Weekly training load compliance report against the periodisation plan
Problem
Strength and conditioning staff set a weekly training load target for each athlete — distance, high-speed running, session RPE — in a planning spreadsheet or the athlete management system's planning module. What actually gets delivered lives in a separate export from the GPS platform. Comparing the two means pulling both files, aligning athlete IDs and column headers by hand, and eyeballing variance — a task that takes an hour nobody has on a normal week and gets skipped entirely on a busy one. Periodisation drift then accumulates quietly across a training block. By the time anyone notices an athlete has been running twenty percent over target for three weeks running, it is usually because of a soft-tissue complaint, not because the report caught it first.
Product idea
A reporting layer that takes the weekly plan — uploaded as a spreadsheet or entered directly — and the GPS platform's load export, matches them by athlete and week, and produces a compliance report: per-athlete variance against target, cumulative drift across the block, and a squad-wide view ranking who is furthest over or under plan. Coaches filter by position group, week or metric rather than typing a query. It does not plan sessions or push data back into the GPS platform — it is read-only analysis sitting downstream of both, built to answer one question fast: who drifted from the plan this week, and by how much.
Who it is for
Strength and conditioning coaches who set the weekly plan, sports scientists checking load trends, and the Head of Performance who sponsors it and brings the report to selection and review meetings.
Possible first version
A web app accepting a CSV upload of the weekly plan and a CSV export from the GPS platform, matched by athlete ID and week, producing a per-athlete compliance table, a squad-wide ranked variance view, and a four-week rolling drift chart per athlete. Filters by position group and metric. Out of scope for version one: any live connection to the GPS vendor's API, automated plan creation, and folding in wellness or medical data — this version compares planned load against delivered load only.
- Build classification
- Workflow application
- Rough effort
- 4-6 week first release
- Roles involved
- Head of Performance, Strength & conditioning coach, Sports scientist, Performance analyst
- Relevant to
- Professional club, Collegiate athletics, Academy & youth, Women's league
- Systems in play
- GPS and wearable tracking platforms, Spreadsheets, Athlete management systems
- Product framing
- Analyse data
Questions we get asked
What do we need in place before this produces anything useful?
You need a weekly plan expressed as numbers per athlete — even a simple spreadsheet with target distance, high-speed running and session RPE per week is enough — and a GPS export with matching athlete identifiers. If the plan currently lives only in a coach's head, the first version's value is limited to whatever week you're willing to write targets down for. Most of the setup cost is agreeing a consistent athlete ID and column format between the plan and the export, not building anything new.
Does this replace the planning module in our athlete management system?
No. It sits downstream of it. Your athlete management system or spreadsheet stays the place where the plan is set; the GPS platform stays the place load is recorded. This tool's only job is comparing what was planned against what was delivered and surfacing the gap, because today that comparison happens by hand or not at all. If your existing system already produces this comparison natively, you do not need this.
Our coaches already eyeball load numbers each week — why formalise it?
Eyeballing works until the week gets busy, and the weeks it gets skipped are usually the weeks load is spiking, which is exactly when the check matters most. This does not ask coaches to change how they plan or record load. It removes the manual export-and-align step, so the comparison happens whether or not anyone had an hour spare that Friday.
What happens when an athlete's export is missing for a week, say through injury or a device fault?
The report shows that athlete as no data for that week rather than guessing or interpolating a figure, and it is flagged separately from genuine under-target compliance so the two are never confused. An athlete out through injury is not the same finding as an athlete who trained below plan, and folding them together would make the report untrustworthy the first time someone checked it against reality.
Is this your workflow?
Tell us one sports workflow that still runs on paper, spreadsheets, WhatsApp or an outdated system. We will map it and show you what a simpler product looks like.
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