It is widely known that most defensive advanced stats fail to capture a player’s worth on that end. Defense is just not something that can be truly judged without sifting through hours of tape, but one thing that can be measured is the defensive workload for NBA players.

The goal behind this methodology was to discover which NBA players have the largest defensive workload in the NBA. This is largely measured through the difficulty of assignments through primary matchups.

How was it estimated?

1. NBA matchup data provides plenty of information for which players were directly matched with another for lengths of possessions. It is often estimated using two main metrics, matchup time, and partial possessions. Partial possessions are scored from 0 to 1 with 1 being spending the whole possession guarding that particular player and 0 being, spending none of that possession guarding that particular player.

2. Now, since the goal here is not to estimate the effectiveness of the defense played but the degree of difficulty of a particular assignment. I needed a way to quantify what assignments are considered tough. To do that, I created a singular dimension/numeric score (using PCA) for offensive impact for all NBA players based on an amalgamation of several advanced statistics. The advanced stats used were -

LEBRON; DARKO; EPM; BPM; PER; pTS% (my own creation, go through my post history if you’re interested).

Now since we have a singular number for a players offensive contributions, it is not a reach that this number can be used as a substitute for a player’s offensive impact/matchup-difficulty.

3. Since each player has matched up with 100s of different players, a weighted average was calculated for the number of partial possession spent guarding that particular player and the overall offensive impact across all different matchups. This left us with a singular number (weighted average of all possible matchups accounting for time spent on each matchup).

What does this tell us?

Now the inferences that can be generated based upon this are rather flimsy on first thought. All this tells us is which players spent that most time guarding elite offensive players.

This could mean a few different things based upon the makeup of the team -

• For teams with a variety of elite defenders, these players spent majority of their time guarding the best opposition player to make their life as hard as possible.
• For weaker teams, they may not have a variety of options to guard elite offensive players and may resort to best possible matchup.
• Rim Protectors are often assigned an easier matchup for paint protection. This fails to account for that!
• Weaker defenders/stars are often assigned to weak offensive players to conserve energy.

What were the expected findings?

I expect that this matchup difficulty metric will tell us a lot about the defensive workload of wings/guards who are often required to guard the best opposing players. Additionally, it could provide further insight into hidden gems who have been overworked on weaker teams and may shine on a better roster with a more appropriate workload.

I also expect rim-protectors to be in the middle of the pack due to the roaming feature.

Weak defenders who are hidden on weak offensive players are also expected to be lower on the list. Although, I’d expect them to jump up quite a bit in the playoffs when matchup hunting is more prevalent.

Results

So, here’s the fun part. What did I end up finding?

Players who take on the hardest matchups -

DEF_PLAYER_NAME	Offensive Impact
Luguentz Dort	1.73
Jeremy Sochan	1.63
Cam Reddish	1.44
Alex Caruso	1.44
Jaden McDaniels	1.41
Dillon Brooks	1.32
Vince Williams Jr.	1.29
Derrick Jones Jr.	1.23
OG Anunoby	1.13
Andrew Nembhard	1.00
Isaac Okoro	0.99
Jakob Poeltl	0.94
Jrue Holiday	0.94
Kevon Looney	0.91
Malik Beasley	0.91
Myles Turner	0.88
Keon Ellis	0.87
Herbert Jones	0.86
Andrew Wiggins	0.86
Taurean Prince	0.86

A lot of names you’d often expect to see. However, we do see some weak defenders like Beasley show up. This could be due to rampant matchup hunting or a lack of other elite perimeter defender. Bucks fans, feel free to chime in.

Stars who take on the hardest matchups -

DEF_PLAYER_NAME	Offensive Impact
Scottie Barnes	0.78
Anthony Davis	0.56
Jalen Smith	0.37
Jimmy Butler	0.36
Kawhi Leonard	0.33
Nikola Jokic	0.22
Kevin Durant	0.19
Paul George	0.14
Kristaps Porzingis	0.08
Lauri Markkanen	0.02
Giannis Antetokounmpo	0.00
Jayson Tatum	-0.04
Desmond Bane	-0.04
Collin Sexton	-0.12
Anthony Edwards	-0.13
Joel Embiid	-0.15
Kevin Love	-0.16
Malcolm Brogdon	-0.18

As expected, Embiid and Giannis are down on the list due to their team schemes as roamers.

Stars who take on the easiest matchups -

DEF_PLAYER_NAME	Offensive Impact
Tyrese Haliburton	-0.72
Jalen Brunson	-0.63
Luka Doncic	-0.62
Donovan Mitchell	-0.55
Stephen Curry	-0.53
Tyrese Maxey	-0.51
Trae Young	-0.49
Shai Gilgeous-Alexander	-0.46
Kyrie Irving	-0.38
Devin Booker	-0.38
Damian Lillard	-0.37
CJ McCollum	-0.32
LeBron James	-0.31
James Harden	-0.29
Anfernee Simons	-0.23
Zion Williamson	-0.20
Jamal Murray	-0.19

A lot of these names check the eye-test as players who’d hide on bad defenders.

Which players take on the easiest matchups -

DEF_PLAYER_NAME	Offensive Impact
Doug McDermott	-1.34
Joe Ingles	-1.20
Jaden Hardy	-1.20
Sam Merrill	-1.01
Jordan Hawkins	-0.95
Dalano Banton	-0.94
DeMar DeRozan	-0.94
Garrison Mathews	-0.93
Jordan Clarkson	-0.93
Chris Paul	-0.93
Duncan Robinson	-0.93
Gradey Dick	-0.92
Jevon Carter	-0.91
Cam Whitmore	-0.91
Luke Kornet	-0.91
Malik Monk	-0.89
Isaiah Joe	-0.88
Lonnie Walker IV	-0.86
Bryce McGowens	-0.81
Jalen Green	-0.79

Conclusion - A future for a true defensive advanced statistic?

The matchup difficulty metric does exactly what it’s designed to do. It finds out which players take on the hardest matchups. Now the next step would be incorportating team schemes, DEF rating in the shared minutes and opposition performance relative to their mean performance, and this could be one of the few advanced statistics that captures true defensive impact along with effort expended.