If the Data Does Not Change the Plan, Delete It
Back in the day, when I was coaching CrossFit Endurance seminars all over the world I realized one thing, some athletes collect far more information than they use.
Heart rate variability, sleep scores, strain, readiness percentages, weekly load trend lines — the dashboard keeps filling up, but none of it changes what happens on Monday morning.
The technology usually isn’t the problem. The problem is collecting numbers before you’ve decided what any of those numbers should make you do.
Or if those numbers even actually matter.
Whether you own every new tracking device or train with nothing more advanced than a notebook, the useful order stays the same: identify the problem, choose the information that impacts that problem, take action, and then see whether that action worked.
This is the basic idea behind “decision-first” analysis, which is a fancy way of saying: “Why are you training”
Start with the “why”.
Choose the data second.
You don’t need a dashboard to train strategically. You need just enough information to answer one question before each session: should this session proceed as written, be modified, or disappear from the week entirely?
What Decision-First Monitoring Means
The standard approach to monitoring is additive. You buy a device, sync it to an app, and let the app decide what deserves your attention. Over time, the display gets richer, the graphs get more detailed, and the weekly review gets longer. None of that is automatically bad. But when you add inputs without first defining the decision, you create more noise to sort through, not more useful signal.
Decision-first inverts the process:
- Does the metric support your decision?
- Choose only the information that changes that decision.
- Act on what you find.
- Check whether the action produced the intended result.
For every metric you track, decide what result would make you change the plan.
If you can’t name one, the metric isn’t helping you make a training decision.
It’s just another number on the dashboard.
Four Monitoring Categories That Drive Decisions
If you’re a career military officer, veteran, or just busy professional fitting training into a compressed week, start with four categories. Together, they give you enough information to answer the proceed-modify-skip question before each session without turning the log into a second job.
Session RPE and duration. After each session, record a 1–10 rating of perceived exertion and how long you trained. You’re not trying to justify the workout or prove that you worked hard. You’re looking for drift. If your easy runs keep landing at 7–8 RPE, something is off. Catching that pattern early gives you a chance to adjust before the accumulated fatigue shows up as a missed workout or a pulled hamstring.
Sleep quantity or a simple recovery rating. You don’t need an algorithm to tell you whether you slept well. Record the number — seven hours, five hours — or use a three-point rating of good, average, or poor. Either one captures enough to make a decision. Two consecutive poor nights are useful information. One rough night usually isn’t. The threshold matters more than another decimal place.
Pain or movement limitations. For the purpose of this session decision, the check is binary, and it matters most. Is there pain that changes how you move, limits a specific exercise, or has been present for more than two sessions? If the answer is yes, the session changes. Athletes often leave this out of the log because they assume they’ll notice pain. Of course they notice it. They also get very good at negotiating with themselves once the warmup starts. Writing it down makes that negotiation harder to ignore.
One or two phase-specific performance measures. During a strength phase, this might be a working-set load or a rep count at a given load. During a running phase, it might be pace at a standard effort. These aren’t daily measures. They’re periodic checks that tell you whether the program is doing what it’s supposed to do. Is the training producing adaptation, or are you just completing sessions?
That’s the complete set: four categories, each tied to a decision you may actually have to make.
The Deletion Test
Before you add a metric to your tracking system, ask one question: what result would make me change the plan?
If you can answer with a concrete rule — “if sleep drops below six hours for two straight nights, I push the next heavy session back a day” — keep the metric. You’ve attached a decision to it.
If the honest answer is “I would just note it and continue” or “I’m not sure,” delete it. You aren’t monitoring at that point. You’re collecting.
Tracking is useful when it drives a decision.
Passive accumulation just leaves you with data that gets reviewed, exported, and eventually ignored. Every metric costs you something: time to record it, attention to interpret it, and a little mental bandwidth each time you open the app. That cost is worth paying when the metric leads to action. It isn’t worth paying for a colorful chart you scroll past every week.
What This Looks Like in Practice
A practical monitoring check takes about two minutes at the end of the day.
Write down today’s session — exercise type, duration, and RPE — along with last night’s sleep in hours or a simple rating. Add any pain or restriction worth noting. If today was a check-in session, record the relevant performance number. That’s it.
Review the log weekly, not daily. You’re looking for patterns across the four categories. Three consecutive days of high RPE on sessions that should feel moderate is a pattern. One bad night of sleep in an otherwise clean week is noise. The weekly review is where you decide whether to adjust next week’s loading, keep the plan as written, or flag something for closer attention.
Those daily entries keep you from relying on memory. The weekly review turns what you recorded into a decision about the next week.
When Less Tracking Produces Better Training
Some monitoring increases anxiety without improving a single training decision. If you check a readiness score every morning and let a proprietary algorithm decide how motivated you should feel, you aren’t monitoring your training anymore. You’re outsourcing your judgment.
Your watch isn’t your coach. A readiness score may tell you to take it easy on a day when you feel sharp, then give you a green light on a day when your lower back is tight. In both cases, the score competes with your direct experience instead of adding context to it. The four-category system includes your perception — RPE, a simple recovery rating, and your own pain assessment — alongside objective markers. It doesn’t ask the device to replace your judgment.
Athlete monitoring should help you make better decisions instead of simply giving you more numbers to know. A small, deliberate set of metrics that answers specific questions is more useful than a comprehensive dashboard nobody acts on.
How to Build Your Monitoring System
If you’re starting from scratch or cutting back an overloaded system, use a simple setup.
Choose one input method: a small notebook, a notes app, or a single row in a spreadsheet. Pick the one you’ll actually use consistently, not the one that looks most impressive during setup.
Next, define your decision rules before you start collecting data. A first set might look like this:
- If RPE on easy sessions exceeds 7 for two sessions in a row → reduce next session’s volume by roughly 20 percent.
- If sleep averages under six hours for three consecutive nights → push the next heavy session back one day.
- If any pain is present that limits movement → modify the session to remove the aggravating pattern before proceeding.
- If the phase-specific performance measure shows no improvement across three consecutive check-ins → reassess program structure, not effort.
Write those rules down once. They don’t need to be perfect. They need to exist before the data arrives so you’ll know what to do with it.
Then track only what those rules require. If the rule doesn’t need the number, neither does your log.
Frequently Asked Questions
Do I need a wearable to do this?
No. The four-category system works with perceived effort, sleep quantity, a yes-or-no pain check, and a performance number you can record by hand. A wearable can feed data into the system if you already have one, but it isn’t required. The decision framework matters more than the hardware.
How often should I review my monitoring data?
Weekly. Daily review encourages you to react to single-day noise and start optimizing individual sessions that don’t need to be fixed. A weekly pattern review is where you’re more likely to find a signal that actually warrants changing the plan.
What if I don’t know my decision rules yet?
Start with the four categories and track them for two weeks without changing anything. At the end of those two weeks, ask: what in this log would’ve changed what I did? Your answer becomes the first decision rule. If nothing would’ve changed, that’s useful too. You now know which entries haven’t earned a permanent place in the log.
How long until the system feels automatic?
After the first week, the daily log should take less than two minutes. The decision rules tend to feel more instinctive within a full training cycle, roughly eight to twelve weeks. Most of the friction comes at the beginning, when you’re still remembering to record the information and apply the rules.
What if I’m already using a sophisticated tracking app?
Keep it if you like it. Just add one constraint: for every metric the app shows you, define the rule that would make you act on it. If you can’t write the rule, hide the metric. You can always bring it back later if you find a use for it. You don’t have to abandon the tool. You do have to decide what the tool is for.
