Athlete Training & Load Planning Software
Training planning software that lets performance teams compare different weekly workload scenarios against each athlete's recent load history before committing to the microcycle.
Problem
The coming week's sessions get sketched out on a whiteboard or a shared spreadsheet in the Monday planning meeting: three fixtures in ten days, so cut Tuesday's volume, add a recovery day, extend the captain's rest because he played every minute last week. None of that is checked against what each athlete actually carried the fortnight before. The acute to chronic workload ratio only gets calculated after the week is delivered, when the GPS platform's report lands and shows players spiked well past their usual range. By then the week cannot be undone, and the conversation about who got overloaded happens after the fact instead of before the plan was set.
Product idea
A planning screen where a coach builds a candidate microcycle: number of sessions, intensity per session, rest day placement, and opt-outs for athletes managing a return from injury, then sees the projected effect before committing. Using each athlete's own load history, it calculates where their acute to chronic workload ratio would land under that plan and flags anyone who would move outside their normal range. The coach can build a second version, say five sessions instead of four, and compare both side by side for the same squad. It does not prescribe a better plan. It shows the consequence of the one being considered, so the trade-off between fixture demands and individual load is visible before the week starts rather than after.
Where the AI agent does the work
The projection engine does the calculation that currently only happens after the week is delivered: it takes a candidate plan and each athlete's own load history and works out where their acute to chronic workload ratio would land, flagging anyone who would move outside their normal range before the plan is committed. Today that check waits for the GPS platform's report to land after the week has already run, by which point the overload cannot be undone. Moving the same calculation in front of the Monday planning meeting turns the conversation about who got overloaded from an after-the- fact review into a trade-off the coach can see and adjust for.
- Roles involved
- Strength & conditioning coach, Head of Performance, Sports scientist
- Relevant to
- Professional club, Collegiate athletics, Academy & youth, Women's league
- Systems in play
- GPS and wearable tracking platforms, Spreadsheets, Athlete management systems
A proposal worked through in full
A different problem, taken all the way to architecture, standards and a phased delivery plan — the level of detail any idea here can be developed to.
Sports Fan Engagement Platform for Interactive CampaignsPerformance teams often build the coming week's training plan around fixtures, recovery days, session intensity and individual athlete needs.
The challenge is understanding what that proposed week could mean for each athlete before it is delivered.
This proposed athlete training planning software lets S&C coaches and sports scientists build multiple weekly scenarios and compare their projected workload against recent athlete history: plan the week, model athlete load, compare scenarios, choose the plan.
Test the training week before delivering it
Staff create a proposed microcycle containing training days, rest days, session intensity, expected workload, fixture exposure and individual modifications.
Historical workload comes from the team's existing GPS, wearable or athlete monitoring software. The platform then projects each athlete's workload under the proposed plan.
A coach could compare four training sessions against three sessions with additional recovery, or against a reduced load for selected athletes.
The tool shows the consequence of each option rather than prescribing which one to choose.
Athlete load management by scenario
The athlete load management view could show:
- Recent athlete workload
- Planned weekly workload
- Projected change
- Individual baseline comparison
- Internal thresholds
- Insufficient-history warnings
- Athlete-specific modifications
Teams could optionally include metrics such as the acute:chronic workload ratio where that methodology forms part of their existing practice.
Thresholds should always be configured by the performance team rather than presented as universal injury-risk rules.
Player load planning during fixture congestion
The same scenario engine answers a harder version of the question when the fixtures come faster than the recovery. Three matches in eight days. Which players start all three, who gets reduced minutes, who rests, and what does each option mean for cumulative workload?
Staff enter the fixture congestion period and build a proposed plan per athlete covering starts, rest, reduced minutes, expected minutes and any manual availability hold. Recent player workload comes from the existing GPS or athlete monitoring software, and the platform projects cumulative workload across the whole period.
Squad rotation then becomes a comparison rather than an argument. Minimal rotation, rotation after the first match, or reduced minutes for selected high-load players each show projected match exposure, projected cumulative workload, the recent baseline, configurable thresholds, players requiring review, and where data is missing.
It does not select the team. The software does not understand tactics, form, the opponent, match importance, team chemistry or coaching priorities, and those are most of the decision. It answers one part: if these players play these minutes, what does the projected workload look like?
How it works
1. Import recent load
Upload several weeks of GPS or wearable data.
2. Build the week
Enter proposed sessions, fixtures, intensity and individual adjustments.
3. Compare scenarios
Save two or three versions of the same week.
4. Review projected workload
See how each scenario changes workload across the squad.
5. Choose the plan
Performance staff make the final decision. The software provides the numbers, not the coaching decision.
First release
A three to five week first version could include one squad, one-week microcycle planning, historical load CSV upload, session planning, individual modifications, configurable workload metrics, athlete baseline comparison, up to three scenarios, side-by-side comparison and insufficient-data warnings.
It would not include automatic training recommendations, live GPS integrations or automatic fixture imports.
The opportunity
Existing sports performance software is excellent at showing what athletes already did.
This proposed training planning software focuses on the decision before that: what would happen to athlete workload if we ran this training week?
That gives performance teams an additional layer between planning on a spreadsheet and reviewing workload after the week has already happened.
Questions we get asked
How much historical load data does it need before the projections are useful?
Enough to establish a rolling baseline for each athlete, typically several weeks of consistent GPS or wearable data covering both hard and easy weeks. A squad with patchy tracking history, or players newly signed or coming back from a long injury layoff, will get thinner projections for those individuals until more sessions are logged. The tool flags where the baseline is too short to trust rather than showing a confident number built on too little data.
We already read the fixture list and ease off before a congested week. Why do we need a screen for that?
The fixture list tells you the week is congested. It does not tell you which individual athletes are already carrying elevated load going into it, because that comparison happens in a separate system, if it happens at all. The whiteboard captures team-level judgement; this adds the athlete-level check underneath it. If your squad is small enough that one person tracks every athlete's recent load from memory, the extra screen probably is not worth the time.
Does this replace the reporting we already get from the GPS platform?
No. The GPS platform remains the record of what actually happened; this tool works from an export of that data to model what has not happened yet. It answers a different question: not what the athlete carried last week, but what the athlete would carry if the plan under consideration were run. Version one does not write anything back to the GPS platform or change how its reports work.
What happens if the plan changes on the morning of a session, after a scenario has already been approved?
It deliberately does not try to keep up with that. This is a planning tool for shaping the week ahead, not a live in-session system, so a same-day change, an athlete withdrawn or a session moved for weather, is not reflected automatically and the scenario is not rebuilt in real time. Re-running the affected scenario with the new inputs takes a few minutes, and that stays a manual step for whoever owns the plan that day.
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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