Rocket League © Psyonix LLC / Epic Games, Inc. Rocket League and its logo are trademarks of Psyonix LLC. The Rocket League gameplay recordings in this dataset are used and distributed with Epic Games' permission. This dataset is licensed under CC BY-NC-SA 4.0. Per Section 2(b)(2) of that license, no trademark, publicity, or other rights are granted beyond the copyright license to this dataset. Commercial use of Rocket League content requires separate permission from Epic Games. This dataset and the associated research are not an Epic Games product. All gameplay was generated by bots in private matches; the dataset contains no human player data. You must accept these terms to access the dataset.

Rocket Science

Time-aligned video, keyboard actions, game events, and per-frame game state for all four players, captured from a 2v2 Rocket League match.

This is the dataset behind MIRA, a real-time multiplayer world model trained to simulate Rocket League gameplay — by General Intuition and Kyutai, in collaboration with Epic Games. Code, technical report, and a live demo: github.com/mira-wm/mira · mira-wm.com.

Loading

from mira.data import RocketScienceDataset

ds = RocketScienceDataset.from_hub("kyutai/rocket-science", split="test")
clip = ds.load_match(ds.match_ids()[0], clip_len=16, target_fps=10)[0]

Install the loader with pip install "mira[hf,decode] @ git+https://github.com/mira-wm/mira" (provide your own torch + a compatible FFmpeg), or use the repo's pixi environment.

What's in a sample

One sample is a short (~4 s, 80 frames at 20 fps) window of a match with all four players' synchronised views. A clip is a fixed-length, fps-downsampled slice read from one. For each clip, per perspective:

frames — (P, T, C, H, W) uint8 video (1280×720), one decoded view per perspective.
actions — (P, T, 9) int32 multi-hot keyboard over a fixed key set (W A S D Q E Space LShiftKey LControlKey), OR-ed over each downsample window so it stays frame-aligned.
events — discrete game events (KickoffStarted/Ended, GoalScored, Demolition, GoalReplayStarted/Ended, …) on a single match-wide master clock, mapped onto each perspective's frames via its recording_offset_sec. exclude_replays=True skips clips overlapping goal replays.
physics — per-frame game state, one list of FrameState dicts per perspective, frame-aligned with the video: the ball, the four cars, and the game info (score, overtime, clock). See mira.data.state for the typed field layout.

Perspectives are ordered by player_id; clip.teams gives each one's team (0 / 1). The video is H.264, 1280×720 at 20 fps, no audio.

Layout

kyutai/rocket-science
├── test/
│   ├── index.json          # per-match index: shard path, perspectives, chunk frame counts
│   └── dataset_*.tar       # WebDataset shards
└── train/
    ├── index.json
    └── 000/ … 015/         # shards in numbered subfolders of ≤1,000 files
        └── dataset_*.tar

Split	Matches	Chunks	Shards	Size
train	15,769	1,792,926	15,274	~27 TB
test	62	7,187	61	~109 GB

Each WebDataset sample is one ~4 s chunk of one match (key {match_id}_c{chunk:05d}), bundling all four perspectives: p{i}.mp4 (video), p{i}.jsonl (actions), p{i}.physics.jsonl (game state, one JSON line per frame), and meta.json (match_id, chunk, player_ids, teams). The loader resolves shards through index.json, so the train subfolders are transparent; any WebDataset-aware pipeline works too, e.g. datasets.load_dataset("webdataset", data_files="hf://datasets/kyutai/rocket-science/train/*/*.tar") (for test: .../test/*.tar).

License & attribution

Licensed under CC BY-NC-SA 4.0. Per Section 2(b)(2), no trademark, publicity, or other rights are granted beyond the copyright license to this dataset; commercial use of Rocket League content requires separate permission from Epic Games. This dataset and the associated research are not an Epic Games product. All gameplay was generated by bots in private matches; the dataset contains no human player data.

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