2025 Wrapped

I’m doing this again. There’s something oddly satisfying about pausing at the end of the year and reviewing what the numbers have to say. So here we go, round three.

The year was 2025

Entertainment

• Music Listened: 20,173 minutes (down 17%, average 55min per day)
• Books Read: 7 ¹ (down from 16 last year)
• TV Series: 13 ²
• Films: 7 ³

Home Energy

• Total usage: 15,669.3 kWh (up 22%)
• Total Solar generated: 3162.7 kWh (up 21%)
• Energy Self-Sufficient: 20%

I do appreciate this energy usage is very high (about 4x UK average household). However, for additional context this is for home, heating, hot water, and EV charging and our annual costs are relatively low (for this level of consumption) at just over £1,000 - read more about that here.

Health / Fitness

Running

• Parkrun Completed: 8 (down 2)

Annual Personal Bests

Training & Activity

• Total Steps: 3,607,574 (down 2.8%)

Strange, given I ran over double the distance compared to 2024, I walked significantly less.

• Average Daily Exercise: 46 minutes (up 11 minutes)

• Average Daily Time in Daylight: 81 minutes (down 47%)

A significant difference, and one I didn’t expect to see. My best guess is increasing my running distance means I walked less casually outdoors, reducing my time outside.

Performance Metrics

• Resting Heart Rate: 49 bpm (down from 51)

It has been satisfying to see the conscious effort to improve cardiovascular health can be seen in the data.

• Average VO2 Max: 42.9 (up 8% from 39.8)

Body Composition

• Annual Average: 92.6 kg (up 0.5% on last year)

Comparing to 2024, my weight still fluctuates but averaged similarly over the year. A similar pattern of early year reduction, with lowest during summer (more active) and rising into winter and Christmas. I’m pleased I ended 2025 without the typical peak from overindulgence. A goal for 2026 is to drop below 90kg early, and then sustain for remainder of year.

Groceries

Top Items by Volume

1. 🧼 600 x Dishwasher Tablets
2. 🌯 312 x Tortilla Wraps
3. 🥛 299 x Milk
4. 🧻 192 x Baby Wipes (packs)
5. 🥞 168 x Crumpets
6. 🥚 156 x Eggs
7. 🍅 145 x Tomatoes
8. 🫑 127 x Peppers
9. 🍌 122 x Bananas
10. 🍓 106 x Strawberries punnets

Top Items by Weight

1. 🥛 Milk: 534.88 litres
2. 🍞 Bread: 82.06 kg
3. 🥔 Potatoes: 61.60 kg
4. 🥣 Scottish Oats Porridge: 51.40 kg
5. 🍅 Tomatoes: 45.12 kg
6. 🐓 Chicken Breast: 39.68 kg
7. 🍓 Strawberries: 37.20 kg
8. 🍇 Grapes: 30.22 kg
9. 🫐 Blueberries: 25.43 kg
10. 🥦 Broccoli: 24.64 kg

Top Categories by Spend

1. 🍊 Fruit: 15.1%
2. 🥛 Dairy & Eggs: 13.2%
3. 🥩 Meat & Fish: 12.4%
4. 🥕 Vegetables: 10.3%
5. 🥖 Bakery: 6.4%

Top Items by Presence

1. 🥛 Milk: 52.5%
2. 🍌 Bananas: 38.1%
3. 🍓 Strawberries: 31.9%
4. 🍅 Tomatoe:s 29.6%
5. 🥒 Cucumbers: 28.8%
6. 🫐 Blueberries: 26.8%
7. 🥬 Lettuce: 24.1%
8. 🍇 Grapes: 23.3%
9. 🥦 Broccoli: 21.0%
10. 🫑 Peppers: 19.5%

Shopping Frequency by Day

• Monday: 55 shops (21.4%)
• Friday: 53 shops (20.6%)
• Tuesday: 33 shops (12.8%)
• Saturday: 32 shops (12.5%)
• Wednesday: 30 shops (11.7%)
• Thursday: 29 shops (11.3%)
• Sunday: 25 shops (9.7%)

Travel

Total Distance: 15,258 miles (up 7.3%)

Family Outings

• Swimming: 14
• Thorp Perrow: 9
• Soft Play: 5
• Farm: 4
• Ferry crossings: 2
• Stockeld Park: 1
• Wildlife Park: 1

Photos

Photos: 4,036 (up 17%)

• By Ben: 1,144 (up 28%)
• By Lucy: 2,892 (up 9%)
• Of which selfies: 223
• Videos: 603
• Data: 39.77 GB (up 13%)

Mobile Data

• Total: 122.44 GB (up 72%)

Up from last year even considering I’ve missed January data. Partly because I increased my data allowance and made no effort to be conservative (I stopped being stingy, it was only an extra 90 pence a month 😆).

By Day

By Month

Median Usage Patterns

• Weekdays: 42MB
• Weekends: 237MB (5.6x higher)

The Outlier Effect

18 days over 1GB (5% of the year) accounted for 45.6GB (37% of total usage).

Most of this came from the August holiday week streaming Netflix in a caravan. Remove those outlier days and the baseline drops from 340MB to 220MB per day.

Interestingly, August’s baseline usage (98MB/day) was one of the lowest months when you exclude the holiday streaming, I was simply using my phone less during peak summer outdoor activity.

One mystery remains: April 5th logged 11.33GB in a single day. No idea what that was about.

Work

Slack

• Messages: 14,509
• Reactions: 6,042

GitHub

• Contributions: 1,740 (up 17%)

Insights

Several patterns emerged that weren’t obvious during the year.

The September Anomaly

September stands out as a dramatic outlier across nearly every metric:

• Daily steps crashed to 7,468 (down 40% from August)
• Running distance dropped to 70.62km (down 34%)
• Daily exercise time fell to just 37 minutes (lowest of the year)
• Average time in daylight plummeted to 37 minutes (from 127 in August)

Everything collapsed simultaneously. The reality? Returning from a family holiday with some overindulgence, followed by a hectic work period, made September a less active month. Once the routine broke, the knock-on effects compounded across every metric.

Resting Heart Rate as a Performance Predictor

The correlation between resting heart rate (RHR) and performance was remarkably precise:

• July-August: RHR dropped to 47 bpm → achieved 24:24 parkrun PB
• December: RHR rose to 49 bpm → ran 26:01

The relationship isn’t just correlational, it’s predictive. When my RHR dropped, performance improved. When it rose slightly, performance reflected that almost exactly.

Weight Responds With a Lag

Body weight changes followed activity levels, but with roughly a month’s delay:

• Peak training (May-June: 109-140km) → Lowest weight came in July-August (90.8kg)
• September activity crash → Weight gain appeared in October-November
• Maintained moderate activity through December → Weight stabilised despite festivities

This lag effect explains why short-term changes don’t show immediate results, and why maintaining consistency through difficult periods prevents rapid regression.

Recovery and Resilience

The most important insight isn’t about avoiding the September crash, it’s about what happened after.

Despite lower autumn training volume (vs summer), I finished December with solid performances and maintained cardiovascular fitness. The fitness base built during spring and summer didn’t vanish, it proved resilient through disruption.

This validated what I’d written about in my consistency post: building a strong foundation allows you to weather setbacks without starting from scratch. The real measure isn’t perfection, it’s the ability to return to baseline after disruption.