Since the dawn of baseball
beginning with Abner DoubleDay in the Elysian Fields with the formation of the National Association of Baseball Players in 1871, people have been trying to figure out how to know to measure just who is really good and who is not.
The world has changed a lot since 1871 – just half a dozen years after the Civil War ended – but many of the statistics we use to measure baseball players haven’t changed much.
That is starting to change – but not nearly as quickly Law argues as it should. He defines his main culprits as the stats that most people first think about: Wins for pitchers, batting average for hitters, and RBI.
Here is the reality: the way we track statistics is no longer simple. Pitcher wins, for example, was seen as somewhat of a catch-all to determine if a pitcher pitched well enough for his team to win the game. Yet when that statistic was started, starting pitchers almost always pitched the entire game and therefore had much more control on how much they did influence the game(good or bad). Now it is rare for a pitcher to pitch into the 7th inning AND we know so much more about how defensive positioning plays into accounts not to mention we are punishing good pitchers for being on bad offensive teams.
RBI(Runs Batted In) is another stat that is unfairly influenced by the quality of the other players on your team. If you have players in front of you who are good at getting on base – you will have more chances to drive them in than if you are a good hitter that never has anyone on base when you come to the plate.
For example, on page 35 he shows the example of Joe Carter in 1990 for the San Diego Padres. He hit .232 with a .290 OBP – but was third in RBI for the NL with 115. He made more outs that year than any other hitter in the NL. Yet, he had some of baseballs best ever at getting on base in front of him, including Roberto Alomar(.340 OBP), Tony Gwynn(.357) and Jack Clark(.441). Carter’s was just .290 for the record. That season Carter had 542 baserunners on base for his 697 plate appearances. Next closest was 496 runners on base. So in some sense – who knows how many MORE he SHOULD HAVE knocked in if he had actually hit better that season. Yet the RBI was seen as a seminal stat to be worshipped and he was rewarded in fact with a large contract by the Blue Jays – where of course he is forever remembered with an RBI double to clinch the 1992 World Series and a home run in the 1993 World Series off of Mitch Williams to cement his place in baseball history.
The save stat, invented by Jerome Holtzman and in place for MLB since 1975, is another catch-all stat to measure relievers which again unfairly gives more credit to the reliever who is designated as the “9th inning guy”. This now helps pitchers in salary arbitration but also keeps bad pitchers in the major leagues longer than they should be. We saw the world of baseball start to see their eyes opened to this in the playoffs last year as Andrew Miller in particular was used in every way possible – except just the 9th inning. By contrast, the Orioles lost a one game playoff game when a reliever with arguably one of the absolute best seasons ever didn’t appear in the game.
Between this book and Big Data Baseball -what is even more exciting is thinking about all of the frontiers that we haven’t yet gotten to. The StatCast Revolution is coming, as teams have more data than they currently know what to do with – and how that will affect positioning and even pitch selection remains to be seen. On top of that is how data might help reduce injuries, pitcher stamina and more and you get the feeling that we are just now at the tip of the iceberg as we slowly realize just what we don’t yet know.
Law uses the term Smart Baseball (on Twitter he often hashtags #SmrtBaseball a Simpsons reference) because so many times teams use old conventional wisdom and think they are being smart – in the way Homer says he is Smart, spelled “S-M-R-T” of course. For example, the sacrifice bunt is NOT smart baseball. The stolen base is only smart if the number of times you are CAUGHT stealing doesn’t exceed your successful attemps(hint, any caught stealing is a big waste). Waiting to use your BEST pitcher until there are exactly three outs to go and you are up by no more than 3 runs but at least 1 run is NOT smart baseball.
All in all – the book is a great introduction with some meat on its bones into some of the more advanced sabermetric statistics and gives some good mostly plain english talk into why so many of these widely used stats should be retired ASAP. The better we can measure players the better the talent gets in the sport gets and the quality of play is elevated all the way around. Definitely recommend reading this book!