The whole live-poker workflow.

What the feature set is meant to answer

The features are grouped around the way a serious live player actually improves. First, capture the session with as little friction as possible. Then read the result in context: stake, venue, rake, tips, hours, variance and bankroll. Then turn the session into study by marking hands, tagging leaks and writing a next action while the details are still fresh. If a feature does not support that loop, it is decoration, and decoration does not earn a place in a tracker.

That is why the toolkit looks different from a HUD or solver. Live cash does not create a hand-history feed, and it does not give reliable opponent frequencies at online speed. What it does give you is repeated exposure to the same rooms, the same regulars, the same fatigue patterns and the same bankroll decisions. Overshove is built for those signals: private notes on the player pool, session-length leaks, true hourly by room, confidence on your win rate, and the choice to move up only when the bankroll and sample both support it.

The import and export features are part of the same argument. Your sample is the asset. A tracker should help you build it, read it and leave with it if you ever need to. CSV import protects the history you already earned in a spreadsheet or older app. CSV export keeps Overshove honest, because the data has to remain useful outside the product.

A good way to read this page is by decision type. If the decision is whether to play longer, look at session length, readiness and stop-loss support. If the decision is whether to change stakes, look at bankroll, variance and move-up readiness. If the decision is what to study, look at marked hands, leak tags, player notes and the coach pack. If the decision is whether to trust the tracker at all, look at import, export and the private data model.

The feature set is intentionally opinionated. It favours repeatable review over novelty, clear numbers over dramatic dashboards, and private notes over public bragging. Live cash players already get enough noise from short samples and emotional sessions. The product should make the next decision cleaner, or it should stay out of the way.

If you are new to tracking, start with sessions and bankroll only. Add variance once the sample has enough hours to make the band meaningful. Add the study log when the same mistake appears twice. Add the reads notebook when you notice the same player pattern repeating. The workflow can grow slowly, but the sample should be complete from day one.

That slow adoption path is deliberate. A player should never feel forced to fill out every tool before saving a session. The core log stays simple, and the deeper features are there when the sample starts asking harder questions.