In a system where the typical margin of victory is 30 points or more, the difference between a "consistent" running back scoring 10 points and an "inconsistent" running back scoring 5 in a given week is negligible, but those 30-point spike weeks from the inconsistent back suddenly look a lot more useful.

When analysts model consistency under real-world conditions rather than relying on just-so hypotheticals, they find a negligible effect. For instance, when a poster on Footballguys' message board ran a Monte Carlo simulation on one of his leagues comparing a hypothetical receiver who scored 10 points every week (10ppg average) to a different receiver who scored 5.25 points twelve times and 30 points three times (10.2ppg average), he found both receivers produced an identical winning percentage.

In another simulation, an anonymous author found that if they filled an entire team with consistent players and a second team with inconsistent players, the second team needed to average just 0.5 more points per game (not per player, but for the team as a whole) to achieve the same record as the first.

Because they use intentionally exaggerated examples of "consistent" and "inconsistent" players, studies like these set an upper limit on the potential value of consistency. That upper limit is somewhere around 3 points per season for a maximally consistent player or 8 points per season for an entire maximally consistent team-- just one extra 20-yard reception or one extra 20-yard touchdown run over an entire year.

(This also takes as a given that we can even identify consistent players in advance, which is overly generous. Historically, there is virtually no correlation between a player's consistency from one season to the next.)

Players Don't Exist In a Vacuum

Comparing players one-on-one is dangerous because fantasy football is not a game of one-to-one comparisons. Every consistent or inconsistent player will have six or more teammates around him. 

I was provided an example after the 2021 season. Joe Mixon and James Conner ranked 4th and 5th in points scored but were very inconsistent. Aaron Jones and Josh Jacobs ranked 10th and 11th but were much more consistent from week to week. Someone told me they would prefer the Jones/Jacobs duo to the Mixon/Conner duo, which prompted me to check the box scores.

Individually, Mixon and Conner were inconsistent. Together? Mixon's big weeks happened to coincide with Conner's duds and vice versa. As a result, they outscored the Jones/Jacobs duo in eleven out of eighteen weeks. 

Your Team Is A Portfolio

The key insight here is that when you bundle high-variance assets together, the resulting portfolio has a much lower variance. A single boom/bust player might only boom 25% of the time, but if your lineup features eight boom/bust players, invariably, several players will boom in any given week to offset all the others who busted.

(Hey, if Forbes can write about fantasy football, then Footballguys can write about Modern Portfolio Theory.)

Today, I wanted to test this by seeing if we can find more Mixon/Conner pairs where the duo was more consistent than either back alone.

To do this, we need to define consistency. This is a stickier wicket than it might first seem-- many of the common definitions prove unsuitable for the task. Some choose to define consistency by how often a player hits some sort of minimum threshold-- the two most common ones I've seen are 10 points or "a Top 12 / Top 24 / Top 36 weekly finish".

The problem is that these tend to be less a measure of consistency and more a measure of points scored. (A running back who tops 10 points in fourteen different weeks scored at least 140 points for the season, after all.) They also tend to be fairly arbitrary; by the former measure, a back who scored 9 points in every game would be "less consistent" than a back who scored 11 points four times and zero points every other week.

Another approach is to calculate the standard deviation of a player's weekly scores. This is better-- after all, the whole purpose of standard deviation is to quantify how much a value varies from observation to observation. But standard deviation tends to be proportional to the mean, so this will find that all of the highest-scoring players are also the "most inconsistent".

(For a quick illustration of this, imagine a league with fairly typical scoring settings-- 1 point per 10 yards, 6 points per touchdown, 1 point per reception. Now imagine a running back who averages 15 points per game with a standard deviation of 7 points. If you take that league and double all point values-- giving 1 point per 5 yards, 12 points per touchdown, and 2 points per reception-- the same running back will now average 30 points per game with a standard deviation of 14 points. The standard deviation doubled in size despite the underlying performances remaining unchanged.)

A Suitable Measure

Fortunately, there's a simple fix for this: if we divide a sample's standard deviation by its mean, we get its "coefficient of variation", or CV. A player's CV represents the percentage of a player's average performance that tends to vary from week to week. Players with lower CVs are "more consistent" than players with higher CVs.

With this in hand, I have taken all running backs who have played in at least 15 games this season, sorted them by fantasy points scored in their first fifteen games, and calculated the standard deviation and coefficient of variance for the Top 20 backs. (Why fifteen games? Because an odd number ensures in any comparison, one back will "win" more weeks than the other.)

To make the comparisons cleaner and eliminate any issues with injuries or byes, I am lining comparisons up by game number for the player. As an example, "Game 5" for Bijan Robinson came in Week 5, while for Jahmyr Gibbs it came in Week 6 because the Lions had a Week 5 bye. Here's the full data set for those who would like to play along at home.

We'll describe any back with a CV at least 0.05 points lower as "more consistent", any back with a CV at least 0.05 points higher as "more inconsistent", and any back with a CV within +/- 0.04 points as "equally consistent". From here, we just need to find pairs where a more consistent back outscored a more inconsistent back in at least 8 of 15 weeks despite averaging fewer points per game over the full sample.

Finding Our Huckleberries

As it happens, there are five such pairs. Josh Jacobs (18.04 ppg, 0.36 CV) "beat" De'Von Achane (18.40 ppg, 0.51 CV) in nine games; Aaron Jones (14.49 ppg, 0.40 CV) beat James Cook (17.19 ppg, 0.46 CV) in eight games; Aaron Jones (14.49, 0.40 CV) beat Breece Hall (14.85 ppg, 0.55 CV) in nine games; and Tony Pollard (12.97 ppg, 0.42 CV) and Rico Dowdle (12.09 ppg, 0.45 CV) both beat Rachaad White (13.31 ppg, 0.53 CV) in eight games.

Now we can take those pairs and bundle them together, combining two "inconsistent" backs and letting them compete against the two "consistent" backs who beat them originally. There are eight possible combinations available: Achane and Cook vs. Jacobs and Jones; Achane and Hall vs. Jacobs and Jones; Achane and White vs. Jacobs and Pollard; Achane and White vs. Jacobs and Dowdle; Cook and White vs. Jones and Pollard; Cook and White vs. Jones and Dowdle; Hall and White vs. Jones and Pollard; and Hall and White vs. Jones and Dowdle.

In each of those eight sets, the consistent backs outscored their rival inconsistent backs an average of 8.4 times (and were outscored by the inconsistent back an average of 6.6 times). Did the consistent pairs tend to beat the inconsistent pairs as a result?

Reader, they did not. The best showing by a consistent pair was from James Cook and Rachaad White vs. Aaron Jones and Tony Pollard. In that matchup, the consistent backs (Jones and Pollard) beat the inconsistent backs 7 times and were beaten 8 times.

On the other hand, in the most similar pairing (James Cook and Rachaad White vs. Aaron Jones and Rico Dowdle), the consistent backs won only 3 weeks, with the inconsistent pair notching 12 wins.

In the other six matchups, the consistent backs notched 6 wins once, 5 wins four times, and 4 wins once. Overall, despite these all being instances where the consistent backs beat the inconsistent backs one-on-one, the inconsistent pairs finished with an average record of 10-5 against their more consistent peers.

There's an Even Bigger Problem

Again, the foundational story for the value of consistency is that fantasy football is a weekly game and a consistent back will score higher than an inconsistent back in more weeks. That's such an intuitive story that even when I wrote against the importance of consistency, I never bothered to question it.

And sure, we found five examples of that happening this year. But there were seventeen other pairs where the less-productive back outscored the more-productive back in eight or more weeks. In seven of those pairs, the less-productive back was equally consistent (CV within 0.04 points). And in ten pairs, the less-productive back was more inconsistent than the higher-scoring back he beat in eight or more weeks.

(Only twice did a lower-scoring back win ten times against a higher-scoring back, and in both cases the lower-scoring back was more inconsistent-- De'Von Achane over Derrick Henry and James Conner over Jahmyr Gibbs. The latter example was especially eye-opening; Gibbs ranked seven slots higher, averaged 2.64 more points per game, and was the most consistent back of the year, but Conner still outscored him in ten out of fifteen weeks.)

When a lower-scoring back won more weeks against a higher-scoring back in 2024, the winning back was twice as likely to be more inconsistent rather than more consistent. The exact opposite of what our story suggested.

This was not the result I was expecting to find, so I ran another season just to see if it was a fluke. Here's the same data from 2023:

This time, there were 22 pairs where a lower-scoring back beat a higher-scoring back in at least 8 of 15 weeks. In just four of those cases was the lower-scoring back more consistent than the higher-scoring back. In five of the cases, the lower-scoring back was more inconsistent, and in thirteen cases, the two backs were roughly equally consistent.

Putting It Into Perspective

In each season, there were 190 possible comparisons (1 vs. 2, 1 vs. 3, 1 vs. 4, and so on all the way down to 19 vs. 20). Across both seasons, that was 380 possible pairs. In only 44 of those comparisons (11.6%) did the lower-scoring back win more often than he lost against the higher-scoring back. Far and away the biggest takeaway here should be: if you want to win more weeks, you want the player who scores the most points.

There were 96 comparisons between a higher-scoring back who was more inconsistent and a lower-scoring back who was more consistent, and in just 9 of them the more consistent back won more weeks, a 9.4% rate. There were 175 comparisons between a higher-scoring back who was more consistent and a lower-scoring back who was more inconsistent, and in 15 of them, the more inconsistent back won more weeks, a nearly identical 8.6% rate.

Just to save some math for anyone counting along at home, this means there were 109 comparisons between two equally consistent backs, and in 20 of them, the lower-scoring back won more weeks, an 18.3% rate.

(Why were there so many more inconsistent pairs than consistent pairs? It's largely just a fluke resulting from small sample sizes-- in 2024, the most productive backs just happened to be the most consistent, which resulted in more "higher-ranked consistent vs. lower-ranked inconsistent" pairs. 2023 didn't show the same tendency.)

Finally, there were nine backs who appeared on both the 2023 and 2024 list. The correlation between their CV in 2023 and 2024 was just 0.08. As mentioned above, consistency is itself not consistent.

The Origins of the Myth

Set aside the demonstrated fact that once you start bundling backs together, inconsistent pairs become much more consistent. The entire story that a consistent player will outscore an inconsistent player in more weeks than not has proven to be a myth. And the reason is because the entire idea of a "consistent player" is a myth.

When studies and simulations find what a "consistent player" is worth, they do so using exaggerated hypotheticals-- the mythical "player who scores exactly ten points every week". That player doesn't exist. We can calculate the value, but it's purely an academic exercise because there's no such thing as a consistent player. There's only varying degrees of inconsistency.

2024 Jahmyr Gibbs was the most consistent back of the last two years with a CV of 0.32. (As an aside, Gibbs was below-average in consistency in 2023; remember, consistency is not consistent.) But even Gibbs had massive weekly swings. He scored 12 points in his fifth game and 32 points in his sixth. He scored 25 points in his 11th game and 10 points in his 12th.

On the other end, 2023 Breece Hall was the most inconsistent back with a CV of 0.72, more than twice as high as Gibbs'. But Hall experienced long runs of sustained success; from Game 4 to Game 13 he scored 10, 28, 20, 21, 10, 10, 18, 12, 10, and 26.

That's ten consecutive games, two-thirds of his entire sample. Across that stretch, his CV was 0.43. Hall shows up as "inconsistent", however, because he played on a snap count early in the year as he worked his way back from injury, left a game early late in the year, and finished with a massive spike week (43 points).

The difference between a Breece Hall season and a Jahmyr Gibbs season is sometimes as small as a twisted ankle and a broken tackle.

Dueling Narratives

Proponents of consistency tell a very compelling story. 

• Most fantasy games are close.
• Consistent backs outscore inconsistent backs more often than not.
• Those few extra points are often the difference between winning and losing.
• The excess points from "inconsistent players" in their big weeks often go to waste.
• Therefore, if you want to win, you should prioritize consistency.

I've discussed a lot of numbers to this point, but those numbers are just my way of showing my work. At the end of it all, I have a competing story to tell.

• Despite teams scoring similarly, few fantasy games are close.
• Because games are rarely close, big weeks rarely go to waste.
• Players who score more points outscore players who score fewer points more weeks than not.
• While exceptions exist, increased consistency doesn't make a player more likely to be one of them.
• Even when a player is an exception, bundling his score together with other players usually makes the effect disappear.
• Mostly this is because there's no such thing as "consistency" in fantasy football, only varying levels of inconsistency.
• Additionally, for dynasty purposes, it's very good that consistency doesn't matter because it's not consistent; players who are more or less consistent in one year are no more likely to be more or less consistent again in the next.
• Therefore, if you want to win, all you can do is chase the players who score the most points overall.

Is that story as compelling as the one for consistency? Probably not. But it has the advantage of being true.