Digging Deep into Frank Pilkington’s Virgo Forecasts
I get asked a lot about how I manage to keep track of so much data, and honestly, most of the time it starts with something completely ridiculous. This time around, I decided to tackle something everyone ignores: free online horoscopes. Specifically, I wanted to see if Frank Pilkington’s daily Virgo forecast was actually reliable, or just generic fluff pumped out by some lazy algorithm.
We’re talking about reliability here. In my line of work, if something claims to be a reliable forecast, I have to put it to the test. I picked Virgo because that’s my sun sign, and Pilkington’s site pops up near the top of search results and always looks overly official. So, the experiment was simple, but tedious. I committed to 90 days. A full quarter of life, dedicated to matching a few cryptic sentences against my daily events.
I started up a simple tracking sheet—nothing fancy, just three columns. Column A was the date, Column B was the exact forecast text, and Column C was my rating. I created a five-point scale: 1 was “complete nonsense, the opposite of true,” and 5 was “eerily accurate, described the day perfectly.”
The Messy Process of Tracking Daily ‘Truths’
Every morning, first thing, I logged in and captured the day’s forecast. Then, before I went to bed, I reviewed the day and assigned the score. I recorded things like major meetings, unexpected travel, arguments, or sudden windfalls. The goal was to remove any psychological bias. I wanted to see if, without me actively trying to make the forecast come true, it still managed to hit the mark.
What I quickly realized was how broad the language was. Day after day, it was stuff like, “A sudden opportunity in finance presents itself, but be wary of communication pitfalls,” or “You might feel emotional turbulence regarding a close relationship, requiring patience.” You could apply that to literally any Tuesday.
After the first 30 days, I compiled the initial results. My average score was 2.7. Not reliable, but not completely terrible either. About a third of the time, I felt like the forecast vaguely matched my mood, but rarely did it predict a concrete event. Frank Pilkington was operating in the safe zone of generalized advice and vague warnings. It was a statistical dead end for reliability testing.
But I had committed to 90 days, so I kept going. And that commitment is actually the key to this whole weird exercise. You see, most people would have stopped after a week. Why did I force myself to see it through, tracking something as meaningless as free horoscopes?
The Real Reason Behind the Reliability Test
I’ll tell you why. Because I needed something—anything—to prove that some form of prediction was reliable, even if it was astrological bunk. My need for this experiment kicked off six months ago when my entire life forecast went sideways.
I was heavily invested in a startup project, one I had spent years helping build. We had signed all the papers, shook hands on the partnership, and the financials were moving forward. I had poured every liquid asset I had into that venture, based on the reliable projections we had all calculated. I was assured everything was solid.
Then, without warning, the entire deal imploded. Not because of the market, not because of a bad product, but because my main partner simply decided to pull the plug and restructure the whole thing while I was on vacation. I returned to find my access credentials revoked. I was completely locked out, not just of the business, but of the detailed financial tracking I had managed.
I spent weeks trying to untangle the legal mess. I had been relying on meticulous data and forecasts, only to have the rug yanked right out from under me by sheer, unexpected human capriciousness. The thing I trusted most—predictability—had proven to be the least trustworthy.
So, I started the horoscope experiment. If even something as clearly absurd as a free, generalized online horoscope managed to be consistently unreliable, then maybe my fundamental reliance on perfect forecasts was flawed from the start. It was a strange kind of therapy.
The Final Data Dump and Conclusion
When I finally finished the 90-day cycle, the results were conclusive:
- Total Forecasts Tracked: 90
- Average Reliability Score (1-5): 2.9
- Highest Score (5): 4 instances (usually attributed to vague emotional warnings coinciding with minor annoyances).
- Lowest Score (1): 11 instances (predictions of financial gain or easy travel while the opposite occurred).
Frank Pilkington’s forecasts are exactly what they seem: generalized advice for a mass audience. They are not reliable in any measurable, practical sense. I wasted 90 days tracking something meaningless, but it helped me realize that reliability isn’t found in outside forecasts, but in the internal control you apply to the systems you build yourself. Never trust the forecast of someone else when your money is on the line. I learned that lesson the hard way, and now I share the data, even if it’s just about fake cosmic predictions.
