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.

When I analyze a starting pitcher’s strikeout rate spike, I want to see that it’s driven by an increase in swings and misses induced. It could come from other avenues — a higher rate of strikes thrown or more called or foul strikes. But in my eyes, the most believable way to sustain that strikeout rate surge is by generating additional whiffs. So below are the seven American League starting pitchers that have increased their SwStk% marks the most compared to last season.

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I shop in the bargain bins when it comes to pitching, and I usually do okay. But there’s a pitfall to shopping in those bins, and it comes from velocity. Or lack thereof — the lightly touted, the guys with no pedigree, the guys you find in those bins, they usually don’t have big fastballs. Or they’d be the darling of every scout.

So what, you might say. If they have command and great secondary stuff, then they can ball. Look at Aaron Nola!

Yes, that’s true. But there are inherent difficulties with a bad fastball. So let’s rummage through the bad fastball bucket and see what we find.

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Three years ago, I introduced the best pitcher expected walk percentage formula yet. The formula uses a pair of strike type rates found at Baseball-Reference.com, including a pitcher’s in-play strike percentages, as well as his overall rate of strikes thrown. The beauty of the equation is that it uses components that stabilize quickly, as the rates are per pitch, rather than per inning or per batter. The equation isn’t nearly as strong as my xK% one, as it’s clearly missing sequencing, which may or may not be a consistent skill. But it’s pretty darn good and the best we have at the moment.

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Never before have we seen so many talented young pitchers. And, although I don’t have concrete evidence to support it, it feels like we have never seen so many name-brand starting pitchers struggle.

Everyone slumps. David Price, for example, is slumping. But with an atrocious strand rate (LOB%) and elevated batting average on balls in play (BABIP), it’s the type of slow start that savvy fantasy owners should target as a buy-low opportunity.

Other starters enduring equally slow starts can’t be defended quite as easily. Inversely, still more starters are masking their ugly peripherals with typical production, as expected. You may want to consider selling the names below. All three make me sad because, while not especially old, each of them has stared down his mortality at one point or another this season, as we normal folk do every day when we look in the mirror. All our demises are imminent, a truth made painfully true by the beautiful yet cruel sport we love so.

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Three years ago, I introduced the best pitcher expected walk percentage formula yet. The formula uses a pair of strike type rates found at Baseball-Reference.com, including a pitcher’s in-play strike percentages, as well as his overall rate of strikes thrown. The beauty of the equation is that it uses components that stabilize quickly, as the rates are per pitch, rather than per inning or per batter. The equation isn’t nearly as strong as my xK% one, as it’s clearly missing sequencing, which may or may not be a consistent skill. But it’s pretty darn good and the best we have at the moment.

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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.

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It’s that time of year again, American League starting pitcher tier update time! You are no doubt well aware by now that ERA means literally nothing to me this early in the season. Player movement between tiers will only occur when there’s a change in underlying skill, pitch mix, or velocity.

Tiers are named for the best characters on the brilliant FXX show, Man Seeking Woman.

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It’s understandable if you came into the season with Chris Tillman buried on your starting pitcher list. After back-to-back intriguing seasons in 2013-14, he ran all the back toward and even beyond his ominous FIP numbers with a 4.99 ERA in 173 innings. In those two solid seasons, he posted a 3.52 ERA, but was all the way up at a 4.22 FIP. An already-tenuous skillset sank further, yielding a 1.9 K:BB ratio and took Tillman off the radar in just about every league type.

On Tuesday night he dropped seven strong on the Yankees, shrinking his ERA to 2.81 and tying a career-high with nine strikeouts (7th ever, 2nd this year). This time around, there’s actually support for his numbers. He has a 2.64 FIP thanks in large part to a 26% strikeout rate and just 24 hits allowed in 32 innings. His 9% walk rate is a little high, but workable with those strikeout and hit rates for sure. His 11% swinging strike rate is far and away a career-high and supports the surge in punchouts.

What’s Tillman doing to draw such strong results? Let’s take a look at the three main areas that I (and most, I think) often look to first when a pitcher is showing a big change in performance, for better or worse.

VELOCITY

I’m fairly certain that velocity is the first check for everybody when seeing what’s up with a pitcher. Brooks has Tillman up over a full tick at 93.8 MPH – a career-best and his first time north of 93 on average since 2012. The cutter is the only other pitch where more velocity would help and while he is up, it’s negligible at just 0.6 MPH. The 87.4 MPH mark is second-best in his career behind the 87.5 he logged in 2013. His velocity increase is a tangible, positive change, but it alone certainly doesn’t explain this jump in performance.

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A few weeks back, I looked at hitter stats that you can use early in the season. And they presaged the Domingo Santana mini-breakout! Now it’s time to look at pitchers, and let you into my toolbox.

There will be leaderboards.

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