---
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):

```bash
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.