This article is by no means intended to give a full picture of Rick Barnes’ tenure at Texas, but rather point out why he may have needed to go. I am a Rick Barnes fan and appreciate everything he did for Longhorn basketball, but I also recognize that, in the immortal words of Dr. Seuss’ ‘Marvin K. Mooney’, it was time for Rick to, “Go, Go, Go.”
The concept of Pythagorean Luck is derived from the difference between a team’s Pythagorean Winning Percentage (invented for baseball by the legendary Bill James) and their actual winning percentage. In layman’s terms, this is a difference between their expected winning percentage (based on actual offensive and defensive production) and their actual winning percentage.
Pythagorean Luck may also indicate whether a team is under or over performing. Teams tend to, “regress to the mean” or average out over a lifetime. Some years you have good luck and sometimes you have bad luck.
To find Pythagorean Luck you must first calculate Pythagorean Winning Percentage. This can be done many ways and I have decided to show two of the ways in this example. (All of the mathematical calculations are at the end, so be sure to read the whole article if you are interested in that.)
TEXAS’ LACK OF LUCK
Since 2002, Texas has been a predominantly ‘unlucky’ team. Using Luck, as determined by actual points scored, Texas had been ‘lucky’ (positive luck or performing above expectations) in only four of 14 seasons (2002, 2003, 2008 and 2014). Even in years where Texas seemed to have extremely good seasons, such as 2006 and 2007, they underperformed, based on scoring.
(NOTE: this evaluation is based solely on pre-tournament data)
Using Offensive and Defensive Efficiency, Texas hasn’t fared any better. Again, four of 14 seasons show positive luck for the Longhorns. This time 2008 and 2014 still rate positively, along with 2004 and 2006.
If we look specifically at results since 2009, only in the 2014 season did the Longhorns seem to perform above what would be expected, based on scoring and defense.
I am sure this is where we could have a more detailed discussion on the lackluster offensive performances of Barnes’ teams at Texas, but the point is this – Texas still should have won more games, even with the offense they were producing.
No team should continually be on the losing side of luck, let alone so far on the other side. As a comparison, Kansas is evenly split with seven years on both sides of the luck spectrum.
TEXAS’ LUCK SINCE 2002
|YEAR||W||L||PTS||DEFPTS||OE||DE||WIN PCT||PTS PYTHAG||EFF PYTHAG||PTS LUCK||EFF LUCK|
This team has been underperforming for years and this year it was in record style.
It boils down to coaching. Luck happens. Luck changes. Poor situation coaching and poor player execution at critical times has haunted this program for a number of years and it was not getting better.
Rick Barnes’ luck had simply run out.
As I stated above, to calculate Luck, you need to first calculate Pythagorean Winning Percentage. The first way is by using actual points scored and allowed and is similar to the way baseball calculates it, using points scored and points allowed:
Pythagorean Winning Percentage = (points scored ^ x)/(points scored ^ x + points allowed ^ x), where x is a value such anywhere between 1 and 18. This formula is credited to Bill James, who applied it to baseball. Houston Rockets GM Daryl Morey is credited with creating the first use of it for basketball.
Here’s a second way to calculate PWP, using Adjusted Offensive and Defensive Efficiencies:
Pythagorean Winning Percentage = (Adjusted Offensive Efficiency ^ x)/(Adjusted Offensive Efficiency ^ x + Adjusted Defensive Efficiency ^ x).
I have elected to use these two popular methods. I have also decided to use only from 2002 to the present. The reason for this was primarily a lack of consistent data for Offensive and Defensive Efficiency. Ken Pomeroy provides this data back to 2002 on his website, so I am electing to use it.
I used approximately 8.4 and 6.5, respectively for the two equations. I arrived at this by completing a least-squares (and least square-root) analysis using all regular season games between 2002 and 2015, minimizing the error between actual and expected values.
To then calculate Pythagorean Luck, you must calculate the difference between these values and the team’s actual winning percentage. Sometimes this is calculated as a straight difference and sometimes as a deviation, using something like the Correlated Gaussian Method, popularized by ESPN and former Denver Nuggets statistician, Dean Oliver.
For my purposes, I simply used the difference (subtraction).