Daily Notes: On Spring Run Environments, In Case You Care
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On Spring Run Environments, In Case You Care
In yesterday’s edition of the Notes, the author published the earliest possible returns regarding league averages for spring training this year — both for the two spring leagues as a whole, and for the Florida and Arizona leagues separately.
A curious reader named Dan — who likely possesses multiple graduate degrees and even more lovers — asked how the spring stats so far in 2013 compared to last year’s spring-training numbers. What this post does is provide the answer to that particular question — while, perhaps, asking several more.
Indeed, some very basic work both with copy-and-pasting and Excel’s VLOOKUP function reveals the following (current through Wednesday):
| League | PA | AB | AVG | OBP | SLG | BABIP | HR% | BB% | K% | R/G |
|---|---|---|---|---|---|---|---|---|---|---|
| Spring 2013 | 6505 | 5779 | .281 | .353 | .442 | .323 | 2.4% | 9.2% | 17.2% | 5.6 |
| Spring 2012 | 36619 | 32904 | .270 | .333 | .422 | .313 | 2.4% | 7.8% | 18.1% | 4.8 |
| — | — | — | — | — | — | — | — | — | — | — |
| Florida 2013 | 3100 | 2773 | .276 | .345 | .430 | .318 | 2.4% | 8.6% | 17.5% | 5.1 |
| Florida 2012 | 18002 | 16162 | .261 | .325 | .401 | .302 | 2.2% | 7.9% | 18.1% | 4.5 |
| — | — | — | — | — | — | — | — | — | — | — |
| Arizona 2013 | 3405 | 3006 | .286 | .359 | .452 | .327 | 2.4% | 9.7% | 16.9% | 6.1 |
| Arizona 2012 | 18617 | 16742 | .279 | .340 | .442 | .323 | 2.5% | 7.7% | 18.2% | 5.1 |
| — | — | — | — | — | — | — | — | — | — | — |
| MLB 2012 | 184179 | 165251 | .255 | .319 | .405 | .290 | 2.7% | 8.0% | 19.8% | 4.3 |
Despite the fact that the weather has been colder than usual in Phoenix of late, runs have been scored at roughly a 20% higher rate in the Cactus League so far this year than in last year’s iteration of the league. A considerable (i.e. .019) increase in on-base percentage — informed by a higher league BABIP, walk rate, and contact rate — appears to be informing the increase in runs so far.
A less dramatic, but still noticeable, increase in run scoring is present in the Grapefruit League is well — which league is also exhibiting rather high on-base percentages.
Is this normal for the earliest days of spring training? Indeed, that’s precisely the sort of question that a more industrious writer would answer. In the absence of such a specimen, this author will merely suggest that we “monitor” the trend — where “monitor” is a verb designed to deflect all responsibility from the future work the findings here probably demand.
In the meantime, inquisitive readers are encouraged to submit their own theories, such that they might be co-opted, and expanded upon, by the present author in later editions of the Notes.
Carson Cistulli has published a book of aphorisms called Spirited Ejaculations of a New Enthusiast.
delmon young hasn’t taken an AB.
A lot of the top starters haven’t pitched yet and when they do it’s for 2 innings before maybe one other MLB caliber pitcher pitches an inning. Then they are followed by fringe prospects usually. Where position players that start usually play 4 or 5 innings so almost half the game when they start.
Other generic “industry” explanations may include: Steroids, WBC, Hitter get in shape faster then pitchers, or Aliens
You forgot the most ubiquitous industry explanation: unions.
And sometimes the Union-Alien cabal.
I don’t have anything to suggest for this topic unfortunately, but I am curious as to how the run environment will change when players leave for the WBC. At first, I thought that the run environment would decrease because many All-Star caliber players will be away. I haven’t done any research, but I think I could be wrong. Since many great players are gone, this means replacement level players will likely be taking their spots, which gives the players who aren’t participating a better chance to produce inflated numbers. Is there data from 2006 and 2009 that would show that Spring Training stats improve or decrease during the WBC?
VLOOKUP, quite possibly my favorite excel function. worked wonders in my pre-database days. countless work hours freed up to be spent on fangraphs