The best part of small sample stats are the enjoyment we get from finding the weird and the extreme. This year at the beginning of May, I discussed a variety of players riding on one side of the bell curve. Let’s revisit these players and stats and find out how they performed the rest of the way.
At the end of April, I calculated hitter xHR/FB rate using my equation to determine who had most underperformed at the time. I identified and discussed 11 of those hitters. Let’s see how many of these hitters actually did improve their HR/FB rates over the rest of the season and how close they came to their xHR/FB marks. Remember that xHR/FB isn’t meant to be predictive, but descriptive. The difference being that xHR/FB rate helps us determine what should have happened, rather than what will happen in the future. It attempts to strip out luck, like the majority of our expected/deserved metrics.
I’m already tired of hearing everyone’s hot take on how Matheny is going to halt the Royals from stealing bases. I’m not sure they are wrong but the analysis, if there is any, is suspect. Most talking heads point to his Cardinals being second to last in stolen bases during his tenure (2012 to all of 2018). The Cardinals weren’t exactly full of speedsters during that time. Here are their top-10 hitters ranked by plate appearances.
| Name | PA | SB | CS |
|---|---|---|---|
| Matt Carpenter | 4807 | 25 | 17 |
| Yadier Molina | 4676 | 45 | 21 |
| Matt Holliday | 3176 | 18 | 8 |
| Kolten Wong | 2836 | 83 | 23 |
| Jon Jay | 2346 | 41 | 24 |
| Allen Craig | 1694 | 10 | 2 |
| Jhonny Peralta | 1639 | 4 | 6 |
| Matt Adams | 1599 | 4 | 4 |
| Paul DeJong | 1597 | 11 | 6 |
| David Freese | 1451 | 5 | 5 |
Talk about “Wheelz”. Of these 10, Yadier Molina was second in steals. A catcher is second. This group would have problems stealing candy for a blind lady.
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Last week, I reviewed and discussed various hitting and pitching metrics and how they have trended over the past five seasons, from 2015 through 2019. After also discussing the early Statcast trends back in mid/late April, let’s take a look again with the full season now in the books.
This year’s edition of the Fantasy Baseball Process by Tanner Bell and myself is finally completed and the e-book is now available for sale (the paper version will be available at Amazon in a few weeks). We added over 50 pages of new material (link to list), cut out some info we felt was not needed, and included the historic standings and Standing Gains Points formulas to help with planning the 2020 season.
Before I move along to some of the highlights, I’d like to thank Dylan Higgins for the editing, Jared Cross for the Steamer projections, Clay Link for the introduction, Rob Silver for giving it a read over, and especially Tanner for hours and hours spent grinding through all the new changes.
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There is no need to beat around the bush with an intro full of cliches and examples. Simply does playing in the postseason wear down a player enough to effect their next season’s production?
Simple answer: Not really.
Less simple answer: Some with hitters, not at all with pitchers.
Complex answer: Danger math.
Yesterday, I shared and discussed a plethora of hitting metric trends from 2015 to 2019. More strikeouts, more fly balls, and more home run power are the obvious trends. Now let’s look at how the early 2019 pitcher trends I discussed in mid/late April ended for the season.
In mid-April, I took an early look at hitting trends in a plethora of metrics since 2015. Now that the 2019 season has concluded, let’s now revisit those metrics and see what 2019 ended up bringing us. Did it continue a trend, reverse a recent trend, or begin a new one?
For a while, I’ve been trying to have other people do my research for me with no luck. I figured with all the smart minds in the stock market and other securities, some method would line up. It really didn’t for the fact that everyone could basically buy or sell as much of every available option to everyone. Some hedge funds or Warren Buffett could buy up an entire asset, but basically it was tough for stocks to run out.
I needed to find a limited asset class where one unique asset (house) and several buyers determine its value. That is why I eventually got to looking into real estate. Most of the public literature involves how to get loans and fix up the house. There is surprisingly little on actually determining a property’s value. So far I’ve only gone to the library and the local book stores to find information since most books are completely useless with nothing beyond, buy low, sell high. I’m not wasting my time and effort on ordering a bunch of books.
When I wrote my article on disappointing 2019 hitters, the data diverged from expectations in one subset of hitters. Injured players dominated the list but they also saw a huge drop in their production to the tune of about 100 points of OPS. While the season-to-season OPS values are never exactly one-for-one, a 100 point dropped is huge especially since the league’s overall OPS jumped 30 points last season. I needed to dig in.
It’s going to get a little nerdy as I have to explain how I examined the data. To try to minimize the pre and post-injury production from the investigation, I only looked at players who were placed on the IL in March or April. Little if any of their production should have been before the injury. A second reason was to help project hitters who are dealing with offseason surgeries (e.g. Adalberto Mondesi). So, over the past 10 seasons, 627 hitters met these criteria.
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