The GOAT Ladder Part 5: #230-226

Who is the greatest NBA player of all time? I will be seeking the NBA GOAT in a series of posts featuring wide-ranging descriptions of the top 250 players in league history. For an explanation of what the stats I’ll be using mean, read the five-part intro starting here and continuing in Part 2, Part 3, Part 4, and Part 5. For each player on the ladder, from #250 to #1, I’ll be including three key graphics (plenty of other views will appear throughout, but these three will be in every write-up):

  1. Grades – Percentile values for the player’s rank among all players in NBA history. They are explained further in Part 5 of the intro.
  2. ON_GOD – A per-game expression of a player’s impact on both offense and defense. ON_GOD is described in Part 4 of the intro.
  3. Z-Scores – A score that standardizes a player’s contribution to allow for comparison across eras. Part 3 of the intro explains D_SCORE, and Part 2 outlines O_SCORE.

Above these graphics, I will report two measurements for each player: his GPA (the average of his grades from the “Report Card”) and career awards. I have gone through and retroactively assigned awards for every NBA season since 1952-53 (the first season for which data is relatively complete). The awards listed here are a record of who I think should have won them, not a record of who actually won them.

If you’re curious about comparing these players with others, you can find both basic box score stats and my suite of advanced stats from the Stats page, or simply by using the “Stats” dropdown menu at the top of the page.

Continue reading “The GOAT Ladder Part 5: #230-226”
 

The GOAT Ladder Part 4: #235-231

Who is the greatest NBA player of all time? I will be seeking the NBA GOAT in a series of posts featuring wide-ranging descriptions of the top 250 players in league history. For an explanation of what the stats I’ll be using mean, read the five-part intro starting here and continuing in Part 2, Part 3, Part 4, and Part 5. For each player on the ladder, from #250 to #1, I’ll be including three key graphics (plenty of other views will appear throughout, but these three will be in every write-up):

  1. Grades – Percentile values for the player’s rank among all players in NBA history. They are explained further in Part 5 of the intro.
  2. ON_GOD – A per-game expression of a player’s impact on both offense and defense. ON_GOD is described in Part 4 of the intro.
  3. Z-Scores – A score that standardizes a player’s contribution to allow for comparison across eras. Part 3 of the intro explains D_SCORE, and Part 2 outlines O_SCORE.

Above these graphics, I will report two measurements for each player: his GPA (the average of his grades from the “Report Card”) and career awards. I have gone through and retroactively assigned awards for every NBA season since 1952-53 (the first season for which data is relatively complete). The awards listed here are a record of who I think should have won them, not a record of who actually won them.

If you’re curious about comparing these players with others, you can find both basic box score stats and my suite of advanced stats from the Stats page, or simply by using the “Stats” dropdown menu at the top of the page.

Continue reading “The GOAT Ladder Part 4: #235-231”
 

The GOAT Ladder Part 3: #240-236

Who is the greatest NBA player of all time? I will be seeking the NBA GOAT in a series of posts featuring wide-ranging descriptions of the top 250 players in league history. For an explanation of what the stats I’ll be using mean, read the five-part intro starting here and continuing in Part 2, Part 3, Part 4, and Part 5. For each player on the ladder, from #250 to #1, I’ll be including three key graphics (plenty of other views will appear throughout, but these three will be in every write-up):

  1. Grades – Percentile values for the player’s rank among all players in NBA history. They are explained further in Part 5 of the intro.
  2. ON_GOD – A per-game expression of a player’s impact on both offense and defense. ON_GOD is described in Part 4 of the intro.
  3. Z-Scores – A score that standardizes a player’s contribution to allow for comparison across eras. Part 3 of the intro explains D_SCORE, and Part 2 outlines O_SCORE.

Above these graphics, I will report two measurements for each player: his GPA (the average of his grades from the “Report Card”) and career awards. I have gone through and retroactively assigned awards for every NBA season since 1952-53 (the first season for which data is relatively complete). The awards listed here are a record of who I think should have won them, not a record of who actually won them.

If you’re curious about comparing these players with others, you can find both basic box score stats and my suite of advanced stats from the Stats page, or simply by using the “Stats” dropdown menu at the top of the page.

Continue reading “The GOAT Ladder Part 3: #240-236”
 

The GOAT Ladder Part 2: #245-241

Who is the greatest NBA player of all time? I will be seeking the NBA GOAT in a series of posts featuring wide-ranging descriptions of the top 250 players in league history. For an explanation of what the stats I’ll be using mean, read the five-part intro starting here and continuing in Part 2, Part 3, Part 4, and Part 5. For each player on the ladder, from #250 to #1, I’ll be including three key graphics (plenty of other views will appear throughout, but these three will be in every write-up):

  1. Grades – Percentile values for the player’s rank among all players in NBA history. They are explained further in Part 5 of the intro.
  2. ON_GOD – A per-game expression of a player’s impact on both offense and defense. ON_GOD is described in Part 4 of the intro.
  3. Z-Scores – A score that standardizes a player’s contribution to allow for comparison across eras. Part 3 of the intro explains D_SCORE, and Part 2 outlines O_SCORE.

Above these graphics, I will report two measurements for each player: his GPA (the average of his grades from the “Report Card”) and career awards. I have gone through and retroactively assigned awards for every NBA season since 1952-53 (the first season for which data is relatively complete). The awards listed here are a record of who I think should have won them, not a record of who actually won them.

If you’re curious about comparing these players with others, you can find both basic box score stats and my suite of advanced stats from the Stats page, or simply by using the “Stats” dropdown of the menu at the top of the page.

Okay, that’s enough preparation. Let’s get this train rolling!

Continue reading “The GOAT Ladder Part 2: #245-241”
 

The GOAT Ladder Part 1: #250-246

Who is the greatest NBA player of all time? I will be answering that very question in a series of posts featuring wide-ranging descriptions of the top 250 players in NBA history. For an explanation of what the stats I’ll be using mean, read the five-part intro starting here and continuing in Part 2, Part 3, Part 4, and Part 5. For each player on the ladder, from #250 to #1, I’ll be including three key graphics (plenty of other views will appear throughout, but these three will be in every write-up:

  1. Grades – Percentile values for the player’s rank among all players in NBA history. They are explained further in Part 5 of the intro.
  2. ON_GOD – A per-game expression of a player’s impact on both offense and defense. ON_GOD is described in Part 4 of the intro.
  3. Z-Scores – A score that standardizes a player’s contribution to allow for comparison across eras. Part 3 of the intro explains D_SCORE, and Part 2 outlines O_SCORE.

Above these graphics, I will report two measurements for each player: his GPA (the average of his grades from the “Report Card”) and career awards. I have gone through and retroactively assigned awards for every NBA season since 1952-53 (the first season for which data is relatively complete). The awards listed here are a record of who I think should have won them, not a record of who actually won them.

If you’re curious about comparing these players with others, you can find both basic box score stats and my suite of advanced stats from the Stats page, or simply by using the “Stats” dropdown of the menu at the top of the page.

Okay, that’s enough preparation. Let’s get this train rolling!

Continue reading “The GOAT Ladder Part 1: #250-246”
 

What is TPA?

by Alan Moghaddam

Chances are if you’re into sports you’ve seen the famed charts from @NBA_Math that feature overlapping pictures of NBA players in a conventional Cartesian plot with a line plotted on it (y=-x). Anything above the line is good, anything below is bad, and average values will tend to walk the line. The graph is a visual attempt to quantify some mystery statistic known as TPA.

This is a standard TPA graph from @NBA_Math

What is TPA?

This is something of a loaded question; the acronym TPA stands for “Total Points Added”. The basic idea behind it is that a player adds points on offense and defense. You then total these subsections to get TPA.

Unfortuantely, the definition above is rather incomplete. We now need to understand Offensive Points Added (OPA) and Defensive Points Saved (DPS), the components which make up TPA. The two subcategories are much more complex than TPA alone.

To get OPA and DPS, we need to use “Box Plus/Minus,” an all-in-one statistic created by Daniel Myers and hosted at basketball-reference.com. I promise we are almost at the bottom of the well here in terms of stat definitions. Box Plus/Minus is a relativistic stat that gauges a player’s impact on team performance when s/he is on the court. S/he again will have an impact on both defense and offense, so accordingly Box Plus/Minus can break down into two stats: Offensive Box Plus/Minus (OPBM) and Defensive Box Plus/Minus (DPBM). We can already see that TPA has the same structure as Box Plus Minus; both purport to measure a player’s impact on both ends of the floor. What is the difference between the two?

Equation 1. Calculation of TPA as a function of Defensive Points Saved and Offensive Points Awarded
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Matchup-Based Defense

Defense is the unsolvable puzzle in NBA analytics. No matter how advanced the advanced stats get, defensive metrics continue to crash against the same conundrums. Better data often leads to better models, and recent years have seen a dramatic improvement in the quality of defensive data available for analysis. Tracking data, opponent shooting data, play-by-play data, and more have all played a hand in modern defensive analysis. In spite of the improvements, or perhaps in part because of the improvements, it is clear that defensive analysis is still not highly accurate.

Most defensive metrics which are currently extant are based on one of two schools of thought. In order to take stock of why defensive analysis is still frequently inaccurate, it will help to investigate the underlying assumptions behind most current models.

The Plus/Minus School of Thought

The most popular method by far is The Plus/Minus School, which counts BPM, RPM, RAPM, PIPM, and more among its adherents. The distinguishing precept of the Plus/Minus School is the belief that we can ascertain a player’s defensive value by evaluating the team’s performance with him on the court, if only we properly adjust for strength of opponent, the team’s talent level, the team’s performance with the player off the court, and the player’s performance level in seasons past. The adjustments made to raw plus/minus are attempts to extract reliable data by excising confounding variables.

Continue reading “Matchup-Based Defense”
 

The So-Called Disappearance of the Big Man, Part 2

In the first half of this study, I analyzed the conditions that would be necessary for a true “league without centers” – an ultimate small-ball paradise without any traditional big men. We found that the offensive value of high-efficiency finishers would be difficult to replace without an unimaginable increase in three-point shooting accuracy.

To this point, we haven’t yet analyzed the point at which most teams would not use a traditional big man for defensive purposes. While the foregoing analysis has laid out what I see as the necessary conditions for a big man to have no purpose on offense, the question remains as to what shape such conditions might take on the defensive end. When would it not make sense to have a big man on the defensive end?

Photo by Scott G Winterton, Deseret News
Continue reading “The So-Called Disappearance of the Big Man, Part 2”
 

The Importance of Shot Selection

by Baltej Parmar (Twitter: @BaltejNBA)

Entering the 2018–19 NBA preseason, the Milwaukee Bucks over/under was set at 47.5 wins by Las Vegas. They just won 44 games in the previous season under the coaching of Jason Kidd. A small improvement was expected from internal growth and the change in coaching from Jason Kidd to Mike Budenhulzer. However, the major jump that ended up taking place should have been possible to foresee by the end of the preseason.

As the preseason was ending, multiple columnists and writers notes the change of the Buck’s offense under Budenholzer. Still, most viewed the Bucks as a middle-of-the-pack team in the East that was likely to end up in the high 40s or maybe break the 50 win mark. Their shot selection drastically changed, but the talent was not highly regarded. Let’s dive into the Bucks offense from a statistical perspective and see what the actual changes were.

Note: I will be ignoring free throws for this current exercise. All data is collected from NBA.com

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The So-Called Disappearance of the Big Man

Photo by Andrew D. Bernstein/Getty Images

          Much ink has been spilled in the latter stages of the three-point revolution on the topic of the march of the traditional big man toward extinction. The low-post scoring, rebounding, bruising, shot-blocking center of previous generations seems to recede further and further from view with every passing season. As teams emphasize floor spacing more and more on offense, the low-post operator vanishes from offensive game plans. Modern offenses often replace the traditional center with a rim runner who sets a high ball screen and rolls to the rim, then gets out of the way or sets another screen.

Defensively, the league continues to transition toward switching on screens, and prizes players who can switch across positions. The big man who can only defend his position is now a liability. The traditional center was typically slower and bulkier than his teammates, which was good for matching up with his opposite number in the low post. Now that the low post game is out of fashion, however, there is little benefit to the added bulk of a traditional big man. Furthermore, because of the evolution of offenses leaguewide, a big man’s lack of quickness is a greater disadvantage on defense than it has ever been.

Continue reading “The So-Called Disappearance of the Big Man”