Win and Win WIAWIS NS-G Limbs

Win and Win WIAWIS NS-G recurve limbs

Win and Win

$788.00 

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You can test this bow at our shop with a shooting range of 20 yards in Washington.  Complete with 32# NS-G limbs and all carbon Win and Win Stabaliser set, you can book in to test shoot the bow by emailing us on eaglearchery@hotmail.co.uk
The Wiawis NS-G Limbs use a limb base made of advanced nano graphene. To create optimal bending distribution, we analyzed the correlation between the stability and speed of our limbs. Thanks to these advancements you will notice the WIAWIS NS-G limbs have a smooth draw while also remaining extremely stable. This provides the archer with better scores and more accurate shooting, both core strengths of Win&Win.

Graphene Limb Base
The Wiawis NS-G limb uses a limb base made of nano graphene prepreg-dispersed in a high molecular epoxy which has been shown to absorb shock and vibration more efficiently, and help stabilize limb momentum after shooting. This new concept of limb construction was solely developed and used by Win and Win.
Strain-Balance Technology
Win and Win has enhanced the 2019 WIAWIS NS limbs in both power and stability by applying Strain-Balance technology. The result of years of research, Strain-Balance technology helps Win and WIN find the optimal limb flex profile through analysing the relationship between stability and speed according to limb flex.
The new NS limbs feature enhanced smoothness while drawing without compromising the arrow speed and accuracy which Win and Win  is known for.
Bow accuracy can be determined by a string movement during a shot. Short, narrow, consistent movement indicates an efficient transfer of energy to the arrow and reduced shooting shock and vibration. Further, consistent and controlled movement reduces bow torque at the moment of shooting  and improves  arrow grouping. 
WIAWIS NS-G  limbs employ nano graphene technology to offer shorter and narrower string movement than any other limbs and provide the most efficient energy transfer. This performance gives better grouping with forgiveness.

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