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

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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.

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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
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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.

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P.J. Tucker Looks to Secure the Bag

After two years as the Rockets’ stopper, P.J. Tucker is looking to secure the bag. Tucker has two seasons and $16.3 million left on his current contract, at the end of which he will be 36 years old. Tucker’s motivation in seeking a contract extension is entirely sensible; his market value is high, meaning he is deserving of a raise. Signing an extension now would also guarantee his income into the final phase of his career. Asking for an extension is the smart move for Tucker, but what should the Rockets do?

In the last four seasons, P.J. Tucker has compiled 17.3 Wins, an average of 4.3 per season. 14.4 of those wins (83.2%) have come on the defensive end, and Tucker is known by reputation around the league as a defensive specialist.

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Top 25 Rebounding Guards in the NBA

Rebounding has traditionally been the domain of big men throughout NBA history. As perimeter players have grown larger and more athletic, however, it has become more and more important for outside players to help out on the boards. Indeed, the last three seasons have even featured a guard (Russell Westbrook) averaging over 10 rebounds per game on his way to averaging a triple double.

(AP Photo/Sue Ogrocki)

Who are the best-rebounding guards in the league? To answer this question, I evaluated the relative difficulty of acquiring each rebound based on whether the rebound was contested or uncontested. By finding the success rates for the offense and the defense on each type of rebound and comparing the expected value with the observed value in each case, I was able to assign an appropriate value for each type of rebound – contested defensive rebounds, uncontested defensive rebounds, contested offensive rebounds, and uncontested defensive rebounds. The result gives us the total rebounding value added by each player. (For a more detailed description of the method for evaluating rebounds, consult The Basketball Bible)

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Jonathan Isaac Under the Microscope

              Jonathan Isaac’s NBA journey began inauspiciously as the number six overall pick by the Orlando Magic. He looked to be at risk of becoming yet another highly talented prospect drafted by a losing franchise whose career becomes a study in disappointment and squandered potential. Two years later, after a breakout season by Nikola Vucevic powered the Magic to a surprising playoff berth, it is time to consider whether or not Jonathan Isaac can be part of a brighter future for Orlando.

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2019 Offseason Crunch

Yesterday I outlined a method to accurately grade offseason moves based on an analysis of the cost of wins in the NBA, the relationship between performance and salary, and a rubric to help the grades make sense. Today, I’m presenting the first annual NBA Offseason Data Crunch, in which I evaluate every move made by every team this summer. Before you dig in, there are two caveats:

  • In what follows I will evaluate all acquisitions in terms of the player’s value relative to the value of his contract. This means that for trades, we are not interested (right now) in figuring out which team won or lost the trade. There is a time for evaluating trades in that manner, but today’s analysis will consider moves purely in terms of cost efficiency.
  • The data crunch will deal only with players who are likely to impact winning or losing NBA games this year, and players whose impact we are able to reliably estimate. Rookies and future draft picks, as they do not have any NBA data, are difficult to forecast with the same accuracy as existing NBA players, so I will leave them aside for now.

Los Angeles Lakers trade NOP for Anthony Davis

          Let’s start with the easiest transaction to grade. Acquiring AD was a home run for the Lakers. Davis is projected to make over a little over $27 million next season, followed by a player option for 2020-21. In the three seasons prior to last year, Davis averaged 12.6 wins per season. At that rate, we would anticipate AD to generate roughly $118.3 million worth of value, meaning that the Lakers are getting a 91 million dollar surplus from trading for AD. Of course, they did have to give up something to get him …

GRADE: A+

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How to Do Offseason Grades the Right Way

            At this time of year, NBA analysts, fans, and front offices are all concerned with cost efficiency. Free agent season stimulates near-constant conversation evaluating each new contract as a good deal, bad deal, or fair deal. What is the basis of all the conversation, though? To be more specific, what is the standard used to determine whether a player is overpaid, underpaid, or fairly paid? If the standard is subjective, then offseason “grades” merely reflect the degree of correlation between a team’s offseason moves and what I happen to think each player is worth. That correlation is not valuable to anyone aside from me. Nobody else can use grades like that, because the grades only reflect a subjective opinion.

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