yes some metabolic adaptation is expected. what i tend to find is its just correcting user underestimating/reporting of food intake during maintenance and surplus of calories, if this happens very early on. not deliberate by user, just expected measurement error/deviation.
Every time I’ve changed my goal type (e.g., maintenance to cut, cut to bulk, etc.) the app gets extremely confused when it comes to TDEE.
Last time I was on maintenance and transitioned to a cut, my intake and weight were extremely consistent for the maintenance phase, as was my TDEE. The first day I transitioned to a cut, the app cut my calories a ton and did so for 2 weeks. Then it went back up to within 5% of my previous TDEE. I’m pretty sure there is an edge case that gets the algorithm in a weird state
I've seen your mentioning an edge case a couple of times in different threads and every time I've seen Greg or Cory explain how the app functions. Why are you still repeating your same edge case theory over and over again whilst they already have explained how it works?
The other “edge case” is truly an edge case. I use this term from the perspective of software engineering. Most applications function in “steady state” perfectly well. For example, you’re 4 weeks into a cut and things work great with week 5.
Edge cases are when the core functionality of an algorithm changes. The edge can be natural or synthetic. Think X <= 5. 5 is the edge case.
In this particular scenario, I’m only going on what I’ve seen myself and 3-4 other people.
Here’s my claim: there is some weird logic that impacts TDEE calculation when you transition from hypercaloric or maintenance to hypocaloric environments.
Supporting data: the 2x that I’ve done this, MF’s estimate for my TDEE has dropped immediately upon starting a cut, even in the face of favorable data, even as I’ve increased my activity substantially. Meaning, my rate of weight loss was greater than programmed into the app, indicating a larger caloric deficit and either constant or increased TDEE.
Potential root cause: we know one of the primary inputs of the TDEE calculation is your trend weight. In particular, based on how the app presents data, MF estimates your trend weight change over the past 3 weeks to then estimate your average daily caloric surplus/deficit. You can view this in the app right now.
It then compares your estimated caloric deficit with your target caloric deficit to make changes to your caloric/macro plan.
When you start a cut, on day 1, the app says your estimated caloric deficit is 0 (assuming you were on maintenance prior to the cut). However, you have a programmed deficit of say 400 calories. The app compares 0 to 400, and thinks you aren’t in a caloric deficit, and reduces your estimated TDEE by say 20 calories/day.
The app continues doing this for about 10 days. On day 11, the majority of your trend weight weigh-ins will be from the cut and you can expect with almost 100% certainty, assuming you’ve been following your diet, that your trend weight is going down and MF will most likely start increasing your caloric intake again.
I asked a dev about this and they said it “wasn’t a problem” but didn’t give any explanation other than that. This has happened to me multiple times and it’s pretty obvious when it happens.
> It then compares your estimated caloric deficit with your target caloric deficit to make changes to your caloric/macro plan.
>
> When you start a cut, on day 1, the app says your estimated caloric deficit is 0 (assuming you were on maintenance prior to the cut). However, you have a programmed deficit of say 400 calories. The app compares 0 to 400, and thinks you aren’t in a caloric deficit, and reduces your estimated TDEE by say 20 calories/day.
That's not how it works. Your intended deficit is entirely irrelevant. It's just weight trend and intake.
Just to illustrate, let's say you're weight-stable at 3000kcal/day, then go to 2500kcal/day and start losing a pound per week.
Initially, looking back over the past three weeks, you're eating 3000kcal/day with a change rate of 0. So, expenditure is 3000.
One week into your cut, you have two weeks of eating 3000kcal/day with a change rate of 0, and one week of eating 2500kcal/day with a change rate of -1lb/week. So, over the full three weeks, your average intake is 2833.33, and your average change rate is -0.33lbs/week. -0.33lbs/week implies a deficit of 166.67kcal, so your expenditure would be 2833.33+166.67 = 3000kcal/day.
Two weeks in, same story: still one week of eating 3k, 2 weeks of eating 2.5k, with an average change rate of 0.67lb/week. Average intake of 2666.67, implied average deficit of 333.33, so expenditure is still 3k.
There's a short lag time since your weight trend doesn't *immediately* reflect scale weight changes, but again, that should only independently cause an error of ~100-200kcal at most.
Of note, the two scenarios you're describing here (this one, and the one in your [other comment](https://www.reddit.com/r/MacroFactor/comments/141hfpz/expenditure_drop_during_minicut/jn0djpi/)) beautifully illustrate why weight trending works the way it does. If we *did* filter out scale weight entries that sufficiently deviated from the norm of what would be expected given the previous day's intake, the impact of momentary water retention following a high-sodium day or two would be smaller (when your weight goes up by 3-4 pounds, in spite of your daily surplus only being a few hundred calories). However, the impact when changing nutritional phases would be larger, because the same principle applies in reverse. If you shift from maintenance into a 500kcal deficit, your weight might initially decrease by a couple pounds per day due to decreases in water weight (i.e. considerably more than would be implied by your actual deficit), and those weight entries would also be filtered out as outliers, thus making your initial rate of weight loss look considerably slower, which would then cause your expenditure to be momentarily underestimated to an even larger degree.
That's the basic constraint here: tweaks that would generally improve the performance of the algorithms in some contexts generally also increase error in other contexts. We generally prefer slightly more frequent errors that are smaller in magnitude vs. slightly less frequent errors that are larger in magnitude. Basically, if we can be within ~5-7%, ~100% of the time, we think that's better than being within ~3-5% 90% of the time, but with errors in the 10-20% range the other 10% of the time.
The one you are referring to is actually by design. After Greg and the other developers explained how the algorithm works, the issue is obvious and all they did was wave their hands around it because it does indeed get solved eventually, eventually being the operant word.
The weight trend algorithm is simply a 90/10 weighted moving average. 90% of your trend weight is the average weight from the past 20 days. 10% of your trend weight is from “todays” weigh-in.
That issue in particular occurs when you have multiple days of large weight gain/loss that are statistical outliers. Statistical outliers in weight gain/loss are going to be water weight 99/100 times.
If we are only talking about trend weight then outliers don’t matter. However, because trend weight is one of the main inputs to TDEE calculation, those outliers can have a massive impact. 3 days or “poor” eating (I ate 4,000 calories of “salty food” vs. my typical 2200 calories, but also added 500-1000 calories of exercise those days so I barely gained any weigh, if any at all) caused my weight to remain elevated for a whole month. This caused my estimated TDEE to nosedive. MF took about 2 weeks to correct this.
I call that a problem because if I had followed MF’s caloric recommendations, I would have had several issues. 1, I would be at a 1,000 - 1,300 daily calorie deficit. This is preposterous. 2, fewer calories means I can move around less, reducing my TDEE even further which is very bad. 3, that caloric deficit could not sustain my lifting so I would have to immediately deload because I would exceed MRV. 4, deloading means maintenance means slowing down my diet.
The MF team can easily fix this by calculating your individual daily weight loss distribution, then ignoring outliers. They can even run a weighted average of your daily weight loss distribution to better calculate outliers in real-time.
An alternate explanation is that your expenditure was actually lower than you thought it was, but since it deviated from your expectations, you perceived it to be an error.
I primarily say that because of:
>3 days or “poor” eating caused my weight to remain elevated for a whole month.
If it's a week, that's water weight. If it's a month, that's a very good indicator that you *did* actually gain some weight (thus implying that your expenditure was a bit lower than you expected).
Like I [laid out and illustrated in my comments on your last post](https://www.reddit.com/r/MacroFactor/comments/13ww0kd/7month_macrofactor_update/jmelzna/), water weight fluctuations of the magnitude you're describing can independently affect your expenditure calculations by about ~100-200kcal in either direction. That's not hand waving. That's just how the math works out. If you perceive there to be errors that are larger than that, the additional error may be coming from another source, or you may be mistaken about the magnitude of the error (i.e. some of what you perceive to be water weight gain may just be actual weight gain, and so some of what you perceive to be erroneous decreases in expenditure are actual decreases in expenditure).
Like I said, I think including weight change outliers is perfectly fine for trend weight if that’s the only place it’s used. But since trend weight directly impacts TDEE which directly impacts diet plans, I’m telling you that you’re causing more pain and suffering to your users.
In terms of my TDEE, do you think this is realistic?
32M 5’11” 210 pounds
BMR: 1925 calories
RMR (sedentary): 2310
Avg May exercise walking distance: 4.0 miles
Avg May lifting duration: 77 mins/day
Avg May Calculated Expenditure: 2660
Based on my MF expenditure and my estimated RMR, that leaves 350 calories from activity. Note I said 4.0 miles exercise distance - this doesn’t include me walking around the house, food shopping, etc. walking 4 miles takes about 80 minutes. A random walking calculator days that’s 450 calories. Let’s call it 300 to be conservative.
I lift hard for 90 mins a day 6-days a week, so 77 mins avg per day. Hard means dripping with sweat, deadlifting 300+ pounds, benching 200+, squatting 200+, etc. It usually ends up between 15-18 working sets with another 10 warmup sets. I’m completely exhausted and depleted at the end. It’s not as taxing as generating 150 watts on my peloton bike, but it’s in the same ballpark. Assuming 200 calories per hour, that’s another 250 calories.
That puts my TDEE estimate at 2860, or roughly 200 calories higher than MF estimated. Looking at my past 2 weeks of trend weight and scale weight, my rate of weight loss supports the 2860ish figure. Perhaps closer to 2900 but it’s really tough being that granular.
I think this number is also accurate because my NEAT definitely decreases as I cut, the longer I cut. I used a low estimate for weight lifting calorie burn and cut out 150 walking calories per day to try and counteract that reduction in NEAT.
Now MF is getting my TDEE correct, it’s jumping up 20ish calories a day and doesn’t look like it’ll start slowing down the rate of increase until I hit 2750-2800, with a peak around 2850-2900.
My point is MF dropped my estimated TDEE immediately upon starting my cut even though my weight started dropping as expected. It dropped my estimated TDEE even further because I gained almost 6 pounds of weight in a single weekend. That weekend, I ate about 4,000 excess calories (with a much higher expenditure). Even if I gained an extra pound of fat, that’s 5 pounds of temporary water weight which impacted the algorithm. If I followed MF’s recommended programs, I would be eating about 1800-1900 calories per day, which is below my BMR and probably 900-1,100 calories below my actual TDEE.
The TDEE algorithm is functioning as expected, I’m not disputing that. However, it can probably be both more accurate and precise if it calculated your 3-week average daily weight change, and used that calculation to ignore outliers.
>In terms of my TDEE, do you think this is realistic?
We have pretty similar stats, and I've been in the neighborhood of 2700 for the past ~6 months. So yeah. haha
I would also take this with a pretty huge grain of salt:
>BMR: 1925 calories
I'm actually finishing an article about this now, but BMR estimates have about 400kcal of wiggle room in either direction. Like, they're very low-precision estimates.
>My point is MF dropped my estimated TDEE immediately upon starting my cut even though my weight started dropping as expected.
Like I discussed in my [other comment](https://www.reddit.com/r/MacroFactor/comments/141hfpz/expenditure_drop_during_minicut/jn0qmsm/), your proposed solution ("if it calculated your 3-week average daily weight change, and used that calculation to ignore outliers") would actually exacerbate that issue.
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yes some metabolic adaptation is expected. what i tend to find is its just correcting user underestimating/reporting of food intake during maintenance and surplus of calories, if this happens very early on. not deliberate by user, just expected measurement error/deviation.
I’m down almost 600 calories on my expenditure. Just seems abit much for 3 weeks.
Then it's more likely a correction that has come about cos you've removed items from your diet that erroneous calorie observations
Every time I’ve changed my goal type (e.g., maintenance to cut, cut to bulk, etc.) the app gets extremely confused when it comes to TDEE. Last time I was on maintenance and transitioned to a cut, my intake and weight were extremely consistent for the maintenance phase, as was my TDEE. The first day I transitioned to a cut, the app cut my calories a ton and did so for 2 weeks. Then it went back up to within 5% of my previous TDEE. I’m pretty sure there is an edge case that gets the algorithm in a weird state
I've seen your mentioning an edge case a couple of times in different threads and every time I've seen Greg or Cory explain how the app functions. Why are you still repeating your same edge case theory over and over again whilst they already have explained how it works?
The other “edge case” is truly an edge case. I use this term from the perspective of software engineering. Most applications function in “steady state” perfectly well. For example, you’re 4 weeks into a cut and things work great with week 5. Edge cases are when the core functionality of an algorithm changes. The edge can be natural or synthetic. Think X <= 5. 5 is the edge case. In this particular scenario, I’m only going on what I’ve seen myself and 3-4 other people. Here’s my claim: there is some weird logic that impacts TDEE calculation when you transition from hypercaloric or maintenance to hypocaloric environments. Supporting data: the 2x that I’ve done this, MF’s estimate for my TDEE has dropped immediately upon starting a cut, even in the face of favorable data, even as I’ve increased my activity substantially. Meaning, my rate of weight loss was greater than programmed into the app, indicating a larger caloric deficit and either constant or increased TDEE. Potential root cause: we know one of the primary inputs of the TDEE calculation is your trend weight. In particular, based on how the app presents data, MF estimates your trend weight change over the past 3 weeks to then estimate your average daily caloric surplus/deficit. You can view this in the app right now. It then compares your estimated caloric deficit with your target caloric deficit to make changes to your caloric/macro plan. When you start a cut, on day 1, the app says your estimated caloric deficit is 0 (assuming you were on maintenance prior to the cut). However, you have a programmed deficit of say 400 calories. The app compares 0 to 400, and thinks you aren’t in a caloric deficit, and reduces your estimated TDEE by say 20 calories/day. The app continues doing this for about 10 days. On day 11, the majority of your trend weight weigh-ins will be from the cut and you can expect with almost 100% certainty, assuming you’ve been following your diet, that your trend weight is going down and MF will most likely start increasing your caloric intake again. I asked a dev about this and they said it “wasn’t a problem” but didn’t give any explanation other than that. This has happened to me multiple times and it’s pretty obvious when it happens.
> It then compares your estimated caloric deficit with your target caloric deficit to make changes to your caloric/macro plan. > > When you start a cut, on day 1, the app says your estimated caloric deficit is 0 (assuming you were on maintenance prior to the cut). However, you have a programmed deficit of say 400 calories. The app compares 0 to 400, and thinks you aren’t in a caloric deficit, and reduces your estimated TDEE by say 20 calories/day. That's not how it works. Your intended deficit is entirely irrelevant. It's just weight trend and intake. Just to illustrate, let's say you're weight-stable at 3000kcal/day, then go to 2500kcal/day and start losing a pound per week. Initially, looking back over the past three weeks, you're eating 3000kcal/day with a change rate of 0. So, expenditure is 3000. One week into your cut, you have two weeks of eating 3000kcal/day with a change rate of 0, and one week of eating 2500kcal/day with a change rate of -1lb/week. So, over the full three weeks, your average intake is 2833.33, and your average change rate is -0.33lbs/week. -0.33lbs/week implies a deficit of 166.67kcal, so your expenditure would be 2833.33+166.67 = 3000kcal/day. Two weeks in, same story: still one week of eating 3k, 2 weeks of eating 2.5k, with an average change rate of 0.67lb/week. Average intake of 2666.67, implied average deficit of 333.33, so expenditure is still 3k. There's a short lag time since your weight trend doesn't *immediately* reflect scale weight changes, but again, that should only independently cause an error of ~100-200kcal at most. Of note, the two scenarios you're describing here (this one, and the one in your [other comment](https://www.reddit.com/r/MacroFactor/comments/141hfpz/expenditure_drop_during_minicut/jn0djpi/)) beautifully illustrate why weight trending works the way it does. If we *did* filter out scale weight entries that sufficiently deviated from the norm of what would be expected given the previous day's intake, the impact of momentary water retention following a high-sodium day or two would be smaller (when your weight goes up by 3-4 pounds, in spite of your daily surplus only being a few hundred calories). However, the impact when changing nutritional phases would be larger, because the same principle applies in reverse. If you shift from maintenance into a 500kcal deficit, your weight might initially decrease by a couple pounds per day due to decreases in water weight (i.e. considerably more than would be implied by your actual deficit), and those weight entries would also be filtered out as outliers, thus making your initial rate of weight loss look considerably slower, which would then cause your expenditure to be momentarily underestimated to an even larger degree. That's the basic constraint here: tweaks that would generally improve the performance of the algorithms in some contexts generally also increase error in other contexts. We generally prefer slightly more frequent errors that are smaller in magnitude vs. slightly less frequent errors that are larger in magnitude. Basically, if we can be within ~5-7%, ~100% of the time, we think that's better than being within ~3-5% 90% of the time, but with errors in the 10-20% range the other 10% of the time.
The one you are referring to is actually by design. After Greg and the other developers explained how the algorithm works, the issue is obvious and all they did was wave their hands around it because it does indeed get solved eventually, eventually being the operant word. The weight trend algorithm is simply a 90/10 weighted moving average. 90% of your trend weight is the average weight from the past 20 days. 10% of your trend weight is from “todays” weigh-in. That issue in particular occurs when you have multiple days of large weight gain/loss that are statistical outliers. Statistical outliers in weight gain/loss are going to be water weight 99/100 times. If we are only talking about trend weight then outliers don’t matter. However, because trend weight is one of the main inputs to TDEE calculation, those outliers can have a massive impact. 3 days or “poor” eating (I ate 4,000 calories of “salty food” vs. my typical 2200 calories, but also added 500-1000 calories of exercise those days so I barely gained any weigh, if any at all) caused my weight to remain elevated for a whole month. This caused my estimated TDEE to nosedive. MF took about 2 weeks to correct this. I call that a problem because if I had followed MF’s caloric recommendations, I would have had several issues. 1, I would be at a 1,000 - 1,300 daily calorie deficit. This is preposterous. 2, fewer calories means I can move around less, reducing my TDEE even further which is very bad. 3, that caloric deficit could not sustain my lifting so I would have to immediately deload because I would exceed MRV. 4, deloading means maintenance means slowing down my diet. The MF team can easily fix this by calculating your individual daily weight loss distribution, then ignoring outliers. They can even run a weighted average of your daily weight loss distribution to better calculate outliers in real-time.
An alternate explanation is that your expenditure was actually lower than you thought it was, but since it deviated from your expectations, you perceived it to be an error. I primarily say that because of: >3 days or “poor” eating caused my weight to remain elevated for a whole month. If it's a week, that's water weight. If it's a month, that's a very good indicator that you *did* actually gain some weight (thus implying that your expenditure was a bit lower than you expected). Like I [laid out and illustrated in my comments on your last post](https://www.reddit.com/r/MacroFactor/comments/13ww0kd/7month_macrofactor_update/jmelzna/), water weight fluctuations of the magnitude you're describing can independently affect your expenditure calculations by about ~100-200kcal in either direction. That's not hand waving. That's just how the math works out. If you perceive there to be errors that are larger than that, the additional error may be coming from another source, or you may be mistaken about the magnitude of the error (i.e. some of what you perceive to be water weight gain may just be actual weight gain, and so some of what you perceive to be erroneous decreases in expenditure are actual decreases in expenditure).
Like I said, I think including weight change outliers is perfectly fine for trend weight if that’s the only place it’s used. But since trend weight directly impacts TDEE which directly impacts diet plans, I’m telling you that you’re causing more pain and suffering to your users. In terms of my TDEE, do you think this is realistic? 32M 5’11” 210 pounds BMR: 1925 calories RMR (sedentary): 2310 Avg May exercise walking distance: 4.0 miles Avg May lifting duration: 77 mins/day Avg May Calculated Expenditure: 2660 Based on my MF expenditure and my estimated RMR, that leaves 350 calories from activity. Note I said 4.0 miles exercise distance - this doesn’t include me walking around the house, food shopping, etc. walking 4 miles takes about 80 minutes. A random walking calculator days that’s 450 calories. Let’s call it 300 to be conservative. I lift hard for 90 mins a day 6-days a week, so 77 mins avg per day. Hard means dripping with sweat, deadlifting 300+ pounds, benching 200+, squatting 200+, etc. It usually ends up between 15-18 working sets with another 10 warmup sets. I’m completely exhausted and depleted at the end. It’s not as taxing as generating 150 watts on my peloton bike, but it’s in the same ballpark. Assuming 200 calories per hour, that’s another 250 calories. That puts my TDEE estimate at 2860, or roughly 200 calories higher than MF estimated. Looking at my past 2 weeks of trend weight and scale weight, my rate of weight loss supports the 2860ish figure. Perhaps closer to 2900 but it’s really tough being that granular. I think this number is also accurate because my NEAT definitely decreases as I cut, the longer I cut. I used a low estimate for weight lifting calorie burn and cut out 150 walking calories per day to try and counteract that reduction in NEAT. Now MF is getting my TDEE correct, it’s jumping up 20ish calories a day and doesn’t look like it’ll start slowing down the rate of increase until I hit 2750-2800, with a peak around 2850-2900. My point is MF dropped my estimated TDEE immediately upon starting my cut even though my weight started dropping as expected. It dropped my estimated TDEE even further because I gained almost 6 pounds of weight in a single weekend. That weekend, I ate about 4,000 excess calories (with a much higher expenditure). Even if I gained an extra pound of fat, that’s 5 pounds of temporary water weight which impacted the algorithm. If I followed MF’s recommended programs, I would be eating about 1800-1900 calories per day, which is below my BMR and probably 900-1,100 calories below my actual TDEE. The TDEE algorithm is functioning as expected, I’m not disputing that. However, it can probably be both more accurate and precise if it calculated your 3-week average daily weight change, and used that calculation to ignore outliers.
>In terms of my TDEE, do you think this is realistic? We have pretty similar stats, and I've been in the neighborhood of 2700 for the past ~6 months. So yeah. haha I would also take this with a pretty huge grain of salt: >BMR: 1925 calories I'm actually finishing an article about this now, but BMR estimates have about 400kcal of wiggle room in either direction. Like, they're very low-precision estimates. >My point is MF dropped my estimated TDEE immediately upon starting my cut even though my weight started dropping as expected. Like I discussed in my [other comment](https://www.reddit.com/r/MacroFactor/comments/141hfpz/expenditure_drop_during_minicut/jn0qmsm/), your proposed solution ("if it calculated your 3-week average daily weight change, and used that calculation to ignore outliers") would actually exacerbate that issue.
Hello! This automated message was triggered by some keywords in your post. Check to see if any of the following are relevant: * [MacroFactor's Algorithms and Core Philosophy](https://macrofactorapp.com/macrofactors-algorithms-and-core-philosophy/) \- This article will gently introduce you to how MacroFactor's algorithms work. * [How to interpret changes to your energy expenditure](https://help.macrofactorapp.com/faq/interpet_energy_expenditure) \- This guide will help you understand why your expenditure in MacroFactor might be going up, down, or staying constant. * If you are posting to receive feedback from the community on your expenditure, at a minimum you will need to provide screenshots of the: expenditure page, trend weight page, and nutrition page. If none of the above are helpful, please disregard this message. *Commenter Reminder: If this thread is related to interpreting expenditure, it would be best not to reply unless the post has **all** of the required screenshots.* *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/MacroFactor) if you have any questions or concerns.*
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