The Quarterback Streaming Challenge: Week 2

A look in at the current state of the Quarterback Streaming Challenge.

 It's long been held as a point of fact that by only playing quarterbacks against favorable matchups, they would outperform their typical season-long average for you. So it was a matter of some surprise last year when my research demonstrated that that wasn't the case. Quite the contrary— quarterbacks averaged fewer points per game in weeks they were started than in weeks they were benched.

This was a shocking finding, and like any shocking finding, my first goal became reproducing it. While I was at it, I wanted to test several other common claims about the late-round quarterback, (LRQB), strategy. Can you really find quality starters late? Is the opportunity cost of waiting at the position really lower than any other position? It might be so, it might not be so, but it seemed to me that we needed data either way.

My early research took the form of a natural experiment; essentially, I observed expert leagues and drew conclusions. For the follow-up, I wanted to create a controlled experiment where I could account for any possible confounding factors and give us the truest data I could gather.

To this end, I recruited 21 volunteers to simulate a LRQB strategy to an expert league. Most of them are published analysts in the fantasy space, though a few spots have been given to regular fantasy owners with varying levels of experience.

The volunteers all selected two quarterbacks at the beginning of the season based on a list of players who could be reasonably expected to fall in a draft based on current ADP. They then have two roster spots to devote to the position and $200 in blind-bid waiver dollars to spend acquiring new talent. They were given two mandates: score as many points as possible, and devote as few resources as possible.

Throughout the season I will be chronicling their journey. You can see what the dedicated streamers are doing at the position, perhaps copying their strategy or taking notes in case you find yourself streaming or casting about for a quarterback in one of your leagues, and watching in real time as owners try to prove once and for all the value of the late-round quarterback strategy.

This is The Great Quarterback Streaming Experiment of 2016.


In order to avoid biasing the process, I will be keeping the participants anonymous. While they can see each others' past decisions, I will also be hiding all decisions in each week from the participants to avoid influencing their process.

I did, however, collect some information from them prior to the start of the experiment to catologue their hypotheses entering the project. And while we're not far enough in to really have good data on how things are going, I wanted to open the project by sharing their expectations.

First, I asked all participants to rate four statements on a five point scale. For all statements, a 1 means "strongly disagree", a 2 means "disagree", a 3 means "neither agree nor disagree", a 4 means "agree", and a 5 means "strongly agree".

Statement 1: I usually pursue a LRQB and/or streaming strategy in my 1-quarterback fantasy leagues.

The average of all responses was a 3.52, indicating this was a LRQB / Streaming-friendly crowd. Of the 21 participants, 10 owners answered either "agree" or "strongly agree", while only two chose "disagree" or "strongly disagree". (The rest, of course, were neutral.)

Statement 2: LRQB and/or streaming are the optimal strategy at the quarterback position in 1-quarterback leagues.

The responses here were a little bit less bullish, with an overall average of 3.24. Only seven participants either agreed or strongly agreed, and again only two participants disagreed or strongly disagreed. This was the only question where a majority of participants selected "neither agree nor disagree", indicating that while many owners pursue this strategy for themselves, most do not believe it should necessarily be the de facto approach for everyone.

Statement 3: By carefully selecting matchups, you can get production from a player that outstrips his typical weekly average.

This statement generated what was by far the most positive response with a group average of 4.0, indicating that apparently most of the participants had not read my own work on the subject from last season. (I don't necessarily blame them; my own mother doesn't read my work on the subject, either.) Another possibility is that they've read my work but have decided I have no clue what I'm talking about. (Another stance I wouldn't hold against them in the slightest.)

Regardless of cause, a shocking 17 out of 21 participants indicated that they either agreed or strongly agreed with the idea that by playing matchups they would be able to outperform their starters' typical weekly averages, and only two disagreed. (No one strongly disagreed.) I'm excited that they're all so optimistic, because this was by far the thing I was most interested in rigorously testing this season.

Statement 4: Owners have a good chance to find a solid long-term quarterback starter at the end of the draft or on waivers.

Owners were on the whole lukewarm on this notion, with an average result of 3.29. Opinion was most divided here, with ten owners rating this statement with either "agree" or "strongly agree", but with four "disagrees" or "strongly disagrees", which was double the total on any other question. For my part, I would be inclined to agree with the statement, and I think the ability to find quality quarterbacks off of waivers is the biggest strength of the Late Round Quarterback strategy.


Finally, after rating their agreement with those statements, I asked a pair of open-ended questions designed to gauge their own faith in their ability to successfully execute a LRQB / Streaming strategy. I noted that in the scoring system we were using, teams had averaged 20.4, 19.7, and 19.7 points per game at the quarterback position. I then asked them how many points they expected to score, as well as how many points they expected the rest of the participants to score.

Overall, the participants were optimistic, (as their answers to the four statements would suggest). The group as a whole rated that they expected themselves to score 18.76 points per game this year, which is anywhere from 1 to 1.5 points below the league average team, (who typically invested much more at the position).

Interestingly, the participants were less optimistic about their peers' abilities; the group indicated that they expected the other participants to average just 18.11 points per game, a difference of 0.65 points per game.

Like the residents of Lake Wobegon, we seem to have found ourselves a sample of people where everyone is above-average; 15 of the 21 participants expect to outscore the group as a whole, and three more expect to perfectly match the group average. Only three participants were brave enough to suggest that they expected the overall group to outperform themselves over the course of the season.


The setup of and expectations for the experiment are interesting, no doubt. Next week I'll do a deeper dive into the methodology, too. In the meantime, as I said, the results to this point are too thin to analyze. But I can give a quick overview of where things stand to this point. Again, if you're in a league where you're trying to stream quarterbacks, this should give you a good idea of who the pros like this week.

Added Players in Week 2, (with Waiver bid in parentheses; if there is no dollar value, the player was added in free agency after waivers ran):

With 20 of the 21 participants having declared their starter for this weekend, here are the top choices for week 2:

Best of luck to all participants this week, and to all of you at home who are cobbling together a quarterback stream of your one.


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