FanPost

Pre/Post All-Star Game Performance: Boston Red Sox

I’ve been a reasonably long time lurker here on BtB and I recently decided to try my hand at writing about the sport I love. I’m hoping this fanpost is mildly interesting and reasonably sabermetrically sound. I think it provides some insight into the 2nd half of the season and what we maybe can expect. I apologize in advance for my attempts at sarcastic humor, and if it reads a little article-ly, and for novice excel-ing.

We hear all the time about how players perform better or worse in the second half of the season. For example, Aramis Ramirez of the Chicago Cubs has posted .827 OPS before the All-Star Game and .866 after the game over his career. The slight .039 increase could theoretically indicate the Cubs will get a tiny offensive boost (or so they’re hoping). On the other hand, Adam Dunn of the Natinals (okay really the Washington Nationals) has posted .922 before and .882, which means that .040 drop in OPS will make any remaining Nationals fans cry more over their offense.

We’re going to look at the career hitting splits of the major hitters and pitchers of each team and that are contributors (some DL’s withheld, and there’s a bit of subjectivity here). Then we added them up into team stats, and attempted to convert those team stats into runs (ultimately wins) above replacement. For those of you interested in the methodology, we calculated wOBA and FIP (tRA would have been too tricky) for the respective halves based on combining each player’s career splits and then projected those runs over a half season’s worth of plate appearances and innings.

To recap, we essentially added up all the career split stats and converted to Runs Above Replacement. Sure, there’ll be arguments that certain players might have deteriorated, but that’s no different than what commentators already do when comparing pre/post ASB stats. Plus, we’re also that hoping that our team sample size drowns out any irregularities.

But why go through all this trouble? (and believe me, it took a long time since we don’t know how to webcrawl yet) Well, theoretically it should measure how much better or worse the 2nd half team is compared to the 1st half team in terms of (theoretical) wins. Granted, it doesn’t necessarily mean that the team’s themselves are any worse, but it could forecast better or worse performance

Let’s take a look at the AL leaders: the Boston Red Sox.

 

BOS

1st Half

2nd Half

∆RAR

Batting

90.6

78.0

12.62

SP

85.0

78.9

6.10

RP

35.3

37.2

-1.82

Total

210.9

194.0

16.90

 

We’ve broken it down into 3 areas: hitting, starting pitching, and relievers. Looking at the data it appears that we can expect Boston’s dangerous offense to cool off by about 10 runs (or 1 win), their starting pitching to be worse by about half a win, and their relief pitching to be slightly better. So theoretically, we can expect the 2nd half Boston Red Sox team to be a little worse than the 1st half Boston Red Sox. It’s important to note that these are theoretical wins, not actual wins, which essentially means that if the 1st half and 2nd half teams were to play over the course of half a season, the 2nd half team would come out 16.9 runs, or 1.69 wins, worse.

Let’s go a bit more in-depth:

Batting

BA

OBP

SLG

OPS

BB%

K%

wOBA

1st Half

0.280

0.357

0.464

0.821

10.1%

16.1%

0.365

2nd Half

0.276

0.354

0.455

0.809

10.3%

16.9%

0.360

Diff

0.004

0.003

0.009

0.012

-0.2%

-0.9%

0.005

 

You can see from the hitting table that historically the Red Sox hitters on the current team are slightly worse across all 3 major categories BA/OBP/SLG in the 2nd half of the season, which naturally translates into a slightly lower offensive output. It would also appear that while their walk percentage remains about the same, hitters take a few more strikes.

Pitching

W-L%

ERA

WHIP

K/9

BB/9

HR/9

IP/GS

FIP

1H-SP

0.576

3.81

1.29

7.2

3.10

0.86

6.39

3.93

2H-SP

0.580

3.85

1.26

7.3

2.94

0.98

6.46

4.04

Diff

-0.004

-0.04

0.03

-0.03

0.16

-0.12

-0.07

-0.11

 

For those of us that are fans of the first 3 columns (we prefer not, but they have their uses), you can see that Boston starters over their careers actually appear to perform roughly the same before and after the break. They throw slightly more strikes, less walks and more innings. The only problem is the large increase in home runs given up, which explains their increased FIP and ultimately why Boston starters are about 6 runs worse in the 2nd half.

Pitching

W-L%

ERA

WHIP

K/9

BB/9

HR/9

FIP

1H-RP

0.575

2.70

1.11

9.1

2.96

0.66

3.19

2H-RP

0.639

2.73

1.15

9.2

3.21

0.65

3.12

Diff

-0.064

-0.03

-0.04

-0.08

-0.25

0.01

0.07

 

It appears that Red Sox relievers have performed about the same before and after the break. They’ve gotten more strikeouts and given up fewer home runs, which probably explains the slight run improvement over the 1st half.

Looking at these career 1st and 2nd half splits suggests that the Boston Red Sox offensive output might decrease a bit and that their starters might give up a couple more runs. We’ll narrow down the specific Red Sox players who might be poised to rebound or drop off in the 2nd half a little later using the same methodology. So what’s the point of all this data? Ultimately, the Red Sox are still an insanely good team, but we can maybe expect a teeny bit less in the 2nd half, which should make the AL East race all the more exciting.

Thanks for taking the time to read!

 

Sources: Baseball Reference

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