The fastest bike for The Uber Pretzel
- 128.8 km with the 0.5 km lead-in
- 2381 m of climbing
- 18.6 m/km climb ratio
- 5 named climbs, 1 sprint
- Surface82.7% tarmac12.9% dirt and snow4.4% wood and cobbles
Fastest eligible setup · Standard (Road) · verified data only · Halo bikes hidden
with Princeton Wake 6560 White wheels
4:49:29
26.7 km/h averageestimated for 1 lap with the lead-in
- Data
- Frame and wheels bot-tested
- Upgrades
- Ranked at upgrade stage 5, assumed for bikes you don't own
- Rough surfaces
- Rough surfaces cost this setup about 6:23 minutes here
If time-trial frames are allowed
Canyon Speedmax CFR with Cadex 4-Spoke/Disc (Time Trial)
TT frames are barred in many races.
4:45:15
4:14 faster
What's the fastest bike for The Uber Pretzel?
ZwiftBikes predicts the Specialized S-Works Tarmac SL9 with Princeton Wake 6560 White is the best bike and wheels for The Uber Pretzel in Watopia: the fastest road setup for a 75 kg rider at 225 W, finishing in 4:49:29 (~26.7 km/h). The Specialized S-Works Tarmac SL8 with Princeton Wake 6560 White is 6.2 s behind. Where TT bikes are allowed, the Canyon Speedmax CFR with Cadex 4-Spoke/Disc is 4:14 quicker.
75 kg / 175 cm / 225 W / solo; 1 lap, including any lead-in once. Standard (Road); verified only; unowned Halo bikes excluded.
Every setup, ranked
Gap to the fastest. Open a row for its wheels, upgrades and the numbers behind it.
| # | Frame and wheels | Time | Gap | Gap axis | Aero / climb | Style | Details |
|---|---|---|---|---|---|---|---|
| 1 | Princeton Wake 6560 White | 4:49:29 | fastest | 95 / 83 | all-round | ||
| 2 | Princeton Wake 6560 White | 4:49:35 | +6.23 s | 93 / 83 | all-round | ||
| 3 | Princeton Wake 6560 White | 4:49:36 | +6.61 s | 94 / 82 | climbing | ||
| 4 | Princeton Wake 6560 White | 4:49:45 | +16.34 s | 93 / 81 | climbing | ||
| 5 | Princeton Wake 6560 White | 4:49:51 | +21.49 s | 94 / 78 | aero | ||
| 6 | Princeton Wake 6560 White | 4:49:56 | +26.88 s | 92 / 78 | all-round | ||
| 7 | Princeton Wake 6560 White | 4:49:59 | +29.61 s | 95 / 75 | aero | ||
| 8 | Same frame in another paint: Canyon Aeroad CFR Alpecin Premier-Tech Princeton Wake 6560 White | 4:49:59 | +30.06 s | 95 / 74 | aero | ||
| 9 | Princeton Wake 6560 White | 4:49:59 | +30.27 s | 95 / 75 | all-round |
Something here look wrong? Report it – corrections with a source get folded back into the data.
Why this bike wins here
The Uber Pretzel is hilly, with 18.6 m of climbing per kilometre, the kind of course where low weight usually counts for a little more than aerodynamics. The Specialized S-Works Tarmac SL9 is an all-round frame, the kind of frame that terrain favours. Disc or regular wheels is a close call: the Princeton Wake 6560 White is 13 s faster than the Cadex 4-Spoke/Disc here, and 0.55 kg lighter.
What the terrain rewards, from its climbing alone: aerodynamics against low weight
Aerodynamics 42%Weight on climbs 58%
- Drag area against the stock bike
- −0.0330 m²
- Mass against the stock bike
- −2.14 kg
- Rolling resistance change
- −0.0003
- Time lost to rough surfaces
- 6:23
- Physics model
- Dynamic, measured geometry
The course
1 lap; kilometre positions include the lead-in, ridden once.
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12.2 km · 8.5% 1039 m
Mapped surfaces; the shares describe one lap.
| Surface | Share | Distance | Extra watts |
|---|---|---|---|
| Tarmac | 82.7% | 106.1 km | - |
| Dirt | 10.8% | 13.8 km | - |
| Wood | 3.8% | 4.9 km | - |
| Snow | 2.1% | 2.8 km | - |
| Cobbles | 0.6% | 0.8 km | - |
Extra watts are what the fastest setup needs to hold its pace on each surface rather than on tarmac, averaged over the ride - they appear once a ranked setup and mapped surface positions are there to simulate .
Specialized S-Works Tarmac SL9 / Princeton Wake 6560 White · 225 W · Solo · the whole ride. The line is this setup's simulated pace at every grade and surface change, over a faint elevation backdrop; the strip beneath marks the surface behind each dip.
Similar rides in Watopia
Dynamic physics model active
Every time below is simulated for your weight, height and power over this route’s real, measured elevation data.