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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.
Advanced Statistics
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 5/26
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.
Tier 1
Chris Flexen
Team: Doosan
Price: $8,700 | $27
Matchup: ISO (9th) | wOBA (10th) | SO (6th) | IRT (10th)
Notes: Going to be chalky, but by far the best option on the slate tonight. He gets to face an SK team that has been scuffling all year, and they also don’t hit for much power as they are ranked 2nd to last in the KBO in team ISO. He’s also the heaviest favorite on the night, as Doosan has one of, if not the best offense in the league to provide run support. Throw in the fact that he also averages 1.1 K’s per inning along with going 3/3 in quality starts on the year and you have my favorite pitching option on the night.
Format: ALL (FD) | SP/1 (DK)
Tier 2
Tyler Wilson
Team: LG Twins
Price: $8,900 | $26
Matchup: ISO (6th) | wOBA (6th) | SO (7th) | IRT (8th)
Notes: Wilson is actually my second favorite option on the slate, as while Koo is also a heavy favorite much like Flexen, Kiwoom actually projects to hit lefties pretty well. Instead, I’ll pivot to Wilson who is cheaper on DK as well. People will be a bit thrown off by his high ERA, but that was due to a blow up in his first start. Over his last 2 starts he’s going 13 innings with 13 K’s, allowing 4 runs and has a WHIP of under 1. This Hanwha team has been pretty bad offensively this year as well and they have one of the lowest IRT’s on the night.
Format: ALL (FD) | SP/2 (DK)
Chang-Mo Koo
Team: NC Dinos
Price: $9,600 | $26
Matchup: ISO (6th) | wOBA (6th) | SO (1st) | IRT (9th)
Notes: Koo is going to be GPP only for me tonight, as the matchup is really not great for him despite being a heavy favorite. This will be a battle of the titans here, as Kiwoom has destroyed LHP’s so far this year, and Koo has been basically un-hittable with a 0.41 ERA over 3 starts. His price is the main downside on DK, but he does average more than 1K/IP. However, with Byung-Ho Park the lefty killer and this Kiwoom offense heating up, I don’t see him going unscathed here. I’d say 6 IP, 2/3 ERs and 5-7 K’s is a pretty likely outcome.
Format: GPP (FD) | SP1/2 on DK
Dan Straily
Team: Lotte
Price: $7,300 | $24
Matchup: ISO (8th) | wOBA (9th) | SO (3rd) | IRT (7th)
Notes: Straily was a human pitching machine in the MLB, but his ability to pitch to contact as makes his pitching style fit well in the KBO. He gets a solid matchup here as Samsung ranks 8th in team ISO and 9th in wOBA (for reference there are only 10 teams in the KBO). They also have one of the lowest IRT’s on the slate and Straily has actually been pretty damn successful so far this year. He averages about 1.1 K’s/IP and has a K/BB ratio of 2.5/1. His main issue here is going to be the same one he had in the MLB, giving up the long ball. But with how Samsung has been offensively this year I don’t see him blowing up in this spot at, and he’s priced nicely on both sites.
Format: GPP (FP) | SP/2 (DK)
Tier 3 – Other KBO Pitching Mentions
Chae-Heung Choi ($7,800 | $25) – Lotte has started to scuffle a bit over the last week, as they’ve scored only 18 runs over their last 6 games, and 9 of those game in one game. They’ve been held to 2 runs or less in 4 of those last 6. Choi has been really solid for this Samsung team starting out 3-0 with a 2.65 ERA. He doesn’t have a ton of K potential, but batters just aren’t squaring him up as he’s allowed on 4 extra base hits on the year. Solid hedge type play here tonight as people tend to like to pick on Samsung pitchers.
Drew Gagnon ($6,700 | $24) – This game may not play due to rain, so he’s going to be a strict GPP option here tonight based on weather. He has the highest K% on the slate as he’s K’ed 23 hitters in 16 1/3 innings pitched. KT has also been bitten by the injury bug so their lineup isn’t a worrisome as it normally is. Stay sharp on the weather reports tonight, because he has GPP winning upside if this game plays.
Glossary
OPS (On-base plus Slugging)
SO (Strikeout)
K/9 (Strikeouts per 9 innings)
BB (Walk)
ERA (Earned Run Average)
WHIP (Walks and Hits per Inning Pitched)
QS (Quality Start)
IP (Inning Pitched)
ER (Earned Run)
R (Run)
DK (DraftKings)
FD (FanDuel)
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)