---
license: other
language:
- en
tags:
- prediction-markets
- finance
- time-series
- polymarket
- manifold
- ohlcv
- event-contracts
pretty_name: ImpliedData Prediction Markets Sample
size_categories:
- 100K<n<1M
task_categories:
- time-series-forecasting
- tabular-classification
---

# Prediction Markets Dataset

Historical market metadata and 1-hour OHLCV candle data from two prediction market platforms: Polymarket and Manifold Markets. Collected and maintained by [ImpliedData](https://implieddata.com).

## Files

| File | Description | Rows |
|------|-------------|------|
| `markets_metadata.parquet` | Full market catalog — titles, categories, statuses, dates | ~8.2M |
| `polymarket_ohlcv_1h_sample.parquet` | 1h OHLCV, top 70 Polymarket markets by volume, last 6 months | ~80K |
| `manifold_ohlcv_1h_sample.parquet` | 1h OHLCV, top 60 Manifold markets by volume, last 6 months | ~50K |

> **Note:** `markets_metadata.parquet` includes Kalshi market titles and categories (publicly listed on their website) for research purposes. No Kalshi price or trade data is included in this release.

## Schema

### markets_metadata.parquet

All ~8.2M markets collected across platforms. No price data — catalog only.

| Column | Type | Description |
|--------|------|-------------|
| `market_id` | string | Platform-native identifier |
| `title` | string | Market question text |
| `platform` | string | `polymarket`, `kalshi`, or `manifold` |
| `category` | string | Topic category (politics, crypto, sports, etc.) |
| `status` | string | `open`, `resolved`, `closed`, or `cancelled` |
| `resolution` | string | Outcome if resolved — YES/NO or numeric |
| `opened` | date | Date the market was created |
| `closes` | date | Resolution date, if known |
| `trader_count` | int | Unique traders (null for a portion of markets) |

### *_ohlcv_1h_sample.parquet

One row per market per hour.

| Column | Type | Description |
|--------|------|-------------|
| `timestamp` | datetime (UTC) | Candle open time |
| `market_id` | int | Internal market ID — join with metadata via platform |
| `platform_id` | int | 1 = Polymarket, 3 = Manifold |
| `open` | float | Opening probability (0–1) |
| `high` | float | Highest probability in the hour |
| `low` | float | Lowest probability in the hour |
| `close` | float | Closing probability (0–1) |
| `volume` | float | Total traded volume in the hour |
| `trade_count` | int | Number of trades in the hour |

Prices are implied probabilities, not dollar amounts. A value of 0.73 means the market was pricing the event at 73% probability at candle open.

**Manifold:** Uses play money, not real money. Prices reflect crowd probability estimates but the incentive structure differs from real-money markets. Volume is in Mana (MANA), not USD.

## Platform coverage

| Platform | Markets | Trade records | Date range |
|----------|---------|---------------|------------|
| Polymarket | ~120K | 14.8M | Oct 2020 – present |
| Manifold | ~111K | 5.0M | Feb 2023 – present |

## Loading the data

```python
import pandas as pd

# Market catalog
markets = pd.read_parquet("markets_metadata.parquet")
print(f"{len(markets):,} markets")
print(markets.groupby("platform")["status"].value_counts())

# Polymarket OHLCV candles
candles = pd.read_parquet("polymarket_ohlcv_1h_sample.parquet")
candles["timestamp"] = pd.to_datetime(candles["timestamp"])

# Most active market in the sample
top_id = candles["market_id"].value_counts().index[0]
m = candles[candles["market_id"] == top_id].sort_values("timestamp")
print(m[["timestamp", "close", "volume"]].tail(20))
```

```python
# Load via HuggingFace datasets library
from datasets import load_dataset

ds = load_dataset("ImpliedData/prediction-markets", data_files="polymarket_ohlcv_1h_sample.parquet")
```

## Known limitations

- OHLCV files cover ~130 markets total (top by trade volume). Low-volume markets are not in this release.
- OHLCV date range is limited to the past 6 months. Full histories are available in the [ImpliedData](https://implieddata.com) paid dataset.
- `trader_count` is null for a significant share of markets.
- Manifold data before February 2023 is sparse.

## Full dataset

The complete dataset — all platforms, full trade history, intraday (1m/5m/15m) candles, and continuous updates — is available at [implieddata.com](https://implieddata.com).

## Citation

```bibtex
@dataset{implieddata2026,
  title     = {ImpliedData Prediction Markets Dataset},
  author    = {ImpliedData},
  year      = {2026},
  url       = {https://huggingface.co/datasets/ImpliedData/prediction-markets},
  note      = {Historical trade data from Polymarket and Manifold Markets}
}
```

## License

Underlying market data originates from Polymarket and Manifold Markets and is subject to each platform's terms of service. The schema, documentation, and normalisation methodology are the work of ImpliedData (implieddata.com). This dataset is made available for research purposes only.