Throughout October and November, the BaseballHQ.com staff takes a deep dive into player analysis, cranking out the full stack of 800+ player commentaries that will form the guts of Ron Shandler's 2016 Baseball Forecaster.
As the writers grind away at those player analyses, one of the tools we try to get in their hands first is the Cheater's Bookmark. Placed conspicuously in the very back of the book each year, this quick-hit snapshot of relevant league-wide skills serves as a terrific quick reference guide to calibrate your mind to the current MLB landscape. And as we know, that landscape has been changing quite a bit in recent years.
Here is a six-year scan of the data points tracked on the bookmark:
BA OBP Slg OPS bb% ct% Eye SBO% BPV AL|NL AL|NL AL|NL AL|NL A|N AL|NL AL|NL AL|NL AL|NL ======= ======= ======= ======= === ===== ========= ===== ===== '10 260|255 327|324 406|399 733|723 9|9 80|78 0.48|0.44 10|9 46|46 '11 258|253 319|315 408|391 727|706 8|8 80|79 0.45|0.42 11|10 48|43 '12 256|261 317|323 412|414 729|737 8|8 79|79 0.42|0.43 10|11 43|43 '13 256|258 318|318 406|401 724|719 8|8 78|79 0.41|0.42 9|9 41|44 '14 254|256 312|315 391|395 704|711 8|8 78|78 0.39|0.39 9|9 40|39 '15 256|260 314|320 413|410 728|730 8|8 78|78 0.39|0.40 8|9 40|40
And the pitcher data:
ERA WHIP BABIP Ctl Dom Cmd hr/f BPV AL|NL AL|NL AL|NL AL|NL AL|NL AL|NL A|N AL|NL ========= ========= ======= ======= ======= ======= ===== ====== '10 4.14|4.02 1.35|1.35 299|305 3.2|3.3 6.8|7.4 2.1|2.2 9|9 54|62 '11 4.08|3.81 1.33|1.31 299|300 3.1|3.1 7.0|7.3 2.2|2.3 10|10 64|70 '12 4.09|3.95 1.31|1.31 296|303 3.0|3.1 7.4|7.7 2.5|2.5 12|11 74|79 '13 3.99|3.74 1.32|1.28 296|292 3.1|3.0 7.7|7.5 2.5|2.5 11|10 76|78 '14 3.82|3.66 1.28|1.27 296|295 2.9|2.9 7.7|7.8 2.6|2.6 9|10 82|86 '15 4.01|3.91 1.29|1.30 293|299 2.9|2.9 7.6|7.9 2.6|2.7 11|11 82|87
In the Introduction to last year's book, Ron Shandler compared the 2010-thru-2014 hitting trends to riding a roller-coaster: You feel that you are falling, but you don't necessarily know where the bottom is. Well, it appears we found the bottom (or at least a flat step on the way down) in 2015. Consider:
Since it's always helpful to give concrete examples, let's take a look at a crop of players who achieved league-average performance in various categories:
As always, we provide this data just to do a level-set here in the early-offseason. As we dive into player analysis, draft strategy, etc., it's always a good idea to take a minute and make sure we have a good grasp of what's going on at a macro level within the data set that drives our games.
Now don't forget to order that Forecaster!