SKU: 33306986835

LAZR-16X Full Foam - Red

$152.10 $169.00
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Description

LAZR-16X Full Foam - Red(Includes paddle cleaner & neoprene cover) Pew! Pew! Pew! GRUVNs new LAZR 16X Full Foam (elongated shape) is our new dual density full foam core pickleball paddle. It is a high performance paddle with a Kevlar carbon fiber blend surface and a 16mm core. A great balance of stability, feel, controllable power, pop, and spin. It is USAP PBCoR 0. 43 Certified for tournament play. DuPont and Kevlar are trademarks or registered trademarks of affiliates of

(Includes paddle cleaner & neoprene cover)

Pew! Pew! Pew! GRUVN’s new LAZR-16X Full Foam (elongated shape) is our new dual-density full foam core pickleball paddle. It is a high-performance paddle with a Kevlar-carbon fiber blend surface and a 16mm core. A great balance of stability, feel, controllable power, pop, and spin. It is USAP PBCoR 0.43 Certified for tournament play. DuPont™ and Kevlar® are trademarks or registered trademarks of affiliates of DuPont de Nemours, Inc.

Play Style
This paddle falls in the power category (mid to low-tier power). In the current market it is in about the 83% percentile for power and 70% pop, a great place to be! The dual-density foam core provides a comfortable foamy feel along with great stability. Many players comment how great it feels off the face and how well the paddle seems to grab the ball, allowing them to shape the ball more easily. The core combined with the Kevlar-carbon fiber surface provides a solid amount of power and pop and great spin (2178 RPM!)

Paddle Shape
The long paddle length of 16.5” extends players’ reach and the 5.5” handle length allows for powerful two-handed backhands. The rounded top of the paddle face gives players an aerodynamic feel, and the weight of ~8.0 ounces provides stability and balance for all aspects of the game, including plays at the net and returning hard shots. The paddle has a swing weight of 117 and a solid twist weight of 6.46. It has a 16mm thick full foam core designed to evenly react to the force of impact and provide precision control, while also absorbing vibration and noise.

Product Features:
• The dual-density foam core includes an EPP full foam core surrounded by softer EVA foam. There is a gap between EPP and EVA to prevent layers from separating over time.
• Edge foam starts at the neck and extends into the handle
• Thermoformed
• Handle is honeycomb polypropylene to keep the weight down
• Kevlar-carbon fiber surface provides a bit more pop and power than carbon fiber paddles
DuPont™ and Kevlar® are trademarks or registered trademarks of affiliates of DuPont de Nemours, Inc.

Benefits of a dual -density full-foam core: 
• Enhanced Durability: Full foam doesn't crush like honeycomb cores can, maintaining structural integrity and preventing performance breakdown over time.
• Larger Sweet Spot: Foam fills the core more consistently, eliminating dead spots and providing a predictable, reliable feel across the entire paddle face.
• Superior Control & Spin: Increased dwell time allows for better manipulation, leading to more spin and precise shot placement.
• Less Vibration & Arm Fatigue: The cushioning effect of foam absorbs shock, making it ideal for players with tennis elbow or wrist pain.
• Consistent Feel: Offers a more uniform feel and predictable response,
• Balance of Power & Control: The combination of EPP and EVA foam offer both power and touch.

 

How does the LAZR-16X Full Foam compare to other GRUVN paddles?
The LAZR Full Foam series has a bit more pop and power than our MUVN Full Foam paddles, and a bit more power than our polypropylene paddle series (LAZR, MUVN, CRUZN).  Our LAZR-16HD Solid Foam paddle has more power (it also has a different core). That paddle tested at PBCoR 0.44. The limit has since been reduced to 0.43, and that paddle model can be played in tournaments until May 1st, 2026.

This model comes with two color options: red blend surface and blue blend surface.

Paddle Cover Included
A zippered neoprene cover with the GRÜVN logo to protect the pickleball paddle when not in play ($15 value!).

Paddle Cleaner Included
• Each Kevlar-carbon fiber and carbon fiber paddle comes with a GRUVN paddle cleaner, which is a stick of rubber that is 2.5” x 2” x 1” in size, This is not for graphite or composite paddles). Rub it on your paddle surface to keep it clean and also maximize the spin. It isn't pretty, but your paddle will be after using it :)

 ** PADDLE CARE – IMPORTANT **
Your paddle can become damaged from extreme temperatures. Extreme cold temperatures can cause the hitting surface to become brittle and crack. Extreme high temperatures can soften the hitting surface and can cause delamination. This occurs when the hitting surface separates from the core. Do not leave your paddle out in the sun on a hot day, be sure to cover it from the heat or it can be damaged. Do not leave your paddle in your vehicle during the summer or winter.

(Different computer monitors and mobile phones display colors differently, so the color of your paddle may vary slightly from the representation on your screen) 

SPECS:
Face/Paddle Surface: DuPont™ and Kevlar® + T700 Raw Carbon Fiber  
DuPont™ and Kevlar® are trademarks or registered trademarks of affiliates of DuPont de Nemours, Inc
Paddle Length: 16.5”/ 419.1mm
Face Width: 7.5”/ 190.5mm
Handle Length: ~ 5.5”/ 14cm
Grip Size Circumference: ~ 4.125”/10.5cm
Grip: Flat Grip 
Weight: Average weight of 8.0 oz (+ or - 0.25 oz)/0.5 lbs/227g
Paddle Shape: Elongated
Core Thickness: 16mm/0.63”
Core Material: Dual-Density Full Foam (EPP + EVA)
Core Thickness: 16mm/0.63”
Swing Weight:  ~ 111 -117
Twist Weight: ~ 6.46
Spin Rate: ~ 2178 RPM
Balance Point: ~ 243

USAP PBCoR 0.43 Certified for tournament play.

SHIPPING
(Ships within 24 hours on regular business days)
US: 2-5 days ($5USD shipping flat rate)
Canada: 7-10 days ($8USD shipping flat rate)
International: 7-10 days ($9USD shipping flat rate)

WARRANTY
GRUVN's LAZRFull Foam series of pickleball paddles are guaranteed to be free of manufacturing defects for a period of 6 months from the date of purchase. If found to be defective, a repair or replacement will be issued.

What does the warranty not cover?
• Normal wear and tear, or damages caused by abuse or negligence, including grip, edge guard, face and core materials.
• User modification, fading or scratched surfaces, or hitting other objects other than the ball (like the ground or other paddles).
• Use of paddle in temperatures below 40F or 5°C.
• Paddles being played in or stored in very hot or very cold weather.
• Rattling that doesn't affect performance.
• Warranty is non-transferable and only valid to the original purchaser.
• Warranty does not apply to replacement paddles.
• Other restrictions may apply
• GRUVN may exercise the right to determine whether a paddle is covered by our warranty and whether to replace it.
• Proof of purchase is required

RETURN POLICY
If there is no manufacturing defect, your paddle can only be returned if you ordered the wrong item from our store. You can receive a replacement item from GRUVN.co if the original item is returned to us unused and in its original packaging. GRUVN must be notified about any wrong order within 48 hours of the customer receiving the item. Any price difference in the item exchange will need to be resolved before the replacement item is sent. Otherwise, if there is no manufacturing defect, the item(s) received will not be refunded or returned.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
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  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 33306986835

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4.3 ★★★★★
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Belleville, US
★★★★★ 5
Excellent book, possibly currently unique in coverage of latest ideas
This book is possibly currently unique in its coverage of the latest ideas in the field of deep learning -- and it is a very convenient and good survey of fundamental concepts (linear algebra, optimization, performance metrics, activation function types), different network types (multi-layer perceptron, convolutional neural networks, and recurrent neural networks), practical considerations (data set, training and validation, implementation), and applications (comments on existing real-world/commercial uses). The final 235 pages of the content portion of the book is dedicated to topics in "Deep Learning Research", and these topics are truly at the current frontier. Another reviewer said that one could gain the same knowledge of cutting-edge research by reading all of the latest papers (from academia and industry), but the "research" section of this book offers the following: Selection of the most notable research by the very experienced authors of the book, and collection of similar research in to a broader discussion of themes, and the additional insights. The book covers very advanced and new ideas currently being explored, and it is very nice to be able to have a consistent and coherent presentation of all of those ideas. However, the book is also packed with valuable observations and pointers about more basic aspects of deep learning implementations and practices -- and such commentary is in depth and includes substantial analysis and mathematical derivation (in an intuitive presentation that often includes graphs illustrating the phenomenon). As someone with an intermediate level of knowledge and experience of neural networks, I am really grateful for this book, because seems like the ideal resource for learning cutting-edge ideas and practices, with context. The book has excellent scope and depth, and I am confident that anyone with a solid background in linear algebra, calculus, statistics, and general machine learning, and basic neural networks (multi-layer perceptrons) will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level and a new frontier. I was personally excited to learn about the idea of representing the dependencies of intermediate quantities by directed graphs, and how this can be used to perform calculations for recurrent neural networks efficiently. And I think the long chapter on recurrent neural networks is very helpful. Having said all of this, I think only people with significant working knowledge and experience with neural networks and mathematics -- people whose academic or professional focus has been neural networks for at least a year or two -- would benefit from this book. This book answers a lot of the deeper questions that one is likely to have while developing a solid understanding of the fundamentals, and that's one of the book's tremendous values, but this book assumes an understanding of the fundamentals (but does briskly cover the basics). I think this book is a perfect follow-up book for the excellent book "Neural Network Design (2nd edition)" by Hagan, Demuth, Beale, and de Jesus, and I highly recommend the latter for gaining the solid background needed to have a thrilling experience with the "Deep Learning" book. In summary, I am very glad this "Deep Learning" book was written, and I think the "Deep Learning" book will be a great benefit to a lot of people, and to the evolution of the field.
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Reviewed in the United States on April 18, 2017
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Zygerian99
Louisville, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
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Reviewed in the United States on January 21, 2020
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Shannon
Phoenix, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
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Verified Purchase
William P Ross
Birmingham, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
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Verified Purchase
Adam
New York, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026

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