RADIO
High-variance, volatile football players. The risky bets. We all know who those players are and, most of all, we all know about what they can do--for the good and for the bad. When was the last time you trusted someone like Will Fuller or Amari Cooper to go off the charts and they let you down? You probably don't have to go too far back in time to find out. Just this past season, Fuller reached 53.7 PPR points in Week 5 and then broke 11.1 points just once in the six games he played after that one. That is certainly a volatile player.
During the 2019 season, one of the columns I wrote and spent time working on was related to the concept of "volatility." I covered it on a weekly basis, providing start/sit decisions to fantasy owners/players with different levels of what we can call "risk tolerance." If you're willing to take risks and go for the potential booming performance, then you might want to look at the names on the volatile column. If you'd rather play it safe and avoid any major upset, then the stable column is the one for you.
Now that the season is over, let's take a look at volatility from years past and how we can use it going forward in our fantasy football leagues.
Be sure to check all of our fantasy football rankings for the 2025 playoffs:- Quarterback fantasy football rankings
- Running back fantasy football rankings
- Wide receiver fantasy football rankings
- Tight end fantasy football rankings
- Kicker fantasy football rankings
- FLEX fantasy football rankings
- Defense (D/ST) fantasy football rankings
- Superflex fantasy football rankings
- IDP fantasy football rankings
- Dynasty fantasy football rankings
How To Define Volatility
For my weekly column, I kept things as simple as possible. Every game, players log a fantasy points tally we'll call PPR here. We're accustomed to it and it is nothing new. You know how it goes: one point per reception, a tenth of a point per rushing/receiving yard, six points per touchdown, etc.
Any player with at least two games played during the season would have generated at least two PPR marks, of which we can calculate the average by adding them together and then dividing them by two. We can also start to know how volatile a player is game-to-game just by calculating the standard deviation from that set of two games. What we would get is the variance of those couple of performances compared to the average.
There are Amari Cooper's and D.J. Moore's 2019 seasons and their PPR tallies over the year. When all was said and done, both Cooper and Moore had averaged the exact same 15.5 PPR/G, but as you can see they reached that point in very different ways. Cooper used very bouncy ways while Moore was more of a steady performer.
If we look at their volatility marks over the season, that's exactly what we get: Cooper's volatility was at 11.6 PPR/G while Moore's finished at 5.8 PPR/G. In other common "fantasy-world" words: Cooper was your 2019 boom/bust WR play while Moore fell into the safe-bet category of players.
How To Use Volatility To Our Advantage
The easiest and most straightforward way to make use of any player's volatility is to calculate the range of outcomes we can expect from a player based on it. Take the example above.
| Player | PPR/G | VOL | Floor | Ceiling |
| Amari Cooper | 15.5 | 11.6 | 3.9 | 27.1 |
| DJ Moore | 15.5 | 5.8 | 9.7 | 21.3 |
As you can see, Cooper is definitely the player you'd be putting in your lineup if you feel you'll need a good amount of points to catch your opponent, while Moore is probably the one you'll play if you feel comfortable getting a bunch of safe points without much upside.
Such a simple calculation might not win me a job in NASA, but it is close enough to the actual results both Cooper and Moore posted during the year. Cooper's actual worst three games went for 0, 1.3, and 2.9 PPR, and his best games for 39.6, 31.7, and 26.8 PPR. Moore's worst ended at 1.1, 7.4, and 8.8 while in his best he got 31.3, 21.0, and 20.3 PPR. Excluding the outliers, those numbers align very well with our calculated floors/ceilings using volatility as defined earlier.
How Does Volatility Relate To Fantasy Production?
The first question that comes to mind when trying to understand and assess volatility and its implications is how is it related to actual fantasy production. Are volatile players better overall performers than stable ones? Is volatility tied to average scoring in any way? Let's see.
First of all, I have to say that for this and the rest of the charts/calculations I will be using a dataset containing every game played by every QB/WR/RB/TE since 2000. I have calculated the PPR outcomes of the players myself with the data at hand (that is why the values may slightly vary for those available in other tools of the site, but the changes should be minimal). I have calculated the PPR and the Volatility (VOL) of each player-season, and in the end, I have ended with a dataset containing 11,001 player-seasons. Of those, 9,221 included volatility data (min. 2 games played) and therefore are the data points we can work with.
To get things kickstarted, this is how each of those player-seasons went in terms of PPR (best players at the top) and VOL (most volatile players at the right side).
The relation is obvious and to a certain point expected. The more points a player scores on average, the more volatile he tends to be. It makes sense, as keeping up high PPR-averages is hard and highly unsustainable over a long period of time.
For the plot above I included every player-season available in the dataset. Now, I have trimmed the data points to just those pertaining to players with at least 10 games played in their seasons.
The results are pretty much the same, only now we don't have a bunch of outliers hanging around. For the whole dataset, the correlation between PPR and VOL yielded an R-squared value of 0.64 and for the 10G+ one, it raised to just 0.65, an insignificant difference. Those are high enough numbers to consider there is a strong relation between volatility and production/upside.
Does Volatility Impact Positions Differently?
In order to drill down a little bit more, I have separated the players inside the dataset by position (remember, we're using the four basic positions for fantasy football: QB, RB, WR, and TE). Here is how they compare in terms of volatility and production.
The perception of volatility changes a lot when splitting the data this way:
- Quarterbacks' PPR and VOL have R-squared value of just 0.08, by far the lowest among the four positions.
- Running Backs' PPR-VOL relation goes up to 0.43
- Wide Receivers' and Tight Ends' PPR-VOL relations are the highest at 0.55 both
In contrast to the three skill-positions, all quarterbacks have volatility levels over 3-VOL points (only 19 quarterback-seasons are under the 4-VOL mark, in fact) with an average of 6.5 between all 619 data points.
As an instant takeaway, we would say that pursuing volatile quarterbacks is definitely not a sound strategy, as there seems to be so little relation if any between scoring and volatility at the position, opposite to what happens in the other ones.
That covers most of the initial thoughts about volatility and its impact on fantasy football, although this could just be the tip of the iceberg. That's why I will keep exploring the concept and writing about it in future columns with the goal of getting to fully know if volatility is something to give any sort of importance while making fantasy decisions.
More Fantasy Football Analysis
