no code implementations • 5 Apr 2022 • Sergio Llana, Borja Burriel, Pau Madrero, Javier Fernández
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.
1 code implementation • 18 Jan 2021 • Javier Fumanal-Idocin, Yu-Kai Wang, Chin-Teng Lin, Javier Fernández, Jose Antonio Sanz, Humberto Bustince
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
1 code implementation • 20 Oct 2020 • Javier Fernández, Luke Bornn
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.
no code implementations • 15 Apr 2020 • Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández, Coloma Ballester, Gloria Haro
Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time.
no code implementations • 2 Mar 2020 • Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández, Carlos Rodríguez, Gloria Haro, Coloma Ballester
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.
no code implementations • 25 Sep 2019 • Javier Fernández, Luke Bornn
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.