- OPENING LINE
- PUBLISHER’S SUMMARY
- THE PLOT
- THE AUTHOR
- THE NARRATION
- THE PRODUCTION
- FINAL THOUGHTS
- QUICK FACTS
When Sid Bream touched home just ahead of the throw from Barry Bonds in the 1992 National League Championship Series, it became one of the most iconic moments in the history of the Atlanta Braves franchise. However, for the team on the losing end of that phenomenal game, the final play was when the lights were turned out. At the time, nobody thought the lights would stay out for twenty years, but for the Pittsburgh Pirates, that is exactly what happened.
In ‘Big Data Baseball’ author Travis Sawchik takes a look at what the struggling franchise did in order to turn the lights back on in 2013.
Pittsburgh Pirates manager Clint Hurdle was old school and stubborn. But after 20 straight losing seasons and his job on the line, he was ready to try anything. So when he met with GM Neal Huntington in October 2012, they decided to discard everything they knew about the game and instead take on drastic “big data” strategies.
Going well beyond the number-crunching of Moneyball, which used statistics found on the back of baseball cards to identify market inefficiencies, the data the Pirates employed was not easily observable. They collected millions of data points on pitches and balls in play, creating a tome of reports that revealed key insights for how to win more games without spending a dime. They discovered that most batters struggled to hit two-seam fastballs, that an aggressive defensive shift on the field could turn more batted balls into outs, and that a catcher’s most valuable skill was hidden. Hurdle and Huntington got to work trying to convince the entire Pirates organization and disgruntled fans to embrace these unconventional yet groundbreaking methods. All this led to the end of the longest consecutive run of losing seasons in North American pro sports history.
The Pirates’ 2013 season is the perfect lens for examining baseball’s burgeoning big-data movement. Using flawless reporting, award-winning journalist Travis Sawchik takes you behind the scenes to reveal a game-changing audiobook of miracles and math.
©2015 Travis Sawchik (P)2015 Macmillan Audio
I maintain that out of all the major North American sports, baseball makes for the best books. There’s just something about the quirks of the game, the tradition of the game and the personalities involved that always make for the best stories. After reading ‘Big Data Baseball’ I am as confident in my theory as ever.
I suspect that some people will see a title like ‘Big Data Baseball’ and view it as a clone of ‘Moneyball’. However, anyone that jumps to that conclusion will be missing out on a very interesting book.
How is ‘Big Data Baseball’ different from ‘Moneyball’? The most obvious way is that ‘Big Data Baseball’ concentrates more on the happenings on the field than it does on what happens in the draft room, at the trade deadline or the history of advanced statistical analysis. You can argue that ‘Moneyball’ is the foundation and ‘Big Data Baseball’ just builds off of that.
‘Big Data Baseball’ focuses more on the defensive and pitching aspects of sabermetrics. The Pittsburgh Pirates of 2012 and the Pirates of 2013 weren’t that much different when it came to roster composition, but there was much improvement in 2013 because of a few key off-season moves and a shift in the way that players played and Clint Hurdle managed the game. Men like Hurdle, catcher Russell Martin and pitcher Francisco Liriano are the main focus of the narrative.
Travis Sawchik chronicles the process from the development of the pitching and defensive theories by the “stat geeks” to the apprehension of old school baseball minds to go against over a hundred years of conventional baseball wisdom. But the truth is that winning can relieve a lot of angst, and winning is exactly what the Pirates did in 2013. The book also looks at the ongoing process to determine what might be done to prevent some of the serious injuries that pitchers in particular are vulnerable to at some point in their career.
Perhaps the most interesting point that Sawchik made in the whole book, at least as it relates to the future, actually came in the epilogue. He pointed out that as concentration on defensive shifts and pitching worked for the Pirates, other MLB teams started to copy it, which then necessitated yet more changes in an effort to stay ahead of the curve. The economics of baseball are such that if you want to be a small market success story, innovation is going to have to be the key to your success. There is an old saying that it is better to be lucky than good. But luck seems to play a smaller part in baseball than it does in other sports. Look no further than the amateur draft and what a crap-shoot it can be for proof of that.
‘Moneyball’, ‘The Extra 2%’ and ‘Big Data Baseball’ make for a fine trilogy. The first book covers the early development of the advanced stats movement, the second looks at how that kind of thinking can be used to improve all aspects of a baseball organization, and this one looks at things from the perspective of those who actually implement these strategies on the field. I’m even more confident that as years pass and more data becomes available and new baseball theories get fleshed out, we’ll get even more books to add to the stats revolution category.
Travis Sawchik makes an interesting choice when telling the story and it is one that I think was for the better. He doesn’t spend a lot of time going over the twenty years of Pirate losing. There is an overview, mentioning a few of the bad draft choices, and some of the drawbacks of being a small-market franchise, but otherwise he focuses on what it took to stop the losing.
I think this was a wise decision because Pirate fans are already well-aware of what happened in the years between 1992 and 2013, and for other readers it would have just gotten old. Yes, the Pirates were bad but they rarely, if ever, reached the levels of ineptitude displayed by the Vince Naimoli led Devil Rays that found their way into ‘The Extra 2%’. If you’re going to focus a lot on losing, it either has to be humorously inept or somehow endearing, and the Pirates weren’t really either for most of that twenty year span. A lot of those seasons the Pirates were just … there.
Pete Larkin was a good choice to narrate the book because he has a very baseball announcer-like quality. There is good inflection in his voice for a book that is more detail than emotion oriented.
There are a couple of mispronunciations that I noticed in the book. In particular the last names of Joey Votto and John Schuerholz are off, but that is the only black mark on an otherwise fine performance.
This track is exactly what you would hope for in a track recorded in 2015. It sounds great, with no glitches or shifts in volume level. The audio chapter stops match up perfectly with the book’s chapters. While there are no sound effects used (sound effects in nonfiction books is just a terrible idea in general), there is a catchy bit of music to open and close the book. Nice work from Macmillan Audio.
‘Big Data Baseball’ is worthy of sitting alongside ‘Moneyball’ and ‘The Extra 2%’ on any baseball fan’s bookshelf. What makes it stand out from its predecessors is that it looks more closely at how implementing a statistics driven strategy affects the men that play and coach the national pastime.
|Title||Author||Narrator||Publisher||Sports||Release Date||Running Time||Score|
|Big Data Baseball: Math, Miracles, and the End of a 20-Year Losing Streak||Travis Sawchik||Peter Larkin||Macmillan Audio||Sports||05/19/2015||8 hours, 30 minutes||8.75/10|
A copy of ‘BIG DATA BASEBALL: MATH, MIRACLES, AND THE END OF A 20-YEAR LOSING STREAK’ was purchased from Audible for review.