2016 Baseball Forecaster: & Encyclopedia of Fanalytics

By Triumph Books

For 30 years, the very best in baseball prediction and statistics
 
The industry’s longest-running publication for baseball analysts and fantasy leaguers, the 2016 Baseball Forecaster, published annually since 1986, is the first book to approach prognostication by breaking performance down into its component parts. Rather than predicting batting average, for instance, this resource looks at the elements of skill that make up any given batter’s ability to distinguish between balls and strikes, his propensity to make contact with the ball, and what happens when he makes contact—reverse engineering those skills back into batting average. The result is an unparalleled forecast of baseball abilities and trends for the upcoming season and beyond.

• Language: English
• Publisher: Triumph Books
• Release date: Jan 15, 2016
• ISBN: 9781633194175

Book preview

RON SHANDLER’S 2016

BASEBALL

FORECASTER

AND ENCYCLOPEDIA OF FANALYTICS

Copyright © 2015, USA TODAY Sports Media Group LLC.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of the publisher, Triumph Books LLC, 814 North Franklin Street, Chicago, Illinois 60610.

Triumph Books and colophon are registered trademarks of Random House, Inc.

This book is available in quantity at special discounts for your group or organization. For further information, contact:

Triumph Books LLC

814 North Franklin Street

Chicago, Illinois 60610

[phone]

www.triumphbooks.com

Printed in U.S.A.

eISBN: 978-1-63319-417-5

Rotisserie League Baseball is a registered trademark of the Rotisserie League Baseball Association, Inc.

Statistics provided by Baseball Info Solutions

Cover design by Brent Hershey

Front cover photograph by Mark J. Rebilas/USA TODAY Sports Images

Author photograph by Kevin Hurley

Ron Shandler’s

BASEBALL

FORECASTER

Editors

Ray Murphy

Brent Hershey

Associate Editor

Brandon Kruse

• • • • • •

Technical Wizard

Rob Rosenfeld

Design

Brent Hershey

Data and Charts

Matt Cederholm

Player Commentaries

Ryan Bloomfield

Rob Carroll

Matt Cederholm

Matt Dodge

Alec Dopp

Brent Hershey

Brandon Kruse

Ray Murphy

Stephen Nickrand

Greg Pyron

Kristopher Olson

Paul Sporer

Brian Rudd

Jock Thompson

Rod Truesdell

Research and Articles

Dave Adler

Matt Cederholm

Patrick Davitt

Ed DeCaria

Brandon Kruse

Stephen Nickrand

Dave Potts

Vlad Sedler

Todd Zola

Prospects

Rob Gordon

Jeremy Deloney

Tom Mulhall

Injury Chart

Rick Wilton

Acknowledgments

Producing the Baseball Forecaster has been a team effort for a number of years now; the list of credits to the left is where the heavy lifting gets done. On behalf of Ron, Brent, and Ray, our most sincere thanks to each of those key contributors.

We are just as grateful to the rest of the BaseballHQ.com staff, who do the yeoman’s work in populating the website with 12 months of incredible content: Andy Andres, Matt Beagle, Dan Becker, Alex Beckey, Bob Berger, Chris Blessing, Brian Brickley, Doug Dennis, Greg Fishwick, Neil FitzGerald, Colby Garrapy, Matt Gelfand, Rick Green, Phil Hertz, Joe Hoffer, Ed Hubbard, Tom Kephart, Chris Lee, Glenn Lowy, Chris Mallonee, Troy Martell, David Martin, Craig Neuman, Harold Nichols, Frank Noto, Josh Paley, Nick Richards, Mike Shears, Peter Sheridan, Skip Snow, Matthew St-Germain, Jeffrey Tomich and Michael Weddell.

Thank you to our behind-the-scenes troopers: our technical dynamic duo of Mike Krebs and Rob Rosenfeld; and to Lynda Knezovich, the patient and kind voice at the other end of your email inquiries.

Thank you to all our industry colleagues, a truly impressive group. They are competitors, but they are also colleagues working to grow this industry, which is never a more evident than at our annual First Pitch Arizona gathering each November.

Thank you to Dave Morgan, Chris Pirrone, and the team at USA Today Sports Media Group.

Thank you for all the support from the folks at Triumph Books and Action Printing.

And of course, thank you, readers, for your interest in what we all have to say. Your kind words, support and (respectful) criticism move us forward on the fanalytic continuum more than you know. We are grateful for your readership.

From Ray Murphy I have contributed to the Forecaster in various capacities for over a decade now, and the opportunity to collaborate with Ron remains as much of an honor today as it was the first time he asked. Ron’s imprint continues to linger over all aspects of this entity that Brent and I now co-manage. Anyone who has attempted to co- anything knows how perilous an undertaking it can be. Brent and I work remarkably well together; not just because Brent has off-the-charts skills and a temperament to match, but because we share an abiding reverence for this thing that Ron created and we are now entrusted with preserving and growing. Of course, I’m no stranger to exemplary co- relationships, as my wife Jennifer is the first and best example of a key life lesson for me: choose your partners well.

From Brent Hershey Anniversaries force us look back. I am humbled and honored to take part in this tradition of running myself crazy for seven weeks in October-November so that fantasy baseballers everywhere can begin their preseason in early December. Thank you, Ron, for the opportunity you extended in 2011 to become more involved in this project—and for a world where analyzing baseball is a year-round activity. Thank you, Ray, for your continued collaborative spirit; it has allowed us to effectively respond to some new challenges this past year. The co- in our titles is a true representation of reality. But most of all, thank you Lorie, Dillon and Eden, for your own passions, talents and zest for life. When I am able to stop and reflect, I couldn’t be prouder of your graceful fortitude in making this earth a better place.

From Ron Shandler It awes me to realize that my 23- and 24-year-old daughters have never known a world in which there was no Baseball Forecaster. How does that happen? Is it about quality, value or just perseverance? I suppose every veteran writer asks that. But after three decades of surviving naysayers, nasty competitors, baseball strikes, cheap magazines, free websites, the bursting dot-com bubble, football, high stakes trolls, daily game elitists, a declining publishing industry and greed, the survival of this book has to be attributed to one thing only: good, old-fashioned American stubbornness. You can’t stop me. Just try.

This past year, when life set me off on a new, unexpected course, Shandler’s Book has remained a constant. My eternal gratitude goes out to Ray, Brent, all the editors, writers, analysts, support personnel, production workers, advertising reps, designers, industry colleagues, media personalities, postal employees, cherished wife and daughters, and the hundreds of thousands of baseball fans over the past 30 years who made that happen. Every single one of you. (Yes, I’m talking to you!) Onward …

TABLE OF CONTENTS

Cover

Title Page

Copyright

Acknowledgments

Segue

Encyclopedia of Fanalytics

Fundamentals

Batters

Pitchers

Prospects

Gaming

Statistical Research Abstracts

Gaming Research Abstracts

Major Leagues

Batters

Pitchers

Injuries

Prospects

Top Impact Prospects for 2016

Top International Prospects

Major League Equivalents

Daily Fantasy

Leaderboards

Draft Guides

Blatant Advertisements for Other Products

Segue

by Ron Shandler

Thanksgiving 1985. Houston, TX.

I am sitting at a large table in a small house located just outside the Inner Loop. I am surrounded by 3,000 in-laws of all shapes and sizes. There are old ones and young ones, large ones in both size and presence, vegetarians and carnivores. New Yorkers, and Coloradans, and Floridians, and one or two Astros fans. There are only two decibel levels—loud and louder.

I have been married for eight months.

I am invisible, mostly because I believe that communication should be thoughtful and measured, not driven with a jackhammer. I don’t know what the heck all these people are talking about anyway. Who are these people? I think I’ve made a huge mistake.

So I wander off in my head, recalling the disappointing results of my first Rotisserie Baseball league. A bunch of high school teachers, a psychologist, a tech executive and I were dipping our toes in the Roto waters, drafting players out of each league’s Eastern Divisions. I finished fourth, led by Dave Stieb of the Toronto Blue Jays and his league-leading 2.48 ERA. Fourth place wouldn’t have been so bad had there been more than six teams.

I had to do better.

Ron? Ron?? Did you hear me? Wouldja pass the potatoes?

No, I didn’t hear you, dammit. How can anyone hear anything?

Where’s my bag? Those books I brought to read on the plane … the Bill James Abstract, The Hidden Game of Baseball, How Life Imitates the World Series. Would anyone miss me if I slinked away?

I am convinced that the answer to winning this Rotisserie thing is hidden somewhere inside those three books. But Bill James, Pete Palmer and Thomas Boswell all have different measures to evaluate talent. Which one is best—runs created, linear weights or total average?

It would be pretty valuable to see all the players listed with those three new statistics presented side-by-side-by-side. Hmm.

There is plenty of time to think; I am unemployed. I just completed the worst 15 months of my career, taking a job in a New Hampshire bank as my ticket out of New York City traffic. This is my third forced job departure in the seven years since graduating from college. There would be three more unceremonious exits before I’d finally tell Corporate America where they could put their pink slips. It took me awhile to figure out that I was not cut out to be an employee.

I figure, what the heck, I’ll just write a book. How hard could it be? I had worked for publishing companies before. I had learned how to do direct marketing. I was a good writer and a magician with LOTUS 1-2-3. And I was a control freak.

Piece of cake.

•••

As you’ve undoubtedly read in numerous places before, the Rotisserie game of the 1980s was a different animal from the game we play today. The standard format was 4x4 (runs and strikeouts didn’t matter), which elevated the value of speedsters and closers. Drafts took place in person, mostly because the only time you were ever online was at 8:00 AM at Dunkin’ Donuts. Standings were published once per week because that’s how often the stats were printed in USA Today. Trades were negotiated using ancient communication—speaking into a corded telephone.

No email. No internet. No smart phones. No real-time updates. Your greatest edge? Having access to a fax machine.

The eight statistical categories were the beginning and end of baseball analysis. A .300 hitter was drafted as a .300 hitter, no matter if his contact rate was 90% or 60%. ERA was the final arbiter for pitching effectiveness, regardless of any measures of control, dominance or command.

Saves were possibly more frustrating than they are today. While MLB teams tended to stay with their closers longer, the best 9th inning pitchers could go for $30-$35, leaving much bigger roster holes when they went down.

The debut edition of this book was entitled, Baseball SuperSTATS 1986, was promoted via a single one-inch advertisement in The Sporting News and cost $9.95. I sold 67 copies. It included all three new statistics as well as a few of my own, including an early version of strand rate.

The purpose of the first two editions was solely to get a better handle on player analysis. It wasn’t until 1988 that we started publishing Rotisserie cheat sheets. The early embryo of the player box you see today appeared in 1990; we didn’t add commentaries until 1994. The first decade of Forecasters were self-published and sold exclusively through mail order. The 1998 edition was the first one you could buy at amazon.com or at Barnes & Noble. USA Today took over in 2009.

The Major League game—the environment in which our fantasy game and this book lives—has undergone massive changes as well. However, like most things in life, change occurs slowly and is subtle. We often don’t realize that things have changed at all until we look back in the rear view mirror several miles later. But can we learn anything by taking a macro-snapshot of the time that the Forecaster has been in existence?

Let’s look at a 32-year scan, a little longer than this book has been in existence but covering the entire period since the publication of Rotisserie League Baseball in 1984—call it the Rotisserie Era. We’re not looking for revelations; just perspective.

(All data is from baseball-reference.com and my personal records. X-axis of all graphs represents time, in 5-year increments.)

Linear-Weighted Power by year

We often talk about the cyclical nature of home runs, but really, it’s about power as a whole. Linear-weighted power is (HR x 1.4)+(2B x 0.8)+(3B x 0.8)/(AB-K) x100.

Note the unusual spike in 1987 (when players like Larry Sheets, Matt Nokes and Brook Jacoby each hit over 30 HRs—and 20 HRs was a stretch in any season before or after). There was a sharp correction in 1988, which was the beginning of a 5-year malaise. Power exploded in 1993 and peaked in 2000, remaining fairly stable until 2006, which was shortly after MLB implemented their strictest drug-testing program. Power tumbled for eight years after that, bottoming out in 2014. It experienced a bit of a rebound this past season.

The challenge is being able to respond to these trends by adjusting each subsequent year’s projections. Periods of stability make the job easier, but then you run into a 1993, or a 2014, or even the unexpected power spike of this past season. That changes the relative value of all power hitters. A 30-HR performance in 1992 was far more valuable than a 30-HR performance in 1993, and fantasy leaguers should have paid less for HRs in ‘93 … had they been able to predict the spike.

The takeaway: Even within short periods of time, there is volatility. That means, 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. There are players like Jonathan Schoop, whose projection is a natural step up after several years of experience. There are players like Carlos Correa, who has hit the ground running. Add these to all the established players with power returning from off-years, like Carlos Gomez. 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.

Stolen bases and times caught stealing, per game

In some ways, steals have followed an inverse trend as compared to power, and you might expect that. But the overall trend is one of decline; speed has become less a part of the game today than it was 32 years ago.

Think about the players who populated our fantasy rosters in the 1980s. In the Forecaster’s inaugural year, the top four base-stealers were Vince Coleman (107), Rickey Henderson (87), Eric Davis (80) and Tim Raines (70). Twenty-four players swiped 30 bases or more. In 2015, only seven players reached the 30-steal level.

In tandem with the declining caught-stealing trend, this graph paints an interesting picture when it comes to stolen base success. From 1984 through 2002—a period of 19 years—the stolen base success rate (SB%) reached 70 percent only four times. In the 13 years since then, it’s never fallen short of 70 percent, hitting 74 percent twice.

The takeaway: With the trend of improving success on the basepaths, why aren’t teams running more? Odds are because baserunners have become scarcer and teams are not willing to risk losing them. This is a trend that makes baseball’s most dominating speedsters highly valuable.

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 your roster around it.

Base Performance Value (Pitchers)

The earliest incarnation of BPV appeared in the Forecaster’s 1993 edition. As you can tell from the above, it was during a time of stable pitching effectiveness. So when we said that 50 was the minimum level at which we’d consider rostering a pitcher, it made a bunch of sense.

Over the years, the impact of pitching evolved and the BPV formula went through several iterations. The one used for this graph is an abbreviated version of the current formula ((Dom – 5.0) x 18) + ((4.0 – Ctl) x 27) as we do not have ground ball data going back the full 32 years to use the full version. Still, this gives us a general sense of what has been going on, with little surprise.

The outlying 1999-2000 values are odd. They could have been attributed to that period’s offensive explosion if the metric wasn’t only looking at walk and strikeout rates. In fact, that sudden BPV drop was caused by league-wide walk rates spiking at 3.75 during that two-year period—they were 3.3 in 1998 and 3.4 in 2001. But control, dominance and command continued to rise despite the offensive surge of the early 2000s. And then they have just kept going. And going. And going.

League-wide BPV has settled in at 79 for each of the past two seasons, blowing away the old goal of 50 as being rosterable. That same relative goal in today’s terms would set a rosterable BPV at about 100, a level that 188 pitchers reached this past year. (That’s another reason why using BPX—the version that indexes BPV to league average—makes more sense these days.)

The takeaway: There is something big going on here, but let’s set it up first.

If this graph stopped at 2009, you might conclude that BPV displayed a moderate growth trend, but nothing too extreme. Then something happened in 2010, and the ratios of strikeouts to walks went nuts. There was a nearly concurrent spike in one other metric, shown below. It’s not tough to make a logical assumption that this is causal …

How does this happen? Is it advanced conditioning? Different development path? Lighter baseballs? New, genetically-engineered arms? How do you explain a 155% increase in extreme skill over seven years? Even a 59% increase over three years?

The stars have been slowly aligning in advance of this phenomenon, but we didn’t reach the tipping point until 2010/2011. What really happened? First, a few more graphs to further set the stage.

Average closer prices in Rotisserie dollars

The volatility of the closer role has been the primary driver that has forced this consistent downward trend. In most all cases, a high failure rate of closers in one year has served to push the average closer price down the subsequent year. So it is no surprise that, while failure rates fluctuate annually, the underlying trend is one that has persisted over time. In the first four years of this graph, the average failure rate was 29 percent; over the most recent four years, it has been 45 percent.

Where have those lost dollars gone? In many cases, they have gone to middle relievers, a speculation on future saves. Before the LIMA Plan was introduced in 1998, you could easily roster a Ken Giles or Wade Davis-type reliever for a buck or reserve round pick. In 2015 drafts, these non-closers on Draft Day went for $6 apiece. In all, more relievers have been earning positive value.

The takeaway: Fifteen years ago, this price volatility prompted the advice to don’t draft saves, as closers were always available in-season. These days, the more appropriate advice might be, don’t pay for saves. Closers are still available in-season but there are so many candidates now that it’s difficult to figure out which ones to chase.

After the average price dropped to $14.79 in 2015—the lowest level recorded—we may have reached the point where saves are cheap enough to speculate on freely at the draft. For the first time, several front-line closers went for less than $10, and with the resulting 45 percent failure rate, bargains could be plentiful. You might be able to roster two front-liners for the same cost as what you used to have to pay for a single elite arm.

That is the fallout from the ever-quickening hooks that major league managers have been employing with their bullpens. It’s directly reflected here:

Number of pitchers used per game

The number of pitchers used in each game has risen from 2.65 in 1984 to 4.11 this past year.

Let’s return to that velocity chart, but add another piece of data:

While the number of bionic-armed pitchers has been rising, the vast majority of them are low-inning hurlers who can afford to rear back and give it all they’ve got. Thirty years ago, when a starting pitcher was pulled from a game, opposing batters would face one or two relievers, each throwing at 90-95 mph for 1-2 innings apiece. Today, batters are seeing 3-4 relievers, each throwing 95-100mph, often for less than an inning. Batters are at an ever-growing disadvantage.

(You also can’t discount the increasing number of starting pitchers who meet the 95 mph velocity threshold. There were a record 11 starters in 2015: Nathan Eovaldi, Noah Syndegaard, Garrett Richards, Yordano Ventura, Gerrit Cole, Joe Kelly, Stephen Strasburg, Kevin Gausman, Matt Harvey, Carlos Martinez and Chris Archer. Jose Fernandez would be on this list had he pitched more innings. Jacob deGrom and Andrew Cashner just missed at 94.9 mph.)

Average number of players used per Major League roster

This is one of those hidden trends that is rarely talked about. In 1984, about 51 players appeared on a Major League roster during the course of a season. In 2015 that number peaked at 69.4. (That sharp drop in the middle was the 1994 strike year.)

Why has this occurred? Blame it on specialization. Blame it on escalating salaries and the rise of disabled list stays as teams attempt to protect their investments. Blame it on short hooks and better rookies and all the variables that have occurred over 30 years.

There were four fewer teams in 1984 and there were 935 batters who saw time in the Majors that year. This past year, 1,348 batters saw time. In 1984, 393 pitchers were on MLB rosters; in 2015, there were 735. In all, there are 755 more players receiving MLB paychecks today than in 1984. That’s a more-than 36 percent increase in the number of players we need to analyze, value and consider rostering on our fantasy teams.

The takeaway: While the number of players seeing major league action each year is rising, the number of games has remained the same. Each team still plays 162 games, which generates a nearly fixed number of outs and innings, and a very narrow range of plate appearances. These days, available playing time is the same but 18 more players per team are fighting for a piece of it.

That is huge.

Add in the fact that the standard fantasy roster structure has held firm to 14 batters and 9 pitchers. This is a split that no longer reflects MLB reality; today’s roster often has more pitchers than hitters. You can see how the environment that our game lives in has become a more challenging place for playing time prognosticators.

Playing time used to be just another element of the forecasting process. Roles were firmer and turnover was rare. There was a level of stability that gave fantasy leaguers more confidence that they could manage their roster with a sense of control. And remember, if nothing else, playing fantasy baseball has always been driven by the perception of control.

These days, playing time is about the most difficult element of performance to project, and these graphs show that it has been getting tougher and tougher each year. You may not have been noticing it overtly—because change can be subtle—but rest assured that your ability to make decisions that influence the fate of your team has been getting weaker each year.

Fantasy Impact

So, in summary … power is down, though cyclical. Steals are down. Pitching is way up. Our trust in saves continues to wane. Nothing very exciting here.

The biggest change over the past 30+ years is that the 23 players we draft each March now have a far lesser impact on the final standings than they did in 1984. The players rostered each spring account for a smaller percentage of each team’s bottom line statistics and serve only to set a very rough foundation for contention.

When we’re drafting in a standard 15-team mixed league (with six reserves), we think we are rostering 435 players out of a pool of 750-800. In reality, we are drafting from a potential pool of more than 1,300 players and growing, each year.

The upshot? In-season management now plays a larger role, and fantasy leaguers more adept at that task tend to do better.

There was once a time when you could wait out a rookie call-up for a few weeks before deciding whether to claim him out of the free agent pool. These days, any call-up with a pulse is grabbed up long before we can reasonably assess the odds of him having any staying power.

Fantasy leaguers hedge the risk of navigating this growing in-season volatility by selecting more and more speculative players at the draft. We’ve always searched out sleepers, but now they have become more a part of a core drafting strategy. Back in the 1980s, Kris Bryant would have been an end-game speculation, not a nearly-full-priced $18 buy like he was in NL Tout Wars last spring. But the experts knew; the in-season churn has become so overwhelming that you have to almost play both games—draft and in-season—at the same time, before the first pitch is even thrown.

In the end, the adept fantasy tacticians win by making successful decisions using smaller and smaller sample sizes:

•  On draft day, we hang on the results of the final spring training games to identify the last few players to win (allegedly) full-season roles.

•  In the early part of the season, a handful of at-bats or innings are all we get to take a chance on a player who could have five months of impact.

•  Later in the season, we might have more data but we’re making decisions that will affect only a handful of at-bats or innings down the stretch.

The full-season game has become driven by the management of small sample sizes.

Segue

There is another game that is driven by the management of small sample sizes.

For many of you, Daily, as in Daily Fantasy Sports (DFS), is a dirty word. I have spent the past two years writing about my distaste for this arrogant new format that has turned an intellectual pursuit into a get-rich-quick scheme.

Then I started playing it more regularly.

No, I haven’t been drinking the DFS Kool-Aid. However, I have grown to appreciate the specific game types that make use of real analytical skills and take place on a level playing field.

You see, we can’t use short time frames or small sample sizes as an excuse any more. Our full season game (let’s call that Seasonal Fantasy Sports, or SFS) has become just a steady stream of small-sample decision points. Of course, you don’t earn cash for every free agent pickup or reserve list activation, but the cash element of DFS can be compartmentalized. There are different formats; some are more skills-based, some more random. DFS games come in a variety of flavors; you just need to find your own personal Rocky Road.

For me, I stick with single-entry 50-50 games. In these, winning means finishing in the top half of all entries. There is no question that this is a winnable format using a skills-based approach alone. You won’t necessarily get rich from these games, but you can still turn $100 into $1,000 over the course of a season. For me, that’s my Cherry Garcia.

Your preference—and tolerance for riskier attacks on your gastronomic system—may vary. (There is an ice cream flavor called Wasabi Pea Dust which I would liken to entering one $3 team into a $1 million tournament. Good luck.)

The biggest advantage of DFS? That ever-growing SFS frustration—playing time—is a known commodity. Yes, your batter might get pulled for a pinch-hitter or your pitcher might get an early hook, but those are variables that you can research and plan around in the player selection process.

While the importance of the draft has been declining in the SFS game, DFS is all about the draft. The type of research is different—it’s more contextual than performance-based—but you still have to assess a laundry list of variables when selecting your players.

And if you were the unlucky owner of Drew Storen, Greg Holland or Steve Cishek this past year, you’ll be happy to know that most DFS games completely eliminate closers from the equation.

DFS also requires many similar skills to SFS. The variables you have to consider when deciding which SFS pitchers to activate on any given day or week are essentially the same in DFS. The budgeting challenges in a salary cap game are identical whether it’s SFS or DFS.

And small-sample decision-making drives both games. When a rookie pitcher is promoted, the SFS gamer needs to make a free agent claim decision, often in advance of the first start. That decision potentially has long-term impact, but in most games, a failed pick-up is easily cut. In DFS, the risk of taking a chance on that first start is limited to that one day’s game. In both cases, the decision may only affect a single outing.

Later in this book, some top DFS experts will go into more detail and share some of their insights. We’re barely scratching the surface of what can be learned about this new game.

Am I about to change teams? Nah. For me, fantasy baseball will always be about the long view. The exhilaration comes with creating a successful new strategy, nailing a breakout performer that nobody else saw coming and grinding out a tough victory. Winning should provide a massive sense of great accomplishment. Picking the right players on one night just doesn’t have the same pay-off for me.

But if I have an hour to kill on a Wednesday evening, I won’t