The Pi-Rate Ratings

February 20, 2020

Comparison of Old & New R+T Ratings

We hope you read our piece earlier this week describing our updated R+T Rating for 2020.  If you didn’t, and if you are a new reader to the PiRate Ratings, after thanking you for stopping buy and remembering you are getting exactly what you paid for here, the following is a quick tutorial on what R+T Rating means.

  1. The R+T Rating is a metric that applies only to the NCAA Tournament.

  2. The R+T Rating attempts to estimate extra scoring opportunities by teams in NCAA Tournament games.

  3. Over the last two decades when the needed statistics to calculate R+T Ratings, the National Champions and most of the Final Four teams rated near the top of the field in R+T Rating.  

  4. The reason the R+T Rating is so important in the NCAA Tournament only is because the other metrics are better applied in an environment where half of the teams in Division 1 are below average offensively, while a separate half of the teams in Division 1 are below average defensively.  In the NCAA Tournament, almost all teams are above average offensively and defensively, so these extra scoring opportunities frequently are the difference.   It only takes one nice scoring spurt to win a tightly contested game in the Big Dance.

We used the same R+T Rating for almost two decades, only slightly tweaking the weighting for these stats.  The old R+T Rating, which we will continue to publish this year, is:

(R * 2) + (S * .5) + (6 – Opp S) + T

R = Rebounding Margin
S = Average Steals Per Game
T = Turnover Margin

This metric shows that rebounding margin is more important than turnover margin, but steals are more important than other types of turnovers.  The reason is that steals lead to the most potential points per possession.  When a team steals the ball, they are usually facing their own basket (whereas on a rebound, their backs are to their own basket).  The team committing the turnover by steal must do a 180° turn to defend, and the stealing team takes off on a fast break.

This R+T Rating helped us pick some big upsets for many years.  Teams with high R+T Ratings and adequate strengths of schedule advanced in the tournaments at the expense of teams with low R+T Ratings.  In multiple years, teams with negative R+T Ratings lost quickly in the Big Dance, even teams that were #2, 3, and 4 seeds.  We correctly picked two different Georgetown teams to be upset as heavy favorites, because those Hoya teams had negative or very low positive R+T Ratings.  For three years, we picked Vanderbilt to lose in the first game against underdogs because Vanderbilt also had negative or very low R+T Ratings.  At the other end of the spectrum, the team with the highest R+T Rating and a significantly strong schedule has cut down the nets multiple times.

If the R+T Rating has been an accurate predictor of potential NCAA Tournament success, why did we need to create a new version?  We did so, because the old version simply counted actual margins without concerning itself with possessions.  Rate stats are more accurate than counting stats.  As we have used as an example many times, a team that outrebounds its opponents 35-30 has done a better job than a team that outrebounded its opponents 43-37.  Strictly counting 43-37 is +6 and 35-30 is only +5, but 35-30 is 53.85% while 43-37 is 53.75%, so 35-30 is a tad better.  We want our stats to be as accurate as possible, so we switched to rate stats over counting stats.

But, we have an issue.  The variables now must change as well, because percentages are totally different from standard numbers.  We have tried to back-test the new variables and include a constant to try to make the outcome look the same but more accurate.

Here is the explanation for the new R+T Rating.

1. Use 4-Factors Rate Stats
A. Offensive Rebound %
B. Opponents’ Offensive Rebound %
C. Steal %
D. Opponents’ Steal %
E. Turnover %
F. Opponents’ Turnover %

2. Take the difference in each stat from the national average for each stat. There will be discrepancies in the offensive and defensive averages due to D1 vs. D2 games, so we set the national average from the mean of the offensive and defensive norms.
For example: O Reb% = 28.43 & D Reb% = 27.79, then the mean Reb% for Division 1 in 2020 is 28.1.

3. For Rebounding Rate Margin & Turnover Rate Margin take the sum of offensive and defensive rates and divide by 2.
Example: A team’s OReb Margin is +6.4% and DReb Margin is -1.2%. Reb Rate Margin would be +2.6%

4. We Keep Steal Rate Margins Separate as in original R+T.

5. The New Formula Now Becomes:

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

 

Here’s how we calculate a sample new R+T Rate.

The Big State University Pumas have these stats

Offensive Rebounding % = 34.8.  With a national Rebound % mean of 28.1, Big State’s offensive rebound rate margin is +6.7% (34.8-28.1)

Opponents’ Offensive Rebounding % = 28.6.  With a national Rebound % mean of 28.1, The defensive margin or Big State’s opponents offensive rebound margin is -0.5 (28.1-28.6)

Now we add the two margins and divide by 2  (+6.7 – 0.5) / 2 = 3.1

3.1 would be the new R number in the equation.

Big State has a steal rate of 10.6% and a defensive steal rate of 9.6%.  The national average steal rate is 9.2%.  

So, Big State’s S Rating would be +1.4 (10.6-9.2).  Their opponents’ S would be +.4% (in this case the higher the number, the worse off it is for the team).

Big State has a turnover rate of 16.8% and a defensive turnover rate of 18.2%.  The national average for turnovers is 16.9%, so Big State’s turnover rate margin would be 0.1%, and their defensive turnover rate margin would be 1.3%.

So Big State’s T Rating would be 0.7,  (.1+1.3)/2

Now we have all the numbers we need to plug into the calculation.

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

For Big State, the equation becomes:

((3.1 * 8) + (1.4 * 2 + ((5 – .4) *2) + (0.7 * 4)))/2.75 = 14.4

Big State’s R+T Rating would be 14.4, which is about average for an NCAA Tournament Team.  We must at this point look at their schedule strength to see if it merits worthiness against teams most likely to advance into additional NCAA Tournament rounds.

So, by now you are maybe wanting to see some real R+T Ratings?  We are going to show you both the old and new R+T Ratings for the current top 20 teams in the nation.

Here is the old R+T list with the schedule strength.  For schedule strength, 50.0 is average.  55.0 and higher means the team has played a tough schedule.  Below 45.0 means the team has played a weak schedule.  Usually national champions have a strength of schedule between 56 and 62, and most Final Four Teams have strengths of schedule between 52 and 62.

Old R+T

Team

R+T No.

SOS

Gonzaga

24.6

53.9

Houston

23.0

55.8

West Virginia

20.6

60.4

Kansas

17.0

62.3

Baylor

17.0

59.4

Duke

16.5

58.6

San Diego St.

15.9

53.6

Louisville

15.3

57.6

Colorado

14.4

57.6

Maryland

13.1

59.9

Florida St.

12.8

57.9

Butler

11.9

59.7

Kentucky

11.9

56.7

Penn St.

10.3

59.8

Dayton

9.4

54.4

Iowa

9.4

60.8

Marquette

8.1

59.8

Villanova

7.5

60.0

Seton Hall

4.9

60.4

Creighton

2.2

60.3

 

Looking at the old R+T, the Big East appears to be a bit overrated this year.  The four Top 20 teams with the lowest R+T Ratings are all Big East teams.

Until last night, Duke had a much more impressive R+T than they do today, but losing by 22 to North Carolina State, and getting outrebounded and committing more turnovers and having the ball stolen more against the Wolf Pack led to the Blue Devils dropping down to sixth.

Gonzaga’s R+T is about where it was when the Bulldogs advanced to the National Championship Game against North Carolina a few years back.  At the moment, their schedule strength is a tad too low, but GU has games remaining against Saint Mary’s and BYU and likely another game against one of the two in the WCC Championship Game.  The Zags’ SOS could move up a little.

 

 

New R+T Rating

 

Team

R+T Rate

SOS

West Virginia

26.5

60.4

Gonzaga

21.5

53.9

Houston

20.9

55.8

Baylor

18.7

59.4

Duke

18.3

58.6

Colorado

15.3

57.6

Kansas

14.4

62.3

Florida St.

12.7

57.9

San Diego St.

12.7

53.6

Louisville

11.9

57.6

Maryland

10.7

59.9

Iowa

9.6

60.8

Penn St.

8.6

59.8

Butler

7.6

59.7

Villanova

5.7

60.0

Marquette

4.1

59.8

Kentucky

3.8

56.7

Seton Hall

3.1

60.4

Dayton

1.6

54.4

Creighton

-5.5

60.3

 

The new R+T gives a little more credit to three of the Big East teams.  Obviously, lower possessions per game in the Big East are partly to blame for lower counting stats, but on the whole, this does not look like a great potential year for the Big East.

Look at the top four teams here.  All four are teams that are west of the Mississippi River.  There hasn’t been an NCAA Champion from west of the Mississippi River since Kansas in 2008.  There hasn’t been an NCAA Champion from west of the Rockies since Arizona in 1997.  Did you know that the last 11 NCAA Champions came from the Eastern Time Zone?  And, did you know that the last NCAA Champion from the Pacific Time Zone was UCLA in 1995?

January 22, 2019

Fun Stuff For Stats Buffs-Part 3: Efficiency

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.

 

 

 

 

 

 

 

 

 

 

 

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