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Projecting Upside and Leveraging it for Your Play Style
Before we get into my favorite plays for tomorrow, I wanted to briefly talk about how I measure/define upside when researching KBO pitchers. For starters, there are often misconceptions about safety and upside. It might seem like those two things are positively correlated but that is not always true. Depending on your contest selection (cash or GPP), you are probably targeting different types of pitchers. In cash, the goal is to roster pitchers who are safer plays more often than not. When playing GPP Tournaments, it can be more beneficial to target upside instead of safety. To put it simply, “safety” and “upside” can be primarily defined by looking at an expected range of outcomes (this tool exists within our DFS Army Research Station). Here is an example to better portray what this might look like for you… Let’s assume the same matchup for the purpose of the exercise:
Pitcher A ($9,000): Scores between 15-25 fantasy points in 88% of his starts dating back to the beginning of last season. In his worst 5 starts, he averaged 12 fantasy points. In his best 5, he averaged 27.
Pitcher B ($7,800): Scores between 15-25 fantasy points in 46% of his starts dating back to the beginning of last season. In his worst 5 starts, he averaged 5.6 fantasy points. In his best 5 starts, he averaged 36.
Clearly, pitcher B is more volatile and would not be my first “cash” game pick. He isn’t trustworthy enough based on his likely range of outcomes to put up a solid score like pitcher A. In cash, a decent score from a player who is high-owned will not hurt your chances nearly as much as it would in GPP. Because 50% of players win in cash, we don’t have to take as many risks to profit – unlike GPP tournaments where a smaller number of people profit and a higher score is more important (the higher you score in GPP, the more money you can win per entry… in cash, you win the same amount whether you finish in the top 1% or barely hit the 50% threshold). Now, this is less about contest selection and more about upside so back to the main point 😊 So when specifically trying to determine upside, what should we be looking for? Here are a few quick indicators for me:
Price vs Range of Outcomes vs Ceiling
I love using our KBO research station to better understand scoring history for certain players and how I might be able to leverage their outcome range (see above example) against their price. In the above example, pitcher B has shown he can score higher than pitcher A at a discount of $1,200. *You can also employ a similar strategy for the site you play on by trying to gauge how the player price on DK differs from his price on FD or vice versa.
Matchup Ranks and Matchup History
Another key factor when determining pitcher upside potential is the opposing offense/where the rank in certain categories within the KBO. Specifically, I like looking at stats like OPS (on base + slugging), strikeouts (how often do they strike out relative to other teams) and walks (what is their plate discipline like). This is true on the micro level and also the macro level in terms of looking at past matchups of the pitcher vs team. How many times has the pitcher faced this offense so far this season and what were the outcomes? What about looking back to 2019? Baseball is beautifully mysterious in some ways and there are hitters who struggle against pitchers sometimes without any glaring statistic to point at. Matchup and matchup history matters.
WHIP and ERA are decent indicators that can help give us a general idea as to how well a pitcher has performed over the course of his season/career. However, there are a few other stats that I like to pay close attention to when digging for upside. These include:
FIP – Fielding independent pitching. Think of it like ERA but with only the things a pitcher has the most control over (strikeouts, walks, HBP, home runs) and removing balls hit in the field of play.
BABIP – Batting average on balls in play. This stat removes outcomes unaffected by the defense (primarily strikeouts and home runs) and like FIP, can help us identify luck and regression trends for pitchers. If a pitcher has a FIP lower than their ERA and a high BABIP, its fair to assume there will be some positive regression. This often leads us to finding pitchers who might be less expensive but still with solid potential upside.
K/9 – Strikeouts per 9 innings. Strikeouts are incredibly important for DFS purposes. Pitchers with high strikeout upside (and potentially in matchups against teams that strikeout a lot) oftentimes have an increased ceiling (although that can also mean more volatile pitching). A higher K/9 means more strikeouts per nine innings.
RS/9 – Run support per nine innings. This one is the least important of the others listed but is helpful when trying to identify other factors that might lead to a pitcher getting the win (4pts on DK and 6pts on FD). A higher RS/9 means their offense scores more runs during their outings. * I also like to combine RS/9 with sportsbook odds to better understand win likelihood.
😅 Whew! That might have been like drinking from a fire hose but I wanted to give a small glimpse into some of my process/motivation for the way I write these articles. There is no right or wrong process and the things listed above are not exhaustive but hopefully this helps give some background. Now let’s get on to those picks!
KBO Pitchers and Picks for 5/24
Here are some of my favorite plays for the upcoming KBO slate. I don’t love a ton on tonight’s slate, but there is a clear option for cash games and some riskier GPP plays. Lets get into it@ * indicates a left-handed pitcher.
Price: $8,900 | $27
Matchup: BA (8th) | OPS (8th) | SO (2nd) | BB (3rd)
Notes: going to be chalky, but by far the best option on the slate tonight. has a great matchup with HAN too and is our top projected P on the slate. This year so far, HAN has the highest K% on the slate vs hand of pitcher and Wright has a K per inning this year. I trust Wright the most in cash games and he even has the upside in GPPs with Hanwa striking out the 2nd most in the league this year and not faring well in other offensive categories
Chan Gyu Lim
Price: $7,200 | $25
Matchup: BA (2nd) | OPS (T1st) | SO (9th) | BB (8th)
Notes: much cheaper and is in a tough spot, but has looked good so far. KT Wiz has been good this year, one of the best teams on offense, but i think we can take a risk at him sine he’s been so good. hes averaging over a K per inning and even though he allowed 4 runs last start, still put up a good fantasy point outing on DK. Even though KTW is in the bottom of the standings, they still are hitting the ball well with the 2nd best average in the league. makes for a good GPP play though. Makes for a solid SP2 option on DK since he’s so cheap, but id find the 2 more dollars on DK here tonight.
Format: GPP (FD) , SP2 on DK
Min Woo Lee
Price: $7,000 | $24
Matchup: BA (9th) | OPS (10th) | SO (T2nd) | BB (9th)
Notes: cheap and facing the worst team in the league so far. SK ranks near the bottom in most categories on offense. They also have the lowest average too. Lee won’t really do too much to surprise you, but he’s cheap and has such a good matchup. Lee probably wont do much with upside, but i feel in this matchup he’s rather safe for cash games. I like using him as an SP2 on DK here since he’s so cheap, but on FD it’s a little harder to swallow. Still $3 cheaper on FD than Wright and has such a good matchup
Tier 3 – Other KBO Pitching Mentions
William Cuevas ($7,800 | $25) – gives up a ton of runs lately, but was able to salvage it with 7 K’s last start. He has the K potential to put up a good start, but is in a tougher matchup here. I dont love pitching today, so an SP2 is going to be hard to come by this morning. He has shown the K upside and pitching on this slate like I said isn’t the best. I have more confidence in him than some of the other options. He does rank as our 3rd highest proj pitcher on our Research Station though.
OPS (On-base plus Slugging)
K/9 (Strikeouts per 9 innings)
ERA (Earned Run Average)
WHIP (Walks and Hits per Inning Pitched)
QS (Quality Start)
IP (Inning Pitched)
ER (Earned Run)
KBO (Korean Baseball Organization)
LHP (Left Handed Pitcher)
BABIP (Batting Average Balls in Play)
Chalky (High Ownership)
RS/9 (Run support per 9 innings)
GPP (Guaranteed Prize Pool)