Basketball Operations Brief

Gregory spicer – statistics – 11/03/25

The NBA has made the excellent decision to invest in analytics by partnering with Amazon Web Services to expand the data available to fans.

In recent years, the NBA has added “tracking” stats, and efficiency equation stats that allow fans to get a deeper look into player production. Now, with their new AWS partnership, the NBA will utilize next-gen camera technology to roll out four new stats throughout the 2025/26 season. 

This data will help quantify certain attributes such as:

• Skill
• Versatility
• Sustainability
• Impact
• Value

Our plan at the B.O.B. is to put together a publication for each of the four new stats as they arrive. The first data was released this week, and is labeled as the “shot difficulty” statistics. 

What is it?

Shot difficulty stats follow the lead of a very popular type of baseball metric – EXPECTED STATS. The NBA is also adding two metrics that track how closely players are guarded – Defender Distance and Defensive Pressure Score. Overall, these numbers work together to tell us how prolific a player is at making difficult shots, how closely they are defended, and what type of shot selection they have. 

The NBA is able to gather this data with their new “optimal player tracking system.” 3D models that track 29 different points on each player’s body, sending in data for every movement. The tracking system is able to capture information 60 times per second, giving each stat a very specific foundation. There are no assumptions. These cameras and models can break down exactly when a player shoots, how far the defender’s hand is, what his angle to the hoop is, how high his feet are off the ground, and essentially everything else. The models then use that data to calculate the “expected” efficiency of the shot they are taking. Here are all 20 “features” analyzed by the AWS 3D models that are included when calculating expected stats.

Shooter Features

• Shot Distance: Distance from player’s center of mass to the hoop
• Shooter’s Vertical Tilt: Degrees of the shooter’s tilt with respect to the Z axis
• Head Angle: Angle of the shooter’s head relative to the basket
• Head Facing Percentage: Percentage of time the shooter’s head has potential visibility of the basket leading up to the shot
• Speed: Shooter’s speed at time of shot
• Velocity to Basket: Shooter’s velocity with respect to the direction of the basket. This is measured by how shot distance is changing over time
• Rotational Speed/Velocity: Direction and speed the shooter’s hips are rotating with respect to the basket
• Full Rotation: Total degrees of rotation the shooter rotates in the second before and after the shot
• Hang Time: The time spent during the air from the last time the shooter leaves the floor before the release up to release time
• Air Time Distance: Two-dimensional distance the shooter travels after last takeoff to release

Defender Features

• Closest Defender Joint Distance: Distance from the closest defender’s nearest hand and the ball
• Relative Height of Contest: The difference between the closest defender’s nearest hand height and the height of the ball
• Defensive Hand Contest Angle: Angle between the closest defender’s hand and the shooter’s potential apex
• Vision Interference: Quantity to which the defender is hindering the shooter’s view of the basket
• Elbow Contact Prior To Shoot: Distance between closest defender’s nearest hand to the shooter’s elbow in the 1 second leading up to the shot
• Defender Hip Distance: Distance between defender’s and shooter’s hips
• Defender Angle Relative to Basket: Angle between the closest defender and the shooter, and the shooter and the hoop
• Defender Speed/Velocity: Speed and direction which the defender is moving with respect to the shooter
• Pressure Score: Pressure exerted on shooter by matchup defender
• Average Pressure Score: Average exerted on shooter by all defenders on court

At the bottom of the page, you can find the NBA website’s glossary of new metrics. You’ll notice that most of these stats have an “x” in them. This “x” indicates “expected.” Similar to in baseball, if you’ve ever seen xFIP, xERA, or xSLG. The difference is in interpretation. If a player is shooting above their expected field goal percentage, it’s an indicator of skill and shot making ability. In baseball, having lower expected stats can be an indication of luck. In basketball, players have more consistent production, and luck/variation is less of a factor. 

Why is it important? 

The biggest reason this new data is significant is it allows us to contextualize efficiency. In the last decade, efficiency has emerged as a key part of player evaluation. The NBA website and Basketball Reference have released stats such as True Shooting % (TS%) that calculate a players scoring ability while taking into account that a three-point shot is worth more than a 2-point shot, and also adding in free throw scoring. There are also new shot charts available that tell us exactly how efficient different players are from different spots on the floor.

All of these numbers are great – but can be misinforming. It’s unfair to expect a player like Donovan Mitchell (57% TS), who is tasked with contested shots, isolation scoring, and on-ball offense, to be as efficient as a player like Max Strus (61% TS), who has an easier role. 

Now, with these expected stats, we can take into account how difficult the shots a player takes are when evaluating their scoring ability. 

From a simple perspective, we can also just see who takes tough shots, who makes tough shots, and who is defended closely. It’s another tool to analyze the NBA. 

Early Insight

The data is new, and will need time before it starts giving us any substantial information – but there are still some early takeaways. 

Jokic is a Monster

The NBA used Jokic as its tutorial reference point for the stat, and he certainly lived up to the hype. 

In 2024/25, Jokic had a 56.5 FG%. Based on his shot difficulty; however, he was expected to shoot just 46.8%. This is a 9.7% gap that tells us just how insane Jokic is as a scorer. Not only is he the best playmaking hub for offense, he’s also the strongest shot maker in the league. 

Skilled Bigs are Outliers

The leaders of the pool for FG%+ –  the gap between a player’s xFG% and their actual FG% – are predominantly star guards. Players like Donovan Mitchell, Luka Doncic and Malik Monk are at the top. There aren’t many centers in the mix, but the upper ranks are littered with a few of the NBAs most skilled bigs. 

Nikola Vucevic (12.9%), Chet Holmgren (10.7%) and Julius Randle (10.4%), sit with Jokic (9.9%) as a few of the lead bigs so far this season. 

Finally, What About These Defender Stats?

The full defensive breakdown analytics that NBA/AWS are working on haven’t been released, but we do have two metrics that track defenders based on the offensive player. This is in the form of “defender distance” and “defender pressure.” These stats are meant to help us evaluate how a player is guarded by opposing defenses. Players who are guarded closely are taking on more attention from the defense – making it more difficult for them to score. It’s another factor to include when contextualizing a player’s efficiency. 

The first stat is straight-forward. “Defender distance” tracks how close the ball is to the nearest defender. A player who has a smaller number, is likely being hounded by defenses or double teamed more often. 

Then there is “Defender Pressure.” This metric is built around other data that is yet to be released, so the math behind it is unknown for now. The NBA website describes it as:

“A measure of how closely a player is guarded using player tracking data. It is a proprietary NBA algorithm that takes into account defensive principles.” 

Demar DeRozan is currently the most tightly guarded player with a Def PS of 0.879. 

One Last Notable Example

Despite most of the leaders for these new stats being ultra-skilled guards and savvy bigs, there is one under-the-basket center dominating the ranks. 

Hornets rookie Ryan Kalkbrenner is emerging as one of the steals of the draft. The 34th overall pick out of Creighton has started all seven games for the Hornets and is having an excellent season. He is averaging 9.0 PTS / 6.6 TRB / 2.1 BLK / 1.3 STL, while leading the NBA in FG% at 81%. 

The Shot Difficulty stats we’ve discussed support his emergence:

xFG% – 65.4%

FG% – 81.1%

FG%+ – 15.7% (2nd in NBA)

DEF PS – 0.859 (7th in NBA)

Next Up

Following the release of this new data, the NBA has three more sets that will come out throughout the season. Given that we already have some defensive pressure stats, next up will likely be the full defensive portfolio centered around defender tracking. INFO HERE

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xFG%

Expected Field Goal Percentage

Definition: The field goal percentage that we would expect an average NBA player to shoot given the player tracking details of each shot taken.

FG%+

Field Goal Percentage Above Expected

Definition: A player’s difference between “Field Goal Percentage” and “Expected Field Goal Percentage”. A good number will be positive because the player is shooting a higher percentage than expected.

MADE xFG%

Made Expected Field Goal Percentage

Definition: A player’s average expected field goal percentage when the field goal attempt is made. A lower percentage indicates more difficult shots attempted.

MISS xFG%

Missed Expected Field Goal Percentage

Definition: A player’s average expected field goal percentage when the field goal attempt is missed. A lower percentage indicates more difficult shots attempted.

MIN xFG% MADE

Minimum Expected Field Goal Percentage Made

Definition: A player’s lowest expected field goal percentage on a made field goal indicating their most difficult made shot.

2PT xFG%

2-Point Expected Field Goal Percentage

Definition: A player’s average expected field goal percentage when a 2-point field goal attempt is attempted. A lower percentage indicates more difficult shots attempted.

3PT xFG%

3-Point Expected Field Goal Percentage

Definition: A player’s average expected field goal percentage when a 3-point field goal is attempted. A lower percentage indicates more difficult shots attempted.

3PT FG%

3-Point Field Goal Percentage

Definition: A player’s made divided by total attempted 3-point field goals.

3PT FG%+

3-Point Field Goal Percentage Above Expected

Definition: A player’s difference between “Expected Field Goal Percentage” on 3-Point Field Goal Attempts and “3-Point Field Goal Percentage.

DEF DIST

Defender Distance

Definition: The distance from the ball to the defender.

DEF PS

Defender Pressure

Definition: A measure of how closely a player is guarded using player tracking data. It is a proprietary NBAalgorithm that takes into account defensive principles.