BASKETBALL AI
Hey crew, welcome to the first issue of the Basketball AI newsletter.
Everywhere you turn AI is dominating the news. AI capabilities are advancing at an unprecedented rate and the real world performance I've observed is insane.
My goal for this newsletter is to deliver the latest Basketball AI news, research, use cases and expert insight that matter to you.
In this issue:
NBA Levels Up with AWS Intelligence Platform
AI Initiative Reduces Achilles Injuries
The $12 Million Employee: Why the Front Office is the New Salary Cap Cheat Code
BYU Men’s Basketball Partners with SkillCorner for AI Analytics
How Gemini Can Revolutionize Coaching for Small College & High School Programs
AI is Just Another Scout
Let’s dive in.
LATEST DEVELOPMENTS
NEWS / NBA
NBA Levels Up with AWS Intelligence Platform
Image source: nba.com
Overview: The new multi-year partnership between the NBA and AWS is more than a cloud deal. It's a massive case study in how AI is becoming the core engine of professional basketball analytics for the NBA and its affiliate leagues (WNBA, NBA G League and Basketball Africa league).
Starting with this 2025-26 season, the new "NBA Inside the Game" intelligence platform, built on AWS, will process billions of player-tracking data points to introduce metrics we've only dreamed of:
Details: Game changing AI metrics.
Defensive Box Score: Quantifies individual defensive effort by using AI to track and assign the Primary Defender for every offensive action (ball pressure, switches, double teams). No more hidden defensive impact!
Shot Difficulty (xFG%): Measures a shot's true difficulty by analyzing the shooter's balance, defender positioning, and interference, giving analysts a much deeper understanding of Player Skill vs Circumstance.
Player Gravity: Quantifies the “Invisible Impact” of a star player by measuring how much defensive attention they draw, creating space for teammates.
Why it Matters: This is the future use of AI technology in basketball. It shows how cloud infrastructure and custom neural networks can transform raw optical data into actionable, competitive insights. Teams that master this technology to find unique and proprietary insights will gain a significant edge in scouting, game planning, and player evaluation.
RESEARCH / NBA INJURY PREVENTION
AI Initiative Reduces Achilles Injuries
Image source: bleacherreport.com
Overview: The NBA 2025 research initiative, “AI Injury-Risk Models Target Achilles Tears Across All Teams”, is a concerted effort to use AI to combat a significant spike in Achilles tendon ruptures which reached a record high of seven cases in the 2024-25 season. This urgent focus stems from the alarming rate of Achilles injuries in the 2024-25 season which saw major players sidelined including Jayson Tatum, Damian Lillard, and Tyrese Haliburton. Achilles tears are one of the most feared injuries in basketball requiring a year or more of recovery and frequently diminishing a player's career long explosiveness and performance.
Details: The initiative focuses on using a federated deep learning model to identify players at high risk of an Achilles tear before the injury occurs.
Data Aggregation: The AI model ingests massive amounts of player data from various sources such as Optical Tracking Coordinates, Wearable/Inertial Data Information (Kinexon), Electronic Medical Records (EMR) (Past injury history) and Game Video.
Risk Identification: The model uses temporal convolutional networks to identify micro overloads and repetitive movements like dorsiflexion peaks coupled with eccentric calf strain that can occur hours or days before microscopic collagen tears in the tendon might be visible via ultrasound.
Predictive Output: The system generates a risk score dashboard that forecasts the rupture probability for the next seven days. This data is delivered directly to team medical and coaching staffs.
Actionable Insights: The model provides specific, actionable workload recommendations to coaches such as "cap jumps at 65 percent in tomorrow's shoot around" or suggesting post-game glute activation protocols.
Why it Matters: By the 2025 Finals the model reportedly flagged twenty seven high risk episodes leading teams to adjust workloads. None of those flagged episodes progressed to a rupture. League wide Achilles injuries are reported to have dropped from eleven in the 2024 season to three in the 2025 season saving an estimated $58 million in salary cap losses.
The initiative marks a shift from reactive medical care to real time league wide predictive risk modeling for athlete health and welfare.
RESEARCH / FRONT OFFICE
The $12 Million Employee: Why the Front Office is the New Salary Cap Cheat Code
Image source: women-of-stem.medium.com
Overview: NBA owners will pay superstars $50 million+ for the guarantee of a few extra wins. However, a groundbreaking study presented at the 2025 MIT Sloan Sports Analytics Conference suggests the most efficient path to winning isn't on the free agent market it's on LinkedIn.
MIT researchers Arnab Sarker and Henry Wang analyzed 12 years of league data and found a direct correlation between front-office brainpower and on-court success: For every 0.8 data analysts a team hires, they generate approximately one additional regular season win.
Details:
Researchers used a "two way fixed effects" model to control for variables like injuries and schedule strength. They established two distinct exchange rates for purchasing a win in 2025:
The Roster Rate: To buy one additional win through player contracts a team must increase payroll by roughly $9.6 million.
The Analyst Rate: To buy that same win through intelligence a team needs to hire 0.8 data analysts.
Why it Matters: The implication is staggering. If 0.8 analysts provide the same value as $9.6 million in player salary then a single data scientist is worth effectively $12 million to an NBA franchise. This highlights a massive market inefficiency. A team might pay a bench player $10 million for 15 minutes of action. Meanwhile, a senior data scientist costing perhaps $200,000 can generate higher value by building the AI models that optimize lineups, flag injury risks, and identify draft sleepers.
AI is the "Engine," but Humans are the "Fuel".
NEWS / COLLEGE
BYU Men’s Basketball Partners with SkillCorner for AI Analytics
Image source: Gemini Nano Banana / Basketball AI
Overview: BYU Men's Basketball has partnered with SkillCorner to implement AI driven analytics comparable to those used in the NBA that leverages computer vision and machine learning directly from a single standard broadcast or video feed. This collaboration, announced on October 22, 2025, marks SkillCorner's first major foray into NCAA basketball and is a bold move by BYU to improve player development, game planning and recruiting.
Details:
Computer Vision for Tracking: AI is used to automatically detect, track, and follow every player and the ball in the video frame.
Machine Learning for Completeness: Sophisticated models extrapolate the positions and movements of players who are temporarily off camera, ensuring a complete and high fidelity dataset for the entire game.
Advanced Game Intelligence: Resulting tracking data is used to generate specific basketball insights like player speed, acceleration, and distance covered. Automated recognition of complex actions like pick-and-rolls, drives and closeouts are also provided.
No In-Arena Hardware Required: The system operates without the need for expensive, proprietary in arena cameras or wearable sensors making it highly scalable and flexible.
Why it Matters: This move is a strong signal of BYU's commitment to building an "NBA-level analytics function." By using data validated by multiple NBA teams, BYU's Director of Analytics and Strategy Akash Sebastian, aims to move beyond subjective assessments to objectively answer critical questions about player tendencies and decision making against specific coverages.
Elite Player Profiling: BYU can now objectively evaluate high turnover NCAA talent using NBA relevant metrics, making their scouting and recruitment more efficient.
Unprecedented Game Planning: The data allows for hyper-specific pre-game and post-game reports that pinpoint opponent weaknesses without sifting through hours of tape.
Scalability: Since the AI works off video feeds, this technology can be used consistently across any league or competition BYU is scouting, dramatically increasing the breadth and depth of their analysis.
The partnership not only pushes BYU to the forefront of college basketball analytics but also demonstrates the immense value of scalable, automated AI driven insights across all levels of professional and collegiate sports.
USE CASE
How Gemini Can Revolutionize Coaching for Small College & High School Programs
Image Source: Nano Banana Gemini / Basketball AI
Overview: For high school and small college programs the biggest disparity isn’t talent it’s staffing. Here’s where Google Gemini can help. Think of Gemini not as a search engine but as a tireless 24/7 assistant coach that can crunch advanced stats, design situational drills, plan practice sessions and more in seconds. And it’s free.
Details:
The Scout: Paste play-by-play text to find patterns. Does the opponent turn it over more against a 2-3 Zone or Man? Who takes the shot in the last 2 minutes?
The Practice Planner: Stuck on how to teach a specific concept? Ask for "3 drills to teach rotations in the Pack Line defense."
The S&C Coach: Create in season maintenance lifts that preserve legs but maintain strength tailored to a gym’s limited equipment.
Sample Prompts (Copy & Paste into Gemini):
Game Planning: "I am pasting the play-by-play logs from our opponent's last two close games. Identify who they go to for a shot when there are under 2 minutes left in the 4th quarter."
Drill Design: "We struggle scoring against a 1-3-1 Zone. Give me 3 competitive breakdown drills, 4-on-4, that teach finding the gaps and corner passing."
Advanced Stats: "Here are the raw stats from our last 5 games. Calculate our Effective Field Goal Percentage (eFG%) and Turnover Rate. Compare these to the high school national average."
Player Development: "My point guard is struggling with confidence after 3 bad games. Write a script for a 5-minute individual meeting to rebuild their confidence without ignoring the turnovers."
SLOB/BLOBs: "Design two Sideline Out of Bounds (SLOB) plays that look identical initially but have one counter option for a 3-point shooter."
Why it Matters: The modern coaching bottleneck can lead to administrative fatigue. Teams play 2-3 games a week and coaches barely have enough time to scout the next opponent. Gemini saves time by grading the previous game’s box score and bridges the gap between "eye test" coaching and "data driven" winning. A two person coaching staff can now output the logistical and analytical work of a ten person department.
Key Benefits:
Massive Time Savings: Reduce 4 hours of admin work to 20 minutes. Spend less time typing and more time coaching.
Deep Insights: Spot statistical trends the eye test might miss.
Efficiency: Turn 2 hours of stat grading into 10 minutes.
Agility: Adjust practice plans instantly based on yesterday’s film.
Many coaches are are already using AI Chatbots / Conversational AI like Gemini or ChatGPT as a valuable assistant coach. Those that are not probably should.
AI is Just Another Scout
Image source: Manus / Basketball AI
Overview: Is Artificial Intelligence the ultimate decision-maker in professional sports? According to one top executive the answer is a definitive NO.
Details:
Daryl Morey, President of Basketball Operations for the Philadelphia 76ers, perfectly frames this necessary balance: "We absolutely use models as a vote in any decision... They still are not beating human, like, super forecasters... So we'll treat them almost like one scout."
This "one scout" perspective is critical. AI models, including Large Language Models (LLMs), excel at prediction and adding signal, but they lack the nuance, context, and intuition of a seasoned human expert.
Why it Matters: The real competitive advantage isn't found in replacing humans, but in using AI as an incredibly powerful advisor and collaborator.
QUICK HITS
🛠 Tools Spotlight:
Tools mentioned in this edition:
NBA on AWS. AWS is a new technology partner of the NBA.
Kinexon Sports. Elite-level player and ball tracking solutions.
SkillCorner. Tracking data and performance insights.
Gemini. Google AI assistant.
COMMUNITY
🤝 Basketball AI Workflows
Every newsletter we showcase how the basketball community is using AI in workflows to work smarter, save time, or find ways to gain a competitive advantage.
This week we focus on Dan Barto, Technical Director Basketball Innovation, at IMG Academy who recently shared insights on LinkedIn about how their institution is integrating Artificial Intelligence into the basketball program.
IMG Academy has focused on embedding AI workflows into daily coaching operations to educate players, streamline planning, save time, and enhance learning and analysis.
The integration has significantly boosted the output of content, education, and analysis for athletes, enabling thought projects to be executed faster than ever before.
Use of AI in workflows is helping IMG Academy move from the "innovation" stage to the "early adopter" stage within the next six months.
This forward thinking approach is driven by a commitment to continually push coaches to grow and maintain their standard of being "One of One."
📆 Upcoming Conferences, Events and Guides:
February 22-24, 2026 National Sports Forum (NSF)
March 6-7, 2026 MIT Sloan Sports Analytics Conference (SSAC)
April 10-11, 2026 Connecticut Sports Analytics Symposium (CSAS)
That’s It:
That’s a wrap for this edition. The next newsletter will be published Tuesday January 6, 2026.
I hope you found the content useful. In the next newsletter I’ll be including ways for you to provide feedback to make sure the content is what you want and can use.
Have a safe and Happy Holiday!!
Until next time,
Terry