Article: What the Brewers' Offense Most Needs to Change in 2023

[Caleb Miller]

The Milwaukee Brewers' offense was better than its raw numbers might have indicated last season, but they could be endlessly frustrating. The culprit, and the thing the team most needs to shift going into 2023, might be an insufficient ability in an increasingly neglected column of the stat sheet.

Image courtesy of © MARK HOFFMAN/MILWAUKEE JOURNAL SENTINEL / USA TODAY NETWORK

Batting average has become a forgotten statistic in modern baseball and is no longer the main focus in evaluating a player. Since the concept of Moneyball came around, teams have focused on more robust statistics, such as weighted on-base average (wOBA) or weighted runs created plus (wRC+), rather than the good, old-fashioned batting average when putting a dollar sign on the metaphorical muscle. The Brewers are one of these teams. 

During the 2022 season, the Brewers held a team batting average of .235, ranking 22nd in MLB. Despite this, they ranked 10th in runs, due to their impressive home run production. They ranked third in MLB in long balls. From an outside perspective, it seemed the Brewers’ strategy was to get on base and swing for the fences during every at bat. They appear to have disregarded batting average, and focused more on players’ slugging percentage and home run rates to increase scoring. While this offensive strategy worked to an extent, it created some problems. 

Diving into situational statistics, with fewer than two outs and a runner on third base, the Brewers scored only 48.9% of the time, ranking them 25th in MLB. Considering that all one would need to score in this situation is a sacrifice fly or a base hit, it is a little ridiculous that their scoring percentage is so low. 

It’s so easy to remember the moments in 2022 where the bases were loaded for Milwaukee with no outs, and nobody scored. A higher batting average is what the Brewers needed, but how much of an impact would it have had?

With runners in scoring position, the Brewers had 295 hits with 464 runs batted in, according to Baseball Reference. This resulted in around 1.57 runs per hit with runners in scoring position. If the Brewers were to increase their batting average to .260 with runners in scoring position, they would produce around 313 hits. If we factor in the 1.57 runs per hit, the Brewers would acquire about 27 extra runs. 

The Brewers had an expected winning percentage of .526 for the 2022 season. An added 27 runs would have given the Milwaukee Brewers an expected winning percentage of .544, and an actual winning percentage that good would have gotten them into the playoffs. 

The Brewers had a decent offense for 2022, but it was clear that they struggled. Although it isn’t the end-all be-all, finding some way to increase the team batting average would certainly help this Brewers offense going into the 2023 season. 

Earlier this week, right here at Brewer Fanatic, Tim Muma and Matthew Trueblood each wrote articles about how the team might achieve that goal. Tim's was about Rowdy Tellez; Matthew's focused on Luis Urías. It would come at the cost of some of the pitches they see and the walks they draw, but it would also likely cut down their strikeout rate, which was the ninth-highest in MLB. Only three teams put the ball in play less often than did Milwaukee last year. Their offense will be more dynamic if they edge closer to the middle of the pack in 2023.

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[Brock Beauchamp]

Wins may be the most important thing in baseball but the team needs to be watchable, too. And there were stretches of Brewers baseball that I just turned off because of things like their sub-50% ability to score a runner from third with less than two outs.

Please fix this, if only for my sanity. 

[sveumrules]

Something to keep in mind about batting average is that AmFam is one of the hardest stadiums to hit singles in, last playing above average for singles in 2014.

Here are AmFam’s individual season StatCast Park Factors for singles…

2022: 87 (30th)
2021: 97 (20th)
2019: 91 (29th)
2018: 95 (23rd)
2017: 98 (18th)
2016: 91 (28th)
2015: 94 (23rd)
2014: 102 (8th)

Meanwhile, here are individual season HR ratings at AmFam over that same time frame…

2022: 117 (9th)
2021: 103 (12th)
2019: 105 (11th)
2018: 108 (11th)
2017: 109 (11th)
2016: 113 (10th)
2015: 134 (2nd)
2014: 119 (6th)

I like that the FO has appeared to trend increasingly towards more contact oriented hitters recently, but it might end up being a suboptimal strategy at AmFam.

[brewcrewdue80]

3 hours ago, sveumrules said:

Something to keep in mind about batting average is that AmFam is one of the hardest stadiums to hit singles in, last playing above average for singles in 2014.

Here are AmFam’s individual season StatCast Park Factors for singles…

2022: 87 (30th)
2021: 97 (20th)
2019: 91 (29th)
2018: 95 (23rd)
2017: 98 (18th)
2016: 91 (28th)
2015: 94 (23rd)
2014: 102 (8th)

Meanwhile, here are individual season HR ratings at AmFam over that same time frame…

2022: 117 (9th)
2021: 103 (12th)
2019: 105 (11th)
2018: 108 (11th)
2017: 109 (11th)
2016: 113 (10th)
2015: 134 (2nd)
2014: 119 (6th)

I like that the FO has appeared to trend increasingly towards more contact oriented hitters recently, but it might end up being a suboptimal strategy at AmFam.

This is a weird stat without changing the field dimensions or other teams changing field dimension or new ball parks.  We have the dome ability to block bad weather. So if not the addition of the 3 factors I mentioned above, how do you adjust singles ball park factors over the years? Does this number come as a reflection to the Pitching on the mound for both teams? The hitters and the combined k rate?  

[sveumrules]

17 minutes ago, brewcrewdue80 said:

This is a weird stat without changing the field dimensions or other teams changing field dimension or new ball parks.  We have the dome ability to block bad weather. So if not the addition of the 3 factors I mentioned above, how do you adjust singles ball park factors over the years? Does this number come as a reflection to the Pitching on the mound for both teams? The hitters and the combined k rate?  

The numbers jump around considerably year to year because every season sees a different array of players with a different array of results. The ball changing year to year (and even within any given year) plays a large roll too.

League average OPS has jumped around pretty considerably over the same time frame from 711 (in 2014) to 733 to 750 to 762 to 740 to 769 to 739 to 706 (in 2022), so components thereof doing the same, especially when isolated to a tiny sample of only 81 games at one stadium isn't really that out of the ordinary.

This is the methodology quoted on the StatCast page...

"Statcast park effects show the observed effect of each displayed stat based on the events in the selected park. Each number is set so that “100” is average for that metric, and the park-specific number is generated by looking at each batter and pitcher, controlled by handedness, and comparing the frequency of that metric in the selected park compared to the performance of those players in other parks."

Here is the full array of single season data for AmFam going back to 2002. If you click over to "Three Year Rolling: Yes" it smooths out the results considerably as they encompass more data.

 

[brewcrewdue80]

1 hour ago, sveumrules said:

The numbers jump around considerably year to year because every season sees a different array of players with a different array of results. The ball changing year to year (and even within any given year) plays a large roll too.

League average OPS has jumped around pretty considerably over the same time frame from 711 (in 2014) to 733 to 750 to 762 to 740 to 769 to 739 to 706 (in 2022), so components thereof doing the same, especially when isolated to a tiny sample of only 81 games at one stadium isn't really that out of the ordinary.

This is the methodology quoted on the StatCast page...

"Statcast park effects show the observed effect of each displayed stat based on the events in the selected park. Each number is set so that “100” is average for that metric, and the park-specific number is generated by looking at each batter and pitcher, controlled by handedness, and comparing the frequency of that metric in the selected park compared to the performance of those players in other parks."

Here is the full array of single season data for AmFam going back to 2002. If you click over to "Three Year Rolling: Yes" it smooths out the results considerably as they encompass more data.

 

You can't sell me on this one.  This doesn't sound like Park Factors at all.  Determined by looking at each pitcher and batter, controlled by handedness and comparing the frequency of that metric in a selected park to the performance of the players in those other parks.  So it's a guess.  An assumption.  I mean the sample size to create such a number and then implement players in a different ballpark and guess the results at that ball park.  You would be putting pitchers and players in ballparks where they didn't even play in, in to that equation.  Brewer hitters strike out a ton as do opposing hitters vs Brewer Batters.  So either that is a huge factor in this ranking, or the sample size they are taking from Miller Park numbers is smaller than typical ballparks. 

2014: Brewer pitchers at home  21.713 k pct  Batters at home  18.574 k pct

2022:Brewer pitchers at home 26.937 k pct  Batters at home 24.538 k pct. 

So if striking out goes in to this park factor well that's quite the change right there between 2014 and 2022.  Or like I said reduces the amount balls put in play making a smaller sample determining this park factor on singles.

Brewer bats overall hit .235 at home in 22  .258 at home in 2014

Pitchers against  .218 at home in 22   against .242 at home in 2014.  

You can see how projections works with K pct affecting Batting averages. 

[sveumrules]

12 minutes ago, brewcrewdue80 said:

You can't sell me on this one.  This doesn't sound like Park Factors at all.  Determined by looking at each pitcher and batter, controlled by handedness and comparing the frequency of that metric in a selected park to the performance of the players in those other parks.  So it's a guess.  An assumption.  I mean the sample size to create such a number and then implement players in a different ballpark and guess the results at that ball park.  You would be putting pitchers and players in ballparks where they didn't even play in, in to that equation.  Brewer hitters strike out a ton as do opposing hitters vs Brewer Batters.  So either that is a huge factor in this ranking, or the sample size they are taking from Miller Park numbers is smaller than typical ballparks. 

2014: Brewer pitchers at home  21.713 k pct  Batters at home  18.574 k pct

2022:Brewer pitchers at home 26.937 k pct  Batters at home 24.538 k pct. 

So if striking out goes in to this park factor well that's quite the change right there between 2014 and 2022.  Or like I said reduces the amount balls put in play making a smaller sample determining this park factor on singles.

Brewer bats overall hit .235 at home in 22  .258 at home in 2014

Pitchers against  .218 at home in 22   against .242 at home in 2014.  

You can see how projections works with K pct affecting Batting averages. 

It’s not a guess. It’s based on every player’s (both Brewers and opponents)  collective performance in AmFam for that season versus those same players’ collective performance in all other parks for that same season.

There are also columns for K/BB because different stadiums have exerted observed effects in those areas over numerous seasons of results with changing player pools. The most extreme example being Coors which is bright red across the board on Three Year Rolling except for the solid blue line for K and lighter blue line for BB.

Yes, as singles become less common the sample size influencing that specific park factor will necessarily be smaller and subject to greater year over year variation as visible in the OP. That’s why (similar to defensive metrics or reliever stats or platoon splits or even just player performance in general) it’s best to look at multiple seasons to get a more reliable idea of what is going on.

[brewmann04]

They need to better with RISP 

[MVP2110]

47 minutes ago, brewmann04 said:

They need to better with RISP 

The Brewers literally had the 2nd highest OPS with RISP last year

[sveumrules]

2 minutes ago, MVP2110 said:

The Brewers literally had the 2nd highest OPS with RISP last year

Yup, problem was they were only 20th in PAs with RISP.

They need to better get RISP.

[Brock Beauchamp]

12 hours ago, sveumrules said:

They need to better get RISP.

One might even say the Brewers need to be RISPy.

[brewcrewdue80]

16 hours ago, sveumrules said:

It’s not a guess. It’s based on every player’s (both Brewers and opponents)  collective performance in AmFam for that season versus those same players’ collective performance in all other parks for that same season.

There are also columns for K/BB because different stadiums have exerted observed effects in those areas over numerous seasons of results with changing player pools. The most extreme example being Coors which is bright red across the board on Three Year Rolling except for the solid blue line for K and lighter blue line for BB.

Yes, as singles become less common the sample size influencing that specific park factor will necessarily be smaller and subject to greater year over year variation as visible in the OP. That’s why (similar to defensive metrics or reliever stats or platoon splits or even just player performance in general) it’s best to look at multiple seasons to get a more reliable idea of what is going on.

It'll be interesting to see where the Brewers rank over the next 3 years when Frelick, Mitchell, Chourio, and Wiemer take on full time rolls. Contreras and Turang as well. The k pct should lower, BA higher so do we go back above 15th or stay lower 6.

[endaround]

38 minutes ago, brewcrewdue80 said:

It'll be interesting to see where the Brewers rank over the next 3 years when Frelick, Mitchell, Chourio, and Wiemer take on full time rolls. Contreras and Turang as well. The k pct should lower, BA higher so do we go back above 15th or stay lower 6.

There is a lot of wish casting on this forum of the Brewers getting in high contact, high average, and low K players.  This is not a new thing (Luis Urias was going to be  new model of Brewer player who hits .300 and doesn't strike out!). But that isn't what is happening.  Frelick is that, but those others are not. 

Mitchell and Wiemer are high K players likely with K rates near 30% or even higher. Wiemer may bring his down to mid 20s. Contreas is a pretty high K player as well, with a K rate above 25%. Turang is a low average moderate K player though his K rate of near 20% in AAA main mean a higher rate in MLB.

[brewcrewdue80]

18 minutes ago, endaround said:

There is a lot of wish casting on this forum of the Brewers getting in high contact, high average, and low K players.  This is not a new thing (Luis Urias was going to be  new model of Brewer player who hits .300 and doesn't strike out!). But that isn't what is happening.  Frelick is that, but those others are not. 

Mitchell and Wiemer are high K players likely with K rates near 30% or even higher. Wiemer may bring his down to mid 20s. Contreas is a pretty high K player as well, with a K rate above 25%. Turang is a low average moderate K player though his K rate of near 20% in AAA main mean a higher rate in MLB.

Looks like for Urias he changed his approach to hit more HRs which got him his debut. With the shift ban, the launch angle craze may dwindle a little not focusing on hitting it over well placed fielders to even over the wall and being able to send solid contact through the holes that wasn't there the previous seasons.  All the guys I listed except Frelick are 23-26 k pct.  I'll wait til they are through their age 27 season before believing they can't improve their contact skills.