FanPost

Portland at Utah 10/7/2014 - Wonder Bread Charts

It's a new season and I've put together Wonder Bread charts for last night's game.

Previously, you would see the charts in the post, however, I'm using Tableau charts these days and haven't found a way to embed the charts into my fan post (the Tableau charts can be embedded via javascript; if anyone has any insight on embedding javascript into a fan post, let me know). Consequently, I am providing links that will open into a new page so you can view the charts.

As a refresher, I've created two different kinds of Wonder Bread charts that attempt to show player value and effectiveness. Ideally, a player should provide good value and be effective in providing that value.

A player can have good value in a game, but value should also be viewed with how effective that player is. Conversely, a player may be effective over a short span (i.e. a player might have a 100 PER, but it might only be for one minute), but if the player only played one or two minutes in the game, he most-likely didn't have a significant impact on the overall outcome of the game.

For more on how value and effectiveness are calculated see the notes below.

For those who are ready for the charts, here are the links:

Portland at Utah - all players (value and effectiveness for all players)

Portland at Utah - Utah players (value and effectiveness for Utah players)

Portland at Utah - Portland players (value and effectiveness for Portland players)

Value:

I quantify a player's value based on his offensive effort (y-axis), defensive effort (x-axis), and calculated approximate value (size of dot). It's preferred for players to be in the upper right hand corner as that shows good defense and good offense; further, a large dot shows a greater overall stat contribution to the game than a small dot does (i.e. approximate value is a counting type number to show how a player is affecting the game stat wise).

Offensive effort is measured by an estimated offensive +/-. Offensive adjusted +/- is calculated on a 40 minute basis and uses the following weights:

+.6111 PTS
-.33918 TSA (where TSA is .44*FTA + FGA)
+.440814 FTA
+.379745 3PA
+.634044 AST
+.77827 ORB
-1.08855 TOV
+.26262 STL
Intercept = -8.57647 (basically all players start out negative 8.6)

Defensive effort is measured by an estimated defensive +/-. Defensive adjusted +/- is calculated on a 40 minute basis and use the following weights:

+.80195 BLKS
+.413919 DRBS
-.07551 PF
+1.597019 STLS
-.26385 TOV
Intercept = -4.69887 (basically all players start out negative 4.7)

Approximate Value attempts to measure how much an individual player is contributing stat wise to the game; it is equal to (((((Points + Assists + Rebounds + Steals + Blocks – Turnovers – Missed Shots – Missed Free Throws) times 2 if for a half) times 82) raised to the 3/4 power) divided by 21)); and average players are in the 6 to 7 range.

Effectiveness:

I measure effectiveness in three different ways, an estimate of the wins produced per 48 minutes (y-axis), the Larry H Miller average (x-axis), and estimated PER (size of dot). The bigger the dot the more effective a player is and vice versa for the smaller the dot. Also, the way this chart is structured, a player in the upper right hand corner played more effectively than a player in the lower left hand corner.

The Larry H Miller average is a simple efficiency measure that is equal to ((Points + Assists + Rebounds + Steals + Blocks – Fouls – Turnovers – Shots) divided by minutes). The average player falls in the .100 to .200 range. It's named after Larry Miller as he would use it as a quick means to assess how a player was doing in a game. Some say that this stat is position biased since big men can rack up a lot of points, rebounds, and blocks, but not have the fouls, missed shots, and turnovers that guards/small forwards have.

Estimated wins produced per 48 takes out position bias; it does this by comparing shooting guards to shooting guards, power forwards to power forwards, etc, and then makes position specific adjustments in the formula. The average player is .100; players producing higher than .100 are producing at a higher level than the average and those below .100 are producing at a lower level than the average.

PER was created by John Hollinger and attempts to measure a player's per minute performance (like the measures above) but then also makes an adjustment for game pace. The average PER rating is 15.

All comments are the opinion of the commenter and not necessarily that of SLC Dunk or SB Nation.