About Shinobi
§01
使命 · MISSION
Science-backed endurance progression.
Shinobi helps endurance athletes track progression from 5K to ultramarathons using research-grounded data.
PRIVACY
Fully client-side.
No accounts. No backend. Your data never leaves the browser. LocalStorage only. Privacy is not a feature — it is a constraint.
CATALOGUE
83 races. 8 categories.
Running, triathlon, cycling, swimming, OCR, adventure, multi-sport, and unique events. Every race profiled across 7 demand axes.
PROGRESSION
8-tier rank system.
From Academy to Sennin. Each tier maps to real endurance milestones — finish races, earn rank.
How We Score
§02
採点 · SCORING
A holistic readiness engine.
Your readiness score is not a single number. It is five weighted components, a weakest-link penalty, and transparent research behind every threshold.
FIVE COMPONENTS
Cardiovascular
25%
VO2max, resting HR, HRV trend, lactate threshold
Training Volume
25%
Weekly distance, long run, TSS, consistency
Race Experience
25%
Completed races at or above target distance
Multi-Sport Breadth
15%
Coverage across swim, bike, run, strength
Strength
10%
Dead hang, pull-ups, squat, deadlift ratios
READINESS METHODOLOGY
Weakest-Link Weighting
Your readiness is only as strong as your weakest pillar. If cardiovascular fitness scores 90% but strength scores 30%, the final readiness is pulled down disproportionately. This prevents athletes from ignoring weak areas.
Coverage Penalty
Races that demand capabilities across multiple domains (e.g., Ironman needs swim + bike + run) apply a coverage penalty when an athlete has not demonstrated breadth. Single-sport specialists are flagged.
Missing Data Penalty
If a metric is not entered, we assume the worst case rather than skipping it. Entering more data always improves accuracy, never inflates your score. Honesty is rewarded.
RESEARCH-BACKED
Every threshold in the engine is derived from peer-reviewed literature. See the full citations below.
Research References
§03
文献 · RESEARCH
Full citations.
13 peer-reviewed references across 7 categories power the readiness engine.
酸素VO2max & Performance2 REFS
Daniels, J. (2022)
Daniels' Running Formula
Human Kinetics (4th ed.)
2022
FINDING
VDOT tables mapping race performances to effective VO2max scores. The foundation for pace-based training zones.
HOW WE USE IT
Used to calculate race readiness scores per distance. VO2max thresholds for each race tier are derived from VDOT tables.
Noakes, T.D. (2001)
Lore of Running
Human Kinetics (4th ed.)
2001
FINDING
VO2max is necessary but not sufficient. Above ~45 ml/kg/min for male marathoners, gains come from running economy and lactate threshold, not higher VO2max.
HOW WE USE IT
We present VO2max as one of three pillars (VO2max, LT, economy), not the sole metric. For ultras, we de-emphasize VO2max.
乳酸Lactate Threshold3 REFS
Farrell, P.A., Wilmore, J.H., Coyle, E.F., Billing, J.E., & Costill, D.L. (1979)
Plasma lactate accumulation and distance running performance
Medicine and Science in Sports, 11(4), pp. 338-344
1979
FINDING
Lactate threshold pace was a stronger predictor of marathon performance than VO2max (r = 0.98 for LT vs r = 0.91 for VO2max).
HOW WE USE IT
LT pace is our primary predictor for half marathon and marathon readiness assessments.
Coyle, E.F. (2007)
Physiological regulation of marathon performance
Sports Medicine, 37(4-5), pp. 306-311
2007
FINDING
Velocity at lactate threshold is the single best laboratory predictor of endurance performance for events 30 min to 4+ hours.
HOW WE USE IT
Validates our use of LT-derived metrics as primary readiness gates for half marathon through ultra distances.
Billat, V. et al. (2001)
The concept of maximal lactate steady state
Sports Medicine, 31(11), pp. 763-783
2001
FINDING
The fraction of VO2max sustainable at LT (%VO2max at LT) is more predictive than absolute VO2max for events >10K.
HOW WE USE IT
For experienced runners, we factor in LT as % of VO2max to refine readiness scoring beyond raw VO2max.
心拍HRV Monitoring3 REFS
Plews, D.J., Laursen, P.B., Stanley, J., Kilding, A.E., & Buchheit, M. (2013)
Training adaptation and heart rate variability in elite endurance athletes: Opening the door to effective monitoring
Sports Medicine, 43(9), pp. 773-781
2013
FINDING
ln(RMSSD) measured each morning is the most practical HRV metric. A progressive decline over 1-2 weeks signals overreaching. Day-to-day CV >10% indicates maladaptation.
HOW WE USE IT
Our HRV readiness signals (green/yellow/red) use the Plews et al. methodology: 7-day rolling average + coefficient of variation.
Plews, D.J., Laursen, P.B., Kilding, A.E., & Buchheit, M. (2014)
Heart rate variability and training intensity distribution in elite rowers
International Journal of Sports Physiology and Performance, 9(6), pp. 1026-1032
2014
FINDING
HRV-guided training: athletes who adjusted intensity based on daily HRV performed equally or better than those on fixed plans, with less overtraining.
HOW WE USE IT
Validates our recommendation for HRV-guided training adjustments in the training advisor.
Buchheit, M. (2014)
Monitoring training status with HR measures: Do all roads lead to Rome?
Frontiers in Physiology, 5, pp. 73
2014
FINDING
Recommends measuring HRV first thing in the morning, supine, over 1-5 minutes. Use 7-day rolling average and CV of ln(RMSSD).
HOW WE USE IT
Our measurement instructions for HRV follow this protocol exactly.
量Training Volume & Injury2 REFS
Nielsen, R.O. et al. (2014)
Excessive progression in weekly running distance and risk of running-related injuries
British Journal of Sports Medicine, 48(3), pp. 146-151
2014
FINDING
Runners who increased distance by >30% over 2 weeks had significantly higher injury risk.
HOW WE USE IT
We flag any 2-week volume increase >30% as a warning in the training plan.
Buist, I. et al. (2010)
No effect of a graded training program on the number of running-related injuries in novice runners
American Journal of Sports Medicine, 38(1), pp. 33-39
2010
FINDING
The 10% rule did not significantly reduce injury rates vs standard programs in novice runners. It's a reasonable heuristic, not an evidence-based threshold.
HOW WE USE IT
We use the 10% rule as a default guardrail but acknowledge its limitations when presenting training plans.
体組Body Composition1 REF
Mountjoy, M. et al. (2018)
IOC consensus statement on Relative Energy Deficiency in Sport (RED-S)
British Journal of Sports Medicine, 52(11), pp. 687-697
2018
FINDING
Low body fat through caloric restriction causes bone stress fractures, hormonal disruption, cardiovascular risk. Males below 5-6% and females below 14% face significant health risks.
HOW WE USE IT
Body composition is shown as informational context only, never as a target. Always paired with RED-S health warning.
力OCR Strength1 REF
Herold, E., Borges, N., Watsford, M., & Abbott, A. (2021)
Physiological and physical predictors of obstacle course racing performance
Journal of Sports Sciences, 39(14), pp. 1639-1648
2021
FINDING
Grip endurance and upper-body pulling strength were the strongest predictors of OCR finish time after running speed.
HOW WE USE IT
Dead hang time and pull-ups are our primary gate-checks for OCR obstacle readiness.
進Progression1 REF
Bassett, D.R. & Howley, E.T. (2000)
Limiting factors for maximum oxygen uptake and determinants of endurance performance
Medicine and Science in Sports and Exercise, 32(1), pp. 70-84
2000
FINDING
For trained runners, lactate threshold explains more variance in distance-running performance than VO2max alone.
HOW WE USE IT
Supports our multi-metric approach to readiness assessment rather than relying on VO2max alone.
The Team
§04
仲間 · TEAM
Built by athletes, for athletes.
§05
待機 · WAITLIST
The native app is coming.
“Every number in this engine traces back to a paper, a study, a finding. We do not guess. 忍 is built on evidence.”
— Shinobi methodology notes