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100 Fantasy Football Tips in 100 Days, Day 5: Beware of ‘Consistency’ in Individual Players

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Today’s tip comes via my book Fantasy Football for Smart People: What the Experts Don’t Want You to Know:

While certain players possess more season-to-season consistency than others, the short NFL season makes over-analysis of each game unavoidable. When a baseball player goes 1-for-10 over a two-game period, we often chalk it up to being unlucky. Meanwhile, when a quarterback turns in two poor performances in a row, the sky begins to fall in fantasy land.

Imagine cutting up the MLB season into 16-game segments. Each player would have a few segments of really poor play and a few periods of outstanding play. Over the course of the entire 162-game season, those peaks and valleys tend to even out, which is why baseball players have such consistent stats from year to year.

Well, the NFL season is too short for those tendencies to always even out. Thus, we often place more emphasis on individual games than we should because, well, it’s all we have to analyze. We label Player X as ‘consistent’ and Player Y as ‘injury-prone,’ not realizing we’re really just looking at the equivalent of one of those little 16-game slivers that MLB players participate in 10 of each season.

Imagine that a group of 25 receivers all have a 50 percent chance of putting up respectable fantasy numbers in a given game (how you define ‘respectable’ is irrelevant to this example). For each player, the odds of posting quality fantasy stats are no better or no worse than a coin flip. What kind of results would we expect?

Typically, you’d see around half of players post between seven and nine respectable games. Almost all of the remaining players would fall between four and 12 respectable games, with a few outliers having either an outstanding season of 13-plus big-time performances or a horrible season of three or fewer quality games.

Actually, the results would closely resemble the graph below, which is a series of 400 virtual coin flips I just completed. I broke the coin flips down into sets of 16 (to represent each game in an NFL season), tracking the number of heads that came up during each trial of 16 flips.

coin

You can see that just over half of the trials ended up with exactly seven, eight, or nine heads. That’s to be expected. What many people don’t anticipate are the trials that end up as outliers: just a couple or all but a few flips being heads.

Actually, of the first 16 flips, 14 were heads. With more flips, however, the number of tails “caught up”, i.e. regressed toward the mean, and all was well in the world of randomness.

The takeaway here is that, in any set of random (or near-random) data, we’ll see lots of “abnormal” results. If you assign Calvin Johnson a 50 percent chance of going for 100 yards and a touchdown in any given game, he’ll probably wind up with somewhere around eight games with such numbers. But there’s also a solid chance that he’ll appear to have either an unusually outstanding or a very poor year. With a 50 percent chance of 100 yards and a score in any game, Megatron is probably around as likely to have either five or 12 stellar games as he is to have exactly eight.

Because the number of games in an NFL season is so low, it’s really easy to see patterns in data that aren’t really there. Over the course of even a few NFL seasons, we’d expect some players to appear to have a huge degree of weekly consistency, even if consistency were completely random. Similarly, even with total randomness, a handful of players would appear to be “all-or-nothing” fantasy options without much consistency, when in reality they possess just as much consistency as the most reliable performers.

You can buy What the Experts Don’t Want You to Know on this site or on Amazon. Don’t forget that I have a big announcement coming later this week.

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