How Surfers Use AI to Analyze Wave Patterns & Improve Performance

AI is changing the way surfers in Australia ride waves. Here's how:

• Wave Forecasting: AI predicts wave height, quality, and conditions with greater accuracy using historical and real-time data.
• Safety: AI identifies dangers like rip currents, helping surfers stay safe in unpredictable waters.
• Performance Tracking: Tools like Flowstate analyse surfing techniques, offering feedback on manoeuvres, wave selection, and body positioning.
• Personalised Training: AI creates tailored training plans based on individual strengths and weaknesses, helping surfers improve faster.
• Video Analysis: AI breaks down footage frame-by-frame, delivering insights into biomechanics and movement patterns.

Whether you're a weekend surfer or a pro, AI tools are helping surfers make smarter decisions, train better, and stay safer in Australia's diverse surf conditions.

Flowstate: Tracking and Shooting Surfers with AI in Wave Pools

What AI Does for Surfing

AI takes ocean data and surfer movements and turns them into practical insights, enabling Australian surfers to make smarter choices both on and off the waves. By processing vast amounts of environmental and performance data, it paints a detailed picture of surfing conditions and individual techniques. Let’s dive into how AI interprets both the ocean’s signals and a surfer’s performance.

How AI Reads Wave and Weather Data

AI systems gather and analyse both historical and real-time ocean and weather data, including buoy readings and tide records, to predict wave height, surf quality, and other key factors at specific spots [3]. Machine learning models, trained on years of data, uncover patterns that traditional forecasting methods often miss. For example, a Queensland study from 2010 to 2022 used a Random Forest model to predict significant wave heights with impressive precision (MSE 0.0074, R² 0.958) [4]. The model zeroes in on critical factors like maximum wave height (Hmax), wave periods (Tz, Tp), and sea surface temperature (SST) [4].

"While the perfect wave will always be a mix of skill, experience, and a dash of luck, machine learning is helping surfers get closer to that ideal wave with more confidence and accuracy than ever before."
– alagar, AI and Data Science Professional [3]

What makes AI stand out is its ability to handle the complex, non-linear behaviour of the ocean while keeping computational costs low [4]. But AI doesn’t stop at predicting waves - it also focuses on improving surfer performance.

How AI Tracks Surfer Movement

AI doesn’t just read the ocean; it also hones in on surfer technique, a crucial aspect when dealing with Australia’s diverse coastal conditions. These systems analyse strengths, identify areas for improvement, and track progress over time [2].

One standout example is Flowstate’s AI system. In February 2025, Flowstate introduced a real-time move recognition system built on a dataset of over 7.4 million recorded waves [2]. This system breaks down specific surfing manoeuvres, identifies the wave’s optimal "pocket" for speed and control, and creates performance clips for coaching and analysis [2]. Beyond tracking moves, AI also offers safety tips, surf spot recommendations, and even gear advice tailored to the day’s conditions [6]. USA Surfing, for instance, uses Microsoft Azure AI to analyse surfing videos, helping coaches refine both athlete and surfboard performance while reducing injury risks [7].

"Move recognition in surfing is a complex challenge, requiring cutting-edge AI in video processing and analysis. Powered by our unmatched surf library with over 7.4 million waves, this breakthrough advances AI-driven sports analytics, elevating performance tracking, competition insights, and automated highlights."
– Chris Hausler, CTO at Flowstate [2]

"This is every coach's dream to have access to. Flowstate continues to create these amazing tools that save so much time that was previously lost to manual processes and enabling coaches to open the world to us to share our knowledge. This to us as coaches is up there with colonising Mars for humanity."
– Andy King, Head Coach at Flowstate [2]

Using AI to Predict Waves

AI is revolutionising how Australian surfers prepare for their sessions, turning complex ocean data into straightforward, actionable forecasts. These tools help pinpoint the best waves along the coastline, enhancing both performance and planning. Here's how forecasting models and data visualisation work together to improve surf training.

AI Wave Forecasting

AI-powered wave forecasting involves analysing a mix of data sources to deliver precise surf predictions for specific Australian locations. These models pull information from historical wave patterns, buoy readings, tide charts, wind speed and direction, and even local topography [3]. A critical step in this process is feature engineering, where the AI focuses on key variables like wave height (measured in metres), wave period, wind direction, and water temperature (measured in Celsius) [3].

Machine learning techniques, such as regression models, time series analysis, and deep neural networks, are then applied to this data. These methods train on historical patterns and fine-tune their parameters to reduce prediction errors [3]. The addition of geographic details, like coastal features and underwater contours (bathymetry), further sharpens the accuracy of these forecasts [8].

Recent advancements in AI have led to significant improvements in forecast reliability. Some systems have cut error rates by up to 50% by integrating more data and refining machine learning techniques [11]. Beyond surfing, tools like Microsoft’s Aurora AI model and Google DeepMind's Graphcast have demonstrated the potential of AI in weather forecasting. For example, Graphcast operates 10 times faster than traditional methods and predicts storm patterns with 70% to 80% accuracy up to two hours in advance [9].

These AI systems now offer detailed predictions on wave height, period, direction, shape, slope, and breaking speed [3][11]. Such precision directly supports surfers in planning their sessions and tailoring their training. Some advanced platforms even incorporate real-time buoy measurements and physical models to account for wave travel time and dispersion, making localised forecasts even more accurate [10].

How AI Shows Data to Surfers

Once the forecasts are ready, the next challenge is presenting this complex information in a way that surfers can easily understand and use. AI platforms cater specifically to Australian surfers by displaying metrics like wave height in metres, wind speed in kilometres per hour, and temperature in Celsius. They also use a 24-hour time format, simplifying planning for both early morning and late afternoon surf sessions.

In 2021, an advanced system was introduced that combines high-resolution bathymetry with nearshore wave models. By processing 25 years of surf reports and satellite data, it performs billions of calculations to deliver highly accurate predictions [13]. This raw computational power is distilled into user-friendly displays that include wave quality ratings, ideal surf times, and recommendations tailored to specific locations.

Modern AI platforms go beyond standard predictions by offering personalised forecasts. These systems consider individual preferences, such as ideal swell size, period, direction, wind conditions, and tides, to generate customised surf reports [11][12].

One of the standout features of these AI tools is their ability to learn continuously. By incorporating fresh data and retraining their models, they improve forecast accuracy over time [3]. This ongoing refinement ensures surfers have the insights they need to make informed decisions, helping them maximise their time in the water while staying safe along Australia's diverse and often unpredictable coastline.

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AI Tools That Improve Surf Performance

AI is reshaping the way Australian surfers refine their skills and elevate their performance. By blending advanced video analysis with biomechanical insights, these tools deliver precise, data-driven feedback. This combination allows athletes and coaches to break down techniques and make meaningful adjustments, paving the way for faster skill development.

Video Analysis and Move Tracking

Today's AI systems dissect surfing footage frame by frame, capturing detailed data on body positioning, timing, and how manoeuvres are executed. This level of analysis goes far beyond what the human eye can detect, offering insights that help coaches identify critical moments and fine-tune techniques [16]. By examining the biomechanics of each movement, these tools provide recommendations that target specific areas for improvement. AI-powered move recognition ensures that no detail is missed, giving surfers and coaches the edge they need to perfect their craft.

Tracking Progress and Training Plans

AI platforms don’t just analyse performance - they help surfers grow over time. By tracking metrics like wave selection, positioning accuracy, and manoeuvre success rates, these systems build detailed profiles that highlight both strengths and areas for improvement. Personalised training plans are then created based on this data, offering tailored guidance for each athlete. For instance, Microsoft's collaboration with USA Surfing uses advanced algorithms to pinpoint areas where surfers can sharpen their technique [14]. Some tools even offer 3D coaching, providing instant feedback on body motion for real-time adjustments [15]. Additionally, ongoing progress tracking helps surfers visualise optimal wave positioning and informs long-term training strategies [5].

AI Tool Features Compared

Different AI features cater to various training needs, making it easier for surfers and coaches to select the right tools. Here’s a quick comparison of what these tools offer:

Feature	Benefit
Real-time Move Recognition	Delivers immediate feedback during practice sessions.
Post-Session Analytics	Allows for detailed reviews and visual breakdowns of recorded sessions.
3D Biomechanical Analysis	Offers precise insights into body motion and positioning.
Pattern Recognition Across Sessions	Tracks trends over time to guide long-term growth.

Some AI coaching platforms are trained on extensive action sports data, enabling them to identify subtle technical details. These insights work hand-in-hand with human coaching, providing a comprehensive approach to improving performance [14].

Adding AI to Your Surf Training

Building on the performance insights discussed earlier, weaving AI into your surf training routine is easier than you might think. All you need to get started is a basic camera and access to an AI platform. For most Australian surfers, this simple setup is enough to kick off AI-powered analysis.

How to Incorporate AI into Your Training

Start by recording your surf sessions with a single land-based camera. Make sure the footage captures your stance and movement patterns clearly.

Once recorded, upload your session footage to an AI platform. The software will analyse the video and generate detailed performance metrics. These insights can include feedback on elements like stance, coil, torque, wave shape, and board dynamics - details that are often missed during manual observation[17].

From there, focus on the specific areas flagged by the AI. For instance, if the analysis highlights issues with your bottom turn positioning, you can dedicate future sessions to drills targeting that weakness. This kind of data-driven approach ensures your training is precise and effective.

Track your progress over time by regularly uploading new session footage. Comparing metrics from different sessions helps identify patterns in your improvement and allows you to tweak your training programme as needed[1]. This ongoing process complements the broader AI-driven strategies discussed earlier, helping you refine your skills continuously.

This step-by-step process mirrors the methods used in professional coaching frameworks, making advanced training tools accessible to surfers at all levels.

Case Study: AI Coaching in Practice

In February 2023, USA Surfing teamed up with Microsoft Azure AI to introduce their Motion Insights framework. This collaboration showcases how AI can revolutionise athlete development[17]. Surfers simply upload their session videos, and the platform provides detailed insights into body positioning, movement patterns, and board dynamics. Coaches then use this data to offer highly specific feedback.

Kevin Schulz, a surfer with USA Surfing known for his aerial skills, shared his thoughts on the system:

"These machine learning models, by measuring angles between the joints of the body while performing surf manoeuvres, can actually help coaches to provide feedback."[17]

The framework also plays a key role in injury prevention. By identifying movements that could lead to injuries, coaches can step in before problems arise. Ryan Simmons, Head Coach at USA Surfing, explained the value of AI in this context:

"A machine will obviously never replace the human relationships between trainers, physical therapists, coaches and athletes, but it does provide another piece of insight and information that so many other sports are using to prevent injuries."[17]

Coaches have found the system invaluable for spotting technical flaws that might have taken months to detect through traditional methods. By measuring joint angles and movement patterns, the AI delivers objective data that helps both coaches and athletes pinpoint necessary adjustments.

This approach has also gained traction in Australia, where surf coaches are increasingly integrating AI into their training programmes. Rather than replacing traditional coaching, the technology acts as a powerful tool to enhance it, providing data-backed insights that sharpen technical skills and reduce injury risks. This case study highlights how AI complements human expertise, making training more targeted and effective.

Conclusion: AI's Impact on Australian Surfing

AI has reshaped the landscape of Australian surfing by offering real-time wave predictions and advanced skill analysis with actionable feedback. This technology not only boosts performance but also enhances safety, providing insights and capabilities that were once out of reach[1].

On the safety front, AI has proven to be a game-changer. In 2019, it played a pivotal role in rescuing a surfer from a rip current after detecting hazardous conditions and alerting nearby surfers[1]. This example highlights AI's dual role as both a performance tool and a critical safety resource, particularly vital in Australia's diverse and often unpredictable coastal waters.

Australia is also doubling down on AI-driven training advancements. The Australian Institute of Sport has committed $1.17 million to install multi-camera video systems in 28 high-performance centres across the country[18]. Among the beneficiaries is Surfing Australia's High Performance Training Centre in Tweed Heads, NSW, where cutting-edge video analysis is now enabling real-time coaching feedback[18].

"This investment makes world-class video technology more accessible to coaches and developing athletes right around the country and will help to super-charge their development for future success." – Matti Clements, AIS Director[18]

Beyond safety and skill refinement, AI is revolutionising competitive surfing. By delivering personalised training programs and objective data, it allows coaches to make immediate adjustments based on precise analysis[1]. This data-driven approach ensures Australian surfers remain competitive, whether tackling local breaks or going head-to-head on the international stage.

From the powerful swells of Western Australia to the intricate waves of the Gold Coast, AI equips surfers with the precision and insights needed to conquer Australia's diverse coastal environments. This fusion of technology and sport is setting the stage for Australian surfers to excel in any challenge the ocean throws their way.

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