Phoenix Suns SportVU

12/20/2015 Ways to Better
Utilize SportVU Data
for the Phoenix Suns
Strategic Career Planning
Ryan Milne
MSLB PROGRAM AT ARIZONA STATE UNIVERSITY

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Contents
Introduction......................................................................................................................... 2
Best Practices and Analysis ................................................................................................ 4
Examining the 4 R’s (Regulatory, Revenue, Reputation, Relationship) ............................ 8
Solutions and Analysis...................................................................................................... 11
- Training Staff............................................................................................................. 12
- Coaching Staff ........................................................................................................... 13
- Front Office ............................................................................................................... 18
Conclusion ........................................................................................................................ 23

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Introduction
SportVU player tracking data provides next-generation sports statistics by using
real-time player and ball positioning tracking technology in order to improve player
performance, and ultimately team performance1. The combination of these innovative
player tracking statistics and STATS’ traditional data creates comprehensive,
sophisticated data streams for basketball and soccer to aid in analytic analysis1. Currently,
my job for the Phoenix Suns is in the basketball operations department as a SportVU
Operator. My work schedule is approximately every other home game for the Suns. The
office is located at the very top of Talking Stick Resort Arena, above the nosebleeds but
just below the actual catwalk, where operators sit behind nothing more than a simple
computer. My job, as my title so eloquently states, is to operate the SportVU program
efficiently so that the analytics department receives the highest quality and most accurate
data about the Suns players’ movements during a live game. The basketball professionals
that use the data collected are mainly the Front Office, Coaching Staff and Athletic
Trainers. Interviews and discussions with these groups revealed a need to find a way to
use the SportVU data more efficiently. The impression was that they have more data than
they know what to do with. My mission in this research paper is explore ways for the
Front Office, Coaching Staff and Athletic Trainers to better utilize the information.
Before examining efficient ways to use the data, let me begin by breaking down
the history of SportVU and explaining how it works. SportVU was created in 2005 by an
1 “Data Feeds – STATS.com.” STATS. Web. 28 Oct. 2015.
1 “Data Feeds – STATS.com.” STATS. Web. 28 Oct. 2015.

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Israeli scientist who had a background in missile tracking and advanced optical
recognition with the intent to put this technology to use in military settings2.
Interestingly, after a little experimentation during some international soccer matches, a
company called STATS LLC purchased SportVU in 2008 when the potential for this
technology in a sports setting was discovered. It wasn’t until a year later that this
analytics technology came to the NBA during the 2010 NBA Finals when the Los
Angeles Lakers took on the Orlando Magic. Soon after, Dallas, Houston, Oklahoma City,
San Antonio and Golden State also implemented SportVu, the most comprehensive and
sophisticated data stream available in the world2. It should be noted as no coincidence
that three of those teams have each won a championship since the implementation of
SportVU with the other two on the verge of one. After a couple more years when the
2013-2014 NBA season rolled around, every team in the league had the technology in
their building.
The system works by placing six cameras strategically across the catwalk of all
NBA arenas. These small cameras then track the movements of all ten players on the
court as well as the referees and the ball. This optical recognition software picks up
images of jersey numbers, in order to figure out which player is which, at twenty-five
times per second and captures every pass, shot, dribble and movement made during a live
game. SportVU then produces data on individual player movement in categories like
distance, drives, speed, touches per possession, catch and shoot, and even defensive
2 Wiley, Antonio. “Industry Insights: The Evolution of Basketball through Technology.”
Warsaw Sports Business Club. 24 May 2014. Web. 1 Nov. 2015.
2 Wiley, Antonio. “Industry Insights: The Evolution of Basketball through Technology.”
Warsaw Sports Business Club. 24 May 2014. Web. 1 Nov. 2015.

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impact. The play-by-play data can be delivered in a report with ninety seconds of a play3.
What makes this even more incredible is that both team personnel and the average fan
have these live statistics at their fingertips.
This is where my role comes in. Throughout the game queries are constantly
popping up on the computers. These queries consist of the images that are taken twenty-
five times a second. When a query pops up on the computer, the operator must tell the
software which player is in the query in order for the software to then collect the correct
data for the correct individual. Other types of queries can consist of either referee queries,
in which the process is the same as the player queries, or ball queries. Ball queries are a
little different in the process. In this specific the operator’s job is to tell the computer
where the ball is in relation to the court and if it is even on the court. The ‘court’ is
defined as everything in bounds so if the ball is out of bounds it is technically not on the
court. In that case the operator checks a box on the screen that tells the computer that the
ball is not on the court. If it is in bounds, the operator enlarges the image to find the ball
and then double-clicks directly on the ball so the software can then pinpoint the ball’s
correct location. Not an incredibly difficult task, however, it takes a lot of focus, patience,
a knowledge of the game of basketball and a clear eye for detail.
Best Practices and Analysis
Due to the fact that the methods of most NBA teams are kept behind closed doors,
it is difficult to truly know who is making the best use of such material in the NBA.
3 Abundis, James, and Luke Knox. “How SportVU Technology Works – The Boston
Globe.” BostonGlobe.com. 30 Mar. 2014. Web. 1 Nov. 2015.

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However, it is widely known that the Houston Rockets lead the charge in all things
analytics. They are mainly known as the team and poster boys for the analytics field.
SportVU is one of many varied software programs used for analytics in the NBA.
Another version of analytical software that is used around the league is wearable
technology from Catapult Sports4. Catapult is an Australian company that is on the
cutting edge of biomechanical analysis, which is the ability to monitor how an athlete is
moving. In the 2014-2015 season, 12 teams used this ahead-of-its-time device, which is
about the size of a car key fob and easily fits into the lining of a compression shirt. This
miniscule device features an indoor GPS system, an accelerometer to measure stops and
starts, a gyroscope to measure the body’s bending and twisting as well as a magnetometer
to measure direction. The most impressive of all the features though is that the
monitoring device has a microprocessor that collects and parses more than 1,000 data
points per second. Not to mention the fact that it can beam that information to the
trainer’s screen of choice in real time.4
The best known usage of this wearable technology came in the 2014-2015 season
by the Golden State Warriors. The soon-to-be champion Warriors were on the heels of a
six-game, nine-day road trip where, naturally, players are going to get worn down. The
director of athletic performance, Keke Lyles, combined both the wearable technology
information with the SportVU data in order to determine where players were physically
and if they needed a rest. One of the multitude of things that SportVU captures is players’
4 Berger, Ken. “Warriors ‘wearable’ Weapon? Devices to Monitor Players While on the
Court.” CBSSports.com. 3 June 2015. Web. 14 Dec. 2015.

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movement intensity and acceleration, so when there are drop-offs it can possibly indicate
fatigue and overuse. As Lyles notes, “A lot of non-contact injuries are fatigue-related. If
we see big drops consistently over the last few games, and we know in practice they’ve
dropped and they’re telling us they’re tired and sore and beat up, then we start painting a
big picture: ‘Yeah, these guys are probably fatigued.’ When they’re fatigued, they’re at a
higher risk.”4
After winning 51 games in the season, Lyle noticed that a few of the Warriors
players started to show signs of fatigue, so head coach Steve Kerr decided to rest his top
four players: Stephon Curry, Klay Thompson, Andrew Bogut and Andre Igoudala. A
decision that was both not popular among fans, but also not the first of its kind. Greg
Popovich, head coach of the San Antonio Spurs, has long been known to rest his starters
throughout his tenure. His decisions were purely based off of coaching instinct and
experience as opposed to pure analytical data. Kerr took a little bit from analytics and
old-school style basketball to sit his star players through a long, strenuous stretch. Below
is sample data that Catapult Sports collects for their NBA clients for wins and losses that
shows the level of intensity of their players for each quarter.

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4
It is clear that there is an incredible amount of information available to these NBA
staff members and at times, an overwhelming amount. The purpose of this paper is
simply to help organizations understand what the most valuable statistics and information
are in order to help them efficiently use this data to its upmost potential. In short, the data
needs to be converted into ‘information’ that is usable. From researching the SportVU
and Catapult data as well as researching how other teams use it, the Toronto Raptors
training staff used the data in a unique way. The Raptors’ director of sports science Alex
McKechnie used the directional data of the players’ movements generated during practice
to change up their conditioning drills. McKechnie noticed that around 80 percent of the
Raptors’ movements were all backwards and side-to-side. After realizing these were
majority of their movements, McKechnie changed the conditioning drills to reflect

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strengthening the muscle groups the players actually use. Catapult’s D-League guinea
pigs (the only teams that actually use the wearable technology in games) showed that
approximately 15.5 percent of player movement was actually forward, which backed up
McKechnie’s notions.4 A recommendation, if the training staff hasn’t already done so,
would be to follow the Raptors’ method here. Look at the directional data from practice
and plan the conditioning drills accordingly.
Examining the 4 R’s (Regulatory, Revenue, Reputation,
Relationship)
A key item to note about this wearable technology is that the NBA only allows it
to be worn in practice, which is the reason for the combination of the practice data and
the in-game SportVU data. Warriors Assistant General Manager, Kirk Lacob noted that,
“It’s gotten to the point where we have to ask the first question: What data can we
understand and how is that going to be helpful? And the secondary questions are, what
are we allowed to do? What is philosophically OK to know? How much should you know
about your employees? How much should you allow your employer to know about you?
And those questions are going to get raised in the CBA.”4 Lacob brought up valid
regulatory problems with the use of such intricate (and some consider private) data.
Despite the fact that the technology continues to get more intricate and what may seem
more personal, all of it is to keep the players healthy, productive, and on the floor longer.

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This would essentially, extend their careers, maximize their performance and in turn,
increase their monetary benefits as well.
Two seasons ago, the Toronto Raptors were among the league’s most injured
teams, specifically in terms of games lost. However, after signing up with the Catapult
wearables, they improved to being one of the NBA’s least-injured teams in the 2013-
2014 season. Some can call it coincidence, but if there is even a slight chance that teams
can limit injuries by just understanding exhaustion levels, you can bet they’ll take it.
Obviously freak injuries can’t be stopped, but ones due to fatigue and over-use are what
these machineries aim to prevent. The key and trickiest part will be fully convincing the
players that this technology is really for their benefit.
“Let’s just say it rolls over into affecting games and coaches changing rotations,
that’s where you might lose some players. You’re playing five or ten less minutes than
you think you should because the readout says you’re overloaded?” The league’s reigning
MVP Steph Curry said. Getting players on board could be tough with the notion of ‘we
know what’s better for your body than you do.’ The NBA is full of egos and telling a
high-profile player to come out when he feels he doesn’t need to is harder and can be
more damaging to relationships in the long-run than most people think. That is only one
small reason for player objections and a reason why more extensive player analytics or
‘the big data’ could not be passed by the CBA in 2017.
While performance analytics have the ability to extend a player’s career, they also
have the capacity to expose hidden physical problems and shorten careers. If a player
shows that he is a heavy risk for injury or that his health will be a consistent concern,
unless he is a LeBron James, that player is going to lose a lot of money. This data could

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expose NBA players, in turn costing them millions and millions of dollars. However,
while it would be costing the players big bucks, it’ll be saving owners tons. This
information will give them the ability to maximize the potential of every player on their
roster while also saving them from spending money on injuries. At the end of the day,
this big data situation will be a big issue when it comes to collective bargaining
agreement talks between leagues and their unions in 2017.5
A main question and concern is whether the cost of SportVU and Catapult are
worth the results. A full complement of 15 Catapult devices costs an estimated $30,000
per season (only .04 percent of the Warriors’ salary expenditure)4 while operating
SportVU costs up to $100,000 per season. It is estimated that in the 2013-2014 NBA
season, that collectively, NBA teams lost $358 million due to injuries from banged up
players not playing. The injury-torn Los Angeles Lakers, alone, lost $44 million.5 That
means that on average each team in the NBA lost about $12 million just from injuries. A
$130,000 cost per year to possibly save multimillions sounds like a no brainer. At the end
of the day it’s great to have all of this information, but it means nothing if you don’t
know what to do with it. Will Carroll, Bleacher Report and leading expert on sports
injury puts it perfectly, “The data shouldn’t be the competitive advantage. The
5 Kamenetzky, Brian. “The Next Big Thing in Sports Data: Predicting (And Avoiding)
Injuries.” Fast Company. 25 Aug. 2014. Web. 14 Dec. 2015.

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competitive advantage is you have smarter guys who understand the data and create
actionable intelligence from it.”5
Solutions and Analysis
Everything leading up to this section of the paper has described the context of the
NBA’s use of SportVU data. It has also explored best practices and analysis of those
practices and finally an examination of the issue relative to regulation, revenue,
reputation and relationship. This section will examine the actual statistics from Phoenix
Suns current players as well as their team in general and offer an analysis as to ways that
the Suns’ staff can better utilize the information in a more efficient manner. Lastly, this
paper will outline the most effective ways for the training staff, the coaches and finally
the front office to use the SportVU data. The coaches section will look at the data from a
team level, while the front office section will look at it from an individual level. All of
the data and statistics below and used throughout the rest of the paper were taken from
the official NBA website6 after the Suns’ 27th game of the season on December 17th,
2015.
Although the main focus will be on three distinct SportVU data user-groups; trainers,
coaches and front office, all of the statistics gathered will be used across the groups in a
coordinated effort. In other words, the specific categories for the training staff and front
office will also be important for the coaching staff to look at and vice versa as well. The
coaching staff will want to know if a player is being overused so they can rest him. The
6 “NBA.com/Stats.” NBA.com. Web. 17 Dec. 2015.

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training staff will want to know if the team or a specific individual is getting blasted on
the boards so they can adjust the conditioning and workout regimen accordingly. And
finally, the front office will want to know all of these important categories because if a
player is injury prone it’ll make a huge difference when contract negotiations come
around. Similarly, the front office will want to know if the team is bottom of the league in
three-point shooting, they’ll most likely look for a shooter in the offseason. This
information is focused on what each user-group should look at first but they are all
absolutely connected. One last and important thing to mention is that the importance of
each statistic will be shown by comparing the Suns to the leaders of the league in the
relative statistic in an effort to prove that these statistics attribute to winning. So it is
incredibly important to keep that in mind.
- Training Staff
Interestingly, the Catapult wearable technology and not from the SportVU data
may be more meaningful for the Suns training staff. As the Toronto Raptors staff
figured out, around 80 percent of their team’s movements were all backwards and
side-to-side. This knowledge came from the Catapult directional data of the
players’ movements that were generated during practice in order to determine
conditioning drills. If the Suns’ practices are anything like the Raptors or the D-
League’s games, which would make sense, around just 15.5 percent of the
movements were forwards4. Suns strength and conditioning trainers might want to

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train players’ bodies for the backward and side-to-side movements that they use
during games.
In terms of using specifically the SportVU data, my suggestion would be to look
at both the Speed and Distance Categories. This will give the staff an idea of what type of
workload the players are exerting. Combine that with the Catapult data and it will be easy
to see if they are being overworked or if their body is getting fatigued. Currently, the
Suns have two players in the top ten in the NBA in the distance in miles’ statistic.
Brandon Knight is fourth in the league at running 2.57 miles per game with an average
speed of 4.34 mph, while Eric Bledsoe is tenth and running 2.49 miles per game with an
average speed of 4.25 mph. Having your two max contracted players both in the top ten
in total distance per game has its pros and cons. It’s great because it shows that the guys
that are getting paid the big bucks are working hard during the game but it isn’t
something to take lightly, those miles add up and it is a very long season.
The last thing to mention is that it would be very beneficial for the training staff to
look at the rest of the SportVU data as well, not just the speed and distance section. The
reason is that it is important for the staff to get a feel for each player’s specific tendencies
and what type of player they are in general so they can plan a workout regimen
accordingly. For example, TJ Warren likes to crash the glass, averaging 1.4 offensive
rebounds per game and 1.0 of them being contested per game. What that should tell the
training staff is that he is going to take a lot of contact and a lot of hits, so a workout
schedule that would specifically prepare him for that would be advantageous.
- Coaching Staff

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The coaching staff might bake the best use of this information. This section will
show and describe the best SportVU categories for coaches to look at in order to
determine, truly, how much production they are getting from their team and their players.
Again as mentioned earlier, this coaching section will look more at the team statistics as a
whole rather than the individual statistics. While the individual statistics absolutely do
matter to the coaches for subbing patterns and simply whether a player should or should
not be playing, the overall team statistics give the coaching staff talking points for their
team and even perhaps reasons as to why they are either winning or losing. For example,
if the Suns are bottom of the league in rebounding and top in turnovers, SportVU data
will give the coaching staff specific ideas of things to work on.
To start, the SportVU rebounding data lets the coaching staff know the true value
of both the team as a whole as rebounders as well as the individual players. It shows more
than just the fact that the Suns averaged 48.4 rebounds per game. because that
information can be misleading. That ’48.4’ number doesn’t describe how hard the players
fought or didn’t fight for the rebounds. It doesn’t tell the coaches whether they were
doing their job by boxing their man out and keeping him off the glass or if it was a gift or
lucky and they were just in the right place at the right time. SportVU data tells that story;
it takes it to another level. The most important statistic to see if you’re getting the most
out of your players on the glass are the ‘Adjusted DREB/OREB Chance%’, which is the
percentage of defensive/offensive rebounds gathered within the vicinity (3.5 ft) and
excludes all deferred rebounds.
The ‘Adjusted DREB Chance%’ and ‘Adjusted OREB Chance%’ are the most
important rebounding statistics. One big thing NBA coaches mention that can either win

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or lose ball games are the number of 50/50 balls that their team gets. This statistic is
essentially the 50/50 balls of rebounding. Now obviously the percentages are going to be
higher on the defensive end than on the offensive end because, naturally, the players
should have better position on the defensive end, but this data still tells a story. When the
data was gathered back in mid-November, now (December 17th, 27 games into the
season) the Suns ranked 10th in the league at an Adjusted Defensive Rebound Chance
Percentage of 76.3%. What should be noted is that the top three in the NBA at this
statistic are the San Antonio Spurs at 80.3% (22-5), the Cleveland Cavaliers at 79.8%
(17-7) and the Miami Heat at 78.8% (15-9). Currently, the Spurs are second in the
Western Conference while the Cavaliers are first and the Heat are fourth in the East,
respectively. However, on the offensive side, the Suns rank 28th in the NBA at 44.5%.
The top three in the league are the Los Angeles Clippers at 55.8% (16-10), and then both
the Golden State Warriors (25-1) and the Detroit Pistons at 55.4% (15-12).
Looking specifically at offense, the Suns coaching staff might first look into the
Passing section of the stats. The 25-1 Golden State Warriors are the league leaders in
eight of the ten passing categories; all except ‘Passes Made’ and ‘Passes Received’,
which are held by the San Antonio Spurs. It is no secret that effective passing leads to
great offense, but the term ‘passing’ is still very broad. Breaking it down deeper, the
coaching staff should look at the ‘AST Adj’ stat. This explains the total sum of a team’s
assists, free throw assists (number of passes made by a player to a recipient who was
fouled, missed the shot if shooting, and made at least one free throw), and secondary
assists (the third party in the assist; pass + pass + made shot) per game. The Suns rank
19th in the league at 28. The top five in the league include the Warriors at 40.8 (25-1),

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Spurs at 34.5 (22-5), Hawks at 34.3 (15-12), Kings at 32.9 (10-15) and the Cavaliers at
32.5 (17-7). All of the teams are in heavy playoff contention besides the Kings, who, no
doubt, are high in the passing category due to the incredible passing ability of Rajon
Rondo.
The second offensive category to look at is ‘Paint Touches.’ ‘Paint Touches’ are
the number of times a player touches and possesses the ball in the paint. This is so
important because every time a team gets into the paint they are putting tremendous stress
on the defense due to their proximity to the basket. It is close to the basket while at the
same time being in the middle of the floor. The location is key because a player can be
close to the basket and outside of the paint on the baseline, but because he is by the
baseline it doesn’t give him any opportunities to create or much room to kick out to an
open teammate due to the fact that the baseline acts as a help defender that isn’t guarding
a man. However, every time the ball enters the paint the defense has to collapse which
opens up a plethora of opportunities. The Suns rank 20th in the NBA at 13. The top five
are the Bucks at 18.2 (10-17), Warriors at 18 (25-1), Cavaliers at 17.7 (17-7), Spurs at
17.3 (22-5) and the Hawks at 17.1 (15-12).
A statistic that follows similar logic to the previous mentioned is the ‘PTS’ in the
post touch category. ‘PTS’ are the total number of points the team scores after having a
touch originate from a pass and reception within twelve feet of the basket. First off, post
touches are incredibly important purely because every time the ball enters the post there
is risk for the defense due to the proximity of the ball to the basket. But it is a real threat
when a team can turn post touches into points. When post touches start turning into post
points it puts strains the defense and can cause doubling, help, or simply the defense

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collapsing as a whole. Once that starts happening, it leaves opportunity for open shots
and cuts to the basket. The Suns sit at 18th in the league scoring 13 points per game. The
top five include the Warriors at 17.7 (25-1), Cavaliers at 17 (17-7), Bucks at 16.4 (10-17),
Hawks at 15.9 (15-12) and Spurs at 15.6 (22-5). Interestingly enough, a Warriors team
that is known mainly for their jump shot ability not only leads the league in points after a
post touch, but they also lead the league in post touches in general.
As the old saying goes, “defense wins’ championships.” The most important
statistic to look at on the defensive end (outside of rebounding mentioned above) is the
Defended Field Goals Attempted stat or the ‘DFGA.’ This is the total number of
opponent field goals attempted when they have a player defending their shot. In other
words, the amount of shots the opposing team takes with a hand in their face. This
statistic is incredibly important because it shows how good and active your defense is.
The higher the number in this stat means the less number of open shots your team is
giving up. The Suns rank 11th in the NBA with 84.7 defended shots per game. The top
three in the league are the Bulls at 90.2 (15-8), Warriors at 90.1 (25-1) and Thunder at
86.8 (17-9).
The final stat that the Suns coaching staff might look at is their Defended Field
Goal Percentage on three pointers. With the value that analytics has been placing on three
pointers it is vital that teams are able to defend them. The more a defense can get teams
to jack up defended threes at make them at a low percentage, not only will their defense
be better but they will also increase offensive opportunities through transition plays.
Long shots create long rebounds, which give teams the chance to get a stop on one end
and a score on the other in an efficiently quick manner. The Suns are 28th out of the 30

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NBA teams letting opponents hit 38% of their defended threes. The top five in this
statistic are the Spurs at 30.3% (22-5), Knicks at 30.4% (12-14), Heat at 31.4% (15-9),
Warriors at 31.6% (25-1) and the Bulls at 32.8% (15-8).
A recap of the important stats for the Suns coaches to look at are the ‘Adjusted
DREB Chance%’ and ‘Adjusted OREB Chance%’ for rebounding, the assist adjustment,
paint touches and points in the post for offense and finally the defended field goals
attempted and defended three-point percentage for defense. These statistics combined are
key contributors to wins and losses in the NBA and are items that should be taken into
account when looking at the SportVU data.
- Front Office
The front office and coaching staff have similar interests when it comes to
looking at statistics. The front office is going to want to know how the team is doing
overall in order to get an idea of what pieces they need to either trade or pick up in the
offseason just as the coaching staff will want to know individual statistics in order to
decide playing time, what a player needs to work on specifically, etc. They both go hand-
in-hand as mentioned earlier. The statistics that will be discussed shortly are more for the
front office to determine the value that a player is bringing to the team.
To start, the most important statistic to look at when evaluating a players’
offensive efficiency is their Effective Field Goal Percentage or ‘eFG%’. This is a field
goal percentage that is adjusted for made three pointers being 1.5 times more valuable
than a two point shot because threes are worth 50% more than twos. The point of this
statistic is to give organizations a better idea of how good certain NBA shooters are and it
allows them to compare guards to big men. To break it down a step further, players who

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take and make a large number of threes usually don’t have as impressive of a field goal
percentage as big men, due to the difficulty and location of their shots. An example
would be take starting guard Eric Bledsoe’s field goal percentage 45.3%.7 Although his
field goal percentage is 45.3%, is ‘eFG%’ is 50.5%. In comparison, starting center Tyson
Chandler’s field goal percentage and ‘eFG%’ is the same at 47.8%. This statistic will tell
the Suns’ front office that Mirza Teletovic is in fact the most effective shooter on their
roster at an ‘eFG’ of 58.9%.
When evaluating or looking for a player that can play defense, the statistic to look
at is the Percentage Points Differential. This stat looks at the difference between the
normal field goal percentage of a shooter throughout the season and compares it to the
field goal percentage when the defensive player is guarding the shooter. So a good
defender will have the differential be a negative percentage because that means that he
holds his opponent to a field goal percentage below his season average. According to the
numbers, without total minutes or minutes per game as a factor, Cory Jefferson has the
best differential at -10.1%. However, if you consider playing time Ronnie Price holds his
opponents to -3.7% and the max contract guard, Eric Bledsoe maintains a differential of -
1.8%. Good to see that he is doing more than just scoring. Regardless, it is clear that the
Suns need to find someone that can lock up opposing stars. Some of the league’s best
(contains players that have played at least half of their games) include Aaron Brooks at -
13.7%, Thomas Robinson at -12%, LeBron James at -11.8%, Jason Smith at -10.2%,
Tony Snell at -9.9%, and surprisingly (but also not that surprising because he is most
likely put on some of the weaker offensive players) Carmelo Anthony at -9.7%.
7 “Eric Bledsoe.” Basketball-Reference.com. Web. 17 Dec. 2015.

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When the front office is looking at point guards, the ‘Potential AST’ statistic is
one that holds underrated value. The ‘Potential AST’ statistic is the number of passes by
a player to teammate in which the teammate attempts a shot, and if made, would be an
assist. In other words, if Eric Bledsoe drives and kicks it to Mirza Teletovic for an open
shot and he shoots it, that is a ‘Potential AST’. The reason this is such an important
statistic is because it shows that the individual is creating opportunities for other players,
whether they go in or not. At that point, the point guard is doing all that he can do and
control, and the rest is up to his teammate to finish the play. For the Suns, starting guard
Eric Bledsoe averages 6.5 assists with the potential of 13.5 per game, while his partner in
crime Brandon Knight averages 5.2 assists with the potential of 9.6 per game. Again, this
is an important statistic for the front office to look at because outside of point guards
creating more opportunities for their teammates, they also need to prove that they aren’t a
one dimensional player in terms of scoring. Having a dual-threat guard that can score and
pass is paramount in today’s game.
Three important statistics that will tell the higher-ups what kind of scorer a player
is, are the catch and shoot percentage, the pull up field goal percentage and drives per
game. These three statistics all correlate, especially for the Suns’ two-point guard system.
And the reason that these are so important, specifically for the Suns, is because it gives
the front office an idea as to how they should play the two together. Let’s break down
Brandon Knight and Eric Bledsoe using these three categories and from there it’ll be
simpler to explain. Below are the statistics for both Bledsoe and Knight in the shooting
categories.

P a g e | 21
As evident from the table above taken directly from the NBA’s site, Bledsoe
thrives off of creating for himself shooting over 10% better off the dribble from the floor
as opposed to having someone pass him the ball and letting it fly. His three-point
percentage is even up 7%. Knight, conversely, shoots about the exact same from the floor
at a little over 38% but drops off significantly when shooting pull up threes as opposed to
catch and shoot long range shots.

P a g e | 22
Bledsoe leads the entire NBA in drives per game more than doubling the amount
of attempts from his counterpart, Knight. While they both shoot a high percentage, their
pass percentage (which is not shown above) shows that Bledsoe is more willing to pass
the ball 39.3% of the time on his drives than Knight is at 22.4%. Putting all three
together, the numbers say that while they are extremely similar players, Bledsoe should
have the ball in his hands, or at least be the one bringing the ball up the court and the
primary ball-handler, the majority of the time with Knight off-ball looking to spot up or
slash. Bledsoe shoots the higher percentage off the dribble, is two times more likely to
drive but also more likely to pass. That is why Knight should be off-ball working on
getting open when Bledsoe drives so he can be ready to catch and shoot or catch and go
straight to the hoop.
A quick recap of the crucial stats to look at from a front office perspective are the
effective field goal percentage for an overall look at how good a shooter is, the
percentage points differential to understand a player’s value on defense, the potential
assist for guards but point guards especially, and wrapped it up with the catch and shoot,
pull up and drive statistics to compare star guards Bledsoe and Knight.

P a g e | 23
Conclusion
The fact that the NBA teams leading the categories presented are also the teams
that are atop the league standings are not a coincidence. It is no coincidence that the
Warriors, Spurs and Cavaliers are teams that are consistently mentioned throughout this
paper. They dominate these areas and the effect is seen throughout their play and overall
wins. As mentioned in the introduction, the mission of this paper was to help the Phoenix
Suns staff members, specifically the front office, coaching staff and athletic trainers, to
find a way to better utilize the enormous amount of data that they are presented with
daily. In today’s age of technology, the amount of data that NBA teams end up with is
incredible and, as the staff has hinted, even overwhelming at times. The ability to not
only understand the data but also to be able to utilize it in a way that is productive for
your team is what sets organizations in the league apart. Hopefully, this in depth look at
SportVU did just that.

Phoenix Suns SportVU

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