Is Proprietary Information Disappearing? by Jesse Wolfersberger April 24, 2012 Carl Crawford, Adam Dunn, and Jayson Werth signed large free agent contracts with new teams last offseason, and each were unequivocal disappointments in 2011 with their new club. This phenomenon is not limited to free agents. In recent memory, several highly touted prospects have been traded and not lived up to expectations with their new teams: Justin Smoak, Brett Wallace, and Kyle Drabek, to name a few. Whenever a player changes teams and fails to live up to expectations, I find myself wondering, “Did his old team see this coming?” In these specific examples, we may never know, but we do know that teams have internal information which creates an advantage in personnel decisions. While this advantage may never completely go away, there is evidence to suggest that it’s starting to disappear. For any given player, all teams have access to public performance statistics, and any team is free to send a scout to watch a major- or minor-leaguer play. That data isn’t proprietary. What is proprietary are the years of internal data, scouting reports, and notes from coaches, doctors, and teammates. In his press conference after having his pending steroid suspension lifted, Ryan Braun gave some insight into the type of internal data the Brewers keep on him: “When we’re in Milwaukee we weigh in at least once or twice a week. I was able to prove that I literally didn’t gain a single pound. Our times are recorded every time we run down the line, first to third, first to home. I literally didn’t get one-tenth of a second faster. My workouts have been virtually the exact same for six years. I didn’t get one percent stronger. I didn’t work out any more often. I didn’t have any additional power or any additional arm strength. All of those things are documented contemporaneously, and if anything had changed, I wouldn’t be able to go back and pretend like it didn’t change.” In one paragraph, Braun revealed that the Brewers keep internal numbers on his weight, three running statistics, workout performance and frequency, and some kind of data on bat speed and arm strength. When the Milwaukee front office met about Braun’s contract and had to decide whether to offer an extension or let him go to free agency, that data certainly helped inform the decision. In some cases, Crawford for example, there is hardly a decision to be made — the team simply cannot afford the player anymore. In other cases, a team might have a cheaper prospect ready to take the player’s place. However, one has to wonder how many times a team has internal information which leads to trading the player or not offering a competitive contract in free agency. This topic has been brilliantly covered by FanGraphs contributor Matt Swartz at The Hardball Times and in their 2012 Annual. Also, this post at The Book Blog discusses Matt’s findings. The gap definitely exists, and its existence should not come as a surprise. In the long run, whoever has more information will make better decisions, and teams have more information about their own players than the rest of the market. Not every player who changes teams is doomed. However, this result suggests that it is likely that Albert Pujols, Prince Fielder, Jose Reyes, Mat Latos, Heath Bell, Carlos Beltran, Michael Pineda, Jesus Montero, and all the other players who changed teams this offseason are more likely to disappoint their new teams than impress them. Taking Matt’s analysis a step farther, this post argues that the proprietary information gap is closing. There is more public information available today, and teams are doing more with it, than there was ten or even five years ago. Consider Pitch FX. Today, anyone can quickly find the speed and movement from every pitch in last night’s game. Ten years ago, if one team had this info and another team didn’t, it would make for a huge competitive advantage. Matt looked at the effect on multi-year contracts, but for trending purposes, let’s just look things on a year-by-year basis. Players who were on the same team as last year are put into one pool and players who changed teams during the offseason are put in the other. Low sample size players and those who changed teams mid-season are thrown out. Overall, hitters who changed teams did 3.6% worse than those than those who did not, and pitchers did 3.7% worse. There is a problem with this data though. The average age of the “leavers” is about a year older than the “stayers.” This is because teams are more likely to hang onto young players due to the arbitration rules. Team-controlled players are cheaper than open-market players, so teams are more likely to keep them around. To fix this issue, we need to restrict the data set to players who are not arbitration eligible. Non-Arbitration Eligible Players Stayers Leavers Hitters (wOBA) 0.338 0.325 Pitchers (SIERA) 4.04 4.20 The average age for both groups is now almost exactly the same, and the advantage still exists, and is actually slightly larger. Hitters who changed teams did 3.9% worse and pitchers did 4.2% worse. This is not a perfect analysis, and if I were just trying to measure the size of the gap, I would defer to Matt’s work. What this method allows us to do is trend the data. For pitchers, the trend is as follows: In less than 10 years, the proprietary information gap has gone from about 7% to about 2%. While players who left their teams did better in 2004 and 2010 than players who stayed, that is unsustainable. There will always be a gap, it is simply impossible for opposing teams to have the same amount of information as a player’s current team. However, it appears as if the amount of information, or the usefulness of that information, is decreasing when it comes to pitchers. Now for the hitters: At first glance, there does not appear to be a trend of any kind. Perhaps this is true. However, note that this graph starts in 1991. Because wOBA is not dependent on batted ball data, where SIERA is, it allows for a longer date range to study hitters. If you just look at recent data, a different story emerges: Definitive? Of course not. Suggestive? I think so, especially considering it mirrors the trend found in the pitcher data. And, just like the pitcher data, there is a natural asymptote at zero — this trend will approach zero, but never completely disappear. In a way, these trend lines represent the sophistication of the market. As the data revolution in baseball began, teams who were ahead of the curve could make advantageous trades and make smarter free agent decisions than the teams who were behind. However, as more teams embrace Sabermetrics, it got harder and harder to make one-sided trades and the free agent market became more and more efficient. The proprietary information gap will never completely disappear, but it is probably half the size it was five years ago, and a quarter the size it was 10 years ago.