Analyzing Past and Future Lineup Performance

For those of us who play in DFS or play in leagues with daily lineups, pitching matchups can be essential. We can always try and rely on the top pitching options, but what if we are either trying to draft a cheaper pitcher in DFS or stream a pitcher with a favorable matchup? Knowing the effectiveness of the opposing lineup is important, and that’s what we’re going to look at this week.

I’d be remiss if I didn’t give the small sample size caveat, since we are looking at two weeks of team lineup data, so we’re also going to look at Steamer projections for the rest of the season to see if what teams have done so far is sustainable or just a small sample size fluke.

Rather than deep dive into every available statistic, I have chosen to look at K% and Runs per game for each team across the first two weeks of baseball. These two stats were chosen because K’s can provide value even if the pitcher gives up some baserunners and runs, so it essentially covers you in case your pitcher has an otherwise off outing. Runs per game are pretty obvious since just because your pitcher racks up strikeouts, if the lineup is scoring runs, you are likely getting crushed in those other categories. So a lineup that strikes out and struggles to score is a lineup I tend to stream against. I have also ranked a team’s K% in descending order and their Runs per game in ascending order, which may seem counterintuitive, but there is a method to my madness. I wanted to be able to create an aggregate of these rankings in order to see who are the worst performing lineups versus the best. So, as can be seen at the top of the table below, a team that ranks 1st in both categories will receive an aggregate of 1, which is not good at all. So here is the table of every teams’ K% and amount of runs scored per game:

Team Lineup Data Through 4/16/2021
Team K% Rank K%(Descending) Runs/Game Rank of Runs/Game (Ascending) Aggregate Rankings
CHC 29.40% 1 2.62 1 1.00
DET 27.60% 5 3.79 6 5.50
BAL 29.00% 2 4.14 10 6.00
TEX 28.80% 3 4.07 9 6.00
PHI 28.00% 4 3.92 8 6.00
SFG 25.40% 12 3.23 2 7.00
TBR 26.10% 8 4.14 10 9.00
MIL 27.00% 6 4.15 13 9.50
PIT 25.60% 11 4.14 10 10.50
OAK 25.70% 10 4.21 14 12.00
NYY 24.10% 18 3.85 7 12.50
CLE 22.60% 21 3.77 5 13.00
SEA 25.80% 9 4.50 17 13.00
NYM 22.50% 22 3.63 4 13.00
WSN 22.20% 24 3.45 3 13.50
MIA 25.30% 13 4.54 18 15.50
COL 24.20% 17 4.23 15 16.00
TOR 25.20% 14 4.54 18 16.00
KCR 26.20% 7 5.09 25 16.00
ATL 25.10% 15 4.57 20 17.50
STL 24.50% 16 4.77 22 19.00
ARI 23.00% 20 4.71 21 20.50
MIN 24.10% 18 4.79 23 20.50
SDP 18.30% 29 4.27 16 22.50
CHW 22.50% 22 5.00 24 23.00
BOS 22.20% 24 5.77 28 26.00
LAA 22.10% 26 5.46 27 26.50
HOU 18.30% 29 5.31 26 27.50
CIN 21.80% 27 6.54 30 28.50
LAD 20.70% 28 6.14 29 28.50

Based on this table, you should be streaming pitchers pitching against the Chicago Cubs as often as possible. They are striking out the most in baseball and scoring by far the least amount of runs in baseball. At least for now, which we’ll look at later on. The Detroit Tigers and Texas Rangers are not surprising names to see near the top of teams to stream against, but Philadelphia is an interesting name to see. Largely because of that 28% K rate that will likely not persist, but good on you if you picked up on their early lineup struggles and found some good starts against them.

The San Francisco Giants are one of the teams I have been keying on streaming against early on and they’ve paid off with the lack of runs they are scoring. Even though they are not striking out at as high of a rate as some of these other teams, they are making weak contact and have one of the lowest wOBA’s in baseball (.293). Pittsburgh, on the other hand, is also a team I have been streaming against and I have not had the same type of luck against. They have a similar strikeout rate to the Giants, but it seems their hits are falling as they have a robust .311 BABIP, so I would expect their performance to drop somewhere between where they are now (which still isn’t great) and the Giants.

The previous table tells us where teams are two weeks in the season. Let’s look at how these current numbers match up with how Steamer thinks they will trend for the rest of the season:

Steamer Lineup Data Through 4/16/2021
Team Runs/Game Rank Runs/Game (Ascending) Expected Runs per Game Rank Expected Runs (Ascending) Expected vs Actual K% Expected K% Expected vs Actual K%
CHC 2.62 1 3.89 8.00 1.28 29.40% 23.89% -5.51
NYY 3.85 7 4.95 30.00 1.11 24.10% 23.61% -0.49
NYM 3.63 4 4.28 19.00 0.65 22.50% 22.30% -0.20
SFG 3.23 2 3.81 5.00 0.57 25.40% 21.04% -4.36
WSN 3.45 3 3.87 6.00 0.42 22.20% 22.18% -0.02
DET 3.79 6 4.20 15.00 0.41 27.60% 24.18% -3.42
CLE 3.77 5 4.12 13.00 0.35 22.60% 21.67% -0.93
TOR 4.54 18 4.87 29.00 0.33 25.20% 21.87% -3.33
OAK 4.21 14 4.43 24.00 0.22 25.70% 23.98% -1.72
SDP 4.27 16 4.43 23.00 0.16 18.30% 21.26% 2.96
PHI 3.92 8 4.06 11.00 0.14 28.00% 21.78% -6.22
TBR 4.14 10 4.23 16.00 0.09 26.10% 24.37% -1.73
TEX 4.07 9 4.11 12.00 0.04 28.80% 25.25% -3.55
MIL 4.15 13 3.99 10.00 -0.17 27.00% 24.32% -2.68
ATL 4.57 20 4.34 20.00 -0.23 25.10% 22.20% -2.90
MIN 4.79 23 4.55 26.00 -0.24 24.10% 22.65% -1.45
COL 4.23 15 3.90 9.00 -0.33 24.20% 24.08% -0.12
SEA 4.50 17 4.13 14.00 -0.37 25.80% 25.50% -0.30
BAL 4.14 10 3.72 4.00 -0.43 29.00% 22.80% -6.20
CHW 5.00 24 4.52 25.00 -0.48 22.50% 23.08% 0.58
HOU 5.31 26 4.80 28.00 -0.51 18.30% 19.50% 1.20
PIT 4.14 10 3.58 2.00 -0.56 25.60% 21.94% -3.66
KCR 5.09 25 4.27 18.00 -0.82 26.20% 22.52% -3.68
STL 4.77 22 3.88 7.00 -0.89 24.50% 22.66% -1.84
ARI 4.71 21 3.69 3.00 -1.03 23.00% 21.09% -1.91
MIA 4.54 18 3.48 1.00 -1.06 25.30% 23.21% -2.09
LAA 5.46 27 4.35 21.00 -1.11 22.10% 20.97% -1.13
BOS 5.77 28 4.42 22.00 -1.35 22.20% 22.69% 0.49
LAD 6.14 29 4.57 27.00 -1.57 20.70% 21.15% 0.45
CIN 6.54 30 4.23 17.00 -2.30 21.80% 22.83% 1.03

Steamer expects some marked improvement from the Cubs, but not enough to say stop streaming against them. Sure, they should strike out at a lower clip and score over a run more per game, but that still has them scoring less than 4 runs a game. Nothing I am really scared of. The Phillies see the biggest change in their strikeout rate, but that’s interestingly not translating into a lot more runs. Although the data so far this season shows the Yankees may be a good team to stream against scoring less than 4 runs a game, Steamer does not think this will continue and I tend to agree, giving them the second largest bump in runs scored behind the Phillies.

Some teams I am noting who were not on the initial list of teams who were good to stream against are the Miami Marlins and the Arizona Diamondbacks. Both teams are expected to drop their runs scored per game by a full run, but I am feeling a lot more comfortable with the Marlins than the Diamondbacks. Though the Marlins’ K% should improve, their lineup is one without a lot of firepower and could be safer bet to yield a few runs though striking them out may prove to be harder as the year progresses. The Diamondbacks, though are projected for under 4 runs per game for the rest of season, also have a .259 BABIP and strikeout at a lower rate than most of the league. This doesn’t necessarily mean all that contact will yield more hits, but I am going to be a little more cautious with them.

A lot of the other teams expected to score less runs by a potentially significant margin are not teams I am ready to stream against yet. Sure, the Cincinnati Reds are scoring an absurd amount of runs right now, but even if and when they regress, I don’t think they are stream-worthy. Same thing with the Boston Red Sox and Los Angeles Angels of Anaheim, and I really don’t know what to tell you if you’re streaming against the Los Angeles Dodgers.

Trying to pick pitching matchups against struggling lineups is a tough business and even when the stars are aligned with the perfect matchup, crazy things can happen, so be forewarned. I mean, even the worst lineups are going to hit awful pitching, so make sure when playing matchups and streaming, you don’t overvalue the ineptness of the lineup so far in favor of a struggling pitcher. It is important to pick your spots and hopefully these tables can give you a better idea of what spots to pick.





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MiamiWeiss21
3 years ago

I would love to have that first table as a running tab on my browser all season…. is that possible? haha 😉 In all seriousness, is there a point where runs/gm and k% stabilize/normalize on a team wide basis? Say may 1st? Or is it only reliable in a 30 day range or so due to personnel changes? Cool data point for the streamer! thanks!