football_league_results — Football league results (2013-2017)
- Description
Results of the games of four national football (soccer) leagues, one network per season, compiled by hand from Wikipedia by Fanuel and Suykens, as distributed by KONECT:
be1_2016: Belgian Pro League, season 2016/2017;de1_2016: German Bundesliga, season 2016/2017;fr1_2016: French Ligue 1, season 2016/2017;uk1_2013: English Premier League, season 2013/2014.
Each node is a team, and a directed edge from team A to team B is a game that A played at home against B. The edges are signed by the goal difference (positive if the home team won, negative if it lost, zero for a draw); the scores of the games are not included. Only the games of the regular seasons are included (in
be1_2016, 239 of the 240 games of the regular season; one is missing). The data identify the teams only by indices (their names are not included).The networks have the following properties:
- Edge
goal_difference: the goals of the home team minus the goals of the away team.
- Tags
- Social Offline Sports Signed Weighted
- Citation
-
- M. Fanuel, J. A. K. Suykens, "Deformed Laplacians and spectral ranking in directed networks." Applied and Computational Harmonic Analysis 47(2), 397-422 (2019) 10.1016/j.acha.2017.09.002 Sci-Hub
- J. Kunegis, "KONECT -- The Koblenz Network Collection." Proceedings of the 22nd International Conference on World Wide Web Companion, 1343-1350 (2013) 10.1145/2487788.2488173 Sci-Hub
- Upstream URL OK
-
http://konect.cc/networks/league-be1-2016
http://konect.cc/networks/league-de1-2016
http://konect.cc/networks/league-fr1-2016
http://konect.cc/networks/league-uk1-2013 - Networks
-
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv be1_2016 16 239 14.94 0.33 14.00 0.03 -0.10 0.97 1 1.00 Directed Unipartite goal_difference 2 KiB 3 KiB 3 KiB 3 KiB de1_2016 18 306 17.00 0.00 16.00 0.03 nan 0.97 1 1.00 Directed Unipartite goal_difference 2 KiB 3 KiB 3 KiB 3 KiB fr1_2016 20 380 19.00 0.00 18.00 inf nan 0.97 1 1.00 Directed Unipartite goal_difference 2 KiB 4 KiB 3 KiB 3 KiB uk1_2013 20 380 19.00 0.00 18.00 inf nan 0.97 1 1.00 Directed Unipartite goal_difference 2 KiB 4 KiB 4 KiB 3 KiB - Ridiculograms*