datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SportsSlomo-CVS
🎥 SportsSloMo-CVS Dataset
This repository contains the dataset presented in the paper Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor.
The Complementary Vision Sensor (CVS), known as Tianmouc, captures synchronized RGB frames together with high-frame-rate, multi-bit spatial difference (SD, encoding structural edges) and temporal difference (TD, encoding motion cues) data within a single RGB exposure. This dataset facilitates research in RGB… See the full description on the dataset page: https://huggingface.co/datasets/mypThu/SportsSlomo-CVS.sports-calendar
Sports Calendar Feeds
Public calendar and scoreboard artifacts for MLB, NHL, NFL, College Football
(NCAA Division I), the English Premier League, and selected men's cricket
competitions.
The feeds update on a deterministic four-hour GitHub Actions schedule. Calendar
events are transparent (Free), use stable first-party UIDs, update completed
games with final scores, and mark called-off fixtures as cancelled.
For normal calendar use, choose the Daily Scoreboard feed. It condenses… See the full description on the dataset page: https://huggingface.co/datasets/karunapu/sports-calendar.sports-trends-dataset
⚽🏀🎾🏏 Sports-Trends Dataset
A leakage-safe, multi-sport match data lake — raw fixtures → engineered features → training splits.
The data backbone of Ruslan Magana Sports Intelligence — refreshed automatically every day.
TL;DR — A continuously-updated, medallion-architecture data lake for football,
basketball, tennis and cricket: immutable raw ingests, cleaned/standardized layers, an
engineered feature store, and ready-to-train chronological splits in… See the full description on the dataset page: https://huggingface.co/datasets/ruslanmv/sports-trends-dataset.sportsmot
SportsMOT
SportsMOT is a large-scale dataset for single-camera multi-object tracking (MOT) in sports videos. It focuses on tracking players in professional sports scenes, where targets exhibit fast and variable-speed motion, frequent occlusion, motion blur, camera motion, and similar team uniforms.
This Hugging Face repository provides SportsMOT in a MOTChallenge-style structure for research, benchmarking, training, and evaluation of multi-object tracking systems in sports… See the full description on the dataset page: https://huggingface.co/datasets/Lekim89/sportsmot.SportsTime
SportsTime
SportsTime is a long-form sports video question answering benchmark for temporal compositional reasoning, accepted to ECCV 2026.
It contains 14,326 open-ended QA pairs with 50,000+ step-wise temporal evidence annotations across 1,575 videos and five team sports: basketball, American football, ice hockey, soccer, and volleyball.
Dataset
This Hugging Face dataset repository provides the annotation files, official train/test split, and video files.… See the full description on the dataset page: https://huggingface.co/datasets/Ustiniansy/SportsTime.SportsMOT
Dataset Card for SportsMOT
Dataset Details
Dataset Description
Multi-object tracking (MOT) is a fundamental task in computer vision, aiming to estimate objects (e.g., pedestrians and vehicles) bounding boxes and identities in video sequences. We propose a large-scale multi-object tracking dataset named SportsMOT, consisting of 240 video clips from 3 categories (i.e., basketball, football and volleyball). The objective is to only track players on the… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/SportsMOT.sportsd
SportsD: On-Ball Soccer Decision Benchmark
SportsD tests whether a vision-language model picks better on-ball soccer actions than
professional players did, using possession-value (VAEP) ground truth from two World Cups.
Each event freezes a real on-ball moment. The model sees the seconds before the moment
and picks one action: a pass to a specific lettered teammate, or a shot. Every
candidate action has a VAEP expected value, so every answer gets a real value score.
1421… See the full description on the dataset page: https://huggingface.co/datasets/addisonwu05/sportsd.sports-cards
Digital Card Magazine Dataset
This dataset contains sports card images and their associated metadata for training machine learning models in card recognition, text extraction, and value estimation.
Dataset Description
Dataset Summary
A comprehensive collection of sports card images and metadata, including:
Front and back card images
OCR-extracted text with confidence scores
AI-analyzed card attributes
Card details (player, team, year, etc.)
Vision API labels… See the full description on the dataset page: https://huggingface.co/datasets/GotThatData/sports-cards.SportsAction
Dataset Card for MultiSports
Dataset Summary
Spatio-temporal action localization is an important and challenging problem in video understanding. Previous action detection benchmarks are limited in aspects of small numbers of instances in a trimmed video or low-level atomic actions. MultiSports is a multi-person dataset of spatio-temporal localized sports actions. Please refer to this paper for more details. Please refer to this repository for evaluation.… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/SportsAction.SportsHHI
Dataset Card for SportsHHI
Dataset Summary
SportsHHI is a dataset for video human-human interaction detection. Please refer to SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos for more details. Please refer to this repository for training and evaluation.
Supported Tasks and Leaderboards
Human-Human Interaction Detection
Details about training and evaluation can be found in the GitHub Repository.
Languages
The class labels… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/SportsHHI.nangang_sports_centersportsbookish-daily-odds
SportsBookISH Daily Kalshi vs Sportsbook Odds
Real-time pricing snapshot comparing Kalshi event-contract probabilities against US sportsbook consensus across nine sports.
Description
Daily-refreshed JSON / CSV export of every active Kalshi market alongside the de-vigged book median across 13+ US sportsbooks. Covers golf (PGA Tour), NFL, NBA, MLB, NHL, EPL, MLS, UEFA Champions League, and FIFA World Cup.
Source
Live data plane:
JSON:… See the full description on the dataset page: https://huggingface.co/datasets/kennyhyder/sportsbookish-daily-odds.sportsett_basketballSportSett:Basketball dataset for Data-to-Text Generation contains NBA games stats aligned with their human written summaries.sportsmot
SportsMOT
SportsMOT is a large-scale dataset for single-camera multi-object tracking (MOT) in sports videos. It focuses on tracking players in professional sports scenes, where targets exhibit fast and variable-speed motion, frequent occlusion, motion blur, camera motion, and similar team uniforms.
This Hugging Face repository provides SportsMOT in a MOTChallenge-style structure for research, benchmarking, training, and evaluation of multi-object tracking systems in sports… See the full description on the dataset page: https://huggingface.co/datasets/Hellfire98/sportsmot.Sports-QAVideos in the Sports-QA dataset proposed in "Sports-QA: A Large-Scale Video Question Answering Benchmark for Complex and Professional Sports".
Detials can be found at the Github page
IndustryCorpus_sports[中文主页]
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus_sports.sport-statisticsLast updated 2026‑09‑21: added results from Round 5 of the English Premier League.
Football Match Data
This dataset provides rich statistical coverage of recent English Premier
League seasons, including detailed match statistics such as ball possession,
corner kicks, yellow and red cards, set pieces, and more.
For additional data or custom requests, please reach out to
team@gamblistics.com — we are happy to share whatever we can.
Match-level, team-level, and player-level… See the full description on the dataset page: https://huggingface.co/datasets/gamblistics-lab/sport-statistics.Leeds_Sports_PoseSince the official website of this dataset is down, I re-upload the dataset to make it publicly accessible.
If there are any violation of license or personal benefits, please contact me and I will quickly take actions.
The original verison of README file is provided below.
Leeds Sports Pose Dataset
Sam Johnson and Mark Everingham
http://sam.johnson.io/research/lsp.html
This dataset contains 2000 images of mostly sports people
gathered from Flickr. The images have been scaled such that the… See the full description on the dataset page: https://huggingface.co/datasets/LiuRunky/Leeds_Sports_Pose.ramanv-image-sports-fitnessSportsMOT-L@article{li2024multi,
title={Multi-Granularity Language-Guided Training for Multi-Object Tracking},
author={Li, Yuhao and Cao, Jiale and Naseer, Muzammal and Zhu, Yu and Sun, Jinqiu and Zhang, Yanning and Khan, Fahad Shahbaz},
journal={arXiv preprint arXiv:2406.04844},
year={2024}
}
Amazon_Sports_and_Outdoors_2023
Dataset Card for Dataset Name
Original dataset can be found on: https://amazon-reviews-2023.github.io/
Dataset Details
This dataset is downloaded from the link above, the category Sports and Outdoors meta dataset.
Dataset Description
This dataset is a refined version of the Amazon Sports and Outdoors 2023 meta dataset, which originally contained product metadata for sports and outdoors products that are sold on Amazon. The dataset includes detailed information… See the full description on the dataset page: https://huggingface.co/datasets/smartcat/Amazon_Sports_and_Outdoors_2023.IndustryCorpus2_sports
IndustryCorpus2: Sports
This repository contains the IndustryCorpus2: Sports domain subset of BAAI/IndustryCorpus2.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryCorpus2:
@misc{shi2024industrycorpus2,
title = {IndustryCorpus2},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin Hao},
year = {2024},
publisher… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus2_sports.Xiang_Wan_BindWeave_KJ_sports_Qwen_Image_4_bind_imagessports_15_AUGball-sports-video-v1
Ball Sports Key Action Video Preview
This is a small preview of four sports videos from the Thordata Ball Sports Key Action product:
basketball: shooting
tennis: hitting
soccer: shooting
soccer: interception
The product listing states that the source collection is 1080p or higher, has no logos, subtitles, mosaics, watermarks, black borders, or noise, and includes metadata. The files in this package are the marketplace preview copies, which are lower-resolution preview encodes;… See the full description on the dataset page: https://huggingface.co/datasets/thordata/ball-sports-video-v1.Akai_Sports_Video_Captions_v1
Akai Sports Video Captions · v1
1,119 sports video clips with expert-reviewed English captions for captioning, retrieval, and multimodal modeling. Video was contributed to Akai Space Labs by contributors; captions were authored and reviewed by Akai labelers.
Preview
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Akaispacelabs/Akai_Sports_Video_Captions_v1.SportsMOT
Dataset Card for SportsMOT
Dataset Details
Dataset Description
Multi-object tracking (MOT) is a fundamental task in computer vision, aiming to estimate objects (e.g., pedestrians and vehicles) bounding boxes and identities in video sequences. We propose a large-scale multi-object tracking dataset named SportsMOT, consisting of 240 video clips from 3 categories (i.e., basketball, football and volleyball). The objective is to only track players on… See the full description on the dataset page: https://huggingface.co/datasets/caihongtang/SportsMOT.Amazon_Sports_and_Outdoors_2014
Amazon Sports & Outdoors Dataset
Directory Structure
metadata: Contains product information.
reviews: Contains user reviews about the products.
filtered:
e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include… See the full description on the dataset page: https://huggingface.co/datasets/milistu/Amazon_Sports_and_Outdoors_2014.Blue_Sports_Boy_Videos_SplitedSportsQA_FineGym