Laser-Focused On Pickleball Performance
Pickleball players are obsessed with getting better. After every game, they search for signals in the noise—game results, DUPR changes, feedback from partners and opponents, coaching advice, and sometimes video or match statistics.
But most pickleball is played as doubles and isolating individual performance in team sports is inherently difficult.
The biggest breakthroughs in team sports analytics came from a simple realization: by linking a player’s actions to their impact on outcomes, we can create metrics that explain both how the player performed and how that performance influenced real-life results.
In baseball, individual actions affect a team’s chances of scoring or preventing runs. In football and basketball, they affect scoring or preventing points.
In pickleball, every shot has one clear purpose: to improve your team’s chances of winning a rally.
PEWPEW measures performance the same way—by evaluating how each shot changes the probability of winning the rally. Using shot-level match data generated from video, the system produces performance reports that explain why matches were won or lost, quantify each player’s impact on the outcome, and reveal strengths and weaknesses across different parts of a player’s game.
These insights can also be expressed as DUPR-like gameplay ratings and structured metrics that power AI-generated match analysis.
What Is PEWPEW?
PEWPEW (Player Estimated Win Probability Effect With Shots) is an analytics framework that measures the value of every shot in a pickleball match.
Using video-derived shot-level data, the system evaluates how each shot contributes to winning or losing a rally and aggregates those effects into player impact metrics and DUPR-like gameplay ratings across different parts of the game.
Because the framework is grounded in rally outcomes, it provides a consistent way to measure how players actually influence match results.
The resulting analytics can power performance dashboards, match reports, player ratings, and structured metrics that enable AI systems to generate clear explanations of match outcomes and player strengths and weaknesses.
Answering The Key Questions Every Player Asks
PEWPEW turns shot-level match data into performance dashboards, match reports, and outcome-based ratings that answer the questions players ask after every match — while providing structured metrics that allow AI systems to generate clear explanations of match outcomes and player strengths and weaknesses.
Why Did I Win or Lose?
PEWPEW aggregates performance across shots and game situations to quantify the factors that actually drove victory or defeat.
What Are My Strengths / Weaknesses?
PEWPEW generates DUPR-like ratings across different parts of the game, revealing strengths and weaknesses throughout your play.
How Did I Actually Play?
PEWPEW credits players for the projected impact of their shots on each point — separating their performance from partners and opponents.
Am I Getting Better?
Track DUPR-like ratings over time to see where your game is improving — and where it still needs work.
Every Shot Needs A Target
The one statistical truth in a doubles pickleball match is the final score and rally count. Any model that evaluates player performance must ultimately be grounded in that reality. If a model cannot explain why one team won and the other lost, it is difficult to trust that it reflects true player value.
Rating systems like DUPR reflect this principle. The DUPR algorithm is designed to predict future match scores based on past results.
While DUPR ratings are often interpreted as skill assessments, what makes pickleball unique is that many different playing styles can produce the same rating. A 3.3 player may hit harder drives than a 3.8. A 4.0 may struggle with dinks but excel at volleys. Players reach the same level through different combinations of strengths and weaknesses.
To understand how those skills translate into results, the game must be measured at the level where outcomes are decided: each individual shot.
PEWPEW does exactly that — quantifying how every shot changes a team’s probability of winning the rally and turning those effects into performance metrics, gameplay ratings, and structured analytics.
Analytics First. AI Second.
Generative AI is a powerful tool for explaining insights and summarizing performance. But when raw match data is fed directly into AI systems, the results can become a black box.
For players who care deeply about improving their game, that lack of transparency matters. They want to understand why certain strengths or weaknesses were identified and whether those conclusions actually reflect what happened on the court.
PEWPEW takes a different approach. Performance is measured using a concrete analytical model that evaluates how each shot changes the probability of winning a rally. Because the methodology is stable, the resulting metrics are calculated consistently and remain accountable to what actually happened on the court.
When insights are built on transparent analytics, they pass the “sniff test” for players and coaches who know their own games.
That level of rigor becomes even more important as video-derived performance metrics begin to connect with broader rating ecosystems. If video results ever influences ratings, the underlying analytics cannot be a black box.
Improving performance starts with precise measurement—not black-box analysis.
Where PEWPEW Fits
PEWPEW Analytics complements the growing ecosystem of video and smart-court technology in pickleball. Platforms that capture match footage and extract shot-level data are creating a powerful new foundation for the sport.
PEWPEW extends that foundation by turning shot-level data into outcome-based performance analytics that explain match results, reveal player strengths and weaknesses, and generate DUPR-like gameplay ratings across different parts of the game.
For video and smart-court platforms, this creates several advantages:
• Deeper performance insights and AI-generated match analysis
Outcome-based analytics explain why matches were won or lost and how players contributed, while structured performance metrics allow AI systems to generate clear summaries of player strengths and weaknesses.
• Greater value from video and shot-tracking data
Platforms that capture shot-level data can deliver richer performance dashboards and match reports that go far beyond raw statistics.
• Allows technology teams to focus on video and AI innovation
Platforms can continue advancing capture technology, computer vision, player verification, data visualization, and user experience without needing to build and maintain complex analytics methodologies.
• New premium analytics and coaching features
Advanced performance insights and gameplay ratings can power subscription tiers, coaching tools, and deeper player engagement.
• Natural alignment with rating ecosystems like DUPR
Outcome-based performance metrics can help connect video-derived insights with broader rating systems.
Built to Integrate with Video Platforms
PEWPEW is designed to operate at enterprise scale, allowing video platforms to generate advanced performance analytics within seconds after a match ends.
The system integrates easily with existing video and smart-court platforms by accepting shot-level match data through a simple API and transforming it into outcome-based analytics—without requiring changes to existing video capture or AI pipelines.
1. Video Platform Captures Match Data
Video systems record matches and generate shot-level data such as player actions, ball trajectories, and rally sequences.
2. Shot data Sent To The PEWPEW API
Each rally is modeled to evaluate how individual shots influence the probability of winning the point.
3. Analytics Returned To The Platform
• Match summaries with individualized player impact metrics
• Structured metrics that support dashboards, reports, and AI-generated match analysis
• Gameplay ratings and player trends across matches
Contact Us
Ready to add performance analytics your players will obsess over?
PEWPEW Analytics is currently seeking video technology and club partners. Reach out to schedule a demo or discuss potential integrations.
You can also e-mail directly at info@pewpewanalytics.com