Predicting the Milwaukee Brewers Regression | Disciples of Uecker

Disciples of Uecker

We'd like to go to the Playoffs, that would be cool.

Through one month, the Brewers are off to a 20-8 start. I can’t really explain how or why this happened, but it did. 5.5 games up on the Cardinals, they are the surprise team in baseball, and back-to-back comeback, extra inning wins in St. Louis convinced a large number of people that this team isn’t just a fluke.

Like I said, I can’t pinpoint how the Brewers got off to such a great start on one thing. They’ve exceeded expectations, plain and simple. And for the team to exceed expectations, a significant amount of players have to do so.

Francisco Rodriguez won’t post a 0.00 ERA all season, Carlos Gomez won’t hit 42 home runs (probably), and Martin Maldonado won’t walk 22 percent of plate appearances.

Put simply, we can expect regression from both the Brewers as a team in the win-loss column, and from players individually. The regression we should expect to happen shouldn’t be for their performance to all of a sudden be terrible, but rather to regress to the expected, projected values. To simulate what we can expect/what may happen over the remaining 134 games, I combined the current numbers of some of the players off to the starts that vary most from their pre-season projections and balanced them out with those projections.

The number-crunching behind it wasn’t too difficult (even for a journalism major). I took the April numbers for the selected players and, because the season is 14/81 (17.3%) of the way done, I multiplied each player’s current slash line (and some other numbers that are incredibly higher than projected, like Maldonado’s BB%) by .173. I then took their PECOTA preseason projections and multiplied those figures by the remaining .827. Add the adjusted April numbers to the PECOTA adjusted numbers and there you have it.

In addition to that, I multiplied each selected player’s ZiPS projected WAR by .827 and added to their value from April.

Carlos Gomez

Current: .293/.352/.569, 7 HR (Adjusted: .051/.061/.098)

PECOTA: .251/.305/.413 (Adjusted: .208/.252/.342, 15.7 HR)

End-of-year projection: .259/.313/.440, 23 HR

Sidenote: The PECOTA projections for Gomez were a little pessimistic. ZiPS projected his OPS almost 60 points higher. 

WAR: 1.2 (Current), 3.3 ZiPS adjusted- 4.5 final

Jonathan Lucroy

Current: .295/.362/.432 (Adjusted: .051/.062/.075)

PECOTA: .272/.325/.410 (Adjusted: .225/.269/.339)

End-of-year projection: .276/.331/.414

WAR: 0.8 (Current), 2.8 ZiPS adjusted- 3.6 final

Lyle Overbay

Current: .279/.380/.395/.376 wOBA (Adjusted: .048/.066/.068/.065 wOBA)

PECOTA: .233/.313/.374/.306 wOBA (Adjusted: .193/.259/.309.253 wOBA)

End-of-year projection: .241/.325/.377/.318 wOBA

WAR: 0.4 (Current), 0.0 ZiPS adjusted- 0.4 final 

Sidenote: I don’t expect Overbay to finish with the same WAR he’s currently listed at. Either up or down from here. Hopefully up. 

Mark Reynolds 

Current: .224/.302/.500, 37.8 K%, 6 HR (Adjusted: .039/.052/.087, 6.5 K%)

PECOTA: .219/.321/436, 30.1 K% (ZiPS), 29 HR (Adjusted: .181/.265/.361, 24.9 K%, 25.3 HR)

End-of-year projection: .220/.317/.448, 31.8 K%, 31 HR

WAR: 0.5 (Current), 1.3 ZiPS adjusted- 1.8 final

Francisco Rodriguez 

Current: 0.00 ERA, 1.18 FIP, 12.94 K/9, 2.25 BB/9, 0.69 WHIP (Adjusted: 0.00 ERA, .20 FIP, 2.24 K/9, 0.39 BB/9, 0.119 WHIP)

PECOTA: 3.25 ERA, 3.72 FIP (Adjusted: 2.69 ERA, 3.08 FIP)

ZiPS: 9.81 K/9, 3.53 BB/9, 1.28 WHIP (Adjusted: 8.113 K/9, 2.92 BB/9, 1.059 WHIP)

End-of-year projection: 2.69 ERA, 3.28 FIP, 10.35 K/9, 3.31 BB/9, 1.178 WHIP

WAR: 0.8 (Current) 0.2 ZiPS adjusted- 1.0 final 

Martin Maldonado

Current: .294/.455/.353, 22.7 BB% (Adjusted:  .051/.079/.061, 3.9 BB%

PECOTA: .235/.298/.372, 6.1 BB% (ZiPS) (Adjusted: .194/.260/.324, 5.3 BB%)

End-of-year projection: .245/.339/.385, 9.2 BB%

WAR: 0.2 (Current), 0.9 ZiPs adjusted- 1.1 final


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