Chris Farhood
cced0ea6b8
The skill had mtb-xco-demands.md but road/TT demands were only diffused through the general docs — an asymmetry given the balanced MTB+road scope. Add two dedicated, self-contained demand profiles (kept separate because mass-start racing and TT differ as much as XCO differs from marathon MTB): - references/road-racing-demands.md: stochastic power profile (Vogt 2007, Ebert 2005/2006, Sanders/van Erp 2021), drafting economics (Blocken 2018), fatigued finishing sprint (Menaspà 2013/2015, Etxebarria 2019), durability as a success determinant (van Erp/Sanders/Lamberts 2021); power governs, HR unreliable (intermittent) — mirrors the MTB doc. - references/tt-demands.md: aero drag dominance + CdA as the top lever (Crouch 2017, Martin 1998, García-López 2008), critical power as predictor (Smith 1999), even-vs-variable pacing (Swain 1997, Atkinson 2007), long-TT durability (Maunder 2021); HR more usable than MTB but still secondary. All new quantitative claims carry verified PMIDs/DOIs (verified via PubMed/ CrossRef); citations.md gains Road-racing and Time-trial sections. Honesty flags: Blocken 2018 and Martin 1998 have no PMID (DOI only); the '~90% aero' soundbite (Kyle & Burke 1984) is unverifiable and marked approximate; criterium-specific literature flagged as a gap; no unverified HR-reliability citation added (TT HR defers to data-confounds.md). Router (SKILL.md) and README layout updated with both docs. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TqrhBhC3GEcKyaw8RTk8G6
288 lines
18 KiB
Markdown
288 lines
18 KiB
Markdown
# Master citation list
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The single source of truth for every quantitative claim in this skill. Each entry: full citation,
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PMID/DOI, and a **confidence flag** from verification against PubMed / DOI resolvers.
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**Confidence key:**
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- ✅ **Confirmed** — PMID and/or DOI verified; title, authors, journal internally consistent.
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- ⚠️ **Confirmed metadata, claim = commonly-cited/approximate** — the paper exists as cited, but the
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exact number attributed to it is widely-repeated rather than verified word-for-word in the source.
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- ❌ **Not found** — could not be confirmed; **do not cite as fact.**
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Verified as of 2026-07-20.
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---
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## Durability / fatigue resistance
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**✅ Muriel et al. 2022** — fatigued-state power differentiates riders; fresh power does not.
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Muriel X, Mateo-March M, Valenzuela PL, Zabala M, Lucia A, Pallarés JG, Barranco-Gil D. *Durability
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and repeatability of professional cyclists during a Grand Tour.* Eur J Sport Sci. 2022;22(12):
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1797–1804. **PMID 34586952 · DOI 10.1080/17461391.2021.1987528.**
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**✅ Spragg, Leo & Swart 2023 (training characteristics)** — durability tracks accumulated
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volume/load; fatigued profile varies more than fresh across a season. *This is the primary "load
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dependency" cite.* Spragg J, Leo P, Swart J. *The relationship between training characteristics and
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durability in professional cyclists across a competitive season.* Eur J Sport Sci. 2023;23(4):
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489–498. **PMID 35239466 · DOI 10.1080/17461391.2022.2049886.**
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> The crisp "reduced load maintains fresh power; sustained load maintains durability" phrasing is
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> Spragg's applied *interpretation* of this data — attribute as commentary, not a quoted result.
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**✅ Spragg, Leo & Swart 2023 (physiological characteristics)** — physiological correlates of
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durability (higher VO2max, gross efficiency, fat oxidation). Spragg J, Leo P, Swart J. *The
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Relationship between Physiological Characteristics and Durability in Male Professional Cyclists.*
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Med Sci Sports Exerc. 2023;55(1):133–140. **PMID 35977108 · DOI 10.1249/MSS.0000000000003024.**
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**✅ Maunder et al. 2021** — canonical definition of durability as a distinct profiling quality.
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Maunder E, Seiler S, Mildenhall MJ, Kilding AE, Plews DJ. *The Importance of 'Durability' in the
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Physiological Profiling of Endurance Athletes.* Sports Med. 2021;51(8):1619–1628.
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**PMID 33886100 · DOI 10.1007/s40279-021-01459-0.**
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---
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## MTB / XCO demands
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**✅ Hays et al. 2018** — XCO demand profile (~25% time above MAP; hard start); HR/power/VO2
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dissociation (VO2 high on descents, %VO2max uncorrelated with %HRmax/%MAP). Hays A, Devys S, Bertin
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D, Marquet LA, Brisswalter J. *Understanding the Physiological Requirements of the Mountain Bike
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Cross-Country Olympic Race Format.* Front Physiol. 2018;9:1062.
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**PMID 30158873 · DOI 10.3389/fphys.2018.01062.**
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**✅ Prinz et al. 2021** — corroborating hard-number demand data (~30% top zone; 334 efforts ~4.3 s
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at ~135% MAP). Prinz B, et al. *(power-profile / demands of XCO)* Int J Sports Physiol Perform. 2021.
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**PMID 33848975 · DOI 10.1123/ijspp.2020-0758.**
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**✅ Protzen et al. 2026** — systematic review: contemporary XCO shifted toward greater anaerobic
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contribution while maintaining high aerobic demand; ~¼ race time above MAP. Protzen G, Inoue A,
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Buzzachera CF, Doma K, Devantier-Thomas B, Herrero-Molleda A, García-López J, Boullosa D. *The
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Physiology of Contemporary Olympic Cross-Country Mountain Biking: A Systematic Review.* Sports Med
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Open. 2026;12:16. **PMID 41739301 · DOI 10.1186/s40798-026-00976-4.**
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**✅ Impellizzeri et al. 2005** — aerobic predictors of XCO (mass-normalized threshold power/VO2).
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*Frame r ≈ 0.6–0.9 as "across studies"; the elite-cohort raw VO2max did not separate riders.*
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Impellizzeri FM, Marcora SM, Rampinini E, Mognoni P, Sassi A. *Correlations between physiological
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variables and performance in high level cross country off road cyclists.* Br J Sports Med.
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2005;39(10):747–751. **PMID 16183772 · DOI 10.1136/bjsm.2004.017236.**
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**✅ Inoue et al. 2012** — anaerobic power predicts XCO race time (r = −0.79, p = 0.006). Inoue A,
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Sá Filho AS, Mello FCM, Santos TM. *Relationship between anaerobic cycling tests and mountain bike
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cross-country performance.* J Strength Cond Res. 2012;26(6):1589–1593.
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**PMID 21912290 · DOI 10.1519/JSC.0b013e318234eb89.**
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**✅ Sánchez-Jiménez et al. 2025** — fatigue-decline magnitudes: Top-10 ~6–10% vs lower ~15–20%.
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Sánchez-Jiménez L, Javaloyes A, Peña-González I, Moya-Ramón M, Mateo-March M. *Record Power Profile
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in Elite Olympic Cross-Country Mountain Bike Cyclists: Normative Values and Fatigue Effects.* Scand
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J Med Sci Sports. 2025;35(11):e70170. **PMID 41285697 · DOI 10.1111/sms.70170.**
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**✅ Novak et al. 2018** — marathon (4-h) MTB predictors differ from lap XCO. Novak AR, Bennett KJM,
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Fransen J, Dascombe BJ. *Predictors of performance in a 4-h mountain-bike race.* J Sports Sci.
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2018;36(4):462–468. **PMID 28406361 · DOI 10.1080/02640414.2017.1313999.**
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---
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## Road-racing demands (mass-start / criterium)
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**✅ Vogt et al. 2007** — TdF mass-start mean power only ~3.1–3.3 W/kg (218–234 W) despite decisive
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higher efforts; stochastic profile. Vogt S, Schumacher YO, Roecker K, Dickhuth H-H, Schoberer U,
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Schmid A, Heinrich L. *Power Output during the Tour de France.* Int J Sports Med. 2007;28(9):
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756–761. **PMID 17497569 · DOI 10.1055/s-2007-964982.**
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**✅ Ebert et al. 2006** — pro men's tour: low mean power with repeated surges above maximal aerobic
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power. Ebert TR, Martin DT, Stephens B, Withers RT. *Power output during a professional men's
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road-cycling tour.* Int J Sports Physiol Perform. 2006;1(4):324–335. **PMID 19124890 ·
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DOI 10.1123/ijspp.1.4.324.**
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**✅ Ebert et al. 2005** — women's World Cup power-output profile (SRM). Ebert TR, Martin DT,
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McDonald W, Victor J, Plummer J, Withers RT. *Power output during women's World Cup road cycle
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racing.* Eur J Appl Physiol. 2005;95(5–6):529–536. **PMID 16151832 · DOI 10.1007/s00421-005-0039-y.**
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**✅ Sanders & van Erp 2021** — updated review: demands strongly shaped by stage/race type. Sanders
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D, van Erp T. *The Physical Demands and Power Profile of Professional Men's Cycling Races: An Updated
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Review.* Int J Sports Physiol Perform. 2021;16(1):3–12. **PMID 33271501 · DOI 10.1123/ijspp.2020-0508.**
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**✅ van Erp & Sanders 2021** — 2,920 files / 20 pros: demands vary by race category and result.
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van Erp T, Sanders D. *Demands of professional cycling races: Influence of race category and result.*
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Eur J Sport Sci. 2021;21(5):666–677. **PMID 32584197 · DOI 10.1080/17461391.2020.1788651.**
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**✅ Blocken et al. 2018** — CFD + wind tunnel: peloton drag drops to ~5–10% of an isolated rider.
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**No PMID — cite by DOI** (journal not MEDLINE-indexed). Blocken B, van Druenen T, Toparlar Y,
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Malizia F, Mannion P, Andrianne T, Marchal T, Maas G-J, Diepens J. *Aerodynamic drag in cycling
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pelotons: New insights by CFD simulation and wind tunnel testing.* J Wind Eng Ind Aerodyn.
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2018;179:319–337. **DOI 10.1016/j.jweia.2018.06.011.**
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**✅ Menaspà et al. 2015** — pro road sprint peak ~17.4 ± 1.7 W/kg, preceded by high-intensity
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lead-in. Menaspà P, Quod M, Martin DT, Peiffer JJ, Abbiss CR. *Physical Demands of Sprinting in
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Professional Road Cycling.* Int J Sports Med. 2015;36(13):1058–1062. **PMID 26252551 ·
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DOI 10.1055/s-0035-1554697.**
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**✅ Menaspà, Abbiss & Martin 2013** — world-class sprinter Grand Tour performance analysis.
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Menaspà P, Abbiss CR, Martin DT. *Performance analysis of a world-class sprinter during cycling
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grand tours.* Int J Sports Physiol Perform. 2013;8(3):336–340. **PMID 23038704 ·
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DOI 10.1123/ijspp.8.3.336.**
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**✅ van Erp, Sanders & Lamberts 2021** — maintaining maximal power after high accumulated work is a
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key success determinant (durability in road racing). van Erp T, Sanders D, Lamberts RP. *Maintaining
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Power Output with Accumulating Levels of Work Done Is a Key Determinant for Success in Professional
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Cycling.* Med Sci Sports Exerc. 2021;53(9):1903–1910. **PMID 33731651 ·
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DOI 10.1249/MSS.0000000000002656.**
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**✅ Etxebarria et al. 2019** — ~1 h prior stochastic cycling cut a subsequent 30 s sprint ~5–6%
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(criterium/finish relevance). Etxebarria N, Ingham SA, Ferguson RA, Bentley DJ, Pyne DB. *Sprinting
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After Having Sprinted: Prior High-Intensity Stochastic Cycling Impairs the Winning Strike for Gold.*
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Front Physiol. 2019;10:100. **PMID 30837886 · DOI 10.3389/fphys.2019.00100.**
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---
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## Time-trial demands
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**✅ Crouch et al. 2017** — review: aerodynamic drag dominates at racing speeds; the rider is ~80% of
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system drag. Crouch TN, Burton D, LaBry ZA, Blair KB. *Riding against the wind: a review of
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competition cycling aerodynamics.* Sports Eng. 2017;20(2):81–110. **DOI 10.1007/s12283-017-0234-1.**
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> The popular "~90% of power to aero at 40 km/h" soundbite traces to **Kyle & Burke 1984**
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> (*Mechanical Engineering*, a trade magazine — **not MEDLINE-indexed, unverifiable, do not cite as
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> primary**). Use Crouch 2017 or Martin 1998 as the verifiable anchor and treat the exact % as
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> approximate.
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**✅ Martin et al. 1998** — validated mathematical model of road cycling power (R²=0.97); aero
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dominates on the flat. **No PMID — cite by DOI** (journal not PubMed-indexed). Martin JC,
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Milliken DL, Cobb JE, McFadden KL, Coggan AR. *Validation of a Mathematical Model for Road Cycling
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Power.* J Appl Biomech. 1998;14(3):276–291. **DOI 10.1123/jab.14.3.276.**
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**✅ García-López et al. 2008** — wind-tunnel position changes cut pro cyclists' drag ~14%; CdA is
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the primary TT lever. García-López J, Rodríguez-Marroyo JA, Juneau C-E, Peleteiro J, Córdova
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Martínez A, Villa JG. *Reference values and improvement of aerodynamic drag in professional
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cyclists.* J Sports Sci. 2008;26(3):277–286. **PMID 17943597 · DOI 10.1080/02640410701501697.**
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**✅ Swain 1997** — vary power on hills/wind (higher into climbs/headwinds) to save TT time. Swain
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DP. *A model for optimizing cycling performance by varying power on hills and in wind.* Med Sci
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Sports Exerc. 1997;29(8):1104–1108. **PMID 9268969 · DOI 10.1097/00005768-199708000-00017.**
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**✅ Atkinson, Peacock & Passfield 2007** — updated model: variable pacing on terrain/wind saves
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time; even power near-optimal on flat/windless. Atkinson G, Peacock O, Passfield L. *Variable versus
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constant power strategies during cycling time-trials: prediction of time savings using an up-to-date
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mathematical model.* J Sports Sci. 2007;25(9):1001–1009. **PMID 17497402 · DOI 10.1080/02640410600944709.**
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**✅ Smith, Dangelmaier & Hill 1999** — critical power predicts 17-km/40-km TT (r = −0.77 to −0.91),
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more than VT or VO2max. Smith JC, Dangelmaier BS, Hill DW. *Critical power is related to cycling time
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trial performance.* Int J Sports Med. 1999;20(6):374–378. **PMID 10496116 · DOI 10.1055/s-2007-971147.**
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*(TT durability draws on Maunder et al. 2021 — see the Durability section above. A dedicated,
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verified HR-reliability-in-TT citation was sought but not confirmed; TT HR guidance defers to
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`data-confounds.md` rather than resting on an unverified source.)*
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---
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## Strength training (incl. masters)
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**✅ Llanos-Lagos et al. 2026 (epub 2025)** — meta-analysis, 17 studies / 262 cyclists: heavy
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strength improves efficiency, anaerobic power, TT performance; **no VO2max effect**. Llanos-Lagos C,
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Ramírez-Campillo R, Sáez de Villarreal E. *Heavy strength training effects on physiological
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determinants of endurance cyclist performance: a systematic review with meta-analysis.* Eur J Appl
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Physiol. 2026;126(1):193–222. **PMID 40632222 · DOI 10.1007/s00421-025-05883-2.** *(Certainty of
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evidence noted as low by the authors.)*
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**✅ Cadore et al. 2013 (epub 2012)** — strength-first sequencing yields greater strength gains in
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the elderly (~35% vs ~22%). Cadore EL, Izquierdo M, Pinto SS, et al. *Neuromuscular adaptations to
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concurrent training in the elderly: effects of intrasession exercise sequence.* Age (Dordr).
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2013;35(3):891–903. **PMID 22453934 · DOI 10.1007/s11357-012-9405-y.** *(This is the "Cadore 2012"
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sequencing cite.)*
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**✅ Cadore & Izquierdo 2013** — interference manageable/muted in older adults except at high
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volume/frequency. Cadore EL, Izquierdo M. *How to simultaneously optimize muscle strength, power,
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functional capacity, and cardiovascular gains in the elderly: an update.* Age (Dordr).
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2013;35(6):2329–2344. **PMID 23288690 · DOI 10.1007/s11357-012-9503-x.**
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**⚠️ English & Paddon-Jones 2010** — commonly cited origin of "~8% muscle loss/decade after 40."
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*Exact figure not verified in abstract; treat as commonly-cited/approximate.* English KL, Paddon-
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Jones D. *Protecting muscle mass and function in older adults during bed rest.* Curr Opin Clin Nutr
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Metab Care. 2010;13(1):34–39. **PMID 19898232 · DOI 10.1097/MCO.0b013e328333aa66.**
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**✅ Volpi, Nazemi & Fujita 2004** — sarcopenia mechanisms; resistance/aerobic training as
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countermeasure (fiber-type-fastest specifics not verbatim-confirmed). Volpi E, Nazemi R, Fujita S.
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*Muscle tissue changes with aging.* Curr Opin Clin Nutr Metab Care. 2004;7(4):405–410.
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**PMID 15192443 · DOI 10.1097/01.mco.0000134362.76653.b2.**
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**✅ Cruz-Jentoft et al. 2019 (EWGSOP2)** — consensus: sarcopenia centers on muscle strength;
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resistance training recommended. *Strongest confirmed cite for "loaded resistance is the primary
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countermeasure."* Cruz-Jentoft AJ, et al. *Sarcopenia: revised European consensus on definition and
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diagnosis.* Age Ageing. 2019;48(1):16–31. **PMID 30312372 · DOI 10.1093/ageing/afy169.**
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---
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## VO2max intervals
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**✅ Yang, Wang & Guan 2025** — network meta-analysis, 51 studies / 1,261 athletes: inverted-U
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dose-response; optimum ~140 s work, work:rest ~0.85. *Weighted toward running-based HIIT.* Yang Q,
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Wang J, Guan D. *Comparison of different interval training methods on athletes' oxygen uptake: a
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systematic review with pairwise and network meta-analysis.* BMC Sports Sci Med Rehabil.
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2025;17(1):156. **PMID 40605061 · DOI 10.1186/s13102-025-01191-6.**
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**✅ Fleckenstein, Braunstein & Walter 2025** — *running*: long (3-min) intervals accumulate more
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time >90% VO2max than intensified 30-s intervals. Fleckenstein D, Braunstein H, Walter N. *Faster
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intervals, faster recoveries — intensified short VO2max running intervals are inferior to
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traditional long intervals in terms of time spent above 90% VO2max.* Front Sports Act Living.
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2025;6:1507957. **PMID 39835194 · DOI 10.3389/fspor.2024.1507957.**
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**✅ Rønnestad & Hansen 2016** — *cycling, opposite result*: 30-s intervals induced more time ≥90%
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VO2peak than longer intervals. Rønnestad BR, Hansen J. *Optimizing Interval Training at Power Output
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Associated With Peak Oxygen Uptake in Well-Trained Cyclists.* J Strength Cond Res. 2016;30(4):
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999–1006. **PMID 23942167 · DOI 10.1519/JSC.0b013e3182a73e8a.** *(Often mis-cited as 2013 = epub.)*
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**✅ Rønnestad et al. 2020** — *cycling*: short (30/15 s) beat effort-matched long (5-min) intervals
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over 3 weeks (+4.7% 20-min power) in elite cyclists. Rønnestad BR, Hansen J, Nygaard H, Lundby C.
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*Superior performance improvements in elite cyclists following short-interval vs effort-matched
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long-interval training.* Scand J Med Sci Sports. 2020;30(5):849–857.
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**PMID 31977120 · DOI 10.1111/sms.13627.**
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**✅ Almquist et al. 2020** — effort-matched acute systemic/muscular responses favor short intervals.
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Almquist NW, Nygaard H, Vegge G, Hammarström D, Ellefsen S, Rønnestad BR. *Systemic and muscular
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responses to effort-matched short intervals and long intervals in elite cyclists.* Scand J Med Sci
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Sports. 2020;30(7):1140–1150. **PMID 32267032 · DOI 10.1111/sms.13672.**
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**✅ Rønnestad et al. 2021** — microcycle shock-block: short intervals → superior adaptations.
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Rønnestad BR, Øfsteng SJ, Zambolin F, Raastad T, Hammarström D. *Superior Physiological Adaptations
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After a Microcycle of Short Intervals Versus Long Intervals in Cyclists.* Int J Sports Physiol
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Perform. 2021;16(10):1432–1438. **PMID 33735833 · DOI 10.1123/ijspp.2020-0647.**
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> **Caveat on the cycling short-interval body of work (Rønnestad 2016/2020/2021 + Almquist 2020):**
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> the short-interval superiority comes chiefly from a **single research group**, and its adaptation
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> claims are challenged by effort-matched work: when **total work duration** is matched, the
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> advantage reportedly disappears (attributed to a Seiler-group study — **unpublished /
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> secondary-source, low evidence tier, not cited as fact**). Present short-interval superiority as a
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> *lab-consistent but not independently settled* finding, not a cycling consensus. See
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> `vo2max-intervals.md`.
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**❌ "Effort-matched cycling replication, no difference" (Seiler group)** — **NOT VERIFIABLE as a
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primary source.** Referenced only via secondary/coaching sources as an unpublished master's thesis
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(~30 cyclists, VO2max ~64, total-work-matched, no short-vs-long difference). Used only to *temper*
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overconfidence in the short-interval side; **do not cite as established evidence.**
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---
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## Distribution / periodization philosophy
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**✅ Seiler 2024** — "long game, not epic workouts"; HIIT is not an acute-maximization problem;
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polarized training as a context-dependent principle. Peer-reviewed Perspective (open access). Seiler
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S. *It's about the long game, not epic workouts: unpacking HIIT for endurance athletes.* Appl
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Physiol Nutr Metab. 2024;49(11):1585–1599. **PMID 39079169 · DOI 10.1139/apnm-2024-0012.**
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**✅ Sun, Yu et al. 2025** — review of training-intensity-distribution models: **no single model
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universally superior**; adapt to sport/phase/athlete. *(Use for the "distribution is context-
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dependent" point — it does NOT claim frequency > distribution.)* Sun Q, Yu Y, Cui J, Lin S, Wang X,
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Zhou T. *Recent advances in training intensity distribution theory for cyclic endurance sports.*
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Front Physiol. 2025;16:1657892. **PMID 41169886 · DOI 10.3389/fphys.2025.1657892.**
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**❌ "Yu et al. 2025" (frequency > distribution)** — **NOT FOUND.** No PubMed paper with Yu as first
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author making this specific claim could be located. **Do not cite.** The nearest real paper
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(Sun/Yu 2025, above) does not support "frequency outweighs distribution." Ground the frequency point
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in Seiler 2024 instead, and label it a heuristic, not a quantified finding.
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---
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## Notes on verification method
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All ✅ identifiers were read from PubMed record pages and cross-checked against DOI resolvers by
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independent verification agents on 2026-07-20. Where a claim's *number* is widely repeated but not
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verbatim in the source abstract, it is marked ⚠️ and the reference docs say so inline. No identifier
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in this list was fabricated; the one unlocatable citation is explicitly marked ❌.
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