2012 Gotta Make Shots Series Part 5

This is the 5th and final post in my 2012 Gotta Make Shots Series.  In the first 4 posts, we took a look back at the last 2 years of the Minnesota state tournament.  In this edition, we'll add up all the totals from the last 4 years and add some stats from our friends to the south.

To see all posts in the series, click here.

Tallying up the Minnesota Results
For 2012, teams with more shots had a combined record of 16-15 (a bit surprising).  Teams with the better shooting percentage were 23-9.

For 2011, teams with more shots were 10-19 while teams with the better percentage were a dominating 26-5

If you add in 2010, teams have combined over the last 3 state tournaments for a record of 40-50 (44.4%) when their team attempts more shots.  Teams with the better shooting percentage have combined over the last 3 years for a record of 73-22 (76.8%)

Class A was especially telling during that time.  Teams with a better shooting percentage were 21-3 while teams with more shots were 7-15.  Class AA teams were 11-12 with more shots but 16-8 with a better percentage.  Class AAA saw results of 12-9 for teams with more shots vs 18-5 with a better percentage.  Finally in class AAAA, teams with more shots were 10-13.  Teams with the better shooting percentage were 18-6

The Iowa Basic Tests
This section comes out of a discussion with blog pal John Carrier, read his coaching blog here.  What we're looking for is a holy grail type of statistic.  Given Stat X, your team will win.  In Iowa teams are required to submit their stats to a specific site on a monthly basis.  That gives us the ability to look at some other stats and see if there's a correlation. We'll use the 2011-12 stats from their 373 teams to do this.  We'll take different stats and see how they correlate to a team's win total.  To determine if there's a correlation, we'll use the Pearson product-moment correlation coefficient (click here to read more about it).  Its a widely used calculation to determine the strength of correlation between 2 items.  The value ranges from -1 to +1.   A value of 0 means no correlation.  A value of 1 is the strongest possible positive correlation.  More of X = more of Y.  -1 is the worst, More of  X means less of Y.   Anything from .1 to .4 is a mild correlation, .4 to .7 is a medium correlation, above .7 is a strong correlation.

In the spirit of this series, the first value we'll calculate is the correlation between wins and FG%.  This can be done with 4 values: Overall FG%, 2 pt FG%, 3 pt FG% and Effective FG%.  Effective FG% is calculated as (FGM + (3s made * 0.5))/FGA.  Here are the results of the correlation calculations.

• Wins and FG% = 0.78
• Wins and 2 Pt FG% = 0.7481
• Wins and 3 Pt FG% = 0.5756
• Wins and Effective FG% = 0.7749

As a Wisconsin guy, lets pull out a favorite Bo Ryan statistic, Points Per Possession.  This is an all encompassing stat of offensive efficiency.  Possessions isn't an exact science and there are many different calculations out there for it. For our purposes, total possessions for a team is calculated as FGA - Offensive Rebounds + Turnovers + (.475 * FT Attempts).

Wins and Points per Possession: 0.8260

This leads us to the Hubie Brown portion of the hypothesis which was that a team needs to increase possessions to be successful.

Wins and Possessions: -0.0902

Since the name of the game is basketball, let's look at the basic stats of points for and points against.

• Wins and Points Per Game Scored: 0.7940
• Wins and Points Per Game Allowed: -0.6421

These are reasonably in line with expectations but notice how points allowed has a fair difference between points allowed.  But both are significant which is logical.

Lets combine a couple of the stats

• FG% and Points Per Game: 0.8090
• Effective FG% and Points Per Game: 0.8150
• Effective FG% and Points Per Possession: 0.9174

The scoring factor that hasn't been looked at yet is Free Throws

• Wins and FT%: 0.4698
• Wins and FT Made Per Game: 0.5432
• FT% and Points Per Possession.  0.6136

So free throws aren't nearly the factor that field goals are.   Since there's a much narrower range of free throw % values, it makes sense that number of free throws made would be more important than the % that you make.

Hubie Brown also talked about offensive rebounds and turnovers as factors so let's look at those next.

• Wins and Offensive Rebound %: 0.5234
• Wins and Turnovers Per Game: -0.3586

We talked about scoring above, but does it matter when you score?

• Wins and Average Pts in 1st Qtr: 0.7831
• Wins and Average Pts in 2nd Qtr: 0.7028
• Wins and Average Pts in 3rd Qtr: 0.7018
• Wins and Average Pts in 4th Qtr: 0.3240

This gives big importance to getting off to a good start.  2nd and 3rd quarters about the same which is logical.  4th quarter being surprisingly not important can be explained by bench play in blowouts.

Teams talk about being unselfish.  Here are a couple of assists stats.  Take it with a grain of salt because assists at the high school level are notorious for how inaccurate they are.

• Wins and % of field goals with an assist: 0.2721
• Wins and Assist/Turnover ratio. 0.7150

This was interesting because we saw the base turnover number above was surprisingly low.  But this leads again to the theory that you can outshoot your turnovers.  Less assists would mean a lower ratio and less wins.

This isn't a scientific study by any means, but it does provide some interesting results.  Defensive numbers weren't available but doing some of these stats on the defensive end such as FG% against, Points Per Possession against etc would also be very interesting to see.  Those stats weren't directly available

Conclusions

• Field goal percentage is still king.
• Turnovers aren't as big a deal as expected.  You can overcome them with good shooting.
• 4th quarter scoring isn't all that big of a deal.
• Number of possessions has no meaning.