---
pretty_name: Player-1-Data
language:
- en
task_categories:
- image-text-to-text
tags:
- gaming
- imitation-learning
- keyboard-mouse-control
size_categories:
- 1K<n<10K
license: other
license_name: source-dependent
license_link: https://huggingface.co/datasets/yyyang/Player-1-Data/blob/main/SOURCES.md
configs:
- config_name: default
  data_files:
  - split: train
    path: data/*.json
dataset_info:
  features:
  - name: id
    dtype: string
  - name: game
    dtype: string
  - name: mode
    dtype: string
  - name: source
    struct:
    - name: recording_id
      dtype: string
    - name: action_clock
      dtype: string
    - name: action_interval_ns
      list: int64
    - name: observation_span_ns
      list: int64
    - name: raw_operation_clock
      dtype: string
  - name: issues
    list: string
  - name: initial_messages
    list:
    - name: role
      dtype: string
    - name: content
      dtype: string
  - name: observation_prompt
    dtype: string
  - name: turns
    list:
    - name: image
      dtype: string
    - name: reasoning
      dtype: string
    - name: action
      dtype: string
    - name: source
      struct:
      - name: action_interval_ns
        list: int64
      - name: observation_time_ns
        dtype: int64
      - name: frame_index
        dtype: int64
      - name: raw_operation_interval_ns
        list: int64
---

# Player-1-Data

Player-1-Data is a collection of gameplay demonstrations for training game-control agents. It contains **6,044 trajectories and 295,207 turns**, including gameplay and in-game GUI interactions. Each turn pairs a screenshot with reasoning and a keyboard/mouse action.

The dataset is part of [Player-1: Learning to Play from Synthetic Experience](https://player-1-project.github.io/); see the [paper](https://player-1-project.github.io/assets/player-1.pdf) for the overall method.

## Contents

| File | Description |
| --- | --- |
| `data/<trajectory_id>.json` | One trajectory per file |
| `images/<trajectory_id>/` | Screenshots referenced by the trajectory |
| `recordings.jsonl` | Source recording and session references |
| `SOURCES.md` | Source links and usage terms |
| `to_parquet.py` | Converter to the SFT training format |

Each trajectory has a `id`, `game`, `mode`, source information, initial messages and ordered `turns`. A turn contains `image`, `reasoning`, `action` and source timing information. Image paths are relative to `images/`. Turns are stored individually; a reader can assemble history as needed.

## Sources

The trajectories come from five recording sources:

| Source | Trajectories |
| --- | ---: |
| GameHorizon Suite | 1,761 |
| D2E | 1,005 |
| Gaming500 | 985 |
| Pixel2Play | 1,140 |
| VPT | 1,153 |

`recordings.jsonl` connects trajectories to their original sessions and filenames. Original recordings are not included. The action and video timestamps may use different clocks; use the declared clock and frame index when relating them. See [SOURCES.md](SOURCES.md) for source links and license terms; source and third-party game-content terms apply.

## Read a trajectory

```python
import json
from pathlib import Path

root = Path("/path/to/Player-1-Data")
trajectory = json.loads(next((root / "data").glob("*.json")).read_text(encoding="utf-8"))
turn = trajectory["turns"][0]
image_path = root / "images" / turn["image"]
print(trajectory["game"], image_path, turn["reasoning"], turn["action"])
```

## Training format

Convert the file tree into training Parquet and images using:

```bash
python /path/to/Player-1-Data/to_parquet.py --output /path/to/output
```

The output contains one Parquet row group per trajectory.

## Citation

```bibtex
@misc{ouyang2026player1learningplaysynthetic,
      title={Player-1: Learning to Play from Synthetic Experience}, 
      author={Mingyu Ouyang and Yiran Wang and Siyuan Hu and Xingyilang Yin and Huiqiang Sun and Guangzhi Wang and Junfu Pu and Cheng Cheng and Honghao Chen and Ying Shan and Mike Zheng Shou and Hwee Tou Ng},
      year={2026},
      eprint={2610.20584},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2610.20584}, 
}
```