Sports Analytics

17 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Sports Analytics models and implementations

Most implemented papers

Sports Camera Calibration via Synthetic Data

lood339/SCCvSD 25 Oct 2018

Here we propose a highly automatic method for calibrating sports cameras from a single image using synthetic data.

Applying Deep Learning to Basketball Trajectories

RobRomijnders/RNN_basketball 12 Aug 2016

Using a dataset of over 20, 000 three pointers from NBA SportVu data, the models based simply on sequential positional data outperform a static feature rich machine learning model in predicting whether a three-point shot is successful.

Cracking the Black Box: Distilling Deep Sports Analytics

xiangyu-sun-789/Cracking-the-Black-Box-Distilling-Deep-Sports-Analytics 4 Jun 2020

This paper addresses the trade-off between Accuracy and Transparency for deep learning applied to sports analytics.

From Motor Control to Team Play in Simulated Humanoid Football

deepmind/dm_control 25 May 2021

In a sequence of stages, players first learn to control a fully articulated body to perform realistic, human-like movements such as running and turning; they then acquire mid-level football skills such as dribbling and shooting; finally, they develop awareness of others and play as a team, bridging the gap between low-level motor control at a timescale of milliseconds, and coordinated goal-directed behaviour as a team at the timescale of tens of seconds.

Unsupervised Learning of Neurosymbolic Encoders

ezhan94/neurosymbolic-encoders 28 Jul 2021

We present a framework for the unsupervised learning of neurosymbolic encoders, which are encoders obtained by composing neural networks with symbolic programs from a domain-specific language.

DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes

ispgroupucl/deepsportlab 1 Dec 2021

In addition to the increased complexity resulting from the multiplication of single-task models, the use of the off-the-shelf models also impedes the performance due to the complexity and specificity of the team sports scenes, such as strong occlusion and motion blur.

LTC-GIF: Attracting More Clicks on Feature-length Sports Videos

iamgmujtaba/ltc-gif 22 Jan 2022

This paper proposes a lightweight method to attract users and increase views of the video by presenting personalized artistic media -- i. e, static thumbnails and animated GIFs.

SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning

nilakshdas/skelevision 2 Apr 2022

Person tracking using computer vision techniques has wide ranging applications such as autonomous driving, home security and sports analytics.

A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications

paddlepaddle/paddlevideo 2 Jun 2022

Finally, we discuss the challenges and unsolved problems in this area and to facilitate sports analytics, we develop a toolbox using PaddlePaddle, which supports football, basketball, table tennis and figure skating action recognition.

Client-driven Lightweight Method to Generate Artistic Media for Feature-length Sports Videos

iamgmujtaba/ltc-gif Conference 2022

This paper proposes a lightweight methodology to attract users and increase views of videos through personalized artistic media i. e., static thumbnails and animated Graphics Interchange Format (GIF) images.