Before getting into the meat of this final installment, I must apologize in advance for the brevity in this last segment. Time constraints have made it impossible to thoroughly peruse individual offensive and defensive efficiency.
That may be a good thing for you the reader, because you can read the dictionary about as quickly as you can go through all the steps involved in calculating individual efficiency. Suffice it to say that there are several parts to this calculation. One must have a lengthy formula on a spreadsheet where a player’s and his team’s statistics can be inputted, and the spreadsheet spits out the numbers.
If you really want to know the entire process, then you absolutely must purchase the book by the number one authoritative source on the matter.
The book is: Basketball on Paper: Rules and Tools for Performance Analysis by Dean Oliver. You might be able to find it in a library, as it is included in the catalog of more than 750 libraries throughout the nation, more than likely at a local college or university library near you.
Just to show you how involved the formulas are, it takes 18 separate calculations from start to finish for each player’s offensive number and almost as many for his defensive number.
The NCAA Selection Committee will use Team Offensive Efficiency and Team Defensive Efficiency in their process of picking the at-large teams and seeding all 68 teams. This is rather simple and can be explained briefly.
Offensive Efficiency = Points scored per 100 possessions
Defensive Efficiency = Points allowed per 100 possessions.
In the 21st Century, possessions are kept as a statistic, but if you cannot find this number, you can estimate it very accurately by this formula.
Team Possessions = FG Attempts + (.475* FT Attempts) – Offensive Rebounds + Turnovers
In the NBA, substitute .44 for .475 in FT Attempts.
Obviously, round the product from the Free Throw Attempts formula to the nearest whole number.
Let’s look at some examples for a game, a season to date, and some past seasons.
Example #1. Nevada vs. Air Force, January 19, 2019
Nevada defeated Air Force 67-52 last Saturday in Reno. The Wolfpack totally shut down the Falcons’ offense, while Air Force played capable defense on the perimeter, forcing Nevada players to hurry their three-point shots.
For the game, Nevada had 57 total field goal attempts, 23 free throw attempts, 9 offensive rebounds, and 14 turnovers.
To calculate possessions, plug the numbers into the equation:
57 + (.475 * 23) -9 + 14 = 73
For Air Force, their stat line included 51 total field goal attempts, just 9 free throw attempts, 3 offensive rebounds, and 21 turnovers.
51 + (.475 * 9) -3 + 21 = 73
Possessions must be equal or off by one or two between the teams, because after one team completes a possession, the other team gets the ball. Two is the most advantageous one team can have over the other in possessions. This comes about when the team that gets the opening tap also gets the last possession of the first half, as well as the first and last possession of the game. It happens very rarely, because in order to have the first and last possession of both halves, there must be an odd number of jump ball calls in the first half so that the team that got the opening tap also gets the first possession of the second half..
Let’s get back to the calculation.
Nevada scored 67 points on 73 possessions
67/73 = 0.918 or 91.8 points per 100 possessions
Air Force scored 52 points on 73 possessions
52/73 = .712 or 71.2 points per 100 possessions
Example #2: Gonzaga vs. San Francisco, January 12, 2019
In this key West Coast Conference game with first place in the league on the line, Gonzaga went to the Bay and beat the Dons 96-83.
Gonzaga: 69 FGA, 21 FTA, 12 Off Reb, 4 TOV
69 + (.475 * 21) – 12 + 4 = 71 possessions
USF: 69 FGA, 25 FTA, 14 Off Reb, 5 TOV
69 + (.475 * 25) – 14 + 5 = 72 possessions
Gonzaga 96 points on 71 possessions = 1.352 points per possession or 135.2 points per 100 possessions.
San Francisco 83 points on 72 possessions = 1.153 points per possession or 115.3 points per 100 possessions.
Example 3: Michigan Wolverines to date
Michigan used to win games by three-point barrages and fast break points and limited defense. Then, after assistant coach Luke Yaklich came to Ann Arbor to install his multiple defenses, the Maize and Blue became just as tough on the defensive side if not better defensively.
So far this year, the Wolverines have these offensive and defensive stats through 18 games.
Offense: 1,021 FGA, 318 FTA, 165 Off. Rebounds, 175 Turnovers in 18 games
1021 + (.475 * 318) – 165 + 175 = 1,182 total possessions and 65.7 possessions per game.
Michigan has scored 1,306 points in 18 games.
1,306 / 1,182 * 100 = 110.5 points per 100 possessions.
Michigan’s Defense has given up: 1,003 FGA, 210 FTA, 142 off. Rebounds, and 237 turnovers.
1,003 + (.475 * 210) – 142 + 237 = 1,198 total possessions and 66.6 possessions per game.
Michigan has surrendered 1,027 points in 18 games.
1,027 / 1,198 * 100 = 85.7 points per 100 possessions.
A raw point spread between two teams can be estimated by combining their offensive and defensive points 100 possessions and factoring in strengths of schedule and home court advantage.
Let’s look at State vs. Tech in an imaginary matchup.
State has an offensive efficiency of 110 points per 100 possessions and a defensive efficiency of 90 points per 100 possessions against a schedule 3 points weaker than average. They average 76 possessions per game, and their home court advantage is worth 3 points.
Tech has an offensive efficiency of 102 points per 100 possessions and a defensive efficiency of 99 points per 100 possessions against a schedule 8 points better than average. They average 66 possessions per game.
For the year in question, the national average for possessions is 70 per game, so State plays at a tempo of about 8.6% above average, while Tech plays at a tempo of about 5.7% below average. Because it is easier for one team to slow pace down more than it is for another team to speed pace up (unless they press full court for most of the game), it can be estimated that this game will have about 69 possessions.
If State outscores its opponents by 20 points per 100 possessions, in 69 possessions, this equates to 13.8 points.
If Tech outscores its opponents by 3 points per 100 possessions, in 69 possessions, this equates to 2.07 points.
To this point, State looks like an 11.73 point favorite over Tech, but this is not the case. Schedule strength and home court advantage must be included.
If Tech’s schedule on average has been about 11 points tougher per game than State, you then add those 11 points in Tech’s favor. Now, the State’s advantage has been reduced to 0.73 points. Tech’s home court advantage is 3 points, so the expected outcome would be State by 3.73, or 4 points.
This is a crude method once used by the PiRate Ratings, as the Blue Rating. We no longer use this method, as there are more accurate ways to determine pointspreads, namely using algorithms of the Four Factors with schedule strengths, home court advantage, and road team disadvantage.
Example 4: Villanova 2018 season
The Wildcats won their second national championship in three years last season, finishing with a 36-4 record. They scored 3,463 points and allowed 2,807 points in 40 games.
Here are their pertinent stats to calculate efficiency.
Field Goal Attempts: 2,440
Opponents: 2,401
Free Throw Attempts: 718
Opponents: 641
Offensive Rebounds: 380
Opponents: 378
Turnovers: 426
Opponents: 512
Possessions: 2,440 + (.475 * 718) – 380 + 426 = 2,827 (70.7 possessions per game)
Opponents: 2,401 + (.475 * 641) – 378 + 512 = 2,839 (71.0 possessions per game)
Offensive Efficiency
3,463/2,827 * 100 = 122.5 points per 100 possessions
Defensive Efficiency
2,807/2839 * 100 = 98.9 points per 100 possessions
How does this compare to past national champions? Because offensive rebounding stats were not officially kept until this century, it can only be estimated for the 20th Century. No doubt the UCLA teams of 1967 thru 1969 and 1972 and 1973 would be off the charts great, as the Bruins dominated in every aspect of the game during their dynasty years.
There are some very fine teams that won championships in recent years, so let’s look at the national champions during this time. The number shown is the total scoring margin per 100 possessions. Of course, schedule strength is not equal for these teams, but on the whole, there is not a lot of difference, as these champions all played schedules between 5 and 10 points above the national average.
When adjusted to schedule strength, here are the 10 best teams in the 21st Century using the PiRate Ratings formula.
2008: Kansas 124.0
2001: Duke 123.6
2018: Villanova 122.9
2010: Duke 122.1
2013: Louisville 121.8
2005: North Carolina 121.7
2012: Kentucky 121.5
2015: Duke 121.3
2016: Villanova 120.9
2009: North Carolina 120.3
2007: Florida 120.1
2002: Maryland 119.6
2004: Connecticut 117.9
2006: Florida 117.1
2017: North Carolina 117.0
2011: Connecticut 115.8
2003: Syracuse 115.1
2014: Connecticut 111.6
Note that the national champions through these seasons were not necessarily the highest rated team by efficiency. For instance, Connecticut was not considered a factor at the end of the 2011 regular season. They finished tied for 9th in the Big East, and thus they had to play in the opening round of the conference tournament. To win the conference tournament, they would have to do something never done before or since–win five games in five days. The Huskies became the big story of Championship Week win Coach Jim Calhoun rode his star guard Kemba Walker to the title, winning five games in five days at Madison Square Garden, as Walker performed for his friends and family from the Bronx, averaging 26 points per game by taking it to the hoop and drawing enough fouls to shoot 54 free throws in just five games.
The Huskies were on a roll, and they won six more games in the Big Dance. They finished 11-0 and still only rose to 15.8 points better than average against an average schedule. Before this 11-game streak, UConn was just 9-9 in the conference. However, the Huskies had played a very difficult schedule that included 18 ranked opponents, in which they went 12-6 in those games. All nine of their losses came to NCAA Tournament teams, so strength of schedule was terribly important in factoring their adjusted efficiency.
2019 Top Efficiency
By now, you must want to know which teams are at the top in total efficiency? It should come as no surprise that the NET Ratings and the Efficiency Ratings are about the same.
Virginia, Duke, Michigan State, Gonzaga, and Tennessee are at the tops in adjusted efficiency, or to put it bluntly, what the NCAA Selection Committee will look at. Likewise, these are also the top five teams in NET Ratings, so if the Selection Committed picked the bracket today, four of these five would be your number one seeds, and the fifth would be the top number two seed.
This doesn’t mean that one of these five teams will win the national championship, but the odds are that from this group of five, there is about a 50-50 chance that one will win the title. Of course, this is only a mid-season ranking. The ranking on March 17.
Individual Efficiency
I won’t begin to explain individual offensive and defensive efficiency, as my only recommendation it to read Basketball on Paper, as Oliver is the Bill James (or Tom Tango) of basketball analysis.
Let me just list which players from the power conferences rate at the top.
Can you guess who is the current number one player in efficiency? I bet if you had one free guess to win a car on a game show, you’d win the car.
The best player in college ball today is the best player in total efficiency. It comes as no surprise that Duke’s Zion Williamson is number one, and he is far ahead of the field. Gonzaga’s Brandon Clarke is a distant number two, and Wisconin’s Ethan Happ is almost as far being Clarke in third place as Clarke is behind Williamson.
Before you think that this rating is due to just these three players being great, let me add that their coaches and teammates are also important in this rating. Coach Mike Krzyzewski has produced a lot of highly efficient players. Sure, most of them were McDonald’s All-Americans, but there are some of these 5-star players in recent history that are not all that efficient.
Vanderbilt’s Simi Shittu was the Number 7 overall player in this current freshman class, a 5-star McDonald’s All-American. The Commodores are one of the least efficient teams from a Power Conference, and Shittu’s numbers have headed south once SEC play began, and the opposition quickly learned his liabilities. Shittu actually owns a negative offensive efficiency rating through 17 games, and an even worse rating in five conference games, as he has negative efficiency in both offense and defense. It doesn’t help his efficiency when he has a 7.8% three-point accuracy, low free throw percentage, and a high turnover percentage. I have heard comparisons made to former St. John’s 5-star player Wayne McKoy from the 1970’s, when McKoy went from top player in the freshman class to never playing in the NBA.
The Pi-Rate Ratings 