Game Format

What the Stake Engine game format requires: static pre-computed simulation files, books in JSONL format, and lookup tables in CSV format.

Overview

Stake Engine requires games to consist entirely of static, pre-computed files. There is no server-side game logic executed at play time. All possible game outcomes must be generated ahead of time and stored in compressed files before a game can be published.

When a betting round is initiated, the RGS selects a simulation number at a frequency proportional to its weight in the lookup table, then returns the pre-computed events for that simulation through the play/ API. The math SDK handles generating all of these files from your game logic.

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Books format

Books are JSONL files (one JSON object per line) stored in library/books/ (uncompressed) or library/books_compressed/ (compressed). Each line represents a single simulation result, keyed by simulation ID.

Each simulation object has the following structure:

{
    "id": 58,
    "payoutMultiplier": 10,
    "events": [
        {
            "index": 0,
            "type": "reveal",
            "board": [...],
            "paddingPositions": [...],
            "gameType": "basegame",
            "anticipation": [...]
        },
        {
            "index": 1,
            "type": "winInfo",
            "totalWin": 10,
            "wins": [
                {
                    "symbol": "L5",
                    "kind": 3,
                    "win": 10,
                    "positions": [...],
                    "meta": {}
                }
            ]
        },
        {
            "index": 2,
            "type": "setWin",
            "amount": 10,
            "winLevel": 2
        },
        {
            "index": 3,
            "type": "setTotalWin",
            "amount": 10
        },
        {
            "index": 4,
            "type": "finalWin",
            "amount": 10
        }
    ],
    "criteria": "basegame",
    "baseGameWins": 0.1,
    "freeGameWins": 0.0
}

This example is simulation 58 from the 0_0_lines sample game. The events array tells the frontend which symbols to reveal, the winning positions and amounts, and how to update the win counters. The payoutMultiplier is the final payout amount for the round.

Each event has an index (its position in the sequence), a type string identifier, and additional fields carrying the state snapshot for that moment in the round.

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Lookup table format

Lookup tables are stored as CSV files in library/lookup_tables/. They summarise the payout for every simulation and are consumed by the optimization algorithm to adjust selection weights so the game achieves its target RTP.

Column	Type	Description
Simulation	int	Simulation number (matches the id in the books file)
Weight	int	Selection weight; all simulations start at 1 and are modified by the optimization algorithm
Payout	float	Final payout multiplier for the round

Example row: 58,1,10 — simulation 58, weight 1, payout multiplier 10×. This matches the payoutMultiplier value in the books file for the same simulation.

File naming follows the convention:

• lookUpTable_<mode>.csv — initial table generated by the simulator
• lookUpTable_<mode>_0.csv — optimized table with adjusted weights
• lookUpTableIdToCriteria_<mode>.csv — maps each simulation to its distribution criteria (e.g. max-win, 0-win, freegame)
• lookUpTableSegmented_<mode>.csv — breaks down which game type (basegame/freegame) contributed to the final payout

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The play/ API response

When a player initiates a round, the RGS:

1. Reads the lookup table for the active bet mode.
2. Selects a simulation number at random, weighted proportionally by each row’s Weight value.
3. Retrieves the corresponding entry from the books file.
4. Returns the events array in the API response body.

The frontend receives only the events array. It must handle every event type in the sequence to render the full round correctly.

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Compressed vs uncompressed format

The compression flag in run.py controls the output format:

Value	Output location	File extension	Use case
False	library/books/	.json	Development and debugging; human-readable
True	library/books_compressed/	.json.zst	Production; required for RGS publication

Running a large number of simulations (above 10,000) with compression = False will produce very large files and trigger a warning. Use uncompressed output only when inspecting simulation results during development.

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Publishing to the RGS

All files required for RGS publication are written to library/publish_files/. This folder contains the books, lookup tables, and an index file. Even if you generate your math results outside of this SDK, you must provide files in a compatible format in this folder structure to upload via the Admin Control Panel (ACP).