Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find any data file at /src/services/worker/edushinka/market-calibration. Couldn't find 'edushinka/market-calibration' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/edushinka/market-calibration@4865835d4dcf5e6f09cd479ba169016dadf9e7e2/betbetter_market_calibration.csv' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.conll', '.conllu', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.tsfile', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.3gp', '.3g2', '.avi', '.asf', '.flv', '.mp4', '.mov', '.m4v', '.mkv', '.webm', '.f4v', '.wmv', '.wma', '.ogm', '.mxf', '.nut', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.3GP', '.3G2', '.AVI', '.ASF', '.FLV', '.MP4', '.MOV', '.M4V', '.MKV', '.WEBM', '.F4V', '.WMV', '.WMA', '.OGM', '.MXF', '.NUT', '.glb', '.ply', '.stl', '.GLB', '.PLY', '.STL', '.pdf', '.PDF', '.nii', '.NII', '.zip', '.idx', '.manifest', '.txn']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                      path=dataset,
                      token=hf_token,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                      path,
                  ...<4 lines>...
                      **download_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1213, in dataset_module_factory
                  raise FileNotFoundError(
                  ...<2 lines>...
                  ) from None
              FileNotFoundError: Couldn't find any data file at /src/services/worker/edushinka/market-calibration. Couldn't find 'edushinka/market-calibration' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/edushinka/market-calibration@4865835d4dcf5e6f09cd479ba169016dadf9e7e2/betbetter_market_calibration.csv' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.conll', '.conllu', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.tsfile', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.3gp', '.3g2', '.avi', '.asf', '.flv', '.mp4', '.mov', '.m4v', '.mkv', '.webm', '.f4v', '.wmv', '.wma', '.ogm', '.mxf', '.nut', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.3GP', '.3G2', '.AVI', '.ASF', '.FLV', '.MP4', '.MOV', '.M4V', '.MKV', '.WEBM', '.F4V', '.WMV', '.WMA', '.OGM', '.MXF', '.NUT', '.glb', '.ply', '.stl', '.GLB', '.PLY', '.STL', '.pdf', '.PDF', '.nii', '.NII', '.zip', '.idx', '.manifest', '.txn']

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Market Calibration Dataset — de-vigged betting probabilities vs real outcomes

36,476 outcome observations (both sides of 18,238 settled two-outcome betting markets) across five sports: each row is a vig-free market-implied probability and whether the outcome happened. A modern, multi-sport dataset for studying market calibration and the favourite–longshot bias — a literature that still leans heavily on decades-old horse-racing data.


Rows	36,476 (both sides of every market — the dataset nets to 0.500/0.500 by construction)
Markets	18,238 settled two-outcome markets
Sports	5 (soccer, baseball, basketball, ice hockey, Australian rules)
Period	November 2024 – July 2026 (month granularity)
Licence	CC BY 4.0

Columns

Column	Meaning
`event_month`	Month the event was played (YYYY-MM)
`sport`	Sport key
`market_family`	`game line` (match-level markets) or `player prop`
`market_implied_probability`	The outcome's de-vigged market-implied probability (vig removed across the market's outcomes), rounded to 3 dp
`outcome`	1 if the outcome occurred, 0 otherwise

Construction — read before analysing

Both sides of every market are included. For every observed outcome at probability p, its complement appears at 1−p with the opposite result. The dataset therefore nets to exactly 0.500/0.500 overall, and calibration deviations appear as an antisymmetric curve. This is the standard construction for bias analysis and means the dataset carries no information about any bettor's or model's selections — only about the market itself.
Probabilities are de-vigged, not raw. Raw implied probabilities contain the bookmaker's margin; these have had it removed across the market's outcomes. Note that de-vig method choice affects how margin is allocated across the probability range — a caveat relevant to interpreting tail behaviour, and itself a research-worthy question the data supports.
Sampling: markets are those covered by an analytics pipeline across five sports; within a market, inclusion of both sides is complete by construction. Rows carry no event, team, player, bookmaker or exact-date identifiers and cannot be mapped to any individual market or price.

Headline findings

Betting markets are impressively well calibrated: across every probability decile, real outcome frequencies track de-vigged implied probabilities within about ±2 percentage points.
A small, systematic tilt survives vig removal: outcomes priced below ~50% slightly overperform their vig-free probabilities (+1 to +2 points) while favourites slightly underperform — consistent with bookmakers loading their margin most heavily onto longshot prices. In raw (vigged) prices this manifests as the classic favourite–longshot bias.
Player-prop markets show a larger tilt than match-level markets, peaking around the 30–40% / 60–70% probability bands (±5 points).

Licence and citation

CC BY 4.0 — free to use, including commercially, with attribution.

Bet Better (2026). Market Calibration Dataset: de-vigged betting probabilities vs outcomes, 36,476 observations. https://betbetter.world/studies/market-calibration

Maintained by Bet Better, which also publishes the Bookmaker Margin Panel, a free sports model API and an open AFL dataset.

No odds, prices, bookmaker identities or wagering data are included. 18+. Most people lose money gambling. If gambling is causing you harm: gamblinghelponline.org.au.

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