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I’ll answer this from a screen-time perspective, not theory. The biggest shift for me with session-based models was accepting that some days simply don’t offer the “clean narrative.” If London is choppy and doesn’t clearly manipulate liquidity, I don’t try to force the PO3 framework onto the day. Some sessions just rotate. Those are usually reduced-size or no-trade days. Trying to make every day fit the model is where most people start bleeding. On the timeframe question, 15m liquidity is fine for bias and context. Dropping to 1m/5m can improve R:R, but it also increases noise and execution errors. Lower timeframes magnify psychological mistakes. If your rules aren’t rock solid yet, 15m + a clean confirmation is often more consistent than hunting micro MSS entries. If you’re serious about making it mechanical, I’d suggest defining:

• Exact time windows you’re allowed to trade

• Maximum trades per session

• What invalidates the day completely

Most consistency doesn’t come from refining entries, but from filtering days. Backtesting sessions over at least 3–6 months will give you a much clearer answer than tweaking after one choppy week.

The simpler your strategy the better. There is a lot of noise when it comes ICT and gets very convoluted when trying to implement in practice. Stick to the high priority factors: 2-3 at most. Check out my bio if you want pure practical execution. No theory.