That said, I would also argue underdogs are over-owned relative to their expectation. The problem with attacking heavy favorites - from a game theory perspective - is ownership tends to be at its peak as well. In general, goaltenders have performed well below their salary-based expectation until the top-20 percentile bucket in Vegas Moneyline Rating, but the Plus/Minus and Consistency skyrockets in the top-five percent. Vegas makes money, so it makes sense that goalies playing in games in which they are more heavily favored perform much better. More importantly, the impact on Plus/Minus in comparison to both Consistency and Ownership is where the true value lies in these charts: Anything over the 50th percentile is favorites and below are underdogs, with the 99th percentile obviously being the largest favorites, etc. This gives us a way to quantify how large or small a favorite is relative to our historical database. The following charts highlight goalies using different percentile buckets for our Vegas Moneyline Rating metric. Historically, favorites are also far more consistent, but they (unsurprisingly) carry much higher ownership as well. Perhaps staring at the very core, is there a difference between Vegas favorites and underdogs? That seems like as good a starting point as any: Favoritesįrom a macro perspective, Vegas favorites only slightly underperform their salary-based expectations in comparison to underdogs. Can be used to identify high-floor players for cash games.īefore we get too deep, we should probably identify a baseline trend. Note that DFS scoring is typically lower for NHL than other sports like NFL or NBA, so the NHL Plus/Minus values we see are likely to be relatively small.Ĭonsistency: The percentage of games in which a player has produced within a standard deviation of his expected points based off of historical scoring and pricing. Plus/Minus: A player’s actual points minus his expected points in the context of their salary-based expectations.
Draftkings moneyline series#
If you’ve already been with us for parts one, two, and three of this series - where we talked about why it makes sense to target peripheral stats for skaters - you’re likely very familiar with our proprietary metrics at FantasyLabs. Using our Trends tool, we can compare the Plus/Minus values to both Consistency and Ownership. This could be why ownership tends to closely mirror Vegas moneylines. Baseline Trend and Vegas Moneyline Rating %Īt goaltender, wins are weighted significantly in both DraftKings & FanDuel scoring. How can we improve our odds of consistency at such a variance-filled position?.There are a few questions we need to ask ourselves:
Nothing worse than having the stone nuts and watching your underperforming goaltender hold you back. This week, it’s time to shift our focus to the goalie position.
The impetus for this entire series comes from Jonathan Bales’ books. This is probably the most important question to answer if you are new to DFS hockey. “What NHL Metrics Should I Prioritize in my Models and Goalie Selection?” The series provides analysis by looking at the dynamics of value, ownership, and consistency by using our massive database of historical trends. The Metric Lab is a deep dive using the FantasyLabs Tools to analyze the predictiveness of different statistics and proprietary data.
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