Archive for Hitters

In DFS, a common strategy to maximize the chances of placing highly in a large tournament is to enter several different lineups. In order to differentiate the lineups you enter and decrease risk, while still basing your lineups on sound data and analytics, you can utilize the concept of maximum player exposure.

The phrase “maximum player exposure” may sound complex, but it’s actually fairly simple. Once you select a maximum player exposure percentage on SaberSim, no player will appear in more than that percentage of the total lineups you generate. For example, if you were to create ten lineups and set the maximum player exposure at 50%, then Clayton Kershaw would appear in no more than five of those ten lineups. This allows for minimization of risk, as you’ll have a greater variety of players and a one bad performance won’t end your day right then and there.

Though it’s tempting to simplify the process of lineup creation by entering a single lineup into a higher-cost tournament, multi-lineup generation offers the ability to increase your odds of hitting just the right combination of players. At the same time, adjusting player exposure allows you to broaden your player pool, thus increasing the odds that you will cash a few lineups, and decreasing the risk of a big loss.

DFS Hitter Projections & Fun with Conditionals

Baltimore Orioles
There are three Orioles in the top ten projected offensive players for DraftKings tonight. Baltimore faces Mike Pelfrey in Camden Yards, and the team is projected to score 5.34 runs per game on average. The top three projected Orioles are Chris Davis, Manny Machado, and Adam Jones, with Davis as the top projected player across all games today. Mark Trumbo and Joey Rickard round out the top five.

Conditional Target: Mike Pelfrey
There are several different routes you could go when applying Conditionals to achieve an optimal Orioles stack. In the following example, I added a Conditional of Mike Pelfrey allowing at least five runs, and applied it to the optimized lineup. Notice that in addition to stacking an optimal combination of Orioles batters, the optimizer also included Ubaldo Jimenez in a pitcher slot, which is partly influenced by the Pelfrey >= 5 RA Conditional; when Pelfrey allows that many runs, Jimenez’s odds of earning a win drastically increase.

Milwaukee Brewers
The Brewers are projected to score 4.45 runs per game in their home matchup against James Shields and the Padres. Miller Park is a hitter-friendly park, and especially increases home run production. Ryan Braun, Chris Carter, and Jonathan Villar all rank in the top ten, and Alex Presley ranks in the top twenty as far as projected DraftKings points for tonight’s games.
A Conditional of Jonathan Villar scoring at least two runs results in an optimal stack of Brewers hitters based on that conditional, and also ensures that James Shields is very unlikely to be included.

Notice that while Ubaldo Jimenez is also included in this optimal lineup, his projected point total is slightly less than it was in the optimal lineup when Pelfrey allowed at least five runs. That’s because the Conditional of Villar scoring at least two runs in his game against the Padres has no effect on the totally separate game of Tigers at Orioles.

DFS Pitcher Projections
The top three pitchers for tonight based on projected DraftKings points are Clayton Kershaw, Vincent Velasquez, and David Price. These projections are mostly in line with the pricing, but just outside the top three is Jimmy Nelson, who faces the San Diego Padres at home. There are a couple more potential value plays outside of the top five, with Ubaldo Jimenez coming in at number six and Aaron Blair at seven.

Streaming Pitcher Options for Friday

Ross Stripling (11% Y!)
Stripling faces Michael Wacha and the Cardinals at home in his Friday matchup. The Dodgers are projected as favorites in that game (55%), and Stripling is projected to have a solid outing (0.38 W/G, 4.71 K/G, 3.68 ERA).

Nicholas Tropeano (8% Y!)
Tropeano faces Nate Karns and the Mariners in Seattle. The Angels are projected as underdogs, but Tropeano is still projected well enough to warrant a stream (0.36 W/G, 4.63 K/G, 3.79 ERA).

Conclusion
There are countless ways in which you can create DFS strategies using SaberSim projections and lineup creation tools. In addition to Conditionals, there are also features that allow you to exclude players, adjust exposure, and much more. To keep you fully informed on all the possibilities, we will continue to explore more strategies in the coming days and weeks. Also, remember to check back for updated projections throughout the day. As teams release official lineups, SaberSim automatically updates accordingly and reruns simulations in order to stay as current as possible.

Welcome back to another edition of the deep league waiver wire, where there’s another opportunity to take advantage of an injury and a preemptive move for an imminent returnee.

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If you’re hurting for outfield help in your deep mixed or mono league, this week’s deep league waiver wire is to the rescue!

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A Better Way to Create Optimal Combinations of Players

Many DFS players utilize a fairly unscientific approach to creating stacks (combinations of batters from one particular team) when building lineups. Rather than making educated guesses at optimal combinations though, it’s more effective to approach the strategy from an objective standpoint that accounts for the interdependence between players within the same game. Batters in different spots in the lineup will be affected differently by performances from other batters within the lineup depending on how many slots they are away from one another. Furthermore, one batter’s specific skillsets and projected rates of outcomes like home runs, steals, and strikeouts will affect others with different specific skillsets and projected rates.

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Let’s go deep down into the depths of your free agent pool. It’s where the risks are great and hidden treasures may emerge. Today’s theme is speculating on two guys that could remain worthless, but will cost you next to nothing to find out.

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Yesterday, I shared a list of the 11 hitters who have enjoyed the most sizable improvement in strikeout rate versus last season. If sustained, there’s a good chance that each of the hitters produce a sweet profit for their owners. On the other side of the coin are the hitters whose strikeout rates have increased the most. This is the danger zone. Let’s dive in.

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Last week, Eno discussed swing rate and ground ball rate changers as we finally started hitting the stabilization points of certain offensive metrics. Now, many hitters have reached the point at which strikeout rate become reliable, which has been found to be at 60 plate appearances. Obviously, all else being equal, a better strikeout rate will lead to better results. More balls in play equals a higher batting average, more home runs, and additional opportunities to drive in and score runs, and steal bases. So who has improved their strikeout rates the most so far compared to 2015?

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Exit Velocity! It’s all the rage now. And it should be. With just one season’s worth of incomplete data, we’re still trying to figure out what it all means. You’re familiar with my xHR/FB rate metric, right? That equation uses a hitter’s batted ball distance to determine what his HR/FB rate “should have” been. Unfortunately, batted ball distance is a result and the goal for any metrics I develop is to use metric that represent underlying skills. Exit velocity is that underlying skill. The hope is that it will eventually replace batted ball distance in my equation.

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So today is normally American League starting pitcher day, but that’s going to be pushed back. Perhaps to Monday. That’s because we’re only a week and a half into the season and there are still some crazy performance metrics being posted. I wanted to highlight them, laugh at them, and discuss them. By next Monday, they could be less crazy and there would be less laughing to do. And nobody wants them.

Statistics as of April 12, but will weave in performances from yesterday’s games when relevant.

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I considered titling this article “Buying Low on Sleepers.” But what is low? It feels more relative than the term discount. We have a general idea of what a player’s preseason market value was. Acquiring a player at less than said market value would be considered buying at a discount. So that’s what I’ll go with here, as the phrase “buying low” is generic advice that lacks the proper context to take action.

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