2017 Baseball Forecaster: & Encyclopedia of Fanalytics
272
2017 Baseball Forecaster: & Encyclopedia of Fanalytics
272eBook
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Overview
Product Details
| ISBN-13: | 9781633196957 |
|---|---|
| Publisher: | Triumph Books |
| Publication date: | 12/15/2016 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 272 |
| File size: | 96 MB |
| Note: | This product may take a few minutes to download. |
About the Author
Read an Excerpt
Baseball Forecaster
And Encyclopedia of Fanalytics
By Ron Shandler
Triumph Books LLC
Copyright © 2016 USA TODAY Sports Media Group LLCAll rights reserved.
ISBN: 978-1-63319-695-7
CHAPTER 1
Devaluation
by Ron Shandler
I once spent several years marveling at a certain player whose underlying power metrics screamed 40 home run potential. Forty is a big number, a feat, a milestone reserved for the very best, and this player seemed poised to take that leap.
Yet, for a variety of reasons, he kept falling short. Maybe it was his 60 percent contact rate and periodic sub-.200 batting average. Maybe it was his streakiness —.164 one month, .289 the next; .171 another month, .344 the next. Whatever the reason, the magical 40 remained elusive.
He came closest in 2014:
AB R HR RBI SB BA
507 68 37 88 5 .227
The 2015 Forecaster said, "He could be a monster. UP: 45 HRs."
But, the forecasting gods were unkind and 2015 turned out to be a bust. Naturally, our recency bias depressed his 2016 expectations to near nothing. His average draft position ranking (ADP) coming into last season was No. 305, which in real terms meant, "Undraftable even in a 13-team mixed league."
In the 13-team FSTA/SiriusXM experts league, he was selected in the fourth reserve round, or No. 339. That meant I did not deem him worthy enough to be among my first 26 picks even though I had seen 45-HR upside just one year earlier.
You can probably guess where this is going. The stubborn few who kept the faith last March — all six of you — were duly rewarded:
AB R HR RBI SB BA
549 84 41 94 3 .222
I suppose this is the long-awaited validation for my pre-2016 Chris Carter projections. I don't know; he only managed the feat by going on an 11-HR tear from September 3 on. Regardless, we evaluate players on a full season's performance; 40 HRs is 40 HRs, right?
Maybe not. There is one nagging little piece of data that takes something away from the accomplishment:
YEAR AB R HR RBI SB BA
R$
2014 507 68 37 88 5 .227 $20
2016 549 84 41 94 3 .222 $15
Despite hitting four more HRs, scoring 16 more runs and driving in six more runners — discounting the minor dips in steals and BA — Carter's 15-team mixed league Rotisserie earnings were $5 less than in 2014 (and pretty crappy for a 40-HR hitter, all in all).
How could that be? The problem: everyone hit in 2016. When it came to home runs, everyone punched a power ticket:
• Every Upton.
• Every Seager.
• Every Davis.
• Two long-term singles hitters who had career power years at age 35.
• Three declining sluggers with sudden power spikes at ages 37 and older.
• Seven rookies who hit more HRs in their first partial MLB season than in any full minor league season.
• My brother-in-law's neighbor's nephew.
• Brad Miller.
Everyone. So in a year when balls were flying over the Green Monster, onto Waveland Avenue and into San Francisco Bay with wanton abandon, the value of any individual homer took a dive.
Rotisserie earnings are benched to the level of offense in any given season, thereby reflecting the context of the day. So, a bigger leaguewide offense will mean a lower value per homer ... and every other offensive event. That's how Carter earned $5 less in a season when he put up bigger numbers.
This phenomenon tends to skew our perspective. I suppose we can't help but talk about a player's individual power growth as if it occurred in a vacuum. But everything has to be evaluated within its own context.
So no, this was not a career power year for Evan Longoria (he showed better skill in every season prior to 2014). Brad Miller's huge breakout was not as big as we think (his expected power index of 116 was just a tick above 2014's 105). And get this: Todd Frazier's career power year came along with the lowest xPX of his career. By a lot.
So we can debate whether Chris Carter's first 40-HR season is an accurate reflection of the skills befitting of that milestone. His xPX has been essentially flat for four straight years. This has been the same player since 2013.
It's possible that hitting 40 home runs is not as elite of a feat as it used to be.
Power and the balls
Take a look at how the power environment has evolved since around the turn of the century:
The last three columns represent the number of players who hit at least 20 HR each year, the average number of HRs those players produced, and the percentage that their homers represented of baseball's entire HR output.
In 2014, only 57 players hit 20 or more HRs; their output represented 35% of all the homers hit that year. Just two years later, there were nearly twice as many 20-HR hitters making up more than half of all the HRs hit.
That meant, every owner in a 15-team mixed league could have rostered seven 20-HR hitters (and six teams could have owned eight). Essentially, you would have been hard-pressed not to trip over a 20-HR hitter in your drafts last March.
I actually projected this, right here, one year ago:
... barring a revelation that some external variable changed in 2015, one would expect power to regress off of this year's spike. But wait ... this 2015 "correction" was the largest single season spike since 1993. Back then it set off a whole new era in power performance. Could we be entering a new cycle?
It's possible. As you scan all the player boxes in this book, you'll see many new players being projected for 20 HRs or more, driven by nothing more than normal trends ... In all, I count 78 players projected for 20 or more HRs. Last year, only 64 players hit at least 20 HRs. This "correction" may have legs.
Right idea, wrong magnitude.
There has been a lot written to analyze this sudden phenomenon. Here is an excerpt of what I wrote back on May 19:
Everyone has their opinions about why baseballs are flying out of ballparks at the most frequent rate in the history of the sport. (Most explanations) can be discounted. There's only one other popularly-held explanation left. But MLB's Powers That Be will never reveal the truth about the baseballs that are being produced.
Yes, I wrote this on May 19.
May 19, 2000. Seventeen years ago. The more things change, the more they stay the same.
But it's interesting to compare the phenomenon from the Steroids Era to the current Post-PED-Power-and-Punchout Era. Something extraordinary happened in 1999 and carried over into the following season on an even bigger scale.
From 1998 to 1999, the major league home run rate jumped from 2.08 bombs per game, to 2.28. By the end of May 2000, hitters were slamming an amazing 2.62 home runs per game. At the time, the talk was about how someone had "flipped a switch." This discounted any explanation that would lend itself to a more gradual change — warmer weather, smaller ballparks, the impact of expansion or suddenly stronger hitters (steroids had not yet become a part of the popular vernacular). Thus, the conclusion was that the baseballs had to be juiced.
Seventeen years later, we're once again using a switch-flipping metaphor for the recent power spike. Prior to the 2015 All Star Break, the home run rate was 1.76 per game; after the Break, 2.20. Our surge continued into 2016, the home run rate climbed to 2.32.
The consensus opinion? It's the balls. (Some attribute the record-breaking summer heat, but it's tough to switch climate on and off at will.)
But that's not the end of the story ...
The sudden power surge in early 2000 forced us to start reassessing our benchmarks. The juiced ball theory took on greater life after Rawlings refused to allow photographs of the machines that wound the yarn around balls.
But then the surge abated as suddenly as it had begun. By September, the homer rate had faded to 2.06 and finished the year at 2.34. It was as if someone had flipped the switch OFF. Any talk of juiced balls vanished as "steroids" became a more attractive headline magnet. We never found out the truth about the balls.
The point is, these tectonic shifts can occur at any time, in any direction. They are not necessarily gradual and they don't have to follow any expected trend. Look at the chart; we can no sooner explain the 20152016 spike than we can the 2000-2002 drop during the height of the Steroids Era. And so, neither can we draw any conclusions about the direction this trend will take in 2017.
Balls.
There were 111 players who hit at least 20 HRs last year. A quick scan of the projections here — admittedly, a rough number at this time of year — and I count 101 potential 20-HR sluggers. That level remains pretty significant though it does reflect some minimal regression. Still, I'm not betting the rent that this home run barrage will continue into 2017.
Deceleration
While home runs were a dime a dozen, stolen bases have become scarcer commodities. The number of elite speedsters dropped to its lowest level in over a decade.
These days, in a 15-team league, teams will average about two players with 20-SB potential. Compare that to five years ago when every team could have rostered three players with 20+ stolen bases.
The 2016 Baseball Forecaster spoke to this phenomenon:
Given that steals have always been centralized in a smaller group of elite players, it has made sense to assign a somewhat inflated value to their contribution. But these days it's even more prevalent. It makes a strong argument for drafting a Jose Altuve or Dee Gordon in the first round, or for $30-plus. I think that approach has become more reasonable to consider these days; just plan the rest of the roster around it.
Will this phenomenon continue?
The first column is the percentage of all plate appearances that have been singles and walks. While this is not a perfect measure of events that create stolen base opportunities, it does provide a rough gauge to track the trend. You can see that this has been declining over time. The 2% decline since 1999 seems small, but that equates to around 4,000 fewer baserunners per year who could potentially put up SBs.
The second column is a bit tangential but interesting nonetheless. It shows the larger Power-and-Punchouts environment in which those potential stolen base opportunities exist. This is the percentage of plate appearances that result in a ball in play — essentially reflecting the global rise in baseball's three true outcomes (homers, walks and strikeouts). The decline here is even steeper, 5% over the past decade alone.
The third column is Stolen Base Opportunity Pct., which measures how often a stolen base is attempted when a batter reaches first by either a single or walk. This trend has fluctuated within a 2% range over time, but as been in decline from its recent 2011 peak. The last two years' decline compares with the corresponding spike in power. No point stealing second when odds are a homer is right around the corner, right?
The final column is the Stolen Base Success Rate, or how often a base-stealer is successful in his attempts. While the last two years have seen a bit of decline, steals success is still better than it was 15 years ago. It would be tough to draw a conclusion that the decline in steals has any connection to runner skill.
So, the decline in bags is a decline in the events that potentially create stolen base opportunities. Writer Joe Sheehan also attributes the phenomenon to the decline in singles, not only to create baserunners but also for driving in those runners who've stolen second base. The risk of a failed steal outweighs the benefit of putting a runner into scoring position if there are fewer run-scoring singles. Again, odds are a homer is right around the corner.
This environment seems like more of a core trend. It might continue. It might stabilize. Or not. If you look at 2002-2007, you might conclude that we're just going through a similar trough now.
So I'm not taking bets for 2017. It's an easy speculation to see how things could turn around. Dee Gordon doesn't get suspended. Roman Quinn potentially sits at the top of the Phillies batting order. Full seasons for Mallex Smith, Keon Broxton, Jose Peraza, and on and on. There were 28 players who stole at least 20 bases last year. A quick scan of the projections here — admittedly, a rough number at this time of year — and I count 40 potential 20-SB speedsters. And we're back out of the trough.
Trickle-down trends
The more that we can't project the environment in which our stats live, the tougher it is to get a read on individual player projections. They are moving targets as well. This book provides a better understanding of skill so you can take aim at those targets with as much precision as is possible. But as Fanalytic Fundamental No. 1 notes: "This is not a game of accuracy or precision; it is a game of human beings and tendencies."
Still, no matter how much we might intuitively know this is true, we are going to obsess over who to rank where and how much to pay for Player A, Player B and Player Z. We can't help it.
QUESTION: If you have the No. 1 seed in your 2017 draft, will you draft Mike Trout, Mookie Betts or Jose Altuve?
ANSWER: It almost doesn't matter.
For starters, owning the No. 1 seed hasn't exactly been a stone cold lock anyway.
For 2017, Trout seems like the safest pick, given what appears to be a high floor. But we could have said the same thing about Albert Pujols not too long ago. One day, the Trout Era will end too.
As far as the best player, well, he can come from anywhere:
Year No. 1 Earner Preseason ADP
2007 Alex Rodriguez 4
2008 Albert Pujols 10
2009 Albert Pujols 2
2010 Carlos Gonzalez 119
2011 Matt Kemp 23
2012 Mike Trout 228
2013 Miguel Cabrera 2
2014 Jose Altuve 92
2015 Jake Arrieta 97
2016 Mookie Betts 16
In fact, our ability to nail anyone in the first round of a 15team draft is just as imprecise. For years I've been parading around the research stating that our success rate in identifying each season's top 15 players is — using the scientific term —"awful."
As in 35.5% awful since 2004.
Several of my industry colleagues have dismissed this research. Their contention is that a player drafted in the first round doesn't need to return first round value, only some reasonably close level. For instance, in 2016, Miguel Cabrera was drafted No. 13 as a $30 player. He finished ranked No. 19, earning $27. That's clearly an acceptable result, even though he didn't finish in the top 15.
However, some might also make a case that the owners of Josh Donaldson (No. 5, $38) should not have been disappointed with his finish at No. 23, earning $26. But in real terms, any player whose end-of-season value is lower than projection means that you are taking a loss on your investment. As much as Donaldson owners may have been satisfied, they still took a $12 loss. I suppose it comes down to your own tolerance level, but I wouldn't be happy with a $12 loss.
Part of the problem is that the slope of player value at the high end of our rankings is incredibly steep. If the 90th ranked player finishes No. 125, your real loss is only about $4. If your No. 1 pick finishes 36th — the same span of picks — your loss is more than $20. The early round misses have far more impact.
But the bottom line is, those failed first-round picks are not finishing just outside the top 15 anyway. They are barely in the top 30. Look:
In fact, most of the players in the ADP top 15 finish nowhere near their draft spot. Look at the past three seasons:
Admittedly, 2016 was one of our better years. But, for all the preseason obsessing we do over getting the best seed and trying to decide who to draft where, these lists look like a whole bunch of blind dart-throws.
The point of all this
When you combine ...
• the volatility of the statistical environment
• the imprecision of player projections, and
• the uncertainty of the drafting process ... you get one hot mess.
Each year, we respond to these variables in pretty much the same way, looking for a silver bullet that doesn't exist. But we don't need to resign ourselves to another year of wanton randomness either.
When it comes to the environment volatility, analysts will do their best job at forecasting, but will ultimately fall back on Merkin's Maxim: "When in doubt, predict that the current trend will continue." There are worse approaches, but frankly, there is not much more we can do. Observe, and react.
When it comes to projective imprecision, forecasters will build ever more elaborate models, scratching and clawing for each thousandth of a decimal point in mean squared error. That's a lot of unnecessary effort.
Your energy will be better spent learning the tools in this book. They'll help you get a better handle on each player's potential. Focus on the peripheral metrics and commentaries, not the projections; that's where the treasures are hidden.
When it comes to drafting uncertainty, tacticians will devise increasingly brilliant strategies to game our opponents, always hoping they respond as lab rats might.
But the year that you try to deplete pitching resources by over-drafting your staff is the year that Chris Archer, Matt Harvey, Dallas Keuchel and Zack Greinke go belly up. The year that you try to corner the market on speed is the year that Dee Gordon gets suspended and Manny Machado stops running. Besides, your league's winner is still going to be the guy who drafts Jonathan Villar and Rick Porcello anyway.
The best we can do here is look for small tactical advantages. It's the little stuff that can give us an unexpected edge. I've found two such tactics that have helped my process over the past few years.
(Continues...)
Excerpted from Baseball Forecaster by Ron Shandler. Copyright © 2016 USA TODAY Sports Media Group LLC. Excerpted by permission of Triumph Books LLC.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.
Table of Contents
Contents
Devaluation,Encyclopedia of Fanalytics,
Fundamentals,
Batters,
Pitchers,
Prospects,
Gaming,
Statistical Research Abstracts,
Gaming Research Abstracts,
Major Leagues,
Batters,
Pitchers,
Injuries,
Prospects,
Top Impact Prospects for 2017,
Top International Prospects,
Major League Equivalents,
Leaderboards,
Draft Guides,
Blatant Advertisements for Other Products,