The Basketball Podcast: EP312 with Dylan Murphy on NBA Coaching Analytics

RELEASE DATE : 20/03/2024

In this week’s basketball coaching conversation, G League head coach Dylan Murphy joins the Basketball Podcast to share insights on coaching analytics.

Dylan Murphy is the head coach of the Osceola Magic, the NBA G League affiliate of the Orlando Magic.

Dylan Murphy has been associated with the Orlando Magic for the past five seasons. His journey began as a basketball operations analyst from 2018 to 2020, where he provided valuable analytics support to the coaching staff. Subsequently, he was promoted to an assistant coach in 2020 and has continued in that role for the last three seasons.

Prior to joining the Magic, Murphy served as an NBA G League scout for the Atlanta Hawks during the 2016-17 season. His responsibilities included identifying potential call-up candidates for the Hawks’ NBA roster.

From 2013 to 2016, Murphy worked as an assistant coach for the Fort Wayne Mad Ants, the NBA G League team for the Indiana Pacers. In the 2013-14 season, the Mad Ants clinched the G League championship with an impressive regular-season record of 34-16 and a perfect 6-0 playoff run. They followed it up with another trip to the G League Finals in the 2014-15 season.

Murphy also served as a graduate assistant with the men’s basketball team at Ball State University in 2018.

One of Murphy’s most notable contributions to the coaching community is the creation of the Basketball Dictionary. This comprehensive resource serves as a compendium of basketball terminology, concepts, and strategies, providing coaches at all levels with a valuable tool for enhancing their understanding of the game.

Dylan Murphy IMAGE

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Dylan Murphy Quotes:

“I think the job of anybody in a basketball organization is to add value. And so, for me, finding ways to leverage data, not just to describe what was going on, but be prescriptive, offer solutions, offer insights that coaches could take on the court versus to saying, ‘We rank 9th in this, 11th in this. That’s good information, but what do we do with that information?”

“As the game changes and as the resources in the NBA get bigger, teams want every minuscule advantage they can get. Analytics is one area where there’s been a lot of growth.”

“When you include free throws, driving to the rack, get fouled in the restricted area, you’re talking about 1.30 to 1.35 points per possession, whereas your average corner three, let’s say you shoot 38%, you’re going to be at 1.14. [points per possession]. That’s a 20 point per 100 possession difference from a corner three to a driving layup. So, the idea that a three is greater than a two, I would change it to three is greater than long two, but a close two is still better than a three.”

“I always think about it like we’re using the data to tell us where to go, and then we’re using the principles of motor learning for how to get there. The tricky part then is how do you incorporate data in a way that’s not overwhelming to a player?  . . We allow the data to set a direction, but we don’t really overwhelm players with data.”

“We’ve found in the past that pace basically has no relationship with offensive efficiency . . So, you play to the tempo of your players. If you have guys that play well playing fast, play fast. But if you have guys that play well playing slow, play slow. Shot locations are efficient, not the timing of it. You’re more likely to get a transition layup if you run early in the clock, but the average transition three is a below average half-court shot. If you get an open transition three, great. But if you just run down and shoot a transition three, it’s a bad shot.”

“When you’re measuring efficiency of that pick and roll, you’re both measuring when there is a ‘direct outcome,’ like the pick and roll led to a shot, what was the efficiency of that? But also, how often is a shot generated from that pick and roll? You can have someone who’s super high efficiency when they get a shot at a pick and roll, but they are unable to get a shot very frequently.”

“Later in the shot clock, there is more urgency to get a shot, whereas earlier in the shot clock there’s more urgency to get a quality shot. When you’re saying which coverages are more efficient, you have to look at which coverage is better for what period in the shot clock.”

“Which is more efficient? Who do I have? . . Actions aren’t efficient, post ups and pick and rolls in themselves aren’t efficient. It’s who’s in the actions that dictates efficiency . . The best way to attack a switch is to have a deep understanding of the efficiencies of your players in certain skill areas. It’s not action A, set B, whatever. I would argue it’s very personnel dependent.”

“The NBA has changed a lot. Teams have realized the value of the offensive glass. To me, there are several prongs to it. The first is that there’s value in creating half court possessions defensively versus transition . . And then there’s the added value of you getting the ball when putbacks on offensive rebounds are one of the most efficient shots in basketball.”

“We have player development plans for all our guys. We established early in the year what we’d be tracking so they knew, and then we present that data to them. But we also tag it all in sports code so we can show the film, too. So it’s not just, here’s a bunch of numbers, here’s what the numbers say . . let’s dive into the video and figure out why X, Y, or Z is happening.”

“I think it just comes back to very similar principles to what all coaches go through, which is holding people accountable is hard. The more expectations you have, the harder it is to hold people accountable to those things. So, in the same way, what’s important is to keep your expectations limited so you can hold people truly accountable to fewer expectations. In the same way, with analytics, pick your few things that you really care about.”

“No tracking structure is ever going to incentivize the behavior you want perfectly. If you’re tracking charges, maybe it doesn’t make sense to draw charge every time . . as long as you’re thinking through what the result of your incentive structure is, and you’re okay with what the potential consequences of it are, then I think it’s great.”

“You just have to be aware that nothing you track is going to say what you want. One thing I love, I heard someone say one time, the data doesn’t say anything. People say things about the data. So, the data is only going to track exactly what you tell it to track. What results from that is what people say about it or how they respond to it.”

“It’s really hard to go vertical legally in the NBA . . if you’re not lined up completely, don’t go vertical. Go block the shot. Because more likely if you’re going to try to go vertical when you’re late then you’re just going to commit an A to B foul. So better to just go try to impact the shot as best you can.”

“The rim is the most important thing. Protect the rim first and then trust that your teammates are going to fly around behind you even if you’re late.”

Dylan Murphy Breakdown:

4:00 – Understanding Analytics
8:00 – Analytics and Basketball Experiences
11:30 – Optimizing Offensive Tempo
13:30 – Super Slow
15:30 – Efficiencies vs Types of Defenses
19:00 – Attacking a Switch
20:30 – Double Teaming a Star Player
25:00 – Offensive Rebounding
28:00 – Decision Making
31:00 – Interpreting the Data
35:30 – Teaching Points
37:30 – Decision Making Defensively
41:00 – Trends in Basketball Analytics
42:00 – Ideas Into Action

 Dylan Murphy Selected Links from the Podcast:

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