TRV Battle Networks
Original Twitter Post: https://twitter.com/scuerij/status/1569491485766328321?s=20&t=4mc7Ec5nLffBiXgXjraIKw
@TheRedVillage | TRV Battle Networks | 12 SEP 2022
New TRVtools analytic exploratory data analysis: TRV Battle Networks
@TheRedVillage Battles can be visualized as a network graph; champs = nodes, and battles = network edges. Coloring edges by Battle Class reveals network structure. This plot is limited to pairs w/ 5+ battles.
Where are all the Heroics? Check the full network (1 or more battles b/n pairs). Heroic class is restricted to a tight Elo range and is occupied by a wide range of champs. These nodes tend to be more peripheral in the network, and these champs tend to quickly graduate.
Coloring edges by pairwise battle count reveals that the node cluster primarily occupied by Immortal class champs tends to exhibit the most action. You don’t need fancy analytics to reach this conclusion, but it’s nice to see. This plot is limited to pairs w/ 5+ battles.
And plotting the full network demonstrates that the vast majority of champ pairs exhibit a small number of pairwise connections. In other words, most champs aren’t facing each other on a routine basis (the exception generally being certain pairs of Immortal class champs).
So, which champs are most central to the battle network? The champ with the highest Centrality scores (both eigenvector centrality and betweenness centrality) is Maul von Truncheon an R4 Paladin.
Maul ranks 17th most battled but seems to bounce between Immortal and Legendary class frequently. Thus, he stands to face a wide diversity of champs, connecting the Immortal and Legendary classes to one another and elevating his network centrality scores.
Check out http://TRVtools.com for more @TheRedVillage analysis. What sorts of network analytics would you like to see added to TRVtools champ pages?