DFS Strategy: Using Conditionals to Fade Pitchers and Stack by Matt Hunter May 5, 2016 In order to differentiate DFS lineups in large tournaments, you can utilize a maneuver commonly referred to as “fading.” A fade consists of avoiding a pitcher who may be highly owned — for instance, Masahiro Tanaka against the Orioles today — in order to capitalize on the off-chance that he has a subpar outing. By using SaberSim’s Conditionals to fade a pitcher, you will also determine which combination of opposing hitters would be optimal in the event of that pitcher having a below-average outing. As we discussed last week, Conditionals are a tool that allows you to modify projections based on the assumption of certain specific events occurring. If you were to use a Conditional of Tanaka giving up 5 or more runs to the Orioles, then only simulation results in which that happened would be included. The Yankees @ Orioles simulation results in which Tanaka did not give up 5 or more runs would be excluded. As a result of that Conditional, Tanaka’s projection would be worse and the Orioles batters’ projections would be better — objectively accounting for the interdependence between hitters in the lineup when Tanaka has a bad outing. When fading a pitcher though, you don’t necessarily need to be extreme with the Conditional you use, since the likelihood of Tanaka allowing more than five runs is relatively low. Rather, you can decide to use a more conservative DraftKings or FanDuel point total for your Conditional. For example, you could apply a Conditional such that only the results of simulated games in which Tanaka scored less than 20 DraftKings points will be included in the projections, an outcome that is somewhat likely (53% according to SaberSim). This particular Conditional results in the following: When this Conditional was applied, the players in the Orioles @ Yankees game had their projections derived only from simulated games in which Tanaka scored less than 20 DraftKings points. Because of this Conditional, not only was Tanaka excluded from the optimized lineup, but also four separate Orioles were included in it. This is just one of many ways to use Conditionals, so please feel free to get as creative as you’d like in finding new ways to gain a competitive edge with them. DFS Batter Projections White Sox Jose Abreu is SaberSim’s top batter for today by projected DFS points, and he doesn’t even show up in the top 30 in DraftKings pricing. His White Sox teammates, however, do not share the same caliber of projection for today’s game against the Red Sox (Owens). Todd Frazier narrowly makes the top 20 projected batters, at which point you have to go another 20 additional slots down to find the next White Sox player. Blue Jays There are a handful of Blue Jays projected well for their matchup against Derek Holland and the Rangers (a game in which the simulator expects Toronto to win almost 70% of the time). Josh Donaldson possesses the best projection among them, but also comes with the highest price tag. Jose Bautista and Edwin Encarnacion are significantly less expensive options and are projected for similar point totals to Donaldson. Troy Tulowitzki rounds out the group with a modest price tag and a top-30 batter projection. DFS Pitcher Projections There are several value plays in today’s top five best-projected starting pitchers. The top two as far as projected DFS points are also the top two in DraftKings price, but after that there are three consecutive bargains — Trevor Bauer, J.A. Happ, and Matt Cain round out the top five. Though each player is flawed and a bit risky, there are several reasons why the simulator likes each one for today’s particular matchups. Trevor Bauer Bauer pitches at home against Michael Fulmer and the Tigers in a game the simulator expects the Indians to win 57% of the time. Thus, while Bauer is projected for a pedestrian ERA (3.62), he is projected for a solid chance at earning a win (41%), and also a great strikeout total (6.27 K over 6.35 IP). J.A. Happ Though an AL matchup in the Rogers Centre is generally daunting, the simulator projects J.A. Happ to match up well against the Rangers in his home park. According to the simulator, Happ and the Blue Jays are 67% likely to win at home against Derek Holland and the Rangers. As a result, Happ has the second highest probability of earning a W among all starting pitchers going today. His 0.51 W/G projection ranks second only behind Jacob deGrom’s projected 0.53 W/G vs the Padres. All this, plus a projected 3.22 ERA and 5.48 strikeouts, in 6.49 innings make J.A. Happ an appealing value play. Matt Cain Matt Cain has not been a good starting pitcher for quite some time. However, the context of his Thursday matchup makes him DFS relevant, particularly given his likely low ownership. Cain faces Chris Rusin and the Rockies in San Francisco, and the simulator projects the Giants to win about 60% of the time. Furthermore, the Rockies have a weak offense without their home park to inflate the numbers, particularly in a Giants home park that serves as somewhat of an antithesis to Coors Field (in 2015, Coors had the highest MLB basic park factor while AT&T had the lowest). The coalescence of home park advantage, low park factor, and weak opposing offense make Matt Cain a viable DFS value play. Streaming Options for Friday Chad Bettis (8% Y!) Chad Bettis faces Madison Bumgarner and the Giants in San Francisco on Friday. Despite the fact that the Giants are projected as having a 61% chance to win the game, Bettis still projects as an acceptable streaming candidate. His projected likelihood of earning a W is not great (31%), and his strikeout projection is also modest (4.40), but his run prevention is projected to be very good (2.46 runs in 6.41 innings for a 3.20 ERA). Tim Adleman (0% Y!) The early simulations for Friday’s matchup between the Brewers (Peralta) and the Reds (Adleman) have Cincinnati winning 59% of the time. Adleman will be making just his second MLB start, but the simulator projects him to do well based on his Minor League track record. The start is in Great American Ballpark, so projected run prevention is the weakest selling point for Adleman as a stream (2.75 runs in 5.91 innings for a 3.87 ERA). However, his W probability (41%) and projected strikeout total (5.59) make him an attractive option, especially for somebody who is so widely available. Conclusion There are countless ways in which you can create DFS strategies using SaberSim projections and optimization 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.