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Found 6 papers, 2 papers with code
Is it worth the effort? Understanding and contextualizing physical metrics in soccer
We present a framework that gives a deep insight into the link between physical and technical-tactical aspects of soccer and it allows associating physical performance with value generation thanks to a top-down approach.
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
In BCI applications, the ElectroEncephaloGraphy is a very popular measurement for brain dynamics because of its non-invasive nature.
Ranked #1 on
EEG 4 classes
on BCI Competition IV 2a
SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer
We present a fully convolutional neural network architecture that is capable of estimating full probability surfaces of potential passes in soccer, derived from high-frequency spatiotemporal data.
Using Player's Body-Orientation to Model Pass Feasibility in Soccer
Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time.
Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players
Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analytics' research.
PassNet: Learning pass probability surfaces from single-location labels. An architecture for visually-interpretable soccer analytics
We propose a fully convolutional network architecture that is able to estimate a full surface of pass probabilities from single-location labels derived from high frequency spatio-temporal data of professional soccer matches.
