Race Across East Germany 2026 ยท ๐Ÿ† Winner

1,169
KM.
47:49.

Apr 30 โ€“ May 2, 2026 ยท Garmin Edge ยท 63.5 kg ยท 10,824m climbing
TSS 2,332 ยท NP 191W ยท IF 0.637 ยท VI 0.985 ยท CdA โ‰ˆ0.42 mยฒ

194W
Avg Power
138bpm
Avg HR
43.3h
Moving
GPS ยท 1,169 km ยท East Germany
01
RACE OVERVIEW
156,062 data points. Every second recorded. A complete picture of a race won.
1,168.9km
GPS Distance
1-second GPS resolution throughout
47h49m
Race Elapsed
Apr 30 11:30 โ†’ May 2 11:19 local
43h19m
Moving Time
90.6% efficiency โ€” exceptionally high
26,978kJ
Total Work
โ‰ˆ600g fat oxidised ยท 30,477 kcal
2,332TSS
Training Stress
โ‰ˆ11 century rides stacked
10,824m
Elevation Gain
9,660m descent ยท Everest ร—1.2
0.985VI
Variability Index
NPรทAP โ€” near-1.0 = ultra-steady
4.0h
Coasting Time
Zero power while moving โ‰ฅ5 km/h
27.0km/h
Moving Avg Speed
Max 66.6 km/h ยท consistent throughout
Full race stream ยท power / HR / altitude ยท hover or touch any point48h ยท 10s resolution
Yellow bars = power output. Red line = heart rate. Blue line = altitude (scaled). Dark bands = night. Hover for exact values.
Power (W)
Heart Rate (bpm)
Altitude (m, scaled)
02
POWER ANALYSIS
194W average ยท NP 191W ยท VI 0.985. Near-perfect pacing for a 47-hour effort. The numbers behind the win.
Mean Maximal Power curve Critical Power Profile
Best average power for each duration. Log scale. Hover any point for values.
Normalised Power fade ยท 30-min rolling NP
How sustainable power evolved through the race. Flat NP = excellent pacing discipline.
Power zone time distribution
Time spent in each intensity zone. Endurance-dominated, as expected for ultra pacing.
Power histogram ยท 10W buckets ยท hover each bar
Frequency of every power reading. Bimodal shows pedalling vs coasting phases.
MMP benchmark table โ€” critical power profile

What this tells you: Your 5-min power of 411W and 10-min of 379W show strong short-duration punch. The 1-hour MMP of 242W after 47 hours of racing is particularly impressive โ€” you were still able to sustain near-ceiling aerobic output at the very end. The 2-hour MMP of 235W confirms this wasn't a one-off spike.

Where to improve: Your estimated CdA of ~0.42 mยฒ is on the higher side for a competitive cyclist (elite TT riders achieve 0.18โ€“0.25 mยฒ). Even modest aero improvements โ€” a lower handlebar position, aero helmet, or tighter jersey โ€” could save 15โ€“25 min over this distance at your average speed. This is your largest single performance lever.

03
CARDIAC ANALYSIS
138 bpm average across 43 hours. Aerobic decoupling โ€“7.0%. Your cardiovascular system actually got more efficient as the race went on.
138bpm
Average HR
72.6% of max ยท Zone 3 sustained
180bpm
Peak HR
94.7% max ยท on early climbs
โ€“7.0%
Aerobic Decoupling
Negative = HR fell for same power
1.41W/bpm
Avg Power:HR
Cardiac efficiency throughout race
HR + Power trace ยท full race ยท hover any point
Heart rate (red) and power (yellow fill) across all 47 hours. Night shading shows nocturnal sections. Note HR trending downward while power holds โ€” negative decoupling.
Power:HR efficiency ยท every 10 min ยท hover each dot
Each dot = one 10-min segment. Upward trend = improving cardiac efficiency as race progresses (negative decoupling is good).
HR zone distribution ยท % time
Breakdown of time in each HR zone. Zone 3 dominance confirms correct ultra pacing zone.

Elite-level cardiac response: Negative aerobic decoupling of โ€“7.0% means your heart was working less for the same power output in the second half of the race. This is the cardiovascular system adapting in real time โ€” stroke volume increasing, cardiac efficiency rising. It's the opposite of what happens in underprepared athletes (who show +10โ€“20% decoupling). This is your strongest physiological signature in this dataset.

04
WEATHER & ENVIRONMENT
โ€“1ยฐC to +26ยฐC ambient ยท wind up to 18 km/h ยท two full nights. Real meteorological data overlaid on your ride.
โ€“1ยฐC
Min Temperature
Pre-dawn hour 13 (midnight night 1)
+26ยฐC
Max Temperature
Peak afternoon ยท hour 29
18km/h
Max Wind Speed
Mostly light โ‰ค8 km/h wind
32.8%
Night Riding
15.7h in darkness ยท two nights
Temperature ยท wind speed ยท HR ยท power ยท full race ยท hover for values
Weather from Open-Meteo historical API aligned to your GPS position. Orange = temperature, blue dashes = wind speed, red = HR, yellow fill = power. Watch HR spike in afternoon heat (hours 26โ€“30).
Headwind vs tailwind ยท power and speed impact
Wind direction relative to your riding heading. Computed from GPS bearing + meteorological wind direction every 10 minutes.
Wind rose ยท wind direction frequency during race
Polar chart showing how often wind came from each direction. Your route vs the dominant wind reveals advantage/disadvantage.
Day vs night performance ยท power ยท HR ยท speed
Temperature vs cardiac efficiency ยท scatter ยท hover each point
Each dot = 1 hour of racing. Shows how heat forces HR up for same power โ€” thermoregulatory cardiac cost.

Weather impact summary: The race conditions were broadly favourable โ€” mostly clear skies, light winds averaging 5โ€“8 km/h. The most significant environmental stressor was the temperature swing: from near-freezing in the early hours of May 1 to 26ยฐC by afternoon. Your HR data shows a clear thermoregulatory response: power held steady but HR climbed 6โ€“8 bpm during the hot afternoon (hours 26โ€“30), representing ~4% extra cardiac cost from heat. Pre-cooling strategy and aggressive hydration at those hours would directly reduce race time.

05
TERRAIN ANALYSIS
10,824m of climbing. Gradient-stratified power analysis. Where you went fast and where you lost time.
Elevation profile ยท coloured by gradient steepness ยท hover for altitude + power
Blue = descent, green = flat, yellow = moderate climb, red = steep. Steeper sections clearly visible as colour shifts.
Power by gradient ยท avg watts at each slope %
How your output responded to terrain. Hover each bar for exact numbers.
Speed by gradient ยท how fast at each slope %
Speed collapses on uphill and explodes downhill. Actual numbers from GPS.
Interactive route map ยท coloured by elevation ยท click any segment

Terrain efficiency observation: On descents (negative gradient), your power drops to near zero โ€” appropriate for recovery. However, speed data suggests you may be leaving time on descents: average descent speed of ~38 km/h is conservative for a race winner. Descending at higher confidence (braking later, higher lean angles) is a technical skill that could save 20โ€“40 min over this course.

06
PACING & STRATEGY
How the race was actually raced. Best and worst efficiency windows. Where you found extra gears โ€” and where the body taxed you.
10-min segment analysis ยท power ยท HR ยท temp ยท efficiency ยท hover each bar
288 ten-minute windows across the race. Hover for full detail on each segment.
Best 10 efficiency windows (highest W:HR)
Segments where you produced the most power per heartbeat โ€” your peak biomechanical efficiency moments.
Worst 10 efficiency windows (lowest W:HR)
Segments where your heart worked hardest relative to power output โ€” heat, fatigue, or terrain effects.
Power consistency (CV%) by hour ยท lower = more metronomic pacing
Coefficient of variation of power within each hour. High CV = erratic power (climbs/descents). Low CV = smooth sustained effort. A consistent race is an efficient race.
07
MECHANICS
Cadence ยท speed ยท left/right balance ยท estimated aerodynamics. The physical machinery behind 1,169 km.
Cadence distribution ยท hover each bar
57 rpm average โ€” typical ultra-distance grinding style. Low cadence saves metabolic cost at sustained low-moderate intensity.
Speed distribution ยท hover each bar
Bimodal: 24โ€“32 km/h (flat terrain cruise) and 36โ€“44 km/h (tailwind/descent sections).
Left / right power balance ยท 30-min rolling average ยท 138,234 samples ยท hover for detail
Deviation from 50/50 reveals leg dominance, fatigue asymmetry, or positional compensation. Yellow band = neutral ยฑ2% zone.

Biomechanical read: Starting balance of ~51.5L/48.5R (mild left dominance) is normal and stable through the race mid-section, with a slight drift in the final third โ€” consistent with accumulated left-leg fatigue rather than injury compensation. No dramatic asymmetric spikes occurred, confirming no acute biomechanical breakdown. To improve: single-leg drills targeting right-leg independent strength could bring balance closer to 50/50 from the start, preserving more capacity in the dominant leg for the final hours.

08
KEY INSIGHTS
What the data says. What you did exceptionally well. What you can improve. Evidence-based, from 156,062 data points.

โœ… Aerobic decoupling โ€“7.0% โ€” your cardiovascular system became more efficient as the race progressed. This is elite-tier physiological resilience. Most athletes show positive decoupling (HR rising for same power) after hour 20. You did the opposite.

โœ… Variability Index 0.985 โ€” NP/AP ratio of 0.985 means your power delivery was extraordinarily smooth. Ultra-even pacing like this minimises glycogen depletion spikes, which is the primary cause of late-race "bonking." This was a masterclass in power management.

โœ… 90.6% moving efficiency โ€” only 4.5 hours off the bike in 48 hours. Self-supported race management was near-optimal. Every stop was brief and purposeful.

โœ… Full neuromuscular recruitment at finish โ€” peak 476W sprint at the finish confirms no central fatigue-induced power cap. You crossed the line with reserves. That's race management, not luck.

โš ๏ธ Estimated CdA ~0.42 mยฒ โ€” significantly above optimal. At 27 km/h average speed, aerodynamic drag accounts for ~85% of resistance. Reducing CdA from 0.42 to 0.35 would theoretically save ~35W for the same speed โ€” translating to roughly 2โ€“3 hours faster over this distance. A bike fit session focused on frontal area reduction is the highest-leverage intervention available.

โš ๏ธ Night-time power drop โ€“11W โ€” power fell from 198W (day) to 187W (night), likely a combination of reduced arousal, cooler temps, and visibility constraints. Structured night-riding training blocks would help maintain output levels across the circadian dip.

โš ๏ธ Heat-induced cardiac cost โ€” HR rose 6โ€“8 bpm in the hottest afternoon hours (26ยฐC+) without a corresponding power increase. Pre-cooling protocols (ice vests, cold fluid ingestion) in the 30 min before those segments would reduce this thermoregulatory overhead.

Complete race statistics