Round-robin Tournament Research Articles

First in first win: Evidence on schedule effects in round-robin tournaments in mega-events

The order of actions in contests may have a significant effect on performance. In this study, we examine the role of the schedule in round-robin tournaments with sequential games between three and four contestants. Our empirical analysis, based on soccer FIFA World Cups and UEFA European Championships, and on two Olympic wrestling events, reveals that there is a substantial advantage to the contestant who competes in the first and third matches. Our findings are in line with the hypothesis that winning probabilities in multi-stage contests with sequential games are endogenously depending on the schedule of contests as predicted by game-theoretical models. We also discuss possible ways to reduce the effect of the schedule.

Round-Robin Tournaments with Limited Resources

We propose a theoretical model of a round-robin tournament with limited resources motivated by the fact that in a real-world round-robin sport tournament participating teams are sometimes forced to distribute their effort over an extended period. We assume that the participating teams have a limited amount of effort that must be distributed between all matches. We model the outcome of each match as a first-price sealed-bid auction. Results are aggregated after all matches are played with respect to the number of wins. The teams distribute their effort striving to maximize the expected payoff at tournament completion. For a three team tournament, we describe the set of all subgame perfect Nash equilibria in pure strategies. For tournaments with a relatively low first prize, we found two types of equilibria: ‘effort-saving’ and ‘burning out’, both leading to unequal payoffs. In contrast, for tournaments with a large first prize a limited budget of effort, in general, does not allow for the first or the last move advantage to be exploited.

Scheduling the Australian Football League

Generating a schedule for a professional sports league is an extremely demanding task. Good schedules have many benefits for the league, such as higher attendance and TV viewership, lower costs and increased fairness. The Australian Football League is particularly interesting because of an unusual competition format integrating a single round-robin tournament with additional games. Furthermore, several teams have multiple home venues and some venues are shared by multiple teams. This paper presents a 3-phase process to schedule the Australian Football League. The resulting solution outperforms the official schedule with respect to minimizing and balancing travel distance and breaks, while satisfying more requirements.

The sport teams grouping problem

The sport teams grouping problem (STGP) concerns the assignment of sport teams to round-robin tournaments. The objective is to minimize the total travel distance of the participating teams while simultaneously respecting fairness constraints. The STGP is an NP-Hard combinatorial optimization problem highly relevant in practice. This paper investigates the performance of some complimentary optimization approaches to the STGP. Three integer programming formulations are presented and thoroughly analyzed: two compact formulations and another with an exponential number of variables, for which a branch-and-price algorithm is proposed. Additionally, a meta-heuristic method is applied to quickly generate feasible high-quality solutions for a set of real-world instances. By combining the different approaches’ results, solutions within 1.7% of the optimum values were produced for all feasible instances. Additionally, to support further research, the considered STGP instances and corresponding solutions files were shared online.

Scheduling the South American Qualifiers to the 2018 FIFA World Cup by integer programming

Every four years, the 10 national teams members of the South American Football Confederation (CONMEBOL) compete for one of the South American slots in the final phase of the FIFA World Cup. The qualifying competition consists of a double round robin tournament. The matches are scheduled in 9 closely spaced pairs known as double rounds. Every team plays twice in each double round. The tournament is spread over 2 years, so the double rounds are months apart. After using the same mirrored schedule for about twenty years, and persistent complaints from its members, CONMEBOL decided to change the schedule for the 2018 World Cup. Supported by one of CONMEBOL’s members, we used integer programmming to construct schedules that overcome the main drawbacks of the previous approach. After exploring many design criteria, we proposed a candidate schedule based on a French scheme. The main feature of the proposed schedule is that every team plays once at home and once away on each double round, a departure from traditional symmetric (mirrored) schemes. This proposal was unanimously approved by CONMEBOL members and is currently being used in the qualifier tournament for the 2018 FIFA World Cup in Russia.

Round-robin tournaments generated by the Circle Method have maximum carry-over

The Circle Method is widely used in the field of sport scheduling to generate schedules for round-robin tournaments. If in such a tournament, team A played team B in its previous match and is now playing team C, team C is said to receive a carry-over effect from team B. The so-called carry-over effect value is a number that can be associated to each round-robin schedule; it represents a degree of unbalancedness of the schedule with respect to carry-over. Here, we prove that, for an even number of teams, the Circle Method generates a schedule with maximum carry-over effect value, answering an open question.

First-mover advantage in round-robin tournaments

We study round-robin tournaments with either three or four symmetric players whose values of winning are common knowledge. With three players there are three rounds, each of which includes one pair-wise game such that each player competes in two rounds only. The player who wins two games wins the tournament. We characterize the subgame perfect equilibrium and show that each player’s expected payoff and probability of winning is maximized when he competes in the first and the last rounds. With four players there are three rounds, each of which includes two sequential pair-wise games where each player plays against a different opponent in every round. We again characterize the subgame perfect equilibrium and show that a player who plays in the first game of each of the first two rounds has a first-mover advantage as reflected by a significantly higher winning probability as well as by a significantly higher expected payoff than his opponents.

Are Sequential Round-Robin Tournaments Discriminatory?

I examine sequential round-robin tournaments with three and four symmetric players. Each player is matched once with each other player. If the matches are organized as Tullock contests (all-pay auctions), the tournament will be almost fair (highly discriminatory): subject to the position of their matches in the sequence of the tournament, the differences in players' ex-ante winning probabilities and expected payoffs will be small (large). The differing results originate from the higher discriminating power of the all-pay auction. Moreover, the resulting discouragement effect in tournaments with all-pay auctions implies lower aggregate effort than in tournaments with suitable Tullock contests. The fairness of round-robin tournaments may be improved by the use of an endogenous sequence of matches or the requirement that players fix their effort ex-ante.

Sequential Round-Robin Tournaments with Multiple Prizes

We examine the fairness and intensity of sequential round-robin tournaments with multiple prizes. With three symmetric players and two prizes, the tournament is completely fair if and only if the second prize is valued half of the first prize, regardless of whether matches are organized as Tullock contests or as allpay auctions. For second prizes different from half of the first prize, three-player tournaments with matches organized as Tullock contests are usually fairer than tournaments with matches organized as all-pay auctions. However, unless the second prize is very small, they are less intense in the sense that players exert less ex-ante expected aggregate effort per unit of prize money. Moreover, we specify how the relative size of the second prize influences the extent and the direction of discrimination as well as the intensity of three-player tournaments. Finally, we show that there is no prize structure for which sequential round-robin tournaments with four symmetric players are completely fair in general.

Coevolutionary CMA-ES for Knowledge-Free Learning of Game Position Evaluation

One weakness of coevolutionary algorithms observed in knowledge-free learning of strategies for adversarial games has been their poor scalability with respect to the number of parameters to learn. In this paper, we investigate to what extent this problem can be mitigated by using Covariance Matrix Adaptation Evolution Strategy, a powerful continuous optimization algorithm. In particular, we employ this algorithm in a competitive coevolutionary setup, denoting this setting as Co-CMA-ES. We apply it to learn position evaluation functions for the game of Othello and find out that, in contrast to plain (co)evolution strategies, Co-CMA-ES learns faster, finds superior game-playing strategies and scales better. Its advantages come out into the open especially for large parameter spaces of tens of hundreds of dimensions. For Othello, combining Co-CMA-ES with experimentally-tuned derandomized systematic $n$ -tuple networks significantly improved the current state of the art. Our best strategy outperforms all the other Othello 1-ply players published to date by a large margin regardless of whether the round-robin tournament among them involves a fixed set of initial positions or the standard initial position but randomized opponents. These results show a large potential of CMA-ES-driven coevolution, which could be, presumably, exploited also in other games.

Scheduling double round-robin tournaments with divisional play using constraint programming

We study a tournament format that extends a traditional double round-robin format with divisional single round-robin tournaments. Elitserien, the top Swedish handball league, uses such a format for its league schedule. We present a constraint programming model that characterizes the general double round-robin plus divisional single round-robin format. This integrated model allows scheduling to be performed in a single step, as opposed to common multistep approaches that decompose scheduling into smaller problems and possibly miss optimal solutions. In addition to general constraints, we introduce Elitserien-specific requirements for its tournament. These general and league-specific constraints allow us to identify implicit and symmetry-breaking properties that reduce the time to solution from hours to seconds. A scalability study of the number of teams shows that our approach is reasonably fast for even larger league sizes. The experimental evaluation of the integrated approach takes considerably less computational effort to schedule Elitserien than does the previous decomposed approach.

Elicitation of Strategies in Four Variants of a Round-Robin Tournament: The Case of Goofspiel

Goofspiel is a simple two-person zero-sum game for which there exist no known equilibrium strategies. To gain insight into what constitute winning strategies, we conducted a round-robin tournament in which participants were asked to provide computerized programs for playing the game with or without carryover. Each of these two variants was to be played under two quite different objective functions, namely, maximization of the cumulative number of points won across all opponents (as in Axelrod’s tournament), and maximization of the probability of winning any given round. Our results show that there are, indeed, inherent differences in the results with respect to the complexity of the game and its objective function, and that winning strategies exhibit a level of sophistication, depth, and balance that are not captured by present models of adaptive learning.

Exploiting Evolutionary Modeling to Prevail in Iterated Prisoner’s Dilemma Tournaments

The iterated prisoner’s dilemma is a famous model of cooperation and conflict in game theory. Its origin can be traced back to the Cold War, and countless strategies for playing it have been proposed so far, either designed by hand or automatically generated by computers. In the 2000s, scholars started focusing on adaptive players, that is, able to classify their opponent’s behavior and adopt an effective counter-strategy. The player presented in this paper, pushes such idea even further: it builds a model of the current adversary from scratch, without relying on any pre-defined archetypes, and tweaks it as the game develops using an evolutionary algorithm; at the same time, it exploits the model to lead the game into the most favorable continuation. Models are compact nondeterministic finite state machines; they are extremely efficient in predicting opponents’ replies, without being completely correct by necessity. Experimental results show that such a player is able to win several one-to-one games against strong opponents taken from the literature, and that it consistently prevails in round-robin tournaments of different sizes.

Double Round-Robin Tournaments

A tournament is a simultaneous n-player game that is built on a two-player game g. We generalize Arad and Rubinstein’s model assuming that every player meets each of his opponents twice to play a (possibly) asymmetric game g in alternating roles (using sports terminology, once at home and once away). The winner of the tournament is the player who attains the highest total score, which is given by the sum of the payoffs that he gets in all the matches he plays. We explore the relationship between the equilibria of the tournament and the equilibria of the game g. We prove that limit points of equilibria of tournaments as the number of players goes to infinity are equilibria of g. Such a refinement criterion is satisfied by strict equilibria. Being able to analyze arbitrary two-player games allows us to study meaningful economic applications that are not symmetric, such as the ultimatum game.

Lower bounds for large traveling umpire instances: New valid inequalities and a branch-and-cut algorithm

Given a double round-robin tournament, the Traveling Umpire Problem (TUP) seeks to assign umpires to the games of the tournament while minimizing the total distance traveled by the umpires. The assignment must satisfy constraints that prevent umpires from seeing teams and venues too often, while making sure all games have umpires in every round, and all umpires visit all venues. We propose a new integer programming model for the TUP that generalizes the two best existing models, introduce new families of strong valid inequalities, and implement a branch-and-cut algorithm to solve instances from the TUP benchmark. When compared against published state-of-the-art methods, our algorithm significantly improves all best known lower bounds for large TUP instances (with 20 or more teams).

Counting the number of round-robin tournament schedules

Counting the number of round-robin tournament schedules

Scheduling asynchronous round-robin tournaments

We study the problem of scheduling asynchronous round-robin tournaments. We consider three measures of a schedule that concern the quality and fairness of a tournament. We show that the schedule generated by the well-known “circle design” performs well with respect to all three measures when the number of teams is even, but not when the number of teams is odd. We propose a different schedule that performs optimally with respect to all measures when the number of teams is odd.

Android-Based Mobile Application for Combined Single Elimination and Round Robin Tournament Types Football Event

Android-Based Mobile Application for Combined Single Elimination and Round Robin Tournament Types Football Event

Branch-and-bound with decomposition-based lower bounds for the Traveling Umpire Problem

The Traveling Umpire Problem (TUP) is an optimization problem in which umpires have to be assigned to games in a double round robin tournament. The objective is to obtain a solution with minimum total travel distance over all umpires, while respecting hard constraints on assignments and sequences. Up till now, no general nor dedicated algorithm was able to solve all instances with 12 and 14 teams. We present a novel branch-and-bound approach to the TUP, in which a decomposition scheme coupled with an efficient propagation technique produces the lower bounds. The algorithm is able to generate optimal solutions for all the 12- and 14-team instances as well as for 11 of the 16-team instances. In addition to the new optimal solutions, some new best solutions are presented and other instances have been proven infeasible.

Evolution of cooperation in Axelrod tournament using cellular automata

Results of the Axelrod Tournament were published in 1981, and since then, evolutionary game theory emerged as an idea for understanding relations, like conflict and cooperation, between rational decision-makers. Robert Axelrod organized it as a round-robin tournament where strategies for iterated Prisoner’s Dilemma were faced in a sequence of two players game. Here, we attempt to simulate the strategies submitted to the tournament in a multi-agent context, where individuals play a two-player game with their neighbors. Each individual has one of the strategies, and it plays the Prisoner’s Dilemma with its neighbors. According to actions chosen (cooperate or defect), points of life are subtracted from their profiles. When an individual dies, some fitness functions are defined to choose the most successful strategy which the new individual will copy. Although tit-for-tat was the best strategy, on average, in the tournament, in our evolutionary multi-agent context, it has not been successful.