PART 2: PLAY TYPES: Can play types predict efficiency?

Hey guys!  I’ve been (very patiently) waiting on more games to become available on Synergy so that I could have more data to work with before diving deeper into the analysis of play types.  But, I’ve grown impatient.  So, I went ahead and had a bit of fun with the numbers that were available to see whether or not there are relationships between frequency of play types and overall offensive efficiency.  In other words, can the frequency of how possessions end predict a team’s overall offensive performance?  Or can the efficiency of a team’s play type determine a team’s overall offensive performance?  Can we deduce which play types most greatly effect overall offensive team’s efficiency?  Kind of.  We cannot necessarily say that a particular play type determines the overall efficiency, but we can say that certain play types have a greater importance in influencing overall offensive performance.  Here’s why…

When looking into the correlation between frequency of play types and overall efficiency (average PPP in overall offense), we can see some significant relationships.  I performed a regression analysis between each team’s play type frequency and their overall offensive efficiency.  In the table below, you can observe each play type with it’s corresponding R-value and I added another column of its P-value to show significance.

Freq

Based on the Pearson’s R value, there was a strong relationship between the frequency of a team’s possession ending in cuts and its overall offensive efficiency.  This is telling us that the more teams that end plays in cuts (regardless of if they capitalize on those cuts by scoring) then the greater offensive performance the team will have.  Offensive rebound put-backs also showed to also be important in determining overall offensive efficiency.  This probably explains why Sheffield is such a hard team to beat and why they’ve blown teams away by greater margins.  Sheffield’s frequency of OR put-backs (9.20%) and cuts (20.10%) are much higher than any other team in the league, thus resulting in better offensive efficiency.

To be honest, I was shocked to see correlations at all.  I expected play type efficiencies to have a more positive relationship with overall efficiencies than frequencies.  Wouldn’t you, too?!  So, I looked into that next.

I did another regression analysis of the play types efficiency ratings for each team and the overall offensive efficiency ratings.  I didn’t find as strong relationships as I thought I would, but I did find that transition and cuts both served to be important play types that may predict a team’s overall offensive efficiency in our league.  Spot ups also had a moderately strong relationship with overall offensive efficiency.  In the table below you’ll see the results from the analysis.

PPP

Takeaways:  Just because a play type is a higher efficiency play type (meaning it has a high average PPP) does not mean that it matters as much in regards to determining overall efficiency.  For example, offensive rebound put-backs are a very efficient way of scoring (hence the 0.919 average PPP in the WBBL), but whether or not your team is scoring on those put-backs does not impact a team’s overall offence as much.  This makes sense if you think about the fact that most teams are good at capitalizing on put-backs.

This same method of regression analysis can be used when looking at just one team, too.  In fact, I think this type of analysis would be more meaningful when performed with a single team.  If you can pin point which play type(s) more greatly affects an opponent’s offensive performance, then you would know which play types to prevent them from executing.  Or you could analyse your own team and observe which play types are resulting in higher offensive efficiencies.  This can tell the coach which play types to focus on or improve on.  And this will very likely vary from team to team.

Again, as I mention at the end of every analysis I perform, we must consider the small sample sizes I’m dealing with.  Unfortunately, not all the games played thus far in the WBBL have been successfully uploaded for me to see the detailed statistics, so the results above may be skewed.  Regardless, the idea and analyzation method of the numbers is the same.

Until next time…

“Any powerful idea is absolutely fascinating and absolutely useless until we choose to use it.” – Richard Bach

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