November 20, 2017

Basketball Metrics Infographic

The infographic below was created by for Seldom Used Reserve by Clemson graduate @adameargle of the Eargle Design Company.  For more info on Adam’s creations you can visit adameargle.com or click on the graphic in the right sidebar.2013_2014BBall-01

Basketball Metrics, Charts, Graphs

Below are some of the metrics, graphs and charts I’ve developed for the basketball team. Some prefer charts, some graphs, some neither. While I appreciate numbers in a table, the graphs can give you a snapshot of what’s happening on say, 2 point and 3 point shots.  In two seconds I can tell Landry Nnoko leads the team in % of two point shots made and Adonis Filer has the highest % on 3s.

The putrid 3 point shooting (at Littlejohn no less) against Georgia Tech pulled the Tigers down to an average of .95 points per 3 point shot (it was .97), but Clemson still averages slightly more points on 3 pointers than 2 pointers.

I’ll be interested to see what happens with free throws at Syracuse. One, will the Tigers get many chances and two, how they’ll fare if they do.  The trend (towards bottom) is slightly downward and the Tigers don’t shoot free throws as well on the road or in ACC play.
2014 Basket Composite 21 All
2014 Basket Composite 21 3PT
2014 Basket Composite PDIFF 21
2014 Basket Composite DPP 21
2014 Composite 21 2PT
2014 Basket Composite TP 21
2014 Composite 21 FT TRENDLINE
2014 FT Breakdown 21
2014 Composite 21 Ind Scr Eff
2014 Composite 21 Ind 2 Pt
2014 Composite 21 Ind 3 Pt

New and Improved Basketball Metrics

I’m still working through the fine details and have plenty of graphs and charts to choose from, so bear with me as I bring this into the 21st century. Until then I hope these suffice.

In this first table I break out 2 and 3 points shots.  What’s interesting is that in “official” stats 2 point shots don’t exist on their own anymore, while 3 points shots taken and made are split out.  That just goes to show you how much the 3 point shot dominates the media these days.  In the coming days I hope to post some information on why the 2 point shot is more important than the 3 point shot (at least for Clemson) despite the hype of the 3.

The Avg Pt/2 and Avg Pt/3 show the average points a player gets for each type of shot.  Basically this takes the % for each shot and translates that to “expected points”.  For example, K.J. McDaniels is shooting 52.6% on 2 point shots.  This means Clemson can expect 1.05 points every time McDaniels shoots a 2 pointer.

The % 2’s and % 3’s show what % of the players shot falls into each category.  In this example, McDaniels shoots 69.8% of the time from 2 point range and 30.2% of the time from 3 point range.

MP/Shot, MP/PF and MP/TO give the average minutes played per shot, personal foul and turnover for each player.  In the table below we see that McDaniels shoots once every 2.5 minutes, commits a foul every 18 minutes and turns the ball over every 13.3 minutes on the court.

Scr Eff is short for scoring efficiency.  This equals points scored divided by potential points (based on number of 2 point shots multiplied by 2 + number of 3 point shots multiplied by 3 + number of free throw attempts).

The totals are interesting in that you can argue that Clemson should shoot more three point shots since they average 0.97 points per 3 vs. 0.93 per 2 point shot.

2014-BB-Indiv-20

The two graphs below track offensive and defensive points per possession for each game.  On the offensive side it’s easy to see the decline since ACC play began (expected), while on the defensive side you can see what happened in the Pitt and North Carolina games quite clearly.
2014-BB-OPPS-20
2014-BB-DPPS-20

The chart below shows the difference (+/-) in points per possession on the offensive and defensive ends for each game.  These numbers indicate that Furman (+0.61) was the largest positive differential and Pittsburgh the worst differential for Clemson.
2014-BB-PLUSMINUS-20The chart below includes 2 and 3 point field goal percentages for Clemson in each game.  It shows Clemson can generally survive an off night shooting 3s, but is much less likely to survive a bad night shooting 2s.  The reason is in the first chart above – 68.2% of Clemson’s shots are from 2 point range and only 31.8% from 3 range.
2014-BB-PCTS-20

This is the same free throw breakdown I’ve been providing for the last several weeks in a different format.  Trending down slightly as 69.6% over the last 5 games indicates.
2014 FT Breakdown 20

Tar Heels Top Tigers, 80-61

Metrics from North Carolina’s 80-61 win over Clemson Sunday night in Chapel Hill.

MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)

Composite Basketball Metrics After 17 Games

Notes and minutiae through the first 17 games of Clemson basketball

  • The Tigers have 9 players averaging at least 11.6 minutes per game.
  • Clemson has managed to win the last two games (@ Va. Tech and home vs. Wake Forest) without Rod Hall’s best games.
  • In the last 3 games Clemson has taken 71 free throw attempts compared to 39 for their opponents.
  • Landry Nnoko continues to be efficient offensively with a 3 for 4 day from the field and 2 of 2 from the line vs. Wake Forest.
  • Jordan Roper and Adonis Filer each have given Clemson something that has been missing in the recent past – someone who can create their own shot.
  • I commented about this during the Wake game, but Josh Smith is vastly improved.  I know, no one quakes in their Nike’s when they see Smith and his 2.3 points and 3.1 rebounds per game don’t seem like much.  But those numbers come in an average of 12.6 minutes.  It’s probably not a wise idea mathematically, but by doubling his minutes Smith’s numbers could be 4.6 and 6.2.  For comparisons sake Landry Nnoko averages 5.7 points and 6.6 rebounds in 24.2 minutes.  Smith still has plenty of rough edges, but he gives Brownell a solid 8-12 minutes per game.
  • Tough stretch coming up that may define the season.

 

MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)

Tigers Defeat Deacs, 61-53

In what was not the prettiest game in the history of college basketball Clemson defeated Wake Forest 61-53 on Satuday with a little help from – well, almost everyone.

Ibrahim Djambo buried 2 three-point shots, Josh Smith scored 3 first half points and pulled down 3 rebounds in 12 minutes and Landry Nnoko not only went 3 of 4 from the field he also made his only two free throw attempts.

Over the last 3 ACC games (Duke, Va. Tech and Wake Forest) Clemson has now attempted 71 free throws while opponents have only attempted 39.

The Tigers went 18-21 from the line Saturday, raising their season mark to 75.3% overall, 77.3% at home and 71.0% in ACC.


MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)

Clemson Free Throw Shooting By Game
FT2014-17

Clemson moves to 3-1 in ACC with win in Blacksburg

Adonis Filer made a move when it counted and Clemson went on to beat Virginia Tech 56-49 in Blacksburg Wednesday night.

It wasn’t the prettiest game, but a win is a win, especially on the road and with the schedule coming up over the next two weeks.

On the flip side, Rod Hall’s 1 assist 4 turnover game caught my attention, especially the cross court pass that was intercepted and allowed Tech to get back in the game and the very nearly unforced backcourt violation that went uncalled.


MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)

Another concern is the free throw shooting is trending back towards the “Clemson usual”. In 50 attempts over the last two games the Tigers have hit 60%. On the positive side, the Tigers were 5 of 6 in the last 1:24 last night and are getting to the line at a good rate and more than their opponents (20 attempts to 14 vs. Tech and 30 attempts to 15 vs. Duke).
FT2014-16
FTBREADOWN2014-16

Tigers dominate VMI, 80-50

The new look lineup for Clemson, with more Jordan Roper and Adonis Filer, started slow, but ended up in a laugher with VMI on Monday.

Filer came in averaging 12.7 minutes per game and played 29 minutes, while Roper started the game averaging 19.2 minutes and played 28.

Roper scored 19 and Filer had 12 points. Filer had 6 assists, but also committed 3 turnovers.

Tigers Roll Gamecocks, 71-57

K.J. McDaniels led the Tigers with 21 points and 10 rebounds and Jordan Roper added 15 points while Rod Hall contributed 14 as the Tigers beat South Carolina Sunday.

Adonis Filer continued his torrid offensive start, scoring 8 points in 9 minutes of play, including 2 for 2 on 3 point shots.

MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)

Basketball Totals Through 2 Games

The stats below are the composite for the first two games. Interesting to note that it’s Adonis Filer who has been the most efficient on offense with a .733 scoring efficiency and total efficiency.

It’s no surprise that McDaniels and Harrison take more shots than anyone while in the game (as a percentage of the teams shots taken).

Note on the points per possession: Because of the calculation used to determine this metric, I’m beginning to think it works well for the team, but not for indviduals. I’ll see if it becomes more stable and a better gauge over the next 6-8 games, but it may end up one that is not very ueseful (for individuals, the team metric is a very important one).


MP/G – Average minutes played per game played in
% Min – % of possible minutes played
Scoring Effiiciency – Equals points scored/potential points socred
Total Efficiency – Takes turnovers into account along with scoring efficiency. For each turnover the average points per possession for a team is added to potential points, lowering a players efficiency
eFG% – Effective field goal %, where 3 pointers are weighted 50% higher
Pts/Possess – Average points scored for each possession
Potential Points – Potential points scored based on shots taken, including FTs
%Shots – Estimated % of a team’s shot taken while player is on floor
Rebounds/Avg MP – Rebounds per average minutes played.
Assists/Avg MP – Assists per average minutes played.
TO/Avg MP – Turnovers per average minutes played
PF/Avg MP – Fouls committed per average minutes played
TO% – Turnovers/Possessions
OR% – Offensive rebounds/Total Rebounds
FT Rate – FTA/FGA
Possessions – Estimated number of possessions in a game. Calculated as FGA-OR+TO+(.475*FTA)