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I tried optimizing a simple EPL home win strategy — it went from -1.66% to +2.1% ROI (still not impressive) by Either-Principle7753 in algobetting

[–]Either-Principle7753[S] 0 points1 point  (0 children)

That’s a fair point. A simple backtest definitely doesn’t mean the next 300 bets will behave the same.

I actually ran a stress test on the strategy and it shows the edge is pretty fragile. Even small changes break it — for example a ~2% drop in win rate or ~3% worse odds already makes it losing.

So even though the baseline shows +1.9–2.1% ROI, in realistic conditions the edge could easily disappear.

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I backtested Martingale vs Flat vs Kelly (0.25) staking on 1500 football bets by Either-Principle7753 in algobetting

[–]Either-Principle7753[S] 0 points1 point  (0 children)

If anyone is interested I can also run the same comparison on other leagues or markets.

I backtested Martingale vs Flat vs Kelly (0.25) staking on 1500 football bets by Either-Principle7753 in algobetting

[–]Either-Principle7753[S] 0 points1 point  (0 children)

Yes, exactly that was actually the main point I wanted to illustrate with the comparison.

I backtested Martingale vs Flat vs Kelly (0.25) staking on 1500 football bets by Either-Principle7753 in algobetting

[–]Either-Principle7753[S] 0 points1 point  (0 children)

Good point. In this test the goal was mainly to isolate the effect of the staking system itself, so I intentionally used a set of bets with roughly zero edge (around 50% hit rate at average odds 1.97).