MyFitnessPal's Database Is Full of Wrong Entries — Why It Matters More Than You Think

Search for "chicken breast" in MyFitnessPal and you will find at least a dozen entries with different calorie counts. One says 165 calories per serving. Another says 128. A third says 231. A fourth says 187 but lists the serving size as "1 piece" without specifying weight. You pick one, log it, and move on — trusting that the number is close enough. But is it?

The answer, according to research on crowdsourced food databases, is that it might not be. And the gap between what you think you are eating and what you are actually eating can be large enough to completely derail your nutrition goals.

How Bad Is MyFitnessPal's Database Problem?

What Does It Look Like When You Search for Common Foods?

Here is what an actual search for common foods in MFP can return. These are real examples of the kind of variation users encounter daily.

Food Search	Entry 1 (cal)	Entry 2 (cal)	Entry 3 (cal)	Entry 4 (cal)	Entry 5 (cal)	Actual (USDA)
Banana (medium)	89	105	121	72	110	105
Chicken breast (100g, cooked)	165	128	231	187	196	165
Brown rice (1 cup, cooked)	216	248	180	232	195	216
Avocado (whole)	234	322	160	280	250	240
Olive oil (1 tbsp)	119	100	130	90	140	119
Greek yogurt, plain (170g)	100	130	89	150	95	100

For some entries, the variation is 50-100 calories on a single food item. When you are logging 15-20 food items per day, those errors do not cancel each other out — they compound.

Why Are There So Many Wrong Entries?

MyFitnessPal uses a crowdsourced database model. This means that any user can submit a food entry, and those entries are available for all other users to find and log. The database has grown to over 14 million food items, which sounds impressive until you realize that a significant portion of those entries are duplicates with conflicting data, entries with incorrect calorie or macronutrient values, entries with ambiguous serving sizes ("1 serving," "1 piece," "1 bowl"), outdated entries for products that have been reformulated, and entries from different countries using different measurement standards.

There is no nutritionist reviewing each submission. There is no automated system that reliably catches errors. The database grows continuously, but its accuracy does not improve at the same rate.

How Do Wrong Entries Compound Over Time?

What Is Calorie Drift?

Calorie drift is the cumulative effect of small database errors across multiple food items logged over days and weeks. Each individual error might seem negligible — 20 calories here, 30 calories there. But they add up in ways that can completely undermine your tracking.

Here is a realistic example of how calorie drift works across a single day.

Daily Calorie Drift Example

Meal	Food	MFP Entry Used	Actual Calories	Error
Breakfast	2 eggs	140	156	-16
Breakfast	Toast with butter	160	195	-35
Breakfast	Coffee with milk	30	45	-15
Lunch	Chicken salad	350	420	-70
Lunch	Dressing (2 tbsp)	80	130	-50
Snack	Apple	72	95	-23
Snack	Peanut butter (1 tbsp)	90	96	-6
Dinner	Pasta with sauce	480	560	-80
Dinner	Parmesan (sprinkle)	20	42	-22
Daily Total		1,422	1,739	-317

In this example, MFP logged 1,422 calories while the actual intake was 1,739 calories — a difference of 317 calories, or about 18%. The user thinks they are in a significant calorie deficit. They are not.

How Does This Add Up Over a Week and Month?

Time Period	Logged Calories	Actual Calories	Cumulative Error
1 day	1,422	1,739	317 calories
1 week	9,954	12,173	2,219 calories
1 month (30 days)	42,660	52,170	9,510 calories

Over a month, the cumulative error of 9,510 calories is equivalent to approximately 1.2 kg (2.7 lbs) of body fat that should have been lost but was not. This is enough to completely explain why someone tracking "perfectly" in MFP sees no results on the scale.

The frustrating part is that the user is doing everything right. They are logging every meal. They are scanning barcodes. They are measuring portions. The problem is not their discipline — it is their data source.

Why Can a Crowdsourced Database Never Be Fully Fixed?

Is It Possible to Clean Up 14 Million Entries?

Theoretically, yes. Practically, no. Here is why.

Scale. With over 14 million food entries, manually reviewing and correcting each one would require thousands of nutritionist-hours. Even at a rate of one entry per minute, reviewing the entire database would take approximately 27 years of full-time work.

Continuous contamination. While entries are being reviewed and corrected, new incorrect entries are being submitted by users every day. The database is a living system that accumulates errors faster than they can be fixed.

Regional variation. A "chicken breast" in the United States has different nutritional values than a "chicken breast" in Germany or Japan due to differences in farming practices, feed, and breed. A single "correct" entry cannot represent all versions of a food.

Product reformulations. Packaged food manufacturers regularly change their recipes, serving sizes, and nutritional labels. Crowdsourced entries from 2019 may be incorrect for the 2026 version of the same product, and no automated system reliably catches these changes.

No accountability. When any anonymous user can submit an entry, there is no accountability for accuracy. A user might submit "pizza — 200 calories" because that is what they want it to be, not what it actually is.

What About MFP's Verified Entries?

MFP does have some verified entries, and they have expanded this program over time. However, verified entries represent a small fraction of the total database. Users still encounter unverified entries constantly, and the app does not always clearly distinguish between verified and user-submitted data. The verified program also requires a Premium subscription to prioritize in search results.

How Do Verified Databases Work Differently?

What Makes a Food Database "Verified"?

A verified food database takes a fundamentally different approach from crowdsourcing. Instead of allowing any user to submit entries, verified databases have professional nutritionists or dietitians review every single entry before it becomes available to users.

This means a smaller database but a more accurate one. Instead of 14 million entries with unpredictable accuracy, you get a curated database where every entry meets a professional standard.

Verified Database Approaches

Approach	Used By	How It Works	Accuracy Level
100% nutritionist-verified	Nutrola	Every entry reviewed by nutrition professionals before publication	Highest — professional standard
Government database (USDA/NCCDB)	Cronometer	Uses lab-tested data from government agencies	Very high — lab-tested
Crowdsourced with verified subset	MyFitnessPal	Bulk user-submitted, small verified subset for Premium users	Variable — depends on which entry you select
Crowdsourced with community moderation	FatSecret, Lose It	User-submitted with community flagging of errors	Moderate — errors caught inconsistently

The trade-off with verified databases is typically a smaller total number of entries. You might not find every obscure branded product or regional food. But the entries you do find are accurate, which matters far more for your results.

How Do You Know If Your Tracking Data Is Reliable?

What Are the Signs of Inaccurate Food Data?

There are several red flags that suggest your calorie tracker's database is giving you bad information.

Multiple entries for the same food with different calorie counts. If you search for a common food and see more than 2-3 entries with significantly different values, the database is crowdsourced and unreliable for that item.

Entries with vague serving sizes. Serving sizes like "1 serving," "1 piece," or "1 bowl" without gram weights are nearly useless. A "bowl" of rice could be 150g or 400g.

Stalled weight loss despite consistent tracking. If your logged calories show a deficit but the scale is not moving after 3-4 weeks, systematic data errors are a likely culprit.

Barcode scans returning wrong products. If scanning a product returns a different item or obviously wrong nutrition data, the barcode-to-food mapping is unreliable.

Round numbers everywhere. Real nutritional data includes odd numbers (165 calories, 31g protein). If you see a lot of entries with suspiciously round numbers (200 calories, 30g protein, 50g carbs), those were likely estimated rather than sourced from actual labels or lab data.

What Should You Do About It?

How Do You Switch to a More Accurate Calorie Tracker?

The most impactful change you can make to improve your tracking accuracy is switching to a calorie tracker with a verified database.

Nutrola maintains a 100% nutritionist-verified food database, meaning every single entry has been reviewed by a nutrition professional before it becomes available. Combined with AI photo logging (which provides a second data point for portion estimation), voice logging for speed, and social media recipe import, it addresses both the accuracy problem and the logging friction problem. At €2.50/month with no ads on any tier, it is also significantly more affordable than MFP Premium. Available on iOS and Android.

Cronometer uses USDA and NCCDB laboratory-tested data, which is highly accurate for whole foods and common ingredients. Its free tier includes access to the verified database. For packaged foods and brand-name products, the database is smaller than MFP's but more reliable.

Can You Keep Using MFP but Improve Accuracy?

If you prefer to stay with MFP, you can improve your accuracy by always cross-referencing MFP entries with the USDA FoodData Central database, choosing entries marked as "verified" when available, avoiding entries with vague serving sizes, weighing your food with a kitchen scale to ensure correct portion logging, and creating your own custom entries based on nutrition label data.

This approach works but adds significant time to every logging session. For most users, switching to a verified database is more practical than manually fact-checking every entry in a crowdsourced one.

The Bottom Line

The database problem is not a minor inconvenience. It is the foundation of everything your calorie tracker does. Every calculation — your daily total, your macro split, your weekly average, your deficit estimate — is only as accurate as the individual food entries it is built from.

When those entries are wrong, every conclusion you draw from your data is wrong too. And the most insidious part is that you cannot tell. The app displays confident numbers that look precise. There is no asterisk that says "this number might be off by 20%."

You deserve a tracking tool where the numbers you see are the numbers you can trust. Whether that is Nutrola's nutritionist-verified database, Cronometer's USDA data, or another verified source, moving away from crowdsourced guesswork is the single most impactful change you can make to your tracking accuracy.

Frequently Asked Questions

How inaccurate is MyFitnessPal's food database?

Searches for common foods like chicken breast can return entries ranging from 128 to 231 calories per 100g serving. With 15-20 food items logged daily, these errors compound — a realistic daily drift of 200-300+ calories can add up to over 9,000 calories of cumulative error per month, enough to completely stall weight loss.

Why does MyFitnessPal have so many duplicate entries with different calories?

MFP uses a crowdsourced model where any user can submit food entries without professional review. With over 14 million entries, the database has accumulated massive numbers of duplicates with conflicting data, ambiguous serving sizes, and outdated nutrition information from reformulated products.

Can MyFitnessPal's crowdsourced database ever be fixed?

Practically, no. Reviewing 14 million entries at one entry per minute would take approximately 27 years of full-time work. Meanwhile, new incorrect entries are submitted daily, and product reformulations continually make existing entries outdated. The contamination rate exceeds the correction rate.

What is a verified food database and why does it matter?

A verified food database has every entry reviewed by a nutrition professional before it becomes available to users. This produces a smaller but consistently accurate database. Nutrola uses 100% nutritionist-verified data, and Cronometer uses USDA/NCCDB lab-tested data — both significantly more reliable than crowdsourced alternatives.

How do I know if my calorie tracker's data is accurate?

Red flags include multiple entries for the same food with different calorie counts, vague serving sizes like "1 serving" or "1 bowl" without gram weights, stalled weight loss despite consistent tracking, and entries with suspiciously round numbers. If you see these patterns frequently, your tracker's database is likely unreliable.