A network-based dynamical ranking system for competitive sports

@article{Motegi2012AND,
  title={A network-based dynamical ranking system for competitive sports},
  author={Shun Motegi and Naoki Masuda},
  journal={Scientific Reports},
  year={2012},
  volume={2}
}
From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating… 
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References

SHOWING 1-10 OF 35 REFERENCES
A network-based ranking system for US college football
American college football faces a conflict created by the desire to stage national championship games between the best teams of a season when there is no conventional play-off system for deciding…
Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis
TLDR
A diffusion algorithm was developed and applied to the tennis contact network in order to rank professional players and Jimmy Connors was identified as the best player in the history of tennis according to the ranking procedure.
Mutually-antagonistic interactions in baseball networks
Dynamic Rating of Sports Teams
We consider the problem of dynamically rating sports teams on the basis of categorical outcomes of paired comparisons such as win, draw and loss in football. Our modelling framework is the cumulative…
An Iterative Procedure for Evaluating Digraph Competitions
TLDR
A competition which is based on the results of (partial) pairwise comparisons can be modelled by means of a directed graph and an iterative process is described that repeats this procedure: at each step the allocation obtained in the previous step determines the new input weights.
Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength
TLDR
Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions.
Which Ball is the Roundest? - A Suggested Tournament Stability Index
All sports have components of randomness that cause the “best” individual or team not to win every game. According to many spectators this uncertainty is part of the charm when following a…
On Generalized Tournament Matrices
played (i.e., there are no ties). The outcome of the tournament may be represented by an n x n tournament matrix T where lij = 1 if player i defeats player j (symbolically, i -+ j) and zero…
Minimizing Game Score Violations in College Football Rankings
TLDR
Using a model for minimizing violations that exploits problem characteristics found in college football, it was found that all previous ranking systems generated violations that were at least 38 percent higher than the minimum.
TrueSkill™: A Bayesian Skill Rating System
We present a new Bayesian skill rating system which can be viewed as a generalisation of the Elo system used in Chess. The new system tracks the uncertainty about player skills, explicitly models…
...
...