2026 So Far - Life Tracking Update
Here are my stats for January to June 2026. This was generated using my data from Exist, and I found it highlights some key facts I hadn't considered as much as I should.
Key Themes
- I should make sure I hit at least 5,500 steps in a day before I retire to play games or watch TV in the evening.
- I should keep up my reading habit, and try and read at least every other day.
- I should continue with my diet plan (Huel!), as it seems to be working!
- I really need to think about what makes the difference between a 5/9 day and one that is 7+
Monthly snapshot
Average daily steps by month
Daily steps β full timeline
Highs and lows
- 6 Jun17,770
- 14 Apr15,877
- 16 Apr13,854
- 18 Jun1,441
- 13 May1,513
- 14 Jan1,519
National Trust & date nights
Both tags strongly associated with high step days. National Trust visits averaged 9,642 steps; date nights averaged 9,715 β nearly double the overall daily average of 5,260.
- 16 Mar11,728
- 15 Feb11,491
- 14 Feb10,098
- 26 Apr10,822
- 12 Apr9,001
- 6 Jun17,770
- 5 Jun13,655
- 21 Jun10,046
- 26 Apr10,822
- 21 Mar7,565
Average mood by month (1β10 scale)
Mood score distribution
Highs and lows
15 days scored a 9; 4 days scored β€ 2. Listed below are the standout examples.
- 14 Apr9 · 15,877 steps
- 15 Feb9 · 11,491 steps
- 11 Apr9 · 11,447 steps
- 24 Jun1 · 2,694 steps
- 31 Jan2 · 1,784 steps
- 9 Jun2 · 2,222 steps
Average daily sleep by month
Daily sleep β full timeline
Highs and lows
- 17 Mar8h 51m
- 20 Feb8h 48m
- 7 Mar8h 45m
- 28 Jun5h 26m
- 4 Apr5h 30m
- 4 Feb5h 41m
Cumulative weight change since 1 Jan
Net weight change per month
Highs and lows
Largest day-over-day changes β likely a mix of real change and weigh-in noise (clothes, hydration, time of day).
- 14 Junβ2.14 kg
- 4 Febβ2.01 kg
- 20 Mayβ1.33 kg
- 18 May+1.77 kg
- 16 Mar+1.68 kg
- 8 Jun+1.32 kg
Average active minutes by month
Steps vs active minutes
Highs and lows
- 26 Apr2h 09m
- 14 Apr2h 07m
- 1 Mar1h 48m
- 21 Jan2m
- 20 Jun2m
- 14 Jan3m
National Trust visits
10 visits β every single one scored mood 8 or 9. Average active time was 52m, nearly double the first-half daily average.
- 13β16 Feb9, 9, 9, 9 mood Β· 38β75m active
- 16 Mar8 mood Β· 11,728 steps Β· 53m active
- 26 Apr9 mood Β· 10,822 steps Β· 2h 09m active
- 2 May8 mood Β· 9,852 steps Β· 16m active
- 24 May8 mood Β· 8,015 steps Β· 20m active
- 5β6 Jun9, 8 mood Β· 13,655 / 17,770 steps
- 26 Apr9 mood Β· 10,822 steps
- 21 Jun9 mood Β· 10,046 steps
- 21 Mar7 mood Β· 7,565 steps
- 4 Jan9 mood Β· 4,359 steps
Average gaming time by month (when played)
Average across days when gaming actually happened β not diluted by zero days.
Average reading time by month (when read)
Total monthly leisure time
Highs and lows
- 15 Apr6h 22m
- 13 Jun5h 00m
- 13 May4h 11m
- 17 Jan1h 51m
- 24 Feb1h 48m
- 24 May1h 47m
Top 3 correlations
Pearson correlation across all 180 days. Values closer to Β±1 mean a stronger relationship; 0 means none.
|
Steps Γ Mood
+0.54
Strong positive (n = 161)
The clearest signal in the dataset. Days with 7,500+ steps averaged mood 7.6 / 10; days under 3,000 steps averaged 5.2 / 10 β a +2.4 point swing. Walking more was the single most reliable mood lever in the data.
|
Gaming Γ Steps
β1,182
Substitution effect
On days with 60+ minutes of gaming, average steps dropped to 4,668 vs 5,850 on days with no gaming β a ~1,200 step deficit. May, the heaviest gaming month (21 days, 1h 47m avg), had the lowest active minutes of the first half.
|
Sleep Γ Mood
+0.09
Effectively none (n = 159)
Counterintuitive but consistent: a longer night didn't predict a better day. Sleep was so stable (7h 21m β 7h 36m every month) that there wasn't enough variation for it to drive mood. A good baseline, but not a useful lever.
|
Other observations
Saturday and Sunday averaged mood 7.0 vs 5.4 on weekdays β a +1.6 point gap, bigger than any single correlation. Sunday was the peak day (mood 7.3, ~6,900 steps); Tuesday was the slump (mood 4.8). Weekday mood is likely the biggest opportunity area for the second half of the year.
Not just correlated β the relationship climbs in clear steps. Days under 3k steps averaged mood 5.2; days at 5k+ averaged 6.7; 7.5k+ averaged 7.6; 10k+ averaged 8.2. Roughly +1 mood point per 2,500 extra steps.
On days that hit 7,500+ steps, included reading, AND had 7+ hours of sleep, mood averaged 7.9 vs 5.7 on every other day β a +2.2 point swing. Only 13 of 180 days hit all three; the compound effect is the strongest single signal in the data.
7.4 kg shed over 6 months β an average of 1.2 kg per month β with March showing the biggest single-month drop (β4.5 kg). The trend held even during quieter movement months, suggesting diet was likely the primary driver.
10β17 April: 8 consecutive days of 5,000+ steps, including a 5-day run of 7,500+. Every day in that stretch scored mood 7β9. Concrete proof of what a sustained high-movement week can look like.
Read on 96 of 180 days (53%) at a steady ~39 minutes per session. Unlike gaming, the monthly average barely moves β a quiet, dependable habit that survived even the toughest months.
6 sick days across the first half of the year (a 5-day cluster in early April, one isolated day in May). On those days active minutes collapsed to just 11m on average β less than half the overall mean β while steps held up surprisingly well at 5,256. Mood averaged 4.67, with the final sick day (7 Apr) hitting a 3. Notably, 3 of the April sick days overlapped with holiday periods β so the Easter mood boost was partly undermined by illness.
Goals for the second half of 2026
This is post 47 of #100DaysToOffload.
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