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Our old method ( described in detail in the “Same-pool avoidance subsection of our previous article) assigned scores based on how far in the bracket players from the same pool could meet one another, and then swapped players around until it found a bracket with a good enough score. Our perspective is that a method is only as good as its worst-case scenario (shortest possible DJ), so we want to optimize to have the best possible worst-case scenario. We also need a way to evaluate how well any shuffling method does at avoiding DJs. You can see that the GT-X example then would be “3–2.” The longer the DJ, the less likely players are to feel cheated by their bracket. So the Shine example above would be a “2–1” DJ since Locus played 2 sets and Mistake played 1 between their meetings. We define the length of a DJ as the total number of sets each player played in between their two meetings. So what we actually need to do is find a better general method for shuffling players into losers bracket to avoid DJs, one that works for every one of the dozens of possible double elimination bracket progressions that we support.ĭJs are impossible to always avoid completely but some are worse than others. The progression in winners bracket is fixed according to seeding, as is the method for dropping players from winners to losers in the same phase ( we talked about how we do this in an earlier article). Shine’s progression had 4 pools with 6 players in each making it out to the next bracket, and GT-X had 4 pools with 4 teams in each advancing. Evaluating Double Jeopardy events and progressionsįor our purposes, a bracket progression can be described by two parameters: the number of pools feeding into each bracket in the next phase, and how many players advance from each pool. These examples prompted us to do a more detailed revision our method to solve these and other potential DJ cases before they could happen. That means the problem is in our method for progressing players from one phase to the next. These are both cross-phase DJs, meaning the two matches happened in different phases of the bracket.
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NAKAT/VoiD have a rematch with Diablo/BestNess in Top 16 after having played them in pools. We started looking into this shortly after Shine 2017, where there were 3 instances of a bad DJ in the Wii U Singles bracket ( here’s one example).
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To be clear, we’re only considering double elimination brackets here, with a power of 2 number of pools. In this article, I’ll show some examples of where this happened, how we approached the problem, and the changes we made. Our multi-phase progressions give unprecedented flexibility in event formats, which makes “one-size fits all” algorithms difficult. Recently we’ve seen examples of our bracket progressions resulting in early double jeopardy situations. It’s not fun for players to experience this and arguably makes results less accurate as well. Double Jeopardy basicsĭouble Jeopardy (DJ) is the situation where 2 players that met in winners bracket later meet up in losers bracket and have to play each other again. We have given our support team tools to proactively identify upcoming bracket configurations with high likelihood of DJ situations. We have implemented tracking tools to “score” our double jeopardy avoidance and identify places we may be falling short.
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We made algorithm improvements to our progressions to make cross-phase DJs less likely for double elimination brackets (a ‘phase’ in smash.gg lingo is a stage of the bracket progression, like pools or top 8). Rematches in losers bracket will be less common now The short version: