Randomness in Competitions

We study the effects of randomness on competitions based on an elementary random process in which there is a finite probability that a weaker team upsets a stronger team. We apply this model to sports leagues and sports tournaments, and compare the theoretical results with empirical data. Our model shows that single-elimination tournaments are efficient but unfair: the number of games is proportional to the number of teams N, but the probability that the weakest team wins decays only algebraically with N. In contrast, leagues, where every team plays every other team, are fair but inefficient: the top $\sqrt{N}$ of teams remain in contention for the championship, while the probability that the weakest team becomes champion is exponentially small. We also propose a gradual elimination schedule that consists of a preliminary round and a championship round. Initially, teams play a small number of preliminary games, and subsequently, a few teams qualify for the championship round. This algorithm is fair and efficient: the best team wins with a high probability and the number of games scales as $N^{9/5}$, whereas traditional leagues require N^3 games to fairly determine a champion.Comment: 10 pages, 8 figures, reviews arXiv:physics/0512144, arXiv:physics/0608007, arXiv:cond-mat/0607694, arXiv:physics/061221

Literary Competitions Organised by the Ministry of Culture and Arts in 1949–1950 in the Light of Archive Records

The subject of this paper are these literary competitions organized by Ministry of Culture and Arts in the late 1940s and early 1950s. Analysys of the materials from archivesenabled to tackle the issues: these competitions are one of the many aspect of stalinism offensive. Competitions encouraged writers for moving problems of socialist realism, they enforced artists for submission in accordance with Government of country.In article characterized six competitions. Most curious was “Third competition on mass song”, in which took part important writer Tadeusz Różewicz

Manipulating Tournaments in Cup and Round Robin Competitions

In sports competitions, teams can manipulate the result by, for instance, throwing games. We show that we can decide how to manipulate round robin and cup competitions, two of the most popular types of sporting competitions in polynomial time. In addition, we show that finding the minimal number of games that need to be thrown to manipulate the result can also be determined in polynomial time. Finally, we show that there are several different variations of standard cup competitions where manipulation remains polynomial.Comment: Proceedings of Algorithmic Decision Theory, First International Conference, ADT 2009, Venice, Italy, October 20-23, 200

Should We Redesign Forecasting Competitions?

The M3-Competition continues to improve the design of forecasting competitions: It examines more series than any previous competition, improves error analyses. and includes commercial forecasting programs as competitors. To judge where to go from here, I step back to look at the M-Competitions as a whole. I discuss the advantages of the M- Competitions in hopes that they will be retained, describe how to gain additional benefit from future competitions, and finally, describe a low-cost approach to competitions.forecasting, forecasting competitions,

Internal Promotion Competitions in Firms

[Excerpt] Using a sample of skilled workers from a cross section of establishments in four metropolitan areas of the United States, I present evidence suggesting that promotions are determined by relative worker performance. I then estimate a structural model of promotion tournaments (treating as endogenous promotions, worker performance, and the wage spread from promotion) that simultaneously accounts for worker and firm behavior and how the interaction of these behaviors gives rise to promotions. The results are consistent with the predictions of tournament theory that employers set wage spreads to induce optimal performance levels, and that workers are motivated by larger spreads

ViZDoom Competitions: Playing Doom from Pixels

This paper presents the first two editions of Visual Doom AI Competition, held in 2016 and 2017. The challenge was to create bots that compete in a multi-player deathmatch in a first-person shooter (FPS) game, Doom. The bots had to make their decisions based solely on visual information, i.e., a raw screen buffer. To play well, the bots needed to understand their surroundings, navigate, explore, and handle the opponents at the same time. These aspects, together with the competitive multi-agent aspect of the game, make the competition a unique platform for evaluating the state of the art reinforcement learning algorithms. The paper discusses the rules, solutions, results, and statistics that give insight into the agents' behaviors. Best-performing agents are described in more detail. The results of the competition lead to the conclusion that, although reinforcement learning can produce capable Doom bots, they still are not yet able to successfully compete against humans in this game. The paper also revisits the ViZDoom environment, which is a flexible, easy to use, and efficient 3D platform for research for vision-based reinforcement learning, based on a well-recognized first-person perspective game Doom

Fluctuation of cognitive-emotional states during competition:an idiographic account

The purpose of this paper is to describe athletes’ cognitive-emotional processes during competitions through an idiographic and ecologically valid study method based on verbal protocols and event sequential analyses. A world-class marksman and regional-level marksman filled in an affect grid after each shot during several competitions. Verbal reports were collected after each set by a delayed retrospective recall method and compared according to perceived performance periods. Event sequential analyses were conducted. The results showed distinct interpersonal patterns of affective states fluctuations and self-regulation strategies. Furthermore, intrapersonal patterns as a function of perceived performance were also identified. We suggest that the proposed methods are useful in studying athletes’ cognitive-emotional processes during ongoing competitions, as they ensure high ecological validity and provide in-depth information for more effective, individually-tailored interventions

Tree Boosting Data Competitions with XGBoost

This Master's Degree Thesis objective is to provide understanding on how to approach a supervised learning predictive problem and illustrate it using a statistical/machine learning algorithm, Tree Boosting. A review of tree methodology is introduced in order to understand its evolution, since Classification and Regression Trees, followed by Bagging, Random Forest and, nowadays, Tree Boosting. The methodology is explained following the XGBoost implementation, which achieved state-of-the-art results in several data competitions. A framework for applied predictive modelling is explained with its proper concepts: objective function, regularization term, overfitting, hyperparameter tuning, k-fold cross validation and feature engineering. All these concepts are illustrated with a real dataset of videogame churn; used in a datathon competition

Tournament Incentives in the Field: Gender Differences in the Workplace

We ran a field experiment in a Dutch retail chain consisting of 128 stores. In a random sample of these stores, we introduced short-term sales competitions among subsets of stores. We find that sales competitions have a large effect on sales growth, but only in stores where the store's manager and a large fraction of the employees have the same gender. Remarkably, results are alike for sales competitions with and without monetary rewards, suggesting a high symbolic value of winning a tournament. Lastly, despite the substantial variation in team size, we find no evidence for free-riding.sales contests, field experiment, gender differences, competition, awards