"Fallout 76" was a buggy, listless wasteland and became an industry laughingstock. "Anthem" barely got off the ground. Recent updates to "Red Dead Online" are causing players to lose faith as they're nickel-and-dimed for dirty clothes and dances. It's a dark coincidence that a video game about abandoned and lost communities could be host to millions of adrift gamers, outraged and disappointed by the recent dud parade of massive, open-world online shooters. In Washington, where the game is set, Ubisoft held a preview event for "The Division 2," the sequel to the company's most successfully launched game ever.

Eric Sondheimer has been covering high school sports for the Los Angeles Times since 1997 and in Southern California since 1976. Get his latest from the field and follow all our prep sports coverage and analysis here. The Southern Section Division 1 track and field preliminary meet at Trubuco Hills High School on Saturday featured a water balloon attack from a lone drone. Near the start of the meet, around 11:30 a.m., a group of people positioned themselves on the hill above the track and allegedly flew a drone carrying water balloons over the track. One race official remarked that the water balloons were completely decimated upon impact.

Given a graph where vertices represent alternatives and arcs represent pairwise comparison data, the statistical ranking problem is to find a potential function, defined on the vertices, such that the gradient of the potential function agrees with the pairwise comparisons. Our goal in this paper is to develop a method for collecting data for which the least squares estimator for the ranking problem has maximal Fisher information. Our approach, based on experimental design, is to view data collection as a bi-level optimization problem where the inner problem is the ranking problem and the outer problem is to identify data which maximizes the informativeness of the ranking. Under certain assumptions, the data collection problem decouples, reducing to a problem of finding multigraphs with large algebraic connectivity. This reduction of the data collection problem to graph-theoretic questions is one of the primary contributions of this work. As an application, we study the Yahoo! Movie user rating dataset and demonstrate that the addition of a small number of well-chosen pairwise comparisons can significantly increase the Fisher informativeness of the ranking. As another application, we study the 2011-12 NCAA football schedule and propose schedules with the same number of games which are significantly more informative. Using spectral clustering methods to identify highly-connected communities within the division, we argue that the NCAA could improve its notoriously poor rankings by simply scheduling more out-of-conference games.