A Case Study in How Tempo and Style of Play Impact Individual Stats

 

Most readers will be at least somewhat familiar with the name London Perrantes.  After all, for the past four seasons he has been a backcourt mainstay for Tony Bennett’s University of Virginia Cavaliers.  During those four seasons starting with 2013-14, UVA went 30-7, 30-4, 29-8 and 23-11.  Certainly, even casual college fans would be aware that during that period, the Cavaliers recorded those ledgers playing roughly half of their games against tough ACC comp.  No one would argue that Virginia was operating extremely successfully at the very highest level of college basketball

During those 4 years, lead guard Perrantes accumulated the following stats:

  • Freshman- 29.9 mpg., 3.8 apg., 3.5 to 1 assist/turnover ratio and .127 assists per minute.
  • Sophomore-33.3 mpg., 4.6 apg., 3 to 1 assist/turnover ratio and .139 assists per minute.
  • Junior-33.2 mpg., 4.4 apg., 2.4 to 1 assist/turnover ratio and .121 assists per minute.
  • Senior- 32.1 mpg., 3.8 apg., 2.2 assist/turnover ratio and .117 assists per minute.

By themselves, Perrantes’ UVA assist/to ratios and assists per minute are impressive and no one would argue that Perrantes played the point guard position at a very high level on a very high level team.  His value to his team was extremely high.

Now, fast forward to several weeks ago when Perrantes played at the Portsmouth Invitational.

Very early it was apparent that he was an accomplished floor leader making plays that directly led to scoring opportunities as well as countless passes on the money that contributed to great ball movement.  That wasn’t surprising by itself because he did that at Virginia.  The difference at Portsmouth was the FREQUENCY of the quality plays.  Last season Virginia played at the second slowest pace in Division I (350 of 351).  Only St. Mary’s (California) played slower.

At Portsmouth, Perrantes’ team averaged 97 points a game.  The pace is general blistering because the PIT is predicated on showcasing college seniors for NBA scouts.  As a result, his PIT stats blew away his UVA numbers.  Playing against 63 other of the nation’s best college seniors, Perrantes averaged 30.0 minutes, 8.7 assists, .289 assists per minute and had an assist/to ratio of 3.25.

Granted, one might argue that 3 PIT games is an insufficient sample size-especially compared to the 142 UVA games in which Perrantes played.  But, clearly, if Perrantes played at the PIT pace for 142 games at 30 minutes each, his numbers would easily exceed his UVA numbers

But that is where Player Efficiency Rating should come in because it allows for pace.  Colleague Dan Hipsher, currently an assistant at Oakland University, points out the flaw in that thinking.   Style of play can be a significant difference maker when it comes to assists for point guards.  Perrantes never averaged more than 4.6 assists at UVA, yet in fewer minutes at PIT, he averaged 8.7 apg.   In addition to the PIT pace, the sets there are screen/roll oriented so the point guard has the ball in his hands more.  Whereas, the offensive philosophy at Viginia is predicated on winning without McDonalds’ All-Americans against McDonalds’ All-Americans.  

At UVA, once he gave up the ball on entry, he would assume a wing role in a double stack format for much of the possession.  And in that offensive scheme as Coach Hipsher points out, just as in all motion type offenses, after entry the numbers of touches is democratic and somewhat restrictive for accumulating assists.

So, what are takeaways for coaches?

  • Statistics should never be taken on face value.  Great examples are NBA and NCAA team and individual rebounding stats from the 50’s 60’s and 70’s.  In 1960, Wilt Chamberlain had 55 rebounds in an NBA game and averaged 27.2 rebounds a game for the season.  Artis Gilmore averaged 22.7 rebounds a game for Jacksonville in 1971 and Bill Chambers of William and Mary had 51 rebounds in a 1953 game.  Simply put, in those years teams took more shots and missed a higher percentage causing more rebounds.   Shot selection and shooting accuracy have improved significantly since.
  • Whether or not a player or a team is effective at a certain pace and/or offensive style, until they play at a different pace or style, it’s difficult to predict the outcome.  One didn’t know Perrantes would be successful at a fast pace until he was.  One might have suspected it but knowing comes with proof.
  • If one player on a team plays more effectively and efficiently at a different pace or with a different style, what would a coach do if two or more other teammates did the same?  Sometimes coaches get comfortable with a pace or style when current personnel might dictate otherwise.   

 

One comment

  1. The depth and attention to statistical details as they relate to different players, different team playing styles, different league play situations, even the same player in highly varying situations. The statistics become dynamic, fluid. The different ways of analyzing the stat along with the other variables to my mind make them so much more reflective and usable. Your work is appreciated Coach.

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