Mistake-based training

Train from your own chess mistakes after review

Start with a real game. Analyze it, save stable missed chances and blunders, then practice the position that actually happened.

Training comes from analyzed games
Missed opportunities and blunders stay separate
No generic puzzle pool is injected
Zero-position games stay honest

Review flow

Start with one game

These pages all lead back to the same place: import a game, review it, and use what the review found.

Step 1

Review a game

Open a recent game, PGN, file, or link in the analysis workspace.

Step 2

Find candidates

ChessIQ looks for missed chances and costly mistakes that have enough support.

Step 3

Save positions

Valid candidates become Training positions tied to the game they came from.

Step 4

Practice the lane

Start all positions or focus on missed opportunities or blunders.

Proof

Why this is different from generic tactics

The context is yours

Each saved position came from a game you reviewed, with the surrounding story still available.

It follows analysis truth

If candidate validation rejects every position, ChessIQ does not pretend training was created.

The lanes are practical

Missed opportunities help you find stronger moves; blunders help you recover costly mistakes.

The history stays connected

Training, Archive, and Statistics all read from the same local reviewed-game history.

Quick answers

Why not just call it puzzles?

The URL stays `/puzzles`, but the product role is Training from your reviewed games.

Can I start with no analyzed games?

You can open Training, but useful positions appear only after review creates them.

Are these random tactics?

No. ChessIQ does not seed a generic puzzle pool into this loop.

Why did one review create nothing?

Short, quiet, already-decided, or unsupported positions may not produce a stable training position.

Start

Bring in a game and review what changed it.

Create training from a game