Posts Tagged ‘Dwight Howard’

If you missed the last post, it was an overview of Expected Value (EV). And while that approach is not a novel concept — check out this similar method — from what I gather, incorporating a large defensive component is. Most of the defensive numbers used are from my stat-tracking. As a refresher, the defensive component of EV includes:

So which individual players fare the best in this metric? Below are the top defensive players in EV from the 2010 playoffs, with defensive usage included as a reference for the size of a player’s role (minimum 30 defensive plays “used”):

2010 Playoffs; Minimum 30 defensive possessions used

Dwight Howard, not surprisingly, had the best playoffs on the defensive end according to this. It’s good to be cautious of how small-sampled the playoffs are, given that one or two games against a hot or cold shooting opponent could skew these numbers. Then again, half the all-defensive team is represented on the list above, and that doesn’t include reputable defenders like Joakim Noah, Luc Richard Mbah a Moute and Tony Allen.

Because the playoffs are not only small sampled in games, but in opponents, it’s always important to consider matchups. Which makes Allen’s performance — mostly versus Dwyane Wade, LeBron James and Kobe Bryant — that much more impressive.

For those wondering about Kevin Garnett and Tim Duncan, they both just missed the cut. Garnett, to me, emphasizes the single greatest challenge in measuring individual defense causally: his greatest strength is probably communicating where to be and what is coming at all times to those around him. Now that’s difficult to quantify.

Finally, here is the complete list of defensive EV from the 2010 playoffs for all qualifying players (min 30 defensive possessions “used”).

Author’s Note: All EV values are relative to league average.

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I’ve talked about “guarded situations” before, but never from the perspective of an individual defender. We can use a “guarding situation” as a quick and dirty operational definition for looking at FG% against individual defenders. To reiterate the definition of a guarded situation:

  • The defender is trying to defend an offensive player without being impeded by a screen or helping on defense
  • The defender is challenging an offensive player at the basket by “engaging” in guarding them
  • The defender is double-teaming in a manner that actually impacts the opponent’s shot

The first situation has a gray area when players are screened out and then “re-engage” in guarding them (or switch on screens and pick up a new man). I look at the defenders stance and spacing from the offensive player to determine if he’s re-engaged: If the defensive player hasn’t had time to establish that position as he otherwise would have, he hasn’t engaged the offensive player again. (For eg, scrambling and lunging at a shot attempt from 4 feet away after being screened isn’t “guarding,” it’s more akin to closing out on a jumper shot.)

The second situation is fairly straightforward — Dwight Howard isn’t engaged in “guarding” a player by leaping across the lane at the last second, after a shot is taken, trying to block it. That’s the equivalent of a closeout on a jump shot, and for these purposes ignored (unless the shot is literally blocked). But when he’s standing in the lane and picks up the attacker coming toward the rim, he is now guarding the offensive player.

The last situation is simply to clarify that an incoming double-team is not an engaged double-team. If Dwayne Wade runs at a post player to double, he isn’t actually guarding him until he gets there. Engaged double- teams count as half attempts for each defender.

From that definition, we can look at how players shoot against defenders. The average guarded shot in 164 team games tracked this year is 40.6%. In last year’s playoffs, it was 39.6%, mostly due to the number of games played by good guarding teams like Boston (35.6% against), Orlando (36.6% against) and Los Angeles (38.0% against).

Here are the individual leaders from the 2010 playoffs in FG% against (min 30 FGA):

2010 Playoff Leaders FG% Against; Min 30 FGA's

There are some not-so-surprising names on that list. Players with good defensive reputations like LeBron James, Howard, Serge Ibaka and Kendrick Perkins. Although it’s always important to keep in mind that playoff samples are heavily influenced by the matchups from a series or two.

There are surprising names there too, perhaps most notably Tony Parker. After 26 FGA against this year, Parker’s opponents are shooting 50%. Ah, small sample sizes! Here are the leaders from games tracked in the regular season so far this year (min 30 FGA):

Min 30 FGA

Again, it might be surprising to see Jason Kidd’s name there, but he just missed the cut for the playoff leaders last year — 31.3% against. Even at his advanced age, he can still defend quite well, and I imagine his large frame and intelligent positioning make scoring on him more difficult than normal.

Another name that might stand out, other than Shannon Brown, is Derek Rose. I will have a post on Rose and the Bulls defense in the near future, but there is no doubt Rose’s athleticism has made him a really solid defender at the point guard position.

Included here is the complete list of qualifying players in FG% against from 2010 playoffs.

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I was excited to see the topic of fouls receive some attention at last week’s Sloan Conference in Boston. Although I’m not sure how I feel about the methodology (confusing) and conclusions (potentially confounded) of that paper. Nonetheless, fouls are a small part of the game that are often overlooked in analysis.

Turns out that drawing fouls is a really good thing. And committing fouls — specifically, shooting fouls — is really bad. Nothing revolutionary there.

On offense, drawing a foul has two effects:

  1. Brings a team closer to the penalty
  2. Causes foul trouble for opposing starters

When a player is in foul trouble, he loses minutes he would otherwise be on the floor (unless he plays for Don Nelson, apparently). Usually, this is on order of 5-10 minutes, as a player sits for a period before he is no longer in “foul trouble.” Occasionally, extreme cases render a player inactive for longer, like Dwight Howard in last year’s first round against Charlotte. Howard averaged around 26 minutes a game when he otherwise would have been playing closer to 40. When starters sit, they are replaced by bench players, who (theoretically) represent a downgrade.

The penalty represents a larger advantage for teams. Every foul before the penalty is 25% of the way to the automatic bonus for a team. Once in the penalty, any foul on the court produces two free throws for a team, which is the most efficient form of offense: The value of an average possession in the NBA is about 1.07 points. The value of two free throws is about 1.52 points.

On the team level, the correlation between fouls drawn per 100 possessions and ORtg is quite strong: 0.56 for last year’s playoffs. For this metric, a “foul drawn” (FD) is only counted when a player is fouled on offense. Setting screens and intentional fouls are excluded.

Here are the leaders from the 2010 playoffs in fouls drawn per 100 possessions, with free throw attempts/100 included as reference:

Clearly, there is a strong correlation between free throw attempts and fouls drawn. This allows a fairly accurate estimate of FD using FTA. However, as is the case with Opportunities Created and assists, it is the outliers who are often the most interesting. Someone like Dwight Howard shoots far less free throws than expected based on the number of fouls he draws because he’s constantly being banged around before the act of shooting, to prevent lobs or on offensive rebounding situations. Here is the full list of players ranked by FD from the 2010 playoffs who played at least 150 possessions.


On defense, committing personal fouls isn’t terribly detrimental to the team. For one, there’s a limit of six per game, and as discussed above, players will simply head to the bench if they foul too much. There is almost no correlation between personal fouls and team defensive rating.

However, there is a correlation between Shooting Free Throws (SF) and defensive rating (0.44 after 104 team games of tracking this year.) This information can be extracted from the play-by-play for comprehensive analysis by noting how many free throws a player gave to the other team by fouling. (eg 3 SF result from fouling on a 3-pointer.)

Again, free throws are the most efficient mode of scoring, so sending a player to the line is spiking the opponent’s offensive efficiency as described above. In short, shooting fouls are bad.* Using the 150 possession qualifier, here is the complete list of players from last year’s playoffs who caused the most free throws for the opposition (SF per 100 possessions).

*The obvious exception is “intentional” fouls to prevent layups or easy attempts around the goal from horribly inefficient free throw shooters.

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