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The Spreadsheet That Helped Me Lose 36kg

MDX
Sun May 17 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · 5 min read

I didn't lose weight by following a diet plan. I lost it by treating my body like a data problem.

36kg. Gone. And the thing that made it stick wasn't willpower, or a coach, or some expensive programme. It was a spreadsheet.

Here's exactly how it worked.


The Problem With Weighing Yourself Daily

Most people step on the scale every morning, see a number they don't like, and feel like they've failed.

That's the wrong way to read the data.

Your body weight fluctuates by 1–3kg every single day based on water retention, sodium intake, sleep, stress, and whether you had a big meal the night before. That fluctuation has almost nothing to do with fat gain or loss.

If you react to daily noise, you'll make bad decisions. You'll crash diet after one bad reading. You'll give up after a week that looked flat but was actually progress.

The fix: weekly averages.


How Weekly Averages Work

Here's the math.

Say your daily weights for one week are:

| Day | Weight (kg) | |-----|-------------| | Mon | 92.4 | | Tue | 93.1 | | Wed | 92.0 | | Thu | 93.8 | | Fri | 92.5 | | Sat | 91.9 | | Sun | 92.2 |

Daily, it looks messy. You went up on Tuesday and Thursday. Panic mode if you're watching daily.

But the weekly average? (92.4 + 93.1 + 92.0 + 93.8 + 92.5 + 91.9 + 92.2) ÷ 7 = 92.56 kg

Now compare that to last week's average. If last week was 93.2 kg — you're down 0.64 kg. Real progress. Invisible if you were watching day-to-day.

That one shift in how I read the numbers changed everything.


The Actual Spreadsheet Structure

I kept it simple. No fancy tools. Just Google Sheets.

Daily Log tab — columns:

| Date | Weight (kg) | Calories In | Notes | |------|-------------|-------------|-------| | 2022-01-03 | 112.4 | 1,850 | | | 2022-01-04 | 113.0 | 2,100 | high sodium dinner | | 2022-01-05 | 111.8 | 1,780 | |

The Notes column mattered more than I expected. It's where patterns showed up — salt, bad sleep, stress eating. Over weeks, I could see exact causes for spikes.

Weekly Summary tab — auto-calculated:

Weekly Avg Weight = AVERAGE(daily weights for that week)
Weekly Avg Calories = AVERAGE(daily calories for that week)
Weekly Delta = This week avg − Last week avg

One formula. Updated itself every week. I could see at a glance whether I was moving in the right direction.


The Calorie Side

I tracked every meal. Not obsessively — I wasn't weighing lettuce. But I got honest about portions.

My starting target: 1,800 kcal/day.

I used MyFitnessPal to log, then pulled the weekly average into the spreadsheet. The number I cared about wasn't any single day — it was the 7-day average calorie intake against the 7-day average weight change.

This is where the real signal lives.

If my 7-day calorie average was 1,800 kcal and my weight was dropping ~0.5 kg/week — that's my maintenance at deficit dialled in. If it stalled, I dropped 100 kcal. No guessing. Just data.


What the Numbers Taught Me

After six months of logging, patterns became obvious:

Salt spikes weight fast. A high-sodium meal could push me up 1.5 kg overnight. Looks terrifying. Gone within 48 hours. The spreadsheet made this visible and I stopped panicking.

Sleep debt stalls fat loss. Weeks where I averaged under 6 hours of sleep — weight barely moved even on the same deficit. I started logging sleep quality in the Notes column because of this.

The deficit compounds. 500 kcal/day below maintenance = ~0.5 kg/week. Multiply by 52 weeks = 26 kg in a year, on paper. Real life was messier but close. I went from 113 kg to 77 kg over roughly 20 months.

Weekends kill averages. My weekday average might be 1,750 kcal. Weekends consistently ran 2,400+. The weekly average smoothed this, but it also showed exactly where I was leaking.


Why This Works When Diets Don't

Diets tell you what to do. The spreadsheet told me what was actually happening.

When you can see your data — really see it, week over week — you stop making decisions based on emotion. You start making them based on evidence.

I'm an engineer by profession. I've been debugging systems since 2005. At some point I realised: my body is just another system. Log the inputs, observe the outputs, adjust the variables.

That's it. That's the whole method.


Start With This

If you want to try this yourself, you don't need my full spreadsheet setup. Start with two columns:

  1. Daily weight (same time, every morning, after bathroom, before food)
  2. Daily calorie estimate (rough is fine to start)

Do that for two weeks without changing anything. Just observe.

You'll learn more about your body in 14 days of honest tracking than you probably have in years of guessing.

The data will tell you what to fix. You just have to be willing to look at it.