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userr99
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ffa-v0.1

Tasks:
Time Series Forecasting
Size:
n<1K
Tags:
forecasting
benchmark
time-series
llm-evaluation
License:
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FFA v0.1 — anonymized items (no truth)
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metadata 
license: other
task_categories:
  - time-series-forecasting
tags:
  - forecasting
  - benchmark
  - time-series
  - llm-evaluation
pretty_name: Frontier Forecasting Arena (FFA) v0.1
size_categories:
  - n<1K

Frontier Forecasting Arena (FFA) — v0.1 (items only)

Anonymized, answer-free evaluation items for the Frontier Forecasting Arena, a historical-replay benchmark that measures forecasting skill with proper scoring rules and is designed so that memorization is measurable rather than assumed away.

This dataset contains the model-facing items only — no ground truth. Skill is verified by the maintainer against held-out truth. That split is the whole point: no real date, absolute level, station, or year ships to a model, so answers can't be looked up or memorized.

Contents

File Arm Items Unit
energy/items.jsonl Energy load 50 168h history + 24h future drivers → 24×(q10,q50,q90)
synthetic/items.jsonl Synthetic (DGP) 50 contamination-proof floor
kalshi/items.jsonl Kalshi weather 50 settled-market snapshot ladder
crypto/items.jsonl Crypto 50 hourly panel → forward window
stock/items.jsonl Stock 50 daily panel → forward window

Each line is one JSON item with a compact columns + packed-row encoding.

How to run it

Use the FFA CLI (code: https://github.com/steves-brain/ffa-benchmark):

huggingface-cli download userr99/ffa-v0.1 --repo-type dataset --local-dir ffa-v0.1
ffa predict --dataset ffa-v0.1 --out submissions/<your-name> \
  --provider openai-compatible --base-url http://localhost:11434/v1 \
  --model <your-model> --harness Ollama --dataset-version v0.1

ffa predict never sees the answers. Send the resulting submission back (see CONTRIBUTING-SUBMISSIONS.md in the GitHub repo) to be scored against private truth and added to the leaderboard.

Scoring spine

CRPS for the continuous arms, Brier/log-loss for binary. Never a single blended skill number — skill is a per-arm vector; only calibration aggregates across arms.

License

See the repository for terms. Built from free public data (EIA, NOAA/NWS, Kalshi, public crypto/stock markets), anonymized.