In graph theory, a tournament is a directed graph with exactly one edge between each two vertices, in one of the two possible directions. Equivalently, a tournament is an orientation of an undirected complete graph. (However, as directed graphs, tournaments are not complete: complete directed graphs have two edges, in both directions, between each two vertices.[1]) The name tournament comes from interpreting the graph as the outcome of a round-robin tournament, a game where each player is paired against every other exactly once. In a tournament, the vertices represent the players, and the edges between players point from the winner to the loser.
Many of the important properties of tournaments were investigated by H. G. Landau in 1953 to model dominance relations in flocks of chickens.[2] Tournaments are also heavily studied in voting theory, where they can represent partial information about voter preferences among multiple candidates, and are central to the definition of Condorcet methods.
If every player beats the same number of other players (indegree − outdegree = 0) the tournament is called regular.
Paths and cycles
Any tournament on a finite number of vertices contains a Hamiltonian path, i.e., directed path on all vertices (Rédei 1934).
This is easily shown by induction on : suppose that the statement holds for , and consider any tournament on vertices. Choose a vertex of and consider a directed path in . There is some such that . (One possibility is to let be maximal such that for every . Alternatively, let be minimal such that .)
is a directed path as desired. This argument also gives an algorithm for finding the Hamiltonian path. More efficient algorithms, that require examining only of the edges, are known. The Hamiltonian paths are in one-to-one correspondence with the minimal feedback arc sets of the tournament.[3] Rédei's theorem is the special case for complete graphs of the Gallai–Hasse–Roy–Vitaver theorem, relating the lengths of paths in orientations of graphs to the chromatic number of these graphs.[4]
Another basic result on tournaments is that every strongly connected tournament has a Hamiltonian cycle.[5] More strongly, every strongly connected tournament is vertex pancyclic: for each vertex , and each in the range from three to the number of vertices in the tournament, there is a cycle of length containing .[6] A tournament is -strongly connected if for every set of vertices of , is strongly connected.
If the tournament is 4‑strongly connected, then each pair of vertices can be connected with a Hamiltonian path.[7] For every set of at most arcs of a -strongly connected tournament , we have that has a Hamiltonian cycle.[8] This result was extended by Bang-Jensen, Gutin & Yeo (1997).[9]
Transitivity
A tournament in which and is called transitive. In other words, in a transitive tournament, the vertices may be (strictly) totally ordered by the edge relation, and the edge relation is the same as reachability.
Equivalent conditions
The following statements are equivalent for a tournament on vertices:
Transitive tournaments play a role in Ramsey theory analogous to that of cliques in undirected graphs. In particular, every tournament on vertices contains a transitive subtournament on vertices. The proof is simple: choose any one vertex to be part of this subtournament, and form the rest of the subtournament recursively on either the set of incoming neighbors of or the set of outgoing neighbors of , whichever is larger. For instance, every tournament on seven vertices contains a three-vertex transitive subtournament; the Paley tournament on seven vertices shows that this is the most that can be guaranteed.[10] However, Reid & Parker (1970) showed that this bound is not tight for some larger values of .[11]
Erdős & Moser (1964) proved that there are tournaments on vertices without a transitive subtournament of size Their proof uses a counting argument: the number of ways that a -element transitive tournament can occur as a subtournament of a larger tournament on labeled vertices is
and when is larger than , this number is too small to allow for an occurrence of a transitive tournament within each of the different tournaments on the same set of labeled vertices.[10]
Paradoxical tournaments
A player who wins all games would naturally be the tournament's winner. However, as the existence of non-transitive tournaments shows, there may not be such a player. A tournament for which every player loses at least one game is called a 1-paradoxical tournament. More generally, a tournament is called -paradoxical if for every -element subset of there is a vertex in such that for all . By means of the probabilistic method, Paul Erdős showed that for any fixed value of , if , then almost every tournament on is -paradoxical.[12] On the other hand, an easy argument shows that any -paradoxical tournament must have at least players, which was improved to by Esther and George Szekeres in 1965.[13] There is an explicit construction of -paradoxical tournaments with players by Graham and Spencer (1971) namely the Paley tournament.
Condensation
The condensation of any tournament is itself a transitive tournament. Thus, even for tournaments that are not transitive, the strongly connected components of the tournament may be totally ordered.[14]
Score sequences and score sets
The score sequence of a tournament is the nondecreasing sequence of outdegrees of the vertices of a tournament. The score set of a tournament is the set of integers that are the outdegrees of vertices in that tournament.
Landau's Theorem (1953) A nondecreasing sequence of integers is a score sequence if and only if:[2]
Let be the number of different score sequences of size . The sequence (sequence A000571 in the OEIS) starts as:
Yao showed that every nonempty set of nonnegative integers is the score set for some tournament.[16]
Majority relations
In social choice theory, tournaments naturally arise as majority relations of preference profiles.[17] Let be a finite set of alternatives, and consider a list of linear orders over . We interpret each order as the preference ranking of a voter . The (strict) majority relation of over is then defined so that if and only if a majority of the voters prefer to , that is . If the number of voters is odd, then the majority relation forms the dominance relation of a tournament on vertex set .
By a lemma of McGarvey, every tournament on vertices can be obtained as the majority relation of at most voters.[18] Results by Stearns and Erdős & Moser later established that voters are needed to induce every tournament on vertices.[19]
Laslier (1997) studies in what sense a set of vertices can be called the set of "winners" of a tournament.[20] This revealed to be useful in Political Science to study, in formal models of political economy, what can be the outcome of a democratic process.[21]
Austen-Smith, D.; Banks, J. (1999), Positive Political theory, University of Michigan Press
Bang-Jensen, J.; Gutin, G.; Yeo, A. (1997), "Hamiltonian Cycles Avoiding Prescribed Arcs in Tournaments", Combinatorics, Probability and Computing, 6: 255–261
Takács, Lajos (1991), "A Bernoulli Excursion and Its Various Applications", Advances in Applied Probability, 23 (3), Applied Probability Trust: 557–585, doi:10.2307/1427622, JSTOR1427622.