Continuing our series from yesterday announcing our 2009/2010 Sabermetric Award winners (more commonly known, I suppose, as the "Sabers"), we now arrive at the Best Sabermetric Primer or Review Article/Series. Being someone relatively new to the sabermetric community this year, I feel like these articles and reviews offer the most to those who are new to the community. Sure, delving into the valuation of prospects or the run values of pitch types is intriguing and important to the community's continuing understanding of the game we love, it is the role of the various primers to introduce and cultivate a new slew of baseball fans interested in the objective analysis of America's pasttime.
That having all been said, let's first review the category description.
Articles that provide excellent introductions to, or summaries of, important fields of sabermetric research. When published online, these are often, but not always, broken up into series because of their necessary length.
There were six entrants into this category, and I'll reveal and review the top three. Let's begin.
Stop me if this sounds familiar. You have a question about baseball, the sort of thing that should be answerable with stats, you think. So you go looking for the stat, but you can't find anyone who computes it the way you want. So you find a site that (maybe) has the raw data you need, copy and paste it into Excel, and bang out a few formulas until you get a result. And all along the way, you've thought: There has to be a better way.
I'm here to tell you that in fact there is—the relational database. And I'm here to help.
I'm no database guru, but I do own a Mac and consider myself smarter than a seventh grader, so I'll volunteer to act as captain of this adventure, and anyone else who's a Mac user and looking to learn how to use databases is free to come along for the ride. I suspect our cycle of learning will look something like:
- Someone asks a question.
- A bunch of people go looking for answers.
- They report back.
- We find something that works.
- We all implement it.
- We celebrate with age-appropriate beverages.
- We aim higher and loop back to #1.
Those were the appropriate introductions to a slew of excellent information provided by both Colin and our former BtB overlord Sky on how to build our plain old home computers into powerful sabermetric tools. Colin, through his article, served as my teacher for SQL over the last few months, and though I have not been doing an awful lot of homework, the introduction and brief primer has inspired me to continue working on it when I can. And what Colin introduced, Sky and the community here at BtB implemented so that those at home with Macs could join in on the fun. While the other articles in this set of nominees explained and answered questions, I would bet that this set was the one that inspired the most work and research out of all of us. And for that, we thank you.
The world of advanced baseball statistics can be an intimidating place for those of us who slept our way through advanced algebra or haven't been a follower of the Bill James revolution from the beginning.
Still, that doesn't mean that we should feel left out when it comes to another way of understanding and appreciating the game we all love. With that in mind, BLS stat doctor Alex Remington will explore a new advanced statistic each week during the offseason, providing a simple primer for the uninitiated.
And that is exactly what Alex does in his ongoing "Everything You Wanted To Know About..." series, which has served as one of the best introductions to the world of sabermetrics that I have read since, well, I've been introduced to sabermetrics. Quite simply, Alex explains some pretty complicated work, but he does so in an absolutely understandable fashion that does not fly above readers' heads. The formatting of Alex' pieces follow a logical set of questions that most people new to a stat (particularly one with a ridiculous-sounding acronym) would probably ask. And the best part of it all is that the explanations work: they are succinct, get the gist of the statistic in question, and spell it out to the reader accordingly. And ultimately, that's all we want in a primer when all the information we started our baseball knowledge with was batting average and home runs.
(drum roll please)
And your winner of the 2009/2010 Saber for the Best Sabermetric Primer or Review Article/Series is...
That’s the beauty of win values – we can express a player’s contribution to his team in ways that are both meaningful and easy to understand. As much as I love WPA/LI, it’s just never going to be something that the casual fan is going to understand without a good bit of explanation. Win values, though – I can tell my mom that Adrian Beltre is a four win player and she’ll understand in 30 seconds. And, without too much more explanation, I can explain that those four wins are worth about $18 million in salary, and so not only is Beltre worth his salary, but he’s actually something of a bargain.
Win Values are a big open door to acceptance of our particular brand of analysis among non-statheady fans, and even within our little insulated community, they’re still a big step forward over the commonly accepted performance metrics of the last few years. However, rather than just telling you that and having you trust us, we figured it’d be a good idea to explain how the win values are calculated and break down each part of the formula for you to see. So, this week, we’ll be looking at the calculations of each part and walking everyone through the steps to create a win value for a particular position player.
That introduction begins a long series covering a step-by-step explanation of Wins Above Replacement that, to date, stands as the first thing to which I would link for those who ask what WAR is good for. The excerpt from Dave's introduction explains clearly why we could all get used to talking about WAR: there is not a value more intrinsic to baseball than the win. Really, it's all we care about, right? It's why we play the game, as a wise man once said in an angry fashion. And Dave brought this idea from the research done in many a mother's basement to the forefront of baseball discussion. We've come a long way in having WAR highlighted in an ESPN.com article on the front page of the baseball section, in only a year's time since the stat was introduced on FanGraphs. I believe Dave's writing style in this series was one of the reasons why this came about. He was able to capture the essence of each step of the WAR calculation and at the same time remain simple for the layman who was just recently introduced. And again, that's all that a primer should aspire to be.
Congratulations Dave Cameron, you are our winner for this category! We'd like to thank all of our nominees, the remaining of which follow in alphabetical order of author's last name.
I'd like to congratulate everyone on being nominated, much was gained in reading each of these articles. I can certainly attest to the fact that 2009 was a great year to be introduced to the world of sabermetrics, and I hope that 2010 brings about more primers and more fans of objective analysis.
Once again, congratulations to Dave Cameron and Win Values series. For that, here is your Saber.
Quick Note: My apologies to Dave Allen yesterday for not quoting an excerpt from his Saber-winning piece. An oversight and mistake on my part. Do enjoy the Saber though, I hope the award helps.