
Hello and welcome back to Mortgage Advisor on FIRE. This week I discuss statistics and data analysis. Also, some small progress on the BTL sale.
Weekly Update
Our tenants have now moved out of the property and I’m delighted that they left the property clean and tidy. Our previous two tenants did pretty much the exact opposite. There are a few cosmetic bits that need addressing but there’s no reason to withhold any of their deposit. Once we’ve done the little jobs the property will be ready for viewings. It’s already listed online and there’s a for sale sign outside the property. Fingers crossed it’s a speedy process from here on out.
On Thursday I met up with a friend to catch up and to drop off some stuff with a charity. Other than that it’s just been another week of work, work, and a bit more work. It’s been great finishing early in the day, but the even earlier starts will take some getting used to. I was working on Saturday whilst Oana took care of the household jobs for the day. We then sat down with a takeaway (Indian) and some TV (For All Mankind). Sometimes the simple things are the best; no bells or whistles, just good company, good food, and good stories.
On Sunday, a little after this post is published, we’ll be having lunch for a family birthday. Then it’s back to another week of work. I’m trying to hold off on booking any holidays until April, at which point I should be able to have at least a week off work every five-six weeks until the end of the year. So, it’s just a case of getting my head down and ticking off the days one at a time.
Data and Statistics
A well-designed spreadsheet is a thing of beauty. It becomes less of a science and more of an art. There’s something so satisfying about constructing a sheet full of little formulas and when you tweak one cell, you see all the other changes follow automatically. The only thing that improves this experience is viewing it on a massive screen. Just like Alan Johnson, “I’ve got a 32” plasma in mine. You get a document up on that baby and you are seriously looking at that document.”

What makes spreadsheets so awesome is not the format of the document itself, but rather the data it stores. Data is not inherently good or bad; data simply is. However, data in the wrong hands can be misleading, or even dangerous.
When it comes to data there are a lot of things to take into consideration, such as;
- What are you trying to measure?
- How are you going to measure it?
- How will the data be collected?
- How will the data be analysed?
- Are you willing to follow the data, question what it suggests, and take appropriate action?
The scientific method has a fairly standard order in which data is collected. The first step is to decide on a research area or question. This can start as broad or narrow as desired, but once you have a question you then start researching that area. Once you have a better understanding of the topic, you may refine your question and form a hypothesis, which is a proposed answer to the question you have asked. You then have to create a way of testing the hypothesis and collect the required data, which you then subject to appropriate analysis. Once the analysis is complete, you discuss your results and, often, propose further research to better investigate your conclusions. This is the strength of science, as it is always building, developing, and evolving. Anyway, back to my point about data…
Too often people approach this whole process in reverse. They decide what it is they believe, and then go searching for data to back up their belief, whilst ignoring data that contradicts their belief. This process is not just a waste of time, it’s offensive to reason and logic. Misleading, false, or fraudulent data can be deadly; just look at what happened to vaccination rates following the false claims that vaccines lead to autism.
When I was studying my BSc I completed my dissertation on home advantage in professional football. I suggested that home advantage was due to stadium design, the placement of fans, and the prematch routine or ritual of the club in question. The first thing I had to do was conceptualise or define home advantage. You can’t just say that because Liverpool wins more games at home than Burnley, then Liverpool has more home advantage. That’s not what you are measuring. You are not measuring Liverpool’s home performance against Burnley’s. You are measuring Liverpool’s home form against their away form, and doing the same for every team, to work out which teams perform much better at home than they do away.
I spent ages on this dissertation. It was months of hard work and it paid off. I was able to work with some great lecturers at the university, and I was able to gain the support and participation of some huge clubs in the Premier League and Championship. Their generosity of time and information was incredible. I got a first on my dissertation and it’s something I’m really happy with. This all came from devising a question, obtaining the right data, and analysing it correctly. It wasn’t enough to just find out if home advantage was a real phenomenon; that’s not all that interesting in itself. The interesting bit is finding out why home advantage exists, and what can be done to improve it.
There are a lot of people out there who assume that because you can measure something, you can control it, and use it to improve performance. However, this fails to account for the ingenuity of the people being monitored. Or, as Bill Gates once said, “I’ll choose a lazy person for a hard job, because a lazy person will find an easy way to do it.”
Often, when people decide to start measuring something, they are measuring the wrong thing, and it can lead to unexpected and unhelpful behaviour. When I was completing my dissertation I had a long talk with one of the sport psychology lecturers who told me about his experience working with a top football club. They’d appointed a manager who was big on data analysis. The manager was trying to improve the pass completion rate for his team, as he felt they were giving possession away too cheaply. The whole team’s performance had been reduced to a single metric; the pass completion percentage.
This team had one player who consistently had much lower pass completion rates than his teammates. This was a creative player who would often try a defence-splitting pass which, if successful, would lead to a great chance to score a goal. 90% of the time, the pass may be unsuccessful, but it only needs to work once for a goal to be scored. However, because this manager was hammering his team to improve their pass completion rates, this player lost his confidence and stopped trying the killer pass, and started playing the safe option instead. Pass completion rates increased, but by almost every other measure the team’s performance worsened. Fewer goals were being scored, fewer points were being won. Players became scared of losing possession of the ball and stopped taking risks. The manager wanted to improve the team’s performance and decided that improving possession retention was the way to go about it. So, the players started performing against this target instead of the targets that actually mattered.
In summary; data can be very powerful as a tool to influence performance. In the hands of those with limited experience, it can be counterproductive. People will, generally, do the absolute minimum required to hit a target they have been set. This is only compounded when the target is arbitrary and seemingly disconnected from reality. The players in that team probably knew that pass completion rates were interesting and insightful, but not the whole story.
What Am I Doing?
TV: For All Mankind (Apple TV).
Audiobook: More Money Than God by Sebastian Mallaby.
For All Mankind continues to be engaging and entertaining. I’m enjoying it, and it takes a lot to keep my interest in TV now. If you like sci-fi and/or alt-history, you should check it out. It’s available on Apple TV.
Financial Update
Assets
Premium Bonds: £13,150.00.
Stocks and Shares ISA: £60,047.49.
Fuck It Fund: £6,029.25.
Pensions: £71,924.10.
Residential Property Value: £228,116.00.
BTL Property Value: £147,203.00.
Total Assets: £526,469.84.



Debts
Residential Mortgage: £173,195.63.
BTL Mortgage: £104,912.43.
Total Debts: £278,108.06.
Total Wealth: £248,361.78.
Investment Income in 2023: £661.27 (target £10,000).



I was asked why I stopped showing the weekly change in the values of my assets and debts. There are two reasons. The first is that I’m constantly pushed for time, and cutting out this step saves me 15-20 minutes and is an easy win. The second reason is that I’m now at a stage where week-to-week performance doesn’t tell me a lot. I can see swings of a couple of thousand pounds in my ISA from one week to the next, and it’s a case of “So what?” Yes, I want the numbers to increase and my investments to grow at a decent rate of interest, but these things don’t work in a straight line.
I don’t have much to talk about in respect of my finances this week either. It’s been a very quiet week in that regard. I would normally have received a rental payment but that ship has sailed. By next week I should have received a dividend payment and I’m hoping to have some viewings lined up for our sale.
That’s all for this week. I hope you have a great week ahead, and please remember to like, share, comment, and subscribe.
Disclaimer
The views and opinions in this blog are my own, and do not represent the views or opinions of my employer, nor should they be considered advice.
If you want personalised financial advice, seek an appropriate professional. If you are in financial difficulty, seek advice via the resources below:
Biolink
You can now find all my social media pages by checking out my Biolink:
bio.link/davidscothern.






































































































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