New Theoretical Insights and Algorithmic Solutions for Reconstructing Score Sequences from Tournament Score Sets

TL;DR

This paper introduces new theoretical conditions and algorithms for reconstructing tournament score sequences from score sets, providing a framework that advances understanding and practical reconstruction methods, with applications in ranking and machine learning.

Contribution

It presents a necessary and sufficient condition for score sequence reconstruction, along with three algorithms, including a polynomial-time method, extending Landau's theorem and verifying Reid's conjecture.

Findings

Developed a polynomial-time reconstruction algorithm.

Created a scalable algorithm for score sequence reconstruction.

Designed a network-building method to find all score sequences.

Abstract

The score set of a tournament is defined as the set of its distinct out-degrees. In 1978, Reid proposed the conjecture that for any set of nonnegative integers $D$, there exists a tournament $T$ with a degree set $D$. In 1989, Yao presented an arithmetical proof of the conjecture, but a general polynomial-time construction algorithm is not known. This paper proposes a necessary and sufficient condition and a separate necessary condition, based on the existing Landau's theorem for the problem of reconstructing score sequences from score sets of tournament graphs. The necessary condition introduces a structured set that enables the use of group-theoretic techniques, offering not only a framework for solving the reconstruction problem but also a new perspective for approaching similar problems. In particular, the same theoretical approach can be extended to reconstruct valid score sets given constraints on the frequency of distinct scores in tournaments. Based on these conditions, we have developed three algorithms that demonstrate the practical utility of our framework: a polynomial-time algorithm and a scalable algorithm for reconstructing score sequences, and a polynomial-time network-building method that finds all possible score sequences for a given score set. Moreover, the polynomial-time algorithm for reconstructing the score sequence of a tournament for a given score set can be used to verify Reid's conjecture. These algorithms have practical applications in sports analysis, ranking prediction, and machine learning tasks such as learning-to-rank models and data imputation, where the reconstruction of partial rankings or sequences is essential for recommendation systems and anomaly detection.