We Have Built 14 Completely Automated Betting Strategies.
Here's What The First 1,000+ Bets Has Taught Us.
Most betting systems require constant attention. You’re glued to the screen, watching matches, waiting for the right moment to strike. It’s exhausting—and it’s a big reason why even good strategies fail. Life gets in the way.
So we asked ourselves a simple question: what if we could remove ourselves from the equation entirely?
Three weeks ago, we switched on 14 fully automated in-play betting strategies. They run 24/7 via BF Bot Manager on the Betfair Exchange. No fixture selection. No manual intervention. No second-guessing.
Just rules. Just execution. Just data.
What We Built
The portfolio consists of 14 distinct strategies, each designed to exploit specific in-play scenarios. They trigger based on combinations of:
Odds movements – Where the market sits at the moment of entry
Match statistics – Dangerous attacks, shots, corners, shots on target
Advanced metrics – xG, possession thresholds
Scoreline conditions – What the score is when we enter
Match timing – Which minute we’re in
We’re not revealing the specific thresholds—at least not yet.
Part of this project is validating whether these edges are real and sustainable.
But we thought it would be fun and interesting to share the journey with you.
The Results So Far
Since 26th January 2026, the portfolio has generated:
Total Bets: 1,022
Profit: +55.46 points
ROI: 5.4%
That’s an average of 49 bets per day across global football markets—leagues from Argentina to Australia, Portugal to Poland.
The equity curve hasn’t been a straight line. We’ve had drawdowns. We’ve questioned the approach. But the portfolio is in profit, and more importantly, we’re learning.
What We’re Testing
This isn’t about “does it win?”—at least, not only that. We’re investigating:
Edge validation – Are these profitable patterns or just variance?
Sample size requirements – How many bets before we trust the data?
Strategy correlation – Do certain strategies move together, or do they diversify risk?
Market efficiency – Are in-play markets genuinely inefficient, or are we chasing noise?
The honest answer is we don’t know yet. We have our theories supported by our internal data but three weeks and a thousand bets is a start—not a conclusion.
What’s Next?
Over the coming posts, we’ll break this down further:
Post 2: “Why These 14 Strategies?”
The logic behind each category—Goals Markets, Scoreline-Specific entries, Team Markets, Lay The Draw, and BTTS. What we’re trying to capture and why.
Post 3: “1,000 Bets Deep: Which Strategies Are Working”
A detailed breakdown of individual strategy performance. The winners, the grinders, and the underperformers. Early observations and what we’re watching.
Following this, we’ll continue publishing updates every 1-2 weeks as the data grows.
Why We’re Sharing This
Because betting content is usually one of two things: hype or hindsight.
We want to try something different—sharing the process in real-time, with full transparency on results. No cherry-picking. No glossing over drawdowns. Just the data, the reasoning, and the lessons.
Whether the portfolio succeeds or fails, we think there’s value in the journey.
Let’s see where 10,000 bets takes us.
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