soccer


Machine learning predicts World Cup winner

#artificialintelligence

The random-forest technique has emerged in recent years as a powerful way to analyze large data sets while avoiding some of the pitfalls of other data-mining methods. It is based on the idea that some future event can be determined by a decision tree in which an outcome is calculated at each branch by reference to a set of training data. However, decision trees suffer from a well-known problem. In the latter stages of the branching process, decisions can become severely distorted by training data that is sparse and prone to huge variation at this kind of resolution, a problem known as overfitting. The random-forest approach is different.


Paul Allen Thought Like a Hacker and Never Stopped Dreaming

WIRED

Iconic tech-company founders often come in pairs: Bill Hewlett and David Packard. The world lost half of one such duo Monday when Paul Allen, who cofounded Microsoft with his childhood friend Bill Gates, died from non-Hodgkin's lymphoma. For the last three decades of his life, Allen was best known as a philanthropist and prolific entrepreneur. He funded the first successful privately financed spacecraft launch and the development of the world's largest aircraft. And he owned two professional sports teams, football's Seattle Seahawks and basketball's Portland Trail Blazers, and co-owned another, soccer's Seattle Sounders.


Learning what life in Japan is like for people with disabilities

The Japan Times

One recent Sunday, 7-year-old Yukito Takanashi of Tokyo was dribbling a soccer ball on a makeshift field. At one point, he put on an eye mask, just like blind soccer players. But he took it off after a while, feeling somewhat uncomfortable. The boy, who has experience playing the game with other children who, like himself, have autism, said it was "difficult" to play with his eyes covered. "It's a good chance to learn about the struggles people with disabilities go through that most people fail to notice in their daily lives," Takanashi's father, Ryoichi, 32, said.


Automata for Infinite Argumentation Structures

arXiv.org Artificial Intelligence

The theory of abstract argumentation frameworks (afs) has, in the main, focused on finite structures, though there are many significant contexts where argumentation can be regarded as a process involving infinite objects. To address this limitation, in this paper we propose a novel approach for describing infinite afs using tools from formal language theory. In particular, the possibly infinite set of arguments is specified through the language recognized by a deterministic finite automaton while a suitable formalism, called attack expression, is introduced to describe the relation of attack between arguments. The proposed approach is shown to satisfy some desirable properties which can not be achieved through other "naive" uses of formal languages. In particular, the approach is shown to be expressive enough to capture (besides any arbitrary finite structure) a large variety of infinite afs including two major examples from previous literature and two sample cases from the domains of multi-agent negotiation and ambient intelligence. On the computational side, we show that several decision and construction problems which are known to be polynomial time solvable in finite afs are decidable in the context of the proposed formalism and we provide the relevant algorithms. Moreover we obtain additional results concerning the case of finitary afs.


BeoutQ: Football live stream network prompts $1 billion lawsuit against Saudi Arabia

The Independent

A Qatar-based sports TV network is seeking $1 billion in damages from Saudi Arabia for the kingdom's alleged involvement in the "most widespread piracy of sports broadcasting that the world has ever seen." BeIN Corporation claims that the pirate network beoutQ has received State support in order to grow into an advanced piracy operation that serves content to potentially millions of viewers through illegal set-top boxes. Global sporting events have been broadcast through the beoutQ network – including the 2018 Fifa World Cup, the Formula One World Championship and the Premier League – after the pirate nework hijacked the feeds of legitimate broadcasters. "Piracy is a major problem facing the sports and broadcasting industries. By supporting beoutQ's widespread and notorious infringement of the intellectual property rights of beIN and its partners, Saudi Arabia is setting a dangerous new precedent," said David Roney, a lawyer at Sidley Austin LLP who is leading the arbitration on behalf of beIN.


VAIN: Attentional Multi-agent Predictive Modeling

arXiv.org Artificial Intelligence

Multi-agent predictive modeling is an essential step for understanding physical, social and team-play systems. Recently, Interaction Networks (INs) were proposed for the task of modeling multi-agent physical systems, INs scale with the number of interactions in the system (typically quadratic or higher order in the number of agents). In this paper we introduce VAIN, a novel attentional architecture for multi-agent predictive modeling that scales linearly with the number of agents. We show that VAIN is effective for multi-agent predictive modeling. Our method is evaluated on tasks from challenging multi-agent prediction domains: chess and soccer, and outperforms competing multi-agent approaches.


Cartoon: Where AI achieves excellence

#artificialintelligence

A recent story about a company planning to replace lawyers with Machine Learning led me to think how it might look like when AI lawyers are deployed. Partner: Finally, we have a lawyer that not only bills for 24 hours per day, but actually works 24 hours a day! This cartoon was ably drawn by Jon Carter. See also other recent KDnuggets Cartoons: Cartoon: Labor Day in the year 2050 Cartoon: Machine Learning takes a vacation Cartoon: Data Scientist was the sexiest job of the 21st century until ... Cartoon: How is Data Science Different From Religion? Cartoon: Thanksgiving, Big Data, & Turkey Data Science Cartoon: What Else Can AI Guess From Your Face? Cartoon: Future Machine Learning Class Cartoon: The First Ever Self-Driving, Deep Learning Grill Cartoon: Mother Of All Data Cartoon: Machine Learning - What They Think I Do Cartoon: the distance between Espresso and Cappuccino Cartoon: Taxes, Artificial Intelligence, and Humans Cartoon: What Happens When AI Masters the March Madness Causation or Correlation: Explaining Hill Criteria using xkcd Cartoon: Perfect Valentine's Dates Found With Data Analysis Cartoon: When Self-Driving Car Machine Learning takes you too far ... Cartoon: Labor Day in the year 2050 Cartoon: Machine Learning takes a vacation Cartoon: Data Scientist was the sexiest job of the 21st century until ... Cartoon: How is Data Science Different From Religion?


Cartoon: Where AI achieves excellence

#artificialintelligence

A recent story about a company planning to replace lawyers with Machine Learning led me to think how it might look like when AI lawyers are deployed. Partner: Finally, we have a lawyer that not only bills for 24 hours per day, but actually works 24 hours a day! This cartoon was ably drawn by Jon Carter. See also other recent KDnuggets Cartoons: Cartoon: Labor Day in the year 2050 Cartoon: Machine Learning takes a vacation Cartoon: Data Scientist was the sexiest job of the 21st century until ... Cartoon: How is Data Science Different From Religion? Cartoon: Thanksgiving, Big Data, & Turkey Data Science Cartoon: What Else Can AI Guess From Your Face? Cartoon: Future Machine Learning Class Cartoon: The First Ever Self-Driving, Deep Learning Grill Cartoon: Mother Of All Data Cartoon: Machine Learning - What They Think I Do Cartoon: the distance between Espresso and Cappuccino Cartoon: Taxes, Artificial Intelligence, and Humans Cartoon: What Happens When AI Masters the March Madness Causation or Correlation: Explaining Hill Criteria using xkcd Cartoon: Perfect Valentine's Dates Found With Data Analysis Cartoon: When Self-Driving Car Machine Learning takes you too far ... Cartoon: Labor Day in the year 2050 Cartoon: Machine Learning takes a vacation Cartoon: Data Scientist was the sexiest job of the 21st century until ... Cartoon: How is Data Science Different From Religion?


Fifa 19 review: EA Sports finally gives an easy answer to Fifa's most pressing question

The Independent

There has only ever been on question to ask about each year's Fifa: is it worth getting? And there's usually been far more than one answer, all kinds of caveats about the kind of features you use and player you are. This year the answer is as simple as the question. The changes are subtle but they are everywhere, and offer something for every kind of player. If you're a fan of authenticity the Champions League will be worth it alone, but if you want silliness like games with no fouls then there's plenty of that too.


Distinguishing Between Roles of Football Players in Play-by-play Match Event Data

arXiv.org Machine Learning

Over the last few decades, the player recruitment process in professional football has evolved into a multi-billion industry and has thus become of vital importance. To gain insights into the general level of their candidate reinforcements, many professional football clubs have access to extensive video footage and advanced statistics. However, the question whether a given player would fit the team's playing style often still remains unanswered. In this paper, we aim to bridge that gap by proposing a set of 21 player roles and introducing a method for automatically identifying the most applicable roles for each player from play-by-play event data collected during matches.