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”
 

The GOAT Ladder: What the Ladder Looks Like

Putting It All Together

How do we put it all together to arrive at a valid answer? There are different levels, and different data sources; how should we stitch them together? What I’ve done is to view a player’s credentials through eleven “windows” side by side, with players receiving a “grade” for each window. Here are the grades on every player’s Report Card:

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The GOAT Ladder: Greatness is in the Eye of the Beholder

Putting Offense and Defense Together

With D_Score and two forms of O_Score in hand, we can combine offense and defense into a “one number” statistic. I have labeled the two variants of this stat differently to help the reader easily apprehend the difference: Total_Score per Possession adds O_Score per Possession to D_Score, while Total_Score adds O_Score by Volume to D_Score. So if you see “Total_Score” without any qualification, I am citing a player’s volume on both ends. When I cite “Total_Score per Possession”, I am referring to a player’s production rate.

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The GOAT Ladder: Defensive Greatness

Defense – The Final Frontier

The final frontier
Image created by Craig Wheeler (https://www.flickr.com/photos/28221085@N03/3379998439)

It has heretofore been impossible to discuss individual defensive performance with any type of common language. Unfortunately, that leaves us with no solid means to debate the defensive merits of the majority of players in NBA history. All previous attempts to analyze defensive value have relied on defensive rebounds, steals, and blocks. In their absence, some models have used rebounds and assists as proxies. Statistics built upon this foundation include Dean Oliver’s DRating, bball-reference’s Defensive Win Shares, and Myers’ D-BPM. Some all-in-one metrics have also used team Defensive Rating as a stand-in for a player’s defensive value. DRating, Wins Produced, and logically even Plus-Minus models (in so far as points allowed is half of a team’s point margin) all use team defensive strength in this way.

The result is a decided favoritism toward big men (who gather rebounds) and players who are on good defensive teams. Many have noticed the result, but have not been able to redress the deficit without the use of superior data. Analyzing defense in this way also substantially misrepresents the merits of perimeter defenders. Such methods reward players with a lot of steals (even if they are poor defenders who gamble a lot) and punish players who don’t get many steals (even if they spend a lot of their time guarding the opponents’ best player.

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The GOAT Ladder: Offensive Greatness

Analyzing Offensive Value in Context

Evaluating a player’s offensive output relative to his background has been one of the areas in which statistical analysis of the NBA has enjoyed the most success, with analysts since the 1980’s having endeavored to calculate the offensive value of players from various eras. To this day, the term “analytics” is synonymous with shooting efficiency in some people’s minds. Previous models have calculated players’ offensive volume (Oliver’s Points Produced, O-BPM, and the lions’ share of bygone metrics PER and WORP), offensive efficiency (Oliver’s Floor Rating, the offensive section of Wins Produced), offensive production rate (The NBA’s ORtg, OWS/48), and offensive impact (O-PIPM and the offensive components of RPM and RAPM). I have thoroughly studied individual player volume, efficiency, and production rate in The Basketball Bible. My study focused solely on the 2015-16 through 2018-19 seasons (the seasons for which full tracking data was available at the time).

Offensive overview of the 2019 Toronto Raptors from The Basketball Bible

There been no significant efforts to ascertain offensive impact for players prior to the play-by-play era (1996-97 through the present). The only metrics that have claimed to measure offensive impact are plus-minus models. Such models rely on changes in point margin while a player is on the floor to infer offensive impact. (sometimes the change in point margin is augmented by the player’s box score statistics and/or prior plus-minus).

It is possible, and indeed valuable, to measure a player’s offensive impact by comparing his performance against league average in a given season. We begin by determining each player’s volume (total points created), production rate (points created per possession), and efficiency (the ratio of points created to points created and lost). After calculating these values, we move to the comparison stage. Some easy-to-understand statistical methods can reveal powerful insights about a player’s relationship to his context using only these numbers. More to the point, I believe we can determine a player’s offensive greatness and how it affects his historical standing.

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The GOAT Ladder: Intro

No matter how strong the pull of the moment is on our attention, the history of the game calls to us. The urge to crown a king and place him in succession to the kings of the past is an echo of the call. Ranking the top 10 or top 20 or top 50 or top 100 players of all time is another echo. The call rings out clearest of all, however, in the eternally debated question “Who is the greatest player of all time?” The GOAT debate is nothing more and nothing less than our predisposition to measure the immediacy of current players against the historical stature of legends from the past.

No matter how one describes greatness, or measures it, the desire is the same. We all want to know who is and was the absolute best. Ring-counters want to know the truth of the matter. So do points-praisers, eye-testers, and analytics afficionados. Coaches want to know who is the best, and so do fans. Everyone involved in the game has the same need to compare, to evaluate players in relation to one another. It’s a competition, after all! If we want to understand what makes teams win, it is crucial to be able to determine which players have a stronger or weaker influence on winning. The goal is not to field an objectively talented team. The goal is to field a team which can defeat opponents as frequently as possible.

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