Kriterion vs MacroFactor
Both apps do the same unusual thing: measure your maintenance calories from what you actually logged and actually weighed, instead of handing you a formula and calling it a day. That part is a tie. Here is what actually differs.
The difference, on one screen Both apps arrive at a maintenance figure the same way. Only one of them shows its working. 1,870 is what this person burns on an average day — eat that, hold your weight. The ± 49 says how cleanly that came out of their weigh-ins: tight, so the scale data is telling a consistent story rather than a noisy one. The figures shown are from a seeded demo account, not a real person.
| Kriterion | MacroFactor | |
|---|---|---|
| TDEE method | Measured from logged intake vs. weight trend | Measured from logged intake vs. weight trend |
| Shows its error margin | Yes — shown as a spread, e.g. “1,870 ± 49 kcal”, so you can see how firm the number is | Not published. You're asked to trust the number once it has stabilised. |
| Water-retention handling | Weigh-ins during a creatine loading phase are excluded from the trend | Not documented |
| Free tier | Logging is free and unlimited, permanently — no card required | None. Every feature sits behind a subscription; the only free access is a trial that asks for payment details up front |
| Training | Built in — sets, reps, RIR, readiness, a HIIT timer with spoken cues | A separate app in their bundle, not part of MacroFactor itself |
| Menstrual cycle tracking | Built in, feeding readiness and training guidance directly | Not offered |
| Food database | UK government lab data (CoFID), USDA, Open Food Facts, plus over 10,500 real UK chain menu items, each entry marked with its source | A large, community-verified database, strongest on US packaged foods |
| Logging speed | 13 actions overall on MacroFactor's own published FLSI benchmark (see below) | 24 actions — MacroFactor's own published score |
| Platforms | iOS, Android, Wear OS | iOS, Android |
What the ± actually tells you
Every calorie app hands you one number. The problem with one number is that it hides how much of a guess it is: “1,870” looks identical whether the app has three months of your data or three days.
So Kriterion shows the spread too. A tight one means your weigh-ins agree with each other, so the figure drawn from them is well pinned. A spread of ± 300 would mean the opposite: too much scatter to act on yet, which is worth knowing before you cut your calories on the strength of it.
“95%” just means 19 times out of 20. Run the same maths on twenty people whose weigh-ins are this consistent, and you would expect the trend figure to land inside the stated range for nineteen of them. Here is what that looks like for two average UK adults:
Both are illustrations, not outputs from a real account. The point is the size of the gap: at that width the number is precise enough to plan a week around, and you can see that for yourself rather than being asked to assume it.
What it does not claim. A tight spread means your scale data is consistent. It does not mean the number is right. The bigger error in any app like this is under-reported food — the tracking literature puts it at 20% or worse — and that is a systematic bias, not random scatter, so nothing in your logged data can measure it and no honest interval can include it. Kriterion would rather say that plainly than hand you a range that quietly implies more than it knows.
Under the hood it is a 95% confidence interval on your weight trend, using a Student's-t critical value rather than the normal-distribution shortcut — which matters in your first few weeks, when a handful of weigh-ins would otherwise look far more certain than they are. You never need to think in those terms. When there isn't enough history to say anything useful, the app says it is still calibrating rather than showing a tidy figure it cannot stand behind. (1,870 ± 49 is an illustration; yours will differ.)
Why the creatine detail is here at all
Three pounds of water retention during a creatine loading phase is not three pounds of fat gained, but a naive weight-trend algorithm can't tell the difference and will quietly shave calories off your target for no reason. Kriterion excludes those weigh-ins from the trend calculation. It's a small thing, and it's exactly the kind of small thing that decides whether a measured number is trustworthy or not.
Logging speed, scored on MacroFactor's own test
MacroFactor publishes a real methodology for this — the Food Logging Speed Index (FLSI): four scenarios, each scored in discrete actions (taps, clicks or selections; typing digits into an already-focused field doesn't count as one). We ran Kriterion through the identical four scenarios, not a looser comparison.
| Scenario | Kriterion | MacroFactor (published) |
|---|---|---|
| Search, non-default serving + 3-digit qty | 5 | 10 |
| Multi-Add (re-log a previous food) | 2 | 6 |
| Barcode, non-default serving + 3-digit qty | 4 | 5 |
| Quick-Add Calories, no food name | 2 | 3 |
| Overall | 13 | 24 |
The MacroFactor numbers are theirs, self-published and taken as given, not independently re-timed by us. The Kriterion numbers are measured against the same scenario definitions: Search and Barcode both require changing the serving size to a non-default unit and entering a three-digit quantity; Multi-Add uses default servings; Quick-Add requires logging a calorie figure with no food name attached at all, which Kriterion's manual entry genuinely allows.
Re-logging a food you've eaten before is where the gap is largest, and it isn't an accident. MacroFactor's own algorithm depends on consistent logging to stay accurate — so does Kriterion's — and the single best way to keep someone logging consistently is to make the thing they do most often, log the same breakfast again, cost as little effort as possible.