On Elo based prediction models for the FIFA Worldcup 2018

We propose an approach for the analysis and prediction of a football championship. It is based on Poisson regression models that include the Elo points of the teams as covariates and incorporates differences of team-specific effects. These models for the prediction of the FIFA World Cup 2018 are fitted on all football games on neutral ground of the participating teams since 2010. Based on the model estimates for single matches Monte-Carlo simulations are used to estimate probabilities for reaching the different stages in the FIFA World Cup 2018 for all teams. We propose two score functions for ordinal random variables that serve together with the rank probability score for the validation of our models with the results of the FIFA World Cups 2010 and 2014. All models favor Germany as the new FIFA World Champion. All possible courses of the tournament and their probabilities are visualized using a single Sankey diagram.Comment: 22 pages, 7 figure

A Simple Non-Markovian Computational Model of the Statistics of Soccer Leagues: Emergence and Scaling effects

We propose a novel algorithm that outputs the final standings of a soccer league, based on a simple dynamics that mimics a soccer tournament. In our model, a team is created with a defined potential(ability) which is updated during the tournament according to the results of previous games. The updated potential modifies a teams' future winning/losing probabilities. We show that this evolutionary game is able to reproduce the statistical properties of final standings of actual editions of the Brazilian tournament (Brasileir\~{a}o). However, other leagues such as the Italian and the Spanish tournaments have notoriously non-Gaussian traces and cannot be straightforwardly reproduced by this evolutionary non-Markovian model. A complete understanding of these phenomena deserves much more attention, but we suggest a simple explanation based on data collected in Brazil: Here several teams were crowned champion in previous editions corroborating that the champion typically emerges from random fluctuations that partly preserves the gaussian traces during the tournament. On the other hand, in the Italian and Spanish leagues only a few teams in recent history have won their league tournaments. These leagues are based on more robust and hierarchical structures established even before the beginning of the tournament. For the sake of completeness, we also elaborate a totally Gaussian model (which equalizes the winning, drawing, and losing probabilities) and we show that the scores of the "Brasileir\~{a}o" cannot be reproduced. Such aspects stress that evolutionary aspects are not superfluous in our modeling. Finally, we analyse the distortions of our model in situations where a large number of teams is considered, showing the existence of a transition from a single to a double peaked histogram of the final classification scores. An interesting scaling is presented for different sized tournaments.Comment: 18 pages, 9 figure

Risk Taking in Winner-Take-All Competition

We analyze a two-stage game between two heterogeneous players. At stage one, common risk is chosen by one of the players. At stage two, both players observe the given level of risk and simultaneously invest in a winner-take-all competition. The game is solved theoretically and then tested by using laboratory experiments. We find three effects that determine risk taking at stage one - an effort effect, a likelihood effect and a reversed likelihood effect. For the likelihood effect, risk taking and investments are clearly in line with theory. Pairwise comparison shows that the effort effect seems to be more relevant than the reversed likelihood effect when taking risk

Student effort and educational attainment: Using the England football team to identify the education production function.

We use a sharp, exogenous and repeated change in the value of leisure to identify the impact of student effort on educational achievement. The treatment arises from the partial overlap of the world’s major international football tournaments with the exam period in England. Our data enable a clean difference-in-difference design. Performance is measured using the high-stakes tests that all students take at the end of compulsory schooling. We find a strongly significant effect: the average impact of a fall in effort is 0.12 SDs of student performance, significantly larger for male and disadvantaged students, as high as many educational policies.student effort, educational achievement, schools

Proceedings of Mathsport international 2017 conference

Proceedings of MathSport International 2017 Conference, held in the Botanical Garden of the University of Padua, June 26-28, 2017. MathSport International organizes biennial conferences dedicated to all topics where mathematics and sport meet. Topics include: performance measures, optimization of sports performance, statistics and probability models, mathematical and physical models in sports, competitive strategies, statistics and probability match outcome models, optimal tournament design and scheduling, decision support systems, analysis of rules and adjudication, econometrics in sport, analysis of sporting technologies, financial valuation in sport, e-sports (gaming), betting and sports

Class tournament as an assessment method in physics courses : a pilot study

Testing knowledge is an integral part of a summative assessment at schools. It can be performed in many different ways. In this study we propose assessment of physics knowledge by using a class tournament approach. Prior to a statistical analysis of the results obtained over a tournament organized in one of Polish high schools, all its specifics are discussed at length, including the types of questions assigned, as well as additional self- and peer-evaluation questionnaires, constituting an integral part of the tournament. The impact of the tournament upon student improvement is examined by confronting the results of a post-test with pre-tournament students’ achievements reflected in scores earned in former, tests written by the students in experimental group and their colleagues from control group. We also present some of students’ and teachers’ feedback on the idea of a tournament as a tool of assessment. Both the analysis of the tournament results and the students’ and teachers’ opinions point to at least several benefits of our approach