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February 18, 2015 The QuintonThe Players We Overlook and the Ambiguity Effect
Every year I look back on the season and say, “How did I miss on that guy?” Unfortunately, I always end up asking this question about multiple players after each season. I am going to venture a guess that I am not alone in experiencing this. That said, it is often a good thing that we miss on some out of nowhere players; to quote Kathryn Schulz’s excellent Being Wrong: Adventures in the Margin Error, “being wrong is often a side effect of a system that is functioning exactly right.” In other words, when dealing with an uncertain future, good process can still lead to misses—to bad results. Missing on Danny Santana posting a .405 BABIP or Michael Brantley posting a HR:FB rate nearly double his previous career high (by “miss,” we mean not paying a draft or auction day price for these breakouts) is actually a positive for our process rather than a knock against it. (Note: If we missed for predictable reasons, then that would be a knock on our process.) However, these misses—the bad beats, the good process-bad outcomes—are not the misses I was talking about earlier. Rather, I was talking about the misses that should have been avoided. More specifically, the ambiguity effect causes us to miss out on players each year. Below we will take a look at the ambiguity effect, its different forms, and some strategies to battle it. When Craig Goldstein and I put together our combined three-year outfield rankings, there was a particular discussion that happened repeatedly that relates to the previously mentioned misses and the ambiguity effect. That discussion always kind of went like this: “Is Player X too low?” This actually worked out great because it forced us to dig into the player and make, hopefully, a better decision as to the player’s ranking. Why is this important to our fantasy baseball decisions? Because almost all of us do this; there are a lot of players to choose from and evaluating them all probabilistically is a daunting task. Consequently, we come up with valuations on the majority of players and ignore the ones that we do not know what to do with. You know these players, I know you do. Whether you make your own rankings, use rankings from the internet, or use some combination of the two, there almost always comes a time in every draft or auction at which you pass over (or consider passing over) the top player on your list or let a player go for less than your assigned auction value. We do this not out of a sense of charity to our leaguemates or masochism. Rather, this is probably just how we make decisions when facing uncertainty. It took me a while to get here, but this is the ambiguity effect, a cognitive bias that shows our preference for more certain odds to less certain odds. The reason that this is considered a cognitive bias rather than just reasonable decision making is because we often pick propositions with worse, but more certain odds than propositions with better, but less certain odds. Here are a few players that I missed last year (and there were certainly many more) because of uncertainty that surrounded them, and I am again guessing that I am not alone: Melky Cabrera, LaTroy Hawkins, Charlie Blackmon, Phil Hughes. Again, the reason we pass on these players is not because we thought they were terrible; rather, we just did not know what to think. As a result, such players often end up being great values because they are being discounted for reasons other than their projected value. There are several different ways an outlook for a player can appear ambiguous and with each way our valuations can be corrupted. Uncertainty about production, health, and playing time all cause us to overly devalue players. Regardless of the reason for uncertainty, our issue is not with a player’s entire range of potential outcomes (the upside is wonderful); rather, our issue is with the most negative outcome. We know we tend to overweight extreme-negative outcomes because of our risk-averse nature. The result of all this is that our valuations for players with seemingly ambiguous odds for future production tend to be attempts at removing all risk. For example, Jarrod Dyson went for about $5 in most AL-Only leagues because of uncertainty over playing time, even though he earned $14 in both 2013 and 2012, while also facing uncertain playing time. As we can see, Dyson got valued at his worst-case scenario because of the ambiguity effect and risk aversion. Okay. So we have an idea regarding the how and why of the ambiguity effect as it relates fantasy baseball, but what can we do about it? Two pieces of advice: 1. Search your valuations for gaps and question marks 2. Put odds on outcomes Lastly, while we try to remove the negative consequences of the ambiguity effect from our own process, we would be keen to take advantage of its consequences on our competitors’ decision making. While every fantasy baseball participant understands that there is no absolute certainty in the game, many participants will take great measures to avoid risk as much as possible. The consequence of this is that there tends to be many profitable yet risky bets for the taking. When these bets fall to us, embrace the risk and take comfort in the cost and potential payoff.
Jeff Quinton is an author of Baseball Prospectus. Follow @jjq01
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A really helpful way to approach my draft, Jeff. Great article.