Daily Dictionary

Daily Dictionary: Effective Field Goal Percentage (eFG%)

The idea behind eFG% is simple - 3 point field goals are worth 50% more than 2 point field goals.  The calculation is also simple: eFG% = (FG + 0.5 * 3P FG) / FGA

Today's post will focus solely on eFG% in the context of individual players.  Over the next few days we'll talk about team eFG% and how we can use eFG% against to analyze team defense.

To help illustrate this point, we've included a top 12 list.

1. Nene Hilario - .615
2. Dwight Howard - .593
3. Arron Afflalo - .581
4. Richard Jefferson - .579
5. Ray Allen - .577
6. Emeka Ofakor - .573
7. Lamar Odom - .568
8. Marcin Gortat - .561
9. Jared Dudley - .560
10. Al Horford - .558
11. Ty Lawson - .553
12t. Stephen Curry - .551
12t. Paul Pierce - .551
12t. Greg Monroe - .551

The styles of play represented by this list are pretty diverse - we have inside scorers in Nene, Dwight, Okafor, Gortat, Horford and Monroe.  Interestingly enough, these have the 6 highest field goal percentages in the league.  This is a pretty simple connection to make, as none of these players take 3 pointers with any frequency whatsoever.

Outside of Lamar Odom, the remaining players on this list are all guys who shoot a high number of threes at a high percentage.

Afflalo - 42.3% on 3.6 attempts/game
Jefferson - 44% on 3.8 attempts/game
Allen - 44.4% on 4.7 attempts/game
Dudley - 41.5% on 3.1 attempts/game
Lawson - 40.4% on 2.1 attempts/game
Curry - 44.2% on 4.6 attempts/game
Pierce - 37.4% on 3.7 attempts/game

Like True Shooting, eFG% attempts to compare the offensive efficiencies of different types of players, and in doing so, highlights the deficiencies of traditional FG%.


Daily Dictionary: Defensive Rating

This post will make the jump back to team-level analysis.  Defensive Rating, while flawed, offers a more complete understanding of a team's overall defensive efficiency.  The statistic is extremely simple - it is merely a measure of how many points a team will allow per 100 possessions.

Below are the teams with the 5 best and 5 worst Defensive Ratings:

1t. Chicago Bulls - 100.3
1t. Boston Celtics - 100.3
3. Orlando Magic - 101.8
4. Milwaukee Bucks - 102.5
5. Miami Heat - 103.5

26. Golden State Warriors - 110.7
27. Minnesota Timberwolves - 111.1
28. Detroit Pistons - 111.7
29. Cleveland Cavaliers - 111.8
30. Toronto Raptors - 112.7

Defensive Rating is not adjusted for pace, which limits its utility.  Despite this limitation, it is still a superior metric for team level defense, as by converting the unit to a point per possession basis, it automatically adjusts for the frequency a team will allow 3 point shots and free throws.

Daily Dictionary - % Assisted

Today's post will take the scope of our analysis away from the world of efficiency and pace and into the world of shot creation.  Shot creation is one of the most important traits of a successful basketball player.  The statistic we can use as a proxy for shot creation is % assisted.  This is a statistic that can be found on HoopData, in the scoring section of their Player Statistics page.

% Assisted - >40 games, >25mpg

We have applied the same Games Played at Minutes/Game boundaries but have also filtered by position.

Point Guards

Shooting Guards

Small Forwards

Power Forwards


League Average % Assisted:

Point Guards - 34.2%
Shooting Guards - 56%
Small Forwards - 62.5%
Power Forwards - 61.4%
Centers - 63.2%

Looking at the league averages by position, the trend is pretty obvious and corroborates with intuitive viewing of the game.  Players who are most likely to create their own shot (have a low % assisted) are point guards and ball dominant wings.  Players who are less likely to create their own shots (have a high % assisted) are spot-up shooters and players who take most of their shots close to the basket.  

Another thing to note is the general fungibility among players who cannot create their own shot.  Of course this doesn't hold for the elite bigs and the players who elite shooters, but in most cases, the key differentiating factor is the ability to get your own shot up at any point in the game and during any point of a possession.



48*((Team Possession + Opponent Possession) / (2*(Team Minutes/5)))

Pace is another team-level statistic that cannot be gleaned by simply viewing a boxscore.  Pace is important to note during an analysis, because it can sometimes skew counting stats such as Points, Rebounds, Assists. Pace roughly estimates the number of possessions used by a team in a given game.

Here are the Top 5 and Bottom 5 teams in pace:

1. Minnesota - 96.5
2t. New York - 95.6
2t. Denver - 95.6
4. Sacramento - 95.2
5. Golden State - 94.8

26. Charlotte - 89.6
27. Atlanta - 89.3
28. Detroit - 89.2
29. New Orleans - 88.7
30. Portland - 87.9

It goes without saying that when holding usage constant, players will use a higher number of raw possessions when in a high pace offense.  This, of course, will lead to more opportunities to accumulate bulk statistics.  Later on in the week I will address in greater detail the impact of pace.



Team: FGA + .44FTA + TOV - OREB
Individual: FGA + .44FTA + TOV - 1/3*Missed FG (included because 1/3 of FGA result in an offensive rebound)

The goal of these first few dictionary posts are to introduce some of the major concepts that will be applied in our game reviews.  We started with a few individual level statistics that more completely measure a players offensive contribution.  True Shooting and Usage are extremely valuable tools, but they fail to measure the impact of Offensive Rebounding and Turnovers on team success.

One key point to understand is that teams will generally have an extremely similar number of possessions in a given game (+/- 1 or 2).  This places a premium on the ability to score efficiently, crash the offensive glass, and limit turnovers.  Matt W. will have a post up shortly on the impact of offensive rebounds and turnovers, so I'll instead focus on scoring.

As I referenced yesterday, many fans tend to overrate pure bulk scoring, and in doing so, they neglect to take into consideration how many possessions are used to get these points.

Player A: 25.3 Points/Game
Player B: 26.7 Points/Game

Player A Possessions Used: 20 + .44(7.1) + 3 - .33(11) = 26.124 - 3.63 = 22.494 Possessions/Game
Player B Possessions Used: 17.5 + .44(7.8) + 3.3 -.33(8.6) = 24.232 - 2.838 = 21.394 Possessions/Game

Player A Points Per Possession = 25.3/22.494 = 1.12
Player B Points Per Possession = 26.7/21.394 = 1.25

Player A is Kobe Bryant, Player B is LeBron James

All of this information is readily available in the boxscore, and can be done for single games or for an entire season (or career).  These simple calculations provide a deeper insight into the offensive contributions of a specific player.


Usage (USG%)- 100 * ((Field Goal Attempts + 0.44 * Free Throw Attempts + Turnovers) * (Team Minutes Played/5)) / (Minutes Played * (Team Field Goal Attempts + 0.44 * Team Free Throw Attempts + Team Turnovers))

A player's usage is derived by calculating the percent of plays used by a specific player when he is on the floor. Usage, like other advanced NBA stats, is actually quite intuitive for anybody who watches a moderate amount of NBA basketball. The league average usage is 18.8%.

The Top 8 in Usage from the 2010-2011 regular season were:

1. Kobe Bryant - 35.1%
2. Derrick Rose - 32.2%
3. Carmelo Anthony - 32.0%
4t. Dwayne Wade - 31.6%
4t. Russell Westbrook - 31.5%
6. LeBron James - 31.5%
7. Amare Stoudemire - 30.9%
8. Kevin Durant - 30.6%

All of these players share a few key traits:

1. They are all viable #1 options for an offense
2. They are all adept at creating their own shot
3. They are all at or near the top of the league in Points Per Game

In our last daily dictionary, Matt W. explained the concept of efficiency by defining and applying True Shooting Percentage (TS%). Here I will show you how to use TS% and USG% together to analyze a player's production. The key takeaway is that when all variables are held constant, a player who sees his USG% rise will generally see his TS% fall. This is because a player who is tasked with being the team's primary source of offense will often see a greater number of lower quality looks, as coaches and teammates alike recognize that a bad shot from their best player may often be the best look they can get on any given offensive possession.

Combining usage and true shooting as elements in your analysis can help provide a more nuanced understanding of offensive contribution. Often a player will be overrated for his bulk scoring; a deeper look into the interplay between usage and efficiency will show that said player gets his points by virtue of dominating the ball.  


True Shooting Percentage (TS%)- Basketball

True Shooting Percentage measures shooting efficiency taking into account the different values in 2 point field goals, 3 point field goals, and free throws.

The formula for calculating TS% is: Points/(2*(Field Goal Attempts + (.44*Free Throw Attempts)))

Ever look at a basketball box score and struggle to figure out a player's efficiency? It can be difficult. You have to look at 2 point field goals, 3 point field goals, and free throws all at the same time! True Shooting Percentage does it all for you. True Shooting Percentage recognizes that 3 point field goal is worth 50% more than a 2 point field goal, as well as that most free throws come in pairs.