Offense and Scoring Runs

With even the casual fan using sabremetrics, albeit in a push rather than pull mode, most should at least have seen, if not come to an understanding, on an offensive metric called wRC+. For the uninitiated, read a freaking book. The basics are that we can use a solid offensive metric called weighted On Base Average and then convert this figure into runs using the following formula:

(wOBA-Lg wOBA)/1.15*PA

This gives us the previously linked weighted Runs Created which can then be compared to league average while factoring in park effects to create wRC+. As an index, each point above 100 is a percentage point better than average, and vice-versa for scores below 100. You can do this for teams or players, but today I want to focus on the former.

The Tampa Bay Rays have featured an, at times, explosive offense:

April: .239/.309/.392, .310 wOBA, 98 wRC+

May: .280/.352/.456, .351 wOBA, 127 wRC+

June: .252/.317/.404, .316 wOBA, 103 wRC+

July: .273/.344/.419, .334 wOBA, 115 wRC+

August: .252/.328/.379, .310 wOBA, 98 wRC+

September: .233/.338/.373, .319 wOBA, 104 wRC+

Total: .258/.331/.408, .325 wOBA, 108 wRC+

May was a clear outlier and we can probably point a finger at a guy who’s name rhymes with Schmatt Schmoyce. Each month is all over the place and it’s poor analysis to derive anything from these arbitrary samples, but it’s interesting to see how OBP and SLG pull wOBA one way or another. The Rays had their second lowest OBP in June, but a 4th highest SLG still left the offense as above average, by wRC+. Conversely, the Rays are throwing their 3rd highest OBP for this partial month, which has led to a third best wRC+ of 104. If you follow the team you’re spitting out your tea (teeth?) and guffawing, “Whaaaaaat?” You say this because you watch the team on a nightly basis before the Matlock comes on and you know that there’s no way this team has featured an above average offense.

Let’s take a look at actual runs scored by each month and the corresponding wRC+:

April: 105 Runs (94 R+), 98 wRC+

May: 166 Runs (140 R+), 127 wRC+

June: 107 Runs (94 R+), 103 wRC+

July: 120 Runs (114 R+), 115 wRC+, also keep in mind the All Star Game leaves fewer real games

August: 89 Runs (77 R+), 98wRC+

September: 28 Runs (64 R+), 104 wRC+

Total: 615 Runs (101 R+), 108 wRC+

R+ compares the Rays to the MLB average for that month so when the Rays score 28 runs this month they’re doing so at a rate that is around 36% below the league average team. This is 40 points below their offensive level by wRC+. We can see that the two don’t match up all that well, outside of July, but it looks like the swings can go both ways as evidenced by May.

Before we go to the next step we can make one little tweak to our R+ figure. By bringing park effects into account we can adjust this number to reflect the hitting environment teams play in half the time. We’ll call this R++ to keep them separate. On the year the Rays have a 106.4 R++ which is around 1.6 points below their wRC+ level of 108. Is that a lot? Here’s a chart showing each statistic for the Rays since 2000:

In 2010, the Rays had a wRC+ of 106, but scored runs relative to league average and adjusting for park effects at a 118.9 clip. Their offense was around 6% better than the league, but they scored runs nearly 19% better for a difference of 12.9. This year’s team has the lowest value of all years with a difference of -1.6. If we’re putting stock in this thing then that’s pretty bad and a reflection that a good offense hasn’t been able to close the deal. How does this compare to other teams:

Well, since 2000 the trend has been that most teams have a higher R++ than wRC+. It’s not a huge amount, but that’s why the trend doesn’t cross through the origin. The first coefficient in our line equation tells us that for every 100 points of wRC+ you should expect an R++ of 101.2 for a difference of around +1.2. Additionally, wRC+ explains around 89% of R++ meaning we’re seeing a very strong relationship between R++ and wRC+.

I’ve labeled the teams with the largest differences between the two. The 2013 Cardinals had the largest difference in the positive direction at +13.8 with an R++ of 118, yet a wRC+ of “only” 104. For those good at skimming, the 2010 Rays had the third largest positive difference for all teams since 2000. The 2006 Blue Jays came in with the largest negative difference of -5.2 with an R++ of 102 and a wRC+ of 107. You can think of this difference as unknown parts of luck, baserunning, and timeliness. The black dot above is this years Tampa Bay Rays. They check in with the 21st largest negative difference of all 420 teams surveyed.

Despite what translates as a strong offensive outfit es nicht spreche the runs this year. At times the offense has hummed along and scored runs. Others, they’ve shown poorly and not scored, but over the past month plus they have not plated runners at the rate you would expect. Over this short month they have shown a strong offense by wRC+, but they’re scoring runs at a rate two-thirds relative to the rest of the league. The luck should balance out, but there’s no telling whether the timeliness of base hits will align with expectations, and the baserunning doesn’t look likely to improve even with a very good baserunner, though poor base stealer, in David DeJesus atop the lineup the majority of days. Here’s hoping the run scoring corrects. And fast.

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About Jason Hanselman

Rays fan.
This entry was posted in Batter Analysis. Bookmark the permalink.

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