The NFL Draft and Information Cascades
Every year in the NFL Draft, a heralded college prospect is projected by almost every source to be a very high pick. Instead, they end up falling, with each new team opting to select another player. Sometimes these huge draft slides can be looked back at in hindsight as a blessing in disguise, as the prospect ends up having a very unimpressive career. Other times, the prospect ends up panning out and having a storied career – some names that come to mind include Aaron Rodgers and Randy Moss – and all the teams that passed on them are forced to watch from the opposing sideline. This article discusses how information cascades can lead to steep draft slides, and even discusses the potential of Justin Fields (once projected as the second quarterback to be drafted) to be a victim of an information cascade based draft slide in the 2021 NFL Draft.
A draft is a great example of a situation where information cascades come into play. Teams pick players and opposing teams watch these picks carefully. There are two states involved, either draft or do not draft, and private signals involved that each team could receive. These signals could include good information such as combine information, season stats, interviews with the team, player comparisons, etc. They could also include bad information, such as behavioral issues or negative player comparisons. Both of these signals would most definitely influence a team’s decision to draft a player. Finally, a decision must be made on a player, whether to draft them or pass on them. These components are generally all present in an information cascade, and as seen are present in a draft. The article then focuses in more on the signals and discusses a few decision biases that can affect these signals. Availability bias is “a tendency to overly rely on easily accessible or available examples when performing an evaluation.” In the case of an NFL quarterback, this could be harmful if a prospect has a glaringly similar play style to a former quarterback who ended up being a draft bust. This was the case with Justin Fields in – his rushing ability and big physical stature drew comparisons to Dwayne Haskins. This definitely hurt Justin Fields, as Haskins played two horrendous seasons before his release from his team, after videos of him at a club during COVID were leaked. Negativity bias is when negative information is overvalued relative to positive information. This was the case with Laremy Tunsil, where right before his draft a video surfaced of him using a bong with a gas mask on. Tunsil instantly fell from a projected top 3 pick to the 13th pick. He was likely a part of an information cascade where each subsequent team put more and more value on this one negative video and continued to pass on him in the draft until the Miami Dolphins finally broke the cascade and selected him. Those twelve teams that passed on him are likely shaking their heads, as Tunsil has had a great career thus far.
Finally, the article goes in depth on Justin Fields. If the New York Jets simply liked Zach Wilson (another QB) more and drafted him second, suddenly Fields drops from the second pick to the third. Then if the next team, the 49ers, observe this new information and factor it into their draft pick, they might see it as a red flag and choose another quarterback. Teams begin to think there may be some unknown negative information around Fields, and thus a cascade begins. With each team that passes on Fields, the concerns grow, and teams potentially continue to pass on drafting him until one team breaks the cascade. This article was written two days before the draft and was actually correct in their prediction. Fields dropped to the 11th pick and the fourth quarterback taken. This drop right now looks like a good move, as Fields and his Chicago Bears have looked relatively unimpressive so far. However, Fields could breakout and have a storied career, making this yet another case of a painful NFL Draft slide – only time will tell.
Source: https://www.fandomanalytics.com/post/the-fall-of-justin-fields-an-information-cascade-theory