he can reach average or above average.

Enes Kanter:

Kanter’s eye test is reflected almost exactly in his jump-shooting clusters on the chart – lethal from the left baseline and slightly closer in on the right baseline, mostly lukewarm from “floater”-type range. His selection is likely the best of Utah’s young core; his highest efficiency areas, for the most part, are his highest volume as well. He shot nearly 39 percent from all midrange shots, and was Utah’s most consistent threat from here all year long. He could do to improve from those little in-between areas outside the restricted area, but to my eye much of this is mental – he rushes shots in these areas, particularly after offensive rebounds, and doesn’t collect his balance enough, areas he can easily improve with age.

Slightly surprising when compared with the eye test are his figures around the hoop. Stuck in my mind are frequent examples of Kanter hesitating on close looks and making life around the basket more difficult for himself, but the numbers bear him out as closer to average than I’d have guessed. Of 67 centers attempting at least 100 shots in the restricted area last season, Kanter’s 62.4 percent puts him 41st, nowhere close to elite but certainly higher than I’d have pegged him on a raw guess. As he improves his confidence and strength while retaining his superb footwork and post game, expect these numbers to continue to rise.

Jeremy Evans:

Despite being a fan favorite and by all accounts one of the nicest guys in the game, Evans’ chart goes a long way toward showing why he’s been unable to find a consistent place in Utah’s rotation. He just hasn’t fully figured out who he is as an NBA player yet, as evidenced by his largely spread out shot locations and his only real clustering taking place around the basket. He expanded his range extensively last year in a more untethered role for the first time in his career, but just didn’t prove effective enough in any of these new areas to warrant real attention from defenses. He remains a beast around the hoop given his ridiculous hops, but his lack of another reliable shot and inability to hold his own down low against bulkier bigs may see the upcoming year as his last in a Jazz uniform.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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Why Our Gordon Hayward Comps Are All Wrong http://saltcityhoops.com/why-our-gordon-hayward-comps-are-all-wrong/ http://saltcityhoops.com/why-our-gordon-hayward-comps-are-all-wrong/#comments Thu, 03 Jul 2014 20:45:00 +0000 http://saltcityhoops.com/?p=12086 Author information
Dan Clayton
Dan Clayton
Dan covered Utah Jazz basketball for more than 10 years, including as a radio analyst for the team’s Spanish-language broadcasts from 2010 to 2014. He now lives and works in New York City where his hobbies include complaining about League Pass, finding good doughnut shops and dishing out assists for the Thoreau It Down team in the Word Bookstore basketball league.
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Do Team USA mates Hayward and Thompson really have similar games? (Getty Images)

Do Team USA mates Hayward and Thompson really have similar games? (Getty Images)

Before you jump off the Gordon Hayward bandwagon, there are some things you should know.

Particularly if your discomfort at the idea of matching a max or near-max offer sheet for the versatile wing has to do with the-devil-you-don’t-know type logic, pull up a chair. I’ve got numbers.

Don’t get me wrong, $60+ million is a lot of money, and if that’s really what Hayward’s offer sheet comes to, the Jazz will wince for about a half a second right before they sign the damn thing and go out for an ice cream cone to celebrate. Why? Because none of the players you think compare to Hayward actually do what he does.

Grass often seems greener elsewhere, the saying goes, so it’s getting more common to hear a response like, “Just let him walk and go get So-and-so instead.” The problem is, in just about every case I’ve heard so far, So-and-so isn’t as complete a player as the Butler product.

For example, Chandler Parsons’ name comes up a lot as a guy who is roughly equivalent to Hayward. It’s easy to see why. The two check all the boxes for the lazy man’s comp: same size, body type, position and complexion. But they also have pretty similar raw numbers. Per 36 minutes, they both averaged almost exactly 16 points on roughly 13 shots. But does that mean their games are comparable?

“Parsons plays in an optimal spread floor system. His stats might be a bit juiced,” ESPN’s Ethan Strauss tweeted while defending a comment that Hayward is better than Parsons. In other words, he’s saying that Parsons raw numbers, while comparable to Hayward’s, have a lot to do with how he’s used and that he plays next to two All-NBA players.

Hayward also gets lumped in statistically and stylistically with players like Warriors guard Klay Thompson, Finals MVP Kawhi Leonard and even teammate Alec Burks, who seems to have surpassed Hayward on some fans’ boards as favorite Jazz wing.

The problem with all these comps: they don’t work. None of those guys do everything that Hayward does. To underscore this point, let’s look at each player’s possession identity to understand their profiles.

Possession usage

Source: mysynergysports.com

Source: mysynergysports.com

Per Synergy, Hayward had 1406 possessions that he “used” for an attempt, a drawn foul or a turnover, not counting the times when he used a particular play type to generate offense for someone else (more on that in a minute). For starters, the only player in this group who had more possessions allocated to them was Thompson, and that’s largely because he just never surrenders the ball. So already we can see that Hayward more central to what his team is doing than the others.

Hayward used 492 of those possessions as the P&R handler or in isolation, meaning plays where he’s responsible for creating. The only guy who came close to that number was Burks (17 fewer) and the other three were somewhere in the 200-300 range. They’re just not expected to create their own shot in the half court.

Where Leonard, Parsons and Thompson are getting the lion’s share of their offense is on play types where other people are creating for them. For each of those guys, 300-400 of their possessions were spot-ups, meaning go stand on the wing while Tony Parker, James Harden or Steph Curry forces defenses to collapse. Hayward was second-to-last among the group in spot shooting possessions, so he didn’t have the luxury of playing off of other guys. He was also dead-last in possessions used off the cut.

The transition column is interesting, too, specifically as it relates to the validity of the Parsons comp. Playing for the pedal-to-the-medal Rockets, Parsons got about 25% more transition possessions than Hayward. I was surprised to see Burks’ transition number so low relative to this crowd, especially since fan perception is that he’s an athletic, dangerous finisher in open court.

Leonard and Thompson are the only ones on this group that use a significant amount of possessions. This is probably because they’re punishing teams that try to cross-match those guys’ elite offensive teammates or aggressively switch on screens, another tactical advantage Hayward doesn’t benefit from.

Finally, Parsons and Leonard also get a lot of high-efficiency second looks, probably because they’re full-time threes, while the others in this group play interchangeably at the wing positions.

So far we’re painting the picture that the other guys on this list are largely system players who have elite teammates creating many of their opportunities. But this is just on possessions “used”; what about the possessions where they pass the ball?

Facilitation

wing facilitation

Source: stats.nba.com

Hayward has the ball in his hands a lot more than his peers in this group, and this is reflected on this pair of graphs. He’s touching the ball a great deal more than the others – close to 70 times per game.

Again, Thompson is a funny outlier here. Where the other guys all pass the ball on 80-90% of their touches, 42% of the time Klay touches, he keeps it, per NBA.com’s player tracking data. And he’s not keeping it to hold it, because his time of possession is also the lowest of all these guys despite having the highest usage. Basically, he catches and then quickly “uses” — takes a shot, draws a foul, or loses the ball — the play.

That’s very different from Hayward, who creates 25% more teammate points per game than the next guy in this group, and 2-3 times as much as the others. The 50 passes per game means that not only is he creating more of his own offense than these other supposed comps, but he’s doing far more facilitation for everybody else, too. Keep that in mind before making a casual comp to someone who reminds you of Hayward.

20/6/6

In an ideal world, you could get this type of complete performance from Hayward but add better talent around him, thus fully unleashing his unique abilities that make him stand out from this crowd. If that happened, it wouldn’t take much for Gordon to reach impressive statistical levels. I threw out that I think his ceiling is as a do-it-all, 20/6/6 guy. Let’s see how realistic that it.

First, scoring. Contrary to popular belief, Gordon didn’t take a noticeably bigger chuck of shots last season, at least on per-minute basis. His per-36 or per-possession FGA numbers were essentially flat from 2012-13. He’s a guy who, pretty consistently now, is going to take 13 shots and 5 free throw attempts per 36 minutes. He did that the season before with the vets still in Utah and he did it last season as the supposed #1 option.

The problem was the much-discussed efficiency drop. He had career lows from the field and downtown, but that’s only part of the story. In his first three years, he was getting 27% of his attempts at the rim, 29% from three, and 33% on two-pointers from farther than 10 feet out. Last season, he dropped to 21% of his attempts coming around the basket and 27% from three while his mid- and long-range 2s went up to 39% of his shots. Having higher-quality teammates and a more spread system might allow Gordon to get the types of shots he’s comfortable with. If he were to maintain his minutes and attempts from last season but return to his previous eFG%, he’d be averaging 17.6 with no other changes.

Then you figure that Snyder has promised more running. The Jazz played at the fifth-slowest pace in the NBA last season, and they scored just 12 points per game on the break. If Snyder wants to run more, the chief architects of the Jazz’s transition offense are going to be Dante Exum and Hayward. It’s not hard at all to envision Hayward adding an extra bucket a game in the open court if the Jazz make a team-level focus on that, and suddenly he’s right at or near 20 points.

What about assists? Hayward had 5.2 assists on 11.2 assist opportunities last season, which means six times per game he put someone in position to score but that player missed the shot. I have no mathematical proof that it will happen less this upcoming season, but if the Jazz put more legit NBA talent around him, it’s more likely that those shots fall. Enough to cover a 0.8 per game gap? We’ll see. Also, if the offense is going to be more pick-and-roll based, Hayward is currently the Jazz’s best P&R handler, so that could led to more assists as well.

From a rebounding perspective, the addition of Exum and probable departure of Richard Jefferson means we’ll see Hayward spend more time at small forward. More possessions also means more rebounds, so even if he doesn’t see a positional bump to his rebounding percentage, a slight uptick in pace could help him on a rebounding front. Even a 3-possession increase to the league average means six more total possessions (three each team). Let’s assume based on minutes that Hayward is on the court for five of them (on average). His rebounds-per-100-possessions number would suggest that he could see a +.4 bump in rebounding average from that one factor alone.

Now, if the Jazz are contending in the next few years, it’s because Exum, Derrick Favors and others have improved, too, so at that point the Jazz may not be as Hayward-dependent and his numbers might be back to something like 17/4/5. But in the short term, 20/6/6 is a real possibility, and would put Hayward in pretty elite company.

For Hayward to join that group would make him an elite-level, Swiss-army utility player that could be the Robin to someone’s Batman on a very good team. And even if he doesn’t quite reach that zenith, the comp exercise above shows he’s already got a better worst-case scenario than players like Parsons, Thompson and others who only do for their teams a portion of what Hayward does for the Jazz.

 

Author information

Dan Clayton
Dan Clayton
Dan covered Utah Jazz basketball for more than 10 years, including as a radio analyst for the team’s Spanish-language broadcasts from 2010 to 2014. He now lives and works in New York City where his hobbies include complaining about League Pass, finding good doughnut shops and dishing out assists for the Thoreau It Down team in the Word Bookstore basketball league.
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Jeremy Evans: One More Chance? http://saltcityhoops.com/jeremy-evans-one-more-chance/ http://saltcityhoops.com/jeremy-evans-one-more-chance/#comments Fri, 20 Jun 2014 22:03:29 +0000 http://saltcityhoops.com/?p=11957 Author information
Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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(Photo by Melissa Majchrzak/NBAE via Getty Images)

(Photo by Melissa Majchrzak/NBAE via Getty Images)

There’s so much going on this time of year for the Utah Jazz, from expected yearly events (next Thursday’s draft and the upcoming free agency period following it) to very rare occurrences for this franchise (a coaching search and a hire, followed by potential changes to staff and even general identity). With all the well-deserved speculation surrounding these more immediate moves, it’s easy to forget several other, perhaps more “known” commodities in Utah’s shop. Roster construction is largely thought of as a top-down art form, but assessing some of those pieces in the middle can make all the difference.

One of such pieces is the likable, if somewhat enigmatic, Jeremy Evans. Since landing in Salt Lake City as the 55th overall pick in 2010, Evans has endeared himself to Jazz fans with his gravity-defying dunks, contagious smile and flashes of sophistication rarely seen from young NBA players. The only problem: his gregarious nature and occasional appearances on Top 10’s around the country have not always shown up in the form of consistent on-court success.

While fans likely know him mostly for reasons above, he’s known for some interesting analytic distinctions within the stat community as well. In his first three seasons before last year, despite never cracking 10 minutes a game on average, Evans posted PER ratings well above league average, even in borderline “mini-star” territory for the ’11-12 and ’12-13 seasons. Using Win Shares per 48 minutes, another popular overall player metric, his showings were even more remarkable – for the 2012-13 year, if you eliminate minute thresholds, Evans finished fourth in the entire NBA for WS/48, behind only LeBron James, Kevin Durant and Chris Paul.

Of course, the whole point of minutes thresholds for these sort of larger metrics is to weed out unsustainable results over small sample sizes, and most would assume there was a fair degree of this at work in Evans’ case. This past season appears to confirm as much, with Evans finally receiving “rotation” minutes (18.3 per game) for the first time in his career. The result: his PER dropped over three full points from the year before and his WS/48 were nearly cut in half.

But both those figures from the ’13-14 season are still above league average, and are more encouraging given the larger sample of minutes he played. And with the upcoming season set to be his last under contract before hitting unrestricted free agency, continued improvement and an ability to stay on the court will be paramount in determining whether he’s worth anything but a minimum contract going forward, either for the Jazz or elsewhere.

Part of the low-usage debate regarding efficiency metrics is centered specifically around players like Evans – bit players who have a couple above-average skills, but are fully aware of this and consequently stay within those strengths, raising their efficiency in ways that seem artificial to some. In Evans’ case, his remarkable leaping and above-the-rim abilities are his calling card, from his pick-and-roll prowess (he shot an even 50 percent last season on attempts as the roll man in such sets, per Synergy) to his work on the offensive glass and in transition (both areas, again per Synergy, where he ranked in the NBA’s top-20 for per-possession efficiency, likely because such a high number of attempts ended in earth-shattering dunks).

But as is typically the case in the evolving NBA, such one-dimensional players will find tough sledding as soon as opponents identify and adjust to their preferred game. Teams got the drop to a certain point last season, sending extra bodies at Evans when he rolled to the hoop, knowing his initiation of rotations when confronted on his way to the rim is badly lacking. And while transition and offensive rebounding opportunities can be situational and tough to specifically game plan against, they’re not enough on their own to qualify a guy for rotation status in today’s NBA.

And unfortunately, beyond these skills, teams have been able to expose some of Evans’ weaker areas. His jumper remains bad, shooting just 35.9 percent last season on all shots classified as “Jump Shots” by NBA.com. He can’t space the floor as a result, a problem when defenses load up to prevent him getting above the rim. He’s a solid rebounder who can certainly get up in the air for his boards, but lacks good boxing-out skills and won’t win too many rough-and-tumble contests down low. His per-minute and per-possession numbers would also seem to indicate that his rebounding has plateaued somewhat, a sign that he’s not introducing little bits of savvy one might hope to see.

Defensively, Evans again has a couple above-average skills while lacking in other areas. He’s a capable and willing helpside defender, and his freaky leaping and length allow for some highlight reel blocks:

He’s developed solid timing on these plays, though he can still be fooled by heady rim finishers with hesitations and counters built into their games. After posting ridiculous and unsustainable block numbers in small samples the previous two seasons, he settled into a still-above-average range this past year in a more realistic minutes distribution, and will always be a danger off the weak side. His long arms have also helped him limit opponent spot-up tries to a low percentage, another asset he’ll retain his entire career.

But again, the positives mostly stop at these limited-impact areas, especially when teams can game-plan for them knowing his particular strengths and, conversely, weaknesses. Evans never filled out since entering the league, and as a result has been brutalized consistently by stronger players:

Evans is listed at just 196 pounds, beanstalk status given his height (6’9), and plays like the one above are common, even from guys like Ersan Ilyasova who likely only rank about average on the size scale for their position. Evans allowed opponents a silly 56.3 percent shooting on finished post plays, per Synergy, and this came mostly against backup units. He’s 26 now, and the chances of him bulking up in any significant way are quite slim – it’s entirely possible this will remain a glaring weakness his entire career. He attempts to augment it by gambling for steals at unorthodox times with his long arms and quickness, and while he has had some success here (he forced turnovers on over 20 percent of finished post plays last year, according to Synergy, a high and unsustainable number), it’s nowhere near enough to offset all the implications of his huge strength disadvantage.

He’s not quite as lacking in other areas defensively, but he’s no stalwart either. His footwork in pick-and-rolls and isolation sets has been suspect, particularly in the latter case, where opponents got him off-balance easily and contributed to his high foul rate on such sets. He’ll frequently lose his man entirely for criminally easy looks, even down low in limited space, and will take silly touch fouls to compound the problem:

Apportioning responsibility for his lack of development in certain areas is difficult, and even more so when attempting to look at year over year improvement based on his limited samples. He spent basically his entire career thus far under Ty Corbin, who certainly had his share of questions regarding player development in his time at the helm, and this certainly may have contributed. In any case, making a few positive adjustments in some of the areas I’ve listed might at this point be a requisite to remaining in Utah given all the young talent and more on the way.

Jeremy Evans is a nice player and an even nicer person, and as a favorite of mine and many others, I write the above with a heavy heart. His ability to remain above league average PER with such a minutes jump last year is a big positive, and if he can seize the opportunity presented by a new staff and culture in his final season under contract, he may very well make me (happily) eat my words. But in such a smart and advanced league, the writing on the wall tells us that his limited high-skill areas will make this an uphill battle, and he may never be anything more than a bench player. I know one thing: I’m going to enjoy every highlight-reel dunk like it’s his last in a Jazz uniform, just in case one of them finally is.

Author information

Ben Dowsett
Ben Dowsett
Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.
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The RPM Smell Test and the Utah Jazz http://saltcityhoops.com/the-rpm-smell-test-and-the-utah-jazz/ http://saltcityhoops.com/the-rpm-smell-test-and-the-utah-jazz/#comments Thu, 10 Apr 2014 21:17:50 +0000 http://saltcityhoops.com/?p=11003 Author information
Dan Clayton
Dan Clayton
Dan covered Utah Jazz basketball for more than 10 years, including as a radio analyst for the team’s Spanish-language broadcasts from 2010 to 2014. He now lives and works in New York City where his hobbies include complaining about League Pass, finding good doughnut shops and dishing out assists for the Thoreau It Down team in the Word Bookstore basketball league.
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Is Hayward less valuable than nine Spurs? A look at RPM. (Photos by D. Clarke Evans/NBAE via Getty Images)

Is Hayward less valuable than nine Spurs? A look at RPM. (Photos by D. Clarke Evans/NBAE via Getty Images)

This week the basketball metrics community gave us another lens through which to analyze player performance. ESPN’s new Real Plus Minus (RPM) stat combines on-court plus/minus with absolute statistical contribution to give us a sense of how much of a team’s success or failure on the scoreboard we can attribute to a certain guy, on either end of the floor.

This comes at an interesting time relative to the dialogue here at SCH, because we’ve been talking lately (here and here) about whether certain stats systems either ladder up to or distract us from a more holistic understanding of basketball. So what’s the verdict on RPM? So far, that it’s an interesting and useful tool, as long as we know what it is and what it isn’t.

Here’s what it’s not. It’s not an overall player rater. Or if that what it attempts to be, it’s a poor one, one that asserts that Chris Andersen, Amir Johnson and Nick Collison would be the best players on the average team. Or that Carmelo Anthony and Damien Lillard are significantly worse than Matt Barnes and Patrick Beverley.

RPM is not altogether new. It’s really an adjusted version of xRAPM, which adds box score stats to Regularized Adjusted +/0 (RAPM, explained here or straight from the creator here). RAPM essentially is an adjusted +/- that tries to quiet the statistical noise created by small-sample outliers and then xRAPM factors in player stats. RPM does this differently than xRAPM by using what’s called Bayesian logic. There are other adjustments, too, but ESPN plays a little coy with us as far as sharing the formula. We know that they try to account for age and current score, which mostly help the tool’s predictive ability, rather than address the blind spots of xRAPM.

Inputs

To understand the blind spots of any stat system, first you have to know where its inputs are. Broadly speaking, all inputs fall into one of just a few categories, such as:

  • Box score - Since these are the most readily accessible, a lot of performance aggregators try to define player performance based on some calculation of the raw sum of their measurable outcomes in a box score. PER, Win Shares and eFG% are examples of metrics you can calculate just by looking at the stat sheet. The caution here is that a lot of very valuable basketball behaviors go unaccounted for, like screening, team defense, a strategic cut, a hockey assist, etc. Behaviors don’t matter, outcomes do.
  • Scoreboard – A whole family of stats tries to address what happens where it matters most, and is usually measured as a function of who is on the floor (player-wise, or combination-wise). The strength here is that this correlates most directly to winning. The drawback is there are a lot of variables that can muck this up with noise. And if you are on a losing team, there’s a good chance your variables (say, teammates) have a more averse impact on your performance here than somebody on a winning team, so right off the bat, the playing field isn’t level. Some versions of stats built around the scoreboard try to adjust to compensate for some of that noise.
  • Play-tracking – Here, you actually watch for specific behaviors and your data set is essentially a series of tick marks for when something happened, either as captured by a person or a video tracking system. This can account for a wider set of behaviors, but relies on accurate classification, which is difficult when you could ostensibly have 30 different offensive systems and 30 different defensive systems. A whole slew of new stats are available in this family, but most are only useful in a very specific context.

There are dozens of wrinkles, adjustments and permutations, but at a broad level, most stat systems are sourced by one or more of those input types, and therefore possess some of the same benefits and watch-outs.

RPM tries to roll together the first two, and then adjust based on the relative performance of people around you. It’s first input is what happened on the scoreboard while you were in, then it tries to figure out how much of that you’re responsible for using a formula that’s roughly similar to WS or PER, and then it looks at who was around you.

+/- Blind Spots

RPM still has the problem of judging a player from a negative-differential team more harshly than his friend on a positive-differential team. Just by being a member of the Miami Heat, your RPM is likely to be positive because most of the time, your team is winning. If you play only in short, hyper-energetic spurts with at least one superstar, you’ll probably reap extra benefit. That might explain how Andersen ranks 13th, while someone like Gordon Hayward is 80+ spots lower.

The adjustment for teammate and opponent quality helps even out the comparison for players on the same team — meaning Jeremy Evans might be forgiven relative to other Jazz players’ RPMs since most of his minutes are with bench units — but he’ll still look worse compared to a statistically similar bench player on a team that usually outscores its opponents. And maybe he should; at the end of the day the most important measure of player quality is winning. But this is the inherent watch-out in using any type of +/- stat to compare players from different teams with very different records.

That probably explains low ratings by most Jazz players. The stat ultimately tries to figure out how much of the team’s plus/minus pie is yours, and if the pie is smaller for the Jazz, then Hayward’s piece is bound to be smaller than a player with similar stats on a winning team. San Antonio, for example, has NINE players with a higher RPM than Hayward, Utah’s best player. I’m as big a believer in the Spurs’ culture and system as anybody, but in overall terms, they do not have nine guys who would be Utah’s best player. Sorry, Boris Diaw. Same goes for OKC, who has 6 players rated above Hayward in RPM even though only three are better in PER — bigger pie from a scoreboard perspective, better numbers for everyone. Would Hayward really be 7th best on the team if he joined the Thunder tomorrow?

Anthony has the 11st best PER in the league, but ranks behind 51 other players in RPM because he plays for a team that usually is getting outscored. That doesn’t mean PER is right and RPM is wrong. His actual value is probably somewhere in between 11th and 52nd. The disconnect here simply represents an invitation to apply intuition and our eyeballs to further investigation.

Box Score Blind Spots

RPM also carries the flaws associated with its box score inputs. Rhetorical question: using just a stat sheet, what’s the best way to determine who had the most impact on a team’s defensive performance? The answer to that question is near impossible. Steals and blocks do some of that, but the very best teams only influence their opponent possessions about 10-15% of the time with those behaviors, so how do we account for the other 85 possessions? Rebounds measure the endpoint of the defensive possession but fail to account for who made the player miss the shot in the first place and how (or, in cases where the shot went in, doesn’t describe the defense at all).

But that’s all the box score has to work with. So any box score-related stat is bound to overvalue those three columns on the stat sheet and completely ignore actual defensive behaviors like denying, positioning, rotations, help, adhering to a team system, etc.

We see this in the results, as even ESPN’s own Kevin Pelton points out. Many of the guys who rate out better than common sense tells us are guys who are thieves, shot-blockers or low-minute “energy guys.” Bruce Bowen would probably rate very poorly, just as he tended to do in PER and Defensive WS, despite having the reputation for being a very good behavioral defender within a team system. In general, anyone with a slight (because the sample is so small on blocks and steals) advantage in those rare occurrences of certain defensive outcomes will rate well regardless of their overall defensive behaviors. This is not a unique blind spot where RPM is concerned; the same is true of just about any box score-generated stat that tries to explain defense in an overall way (like DWS).

Another Tool

Does that mean RPM is bad, or useless, or lying to us? No. It just means that, like with any metric, we have to know what it can tell us and what it can’t. It can tell us who tends to see success on the floor, and it can guess as to how much of that he contributes statistically, but it still can’t articulate the value of defense, screening, cutting, rotating, or how any of those behaviors correlate to the box score. For those types of insights, we have to use a combination of stat systems, basketball knowledge and good old-fashioned basketball-watching.

Do I think Melo is worse than 51 other players in the league? Do I think Hayward would be the 10th best Spur if they acquired him tomorrow? Do I think Nick Collison is a top-10 player? No, no and no, which is why I don’t think this is a good aggregator of overall player value. It is a good next phase in the conversation around the impact that players have on the scoreboard and on winning games, and we should look at it through that lens.

Author information

Dan Clayton
Dan Clayton
Dan covered Utah Jazz basketball for more than 10 years, including as a radio analyst for the team’s Spanish-language broadcasts from 2010 to 2014. He now lives and works in New York City where his hobbies include complaining about League Pass, finding good doughnut shops and dishing out assists for the Thoreau It Down team in the Word Bookstore basketball league.
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