This week on the podcast, we tackled topics concerning failure. We did our part to run in circles around the Astros draft saga and also answered some reader questions. We also spent some time considering and discussing our collective failures as Scoresheet owners in 2014. One of the things we’d like to do is setup a framework for analyzing teams that underperform, in order to identify potential improvements, patterns of mistakes, or other ways that we could have done better on draft day.
The first step is to gather information and data, including the draft day valuations, the real life MLB performance of players to date, and the Scoresheet performance of players to date. The Baseball Prospectus Team Tracker is a helpful tool to get this information, and the remainder can be found on the Scoresheet league pages. Be careful when analyzing team-level results, especially if you’ve made personnel changes (i.e. traded away short term value), because they may not be indicative of mistakes you made on draft day, but the aftermath of going Full Rebuild (tm?).
The next step is to compare the draft day expectations to the real life performance, and then compare the real life performance to Scoresheet performance. In the first comparison, you can figure out whether or not players had a bad season in general, and hopefully identify any potential patterns in the guys you drafted that performed poorly. Perhaps you took too many guys trying to recover from injury or too many veterans on the precipice of collapse, and these are the kinds of things you can avoid going forward. In the second comparison, you can figure out whether you were utilizing the players appropriately on your Scoresheet roster. In most cases, you should be able to get better performance in Scoresheet from your pitchers than in real life by using aggressive hooks like we’ve discussed, and padding the bullpen with some depth.
As warranted, you can dig into some detail on particular players performing below expectations. We’d focus on the key Scoresheet metrics: PA, OBP, SLG for hitters and IP, ERA for pitchers to get a sense of playing quantity and quality. If you’re not sure why a batter struggled, or you want to figure out if it was something that will persist, there are indicators to check. If his OBP seems low, you might want to investigate his BABIP (which influences AVG and thus OBP) and his walk percentage (BB/PA) to see if he’s become less selective or got hit unlucky over the season. If his SLG seems low, you might look at his HR/PA or his extra-base-hit percentage (XBH%) see if there’s underlying reasons that his power dipped. Of course, there are many other ways to investigate the details around player performance, and you’ll find everything you need on the BP player cards—including fascinating stuff like plate discipline. For pitchers, you’ll probably want to check into BABIP, see if his velocity decreased, and see if there were particular games or sequences that might have had a disproportionate impact on his runs allowed.
Finally, you want to sit back and take it all in with some perspective and decide whether you could have done better with the information that was available to you on draft day. We’re not talking about knowing which pitchers would get hurt, but we are talking about making sure you’re taking risk of injury into account properly. We’re not too worried about having to setup some platoons to cover offensive performance, but it might be better to have platoons in the corners and have studs up the middle, rather than vice versa. There are other considerations like these that you may find in the patterns from the comparisons that you do. It could all turn out to look like bad luck, and that’s just as valuable to learn as finding any pattern. Either way, you can come away more informed and go into the next draft with a sense of confidence that you’re doing the best you can with what you’ve got.
Thank you for reading
This is a free article. If you enjoyed it, consider subscribing to Baseball Prospectus. Subscriptions support ongoing public baseball research and analysis in an increasingly proprietary environment.Subscribe now