A reproducible run-level workflow for internal–external training-load integration in alpine skiing

A reproducible run-level workflow for internal–external training-load integration in alpine skiing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article A reproducible run-level workflow for internal–external training-load integration in alpine skiing Wu Yangchenxi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9452740/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Monitoring training load in alpine skiing requires physiological and mechanical information to be aligned under difficult field conditions. Proprietary ecosystems of- ten reduce this problem to a single summary score, but their black-box design limits transparency and makes sensitivity analysis difficult. This paper presents a repro- ducible run-level workflow for training-load fusion. Implemented as a hardware- agnostic modular fusion layer operating on a standardized post-segmentation run- level table, the workflow combines pre-standardized internal and external load com- ponents through an alpha-weighted model. Using a demonstration dataset of 14 runs, we report alpha-sweep correlations, rank-based association, top-k set consis- tency, and phase-wise contrasts. The balanced configuration at α= 0.50 produced equal correlations with the internal and mechanical components (r = 0.965 for both), while high-load run identification remained only partially overlapping across single-domain and fused summaries. The fused metric therefore adds complemen- tary interpretive value rather than simply reproducing one constituent domain. By preserving intermediate analytical stages within an open implementation, the work- flow supports transparent reporting and reproducible comparison in sports engi- neering research. Alpine skiing training load sensor fusion measurement workflow sports engineering reproducibility. Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9452740","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":625200454,"identity":"576d3f0d-61c3-46d3-ac0e-57cd966cf0b0","order_by":0,"name":"Wu Yangchenxi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYPCC//X97A1A2sCCaC3MjDN7DoC0SJCgZcONBBCDCC0GN3IMPxf8YmOWnPn86oYfBRIM/O3dCYS0GEvP7ONh45fOKbvZA3SYxJmzG/BqMbuRYyDN2yPBIzk7J+0GD1CLgUQuQS3Gv3mBphvcPJN28w+RWsykeX4kGBjcYD92myhb7M88K7PmbTiQINmTw3ZbxkCCh6BfJNuTN9/m+XMggZ/9+LObb/7YyPG39+LXwsDAYcDA2AZi8BiASQLKQYD9AQPDHxhjFIyCUTAKRgEWAABKS0ll7FthIgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0006-2815-8311","institution":"Hungarian University of Sports Science","correspondingAuthor":true,"prefix":"","firstName":"Wu","middleName":"","lastName":"Yangchenxi","suffix":""}],"badges":[],"createdAt":"2026-04-17 21:21:59","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9452740/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9452740/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107868733,"identity":"71e01d66-94d4-48aa-9fa1-b8cf215dd5be","added_by":"auto","created_at":"2026-04-27 07:32:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":164973,"visible":true,"origin":"","legend":"","description":"","filename":"skiloadlabrunlevelworkflow.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9452740/v1_covered_4eee7880-b8a1-4f11-9607-bc76be819a43.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA reproducible run-level workflow for internal–external\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003etraining-load integration in alpine skiing\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Hungarian University of Sports Science","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alpine skiing; training load; sensor fusion; measurement workflow; sports engineering; reproducibility.","lastPublishedDoi":"10.21203/rs.3.rs-9452740/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9452740/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMonitoring training load in alpine skiing requires physiological and mechanical\u003c/p\u003e\n\u003cp\u003einformation to be aligned under difficult field conditions. 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