SKU: 36825108662

Stigmata 4 CC Rival AXS 1X Rudy (2025)

Sale price$1934.55 Regular price$2149.50
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Description

Stigmata 4 CC Rival AXS 1X Rudy (2025)The Stigmata blurs the lines between free roading drop bar singletrack slicer and buckled down race winning gravel machine. Its designed for the rider lining up for The Big Event, escaping via the road less traveled or who cant help themselves from finding the hardest way there. Whether your style is baggy or zipped up, the Stigmata is the fast and loose riding partner thats always ready to rise to the occasion. FEATURES: Dropper post compatible. Get

The Stigmata blurs the lines between free-roading drop bar singletrack slicer and buckled down race-winning gravel machine. It’s designed for the rider lining up for The Big Event, escaping via the road less traveled or who can’t help themselves from finding the hardest way there. Whether your style is baggy or zipped up, the Stigmata is the fast and loose riding partner that’s always ready to rise to the occasion.

FEATURES:

  • Dropper post compatible. Get that thing out of the way for hair-brained riding!
  • Long reach – designed around 70mm stems – with a slack head tube angle. Adapting progressive MTB geo for ultra off-road capabilities.
  • Great rollover on fast rolling 700c wheels with up to 50mm tire clearance. Choose fast or fun tires. Or fast and fun tires.
  • The Glovebox allows for extra room to stash the essentials, even with a full complement of frame bags.
  • Low profile fender mounts. If you don’t use fenders, you don’t want to see mounts. But when you want them, you got them.
  • Third bottle mount on the downtube is the only extra mounting point. No unsightly riv-nut zits keeps frame clean and lightweight.
  • No stem/headset cable routing and a standard IS tapered headset, so it’s easy to adjust fit or perform maintenance out in the field.

SPECS:

Frame Carbon CC Gravel
Fork RockShox Rudy Base XPLR, 40mm
Rims/Wheels Easton ARC Offset 25 700c
Hubs [F] DT Swiss 370, 12x100, Centerlock, 28h [R] DT Swiss 370, 12x142, XDr, Centerlock, 28h
Spokes N/A
Tires Maxxis Rambler, 700x45c, DC, EXO, TR
Crankset SRAM Rival 1 DUB Wide
Chainrings 42t
Bottom Bracket SRAM DUB 68mm Road Wide BB
Chain SRAM GX Eagle T-Type, Flattop, 12spd
Front Derailleur N/A
Rear Derailleur SRAM GX Eagle AXS T-Type, 12spd
Cassette/Rear Cogs
SRAM GX Eagle T-Type, 10-52t
Shifters SRAM Rival AXS
Handlebars Zipp Service Course 70 XPLR AL Bar
Stem Zipp Service Course Stem, 70mm
Brakes SRAM Rival AXS
Pedals Sold Separately
Saddle WTB Silverado Medium, CroMo
Seat Post Easton EC70, 27.2, Zero Offset, 350mm
Extras N/A

 

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SKU: 36825108662

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Zay
Charlottesville, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
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Reviewed in the United States on October 23, 2024
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Rory Derrick
Lexington, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
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Cory P.
West Palm Beach, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
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Frank Gonzalez
Fort Morgan, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Phoenix, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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