Welcome back to the Data Viz DFS NFL Preview utilizing data science & data visualizations. Today we will be previewing WRs utilizing targets per game, red zone targets, & TDs. But before we jump head first into all the fun – lets define a few key terms that will help us navigate and understand this article better.
Outlier: If a value is more than 2 standard deviations away from the median, that data point is identified as an outlier. Basically a person or thing that differs significantly from the other members of that data set.
Standard Deviation: Standard deviation is a number used to tell how measurements for a group are spread out from the median, or expected value.
1 Standard Deviation: Data within 1 standard deviation of the median can be considered fairly common and expected. Essentially it tells you that data is not exceptionally high or exceptionally low. 68% of the population falls within 1 standard deviation.
2 Standard Deviations: Data that lies within 2 standard deviations of the mean accounts for 95% of the population. Basically the majority of the population (95%) will fall within 2 standard deviations of the median. All values outside 2 standard deviations are the outliers of the group.
Median: The value or quantity lying at the midpoint of a data set. Basically there is an equal probability of falling above or below the median.
Now that we understand the key terms & why they are useful, it is time to strap on our crazy curly wig & channel our inner Malcolm Gladwell because today our topic is all about outliers.
“Outliers are those who have been given opportunities and who have had the strength and presence of mind to seize them.” – Malcolm Gladwell
I doubt Gladwell was talking about fantasy football when he said the above quote – but man it feels like he was. Let’s reword it so it makes sense when analyzing fantasy football. So instead of saying ‘Outliers are those who have been given opportunities” let’s re-word it to say ‘Outliers are those who have been given high targets per game & high red zone targets.” And instead of saying “who have had the strength and presence of mind to seize them” lets say “who have had the strength to convert these to TDs.”
We will be utilizing this new quote as the foundation of this article: “Outliers are those who have been given high targets per game / high red zone targets and who have had the strength to convert these to TDs.”
The purpose of our first visual is to show what WR are outliers when looking at fantasy points per game. This was executed utilizing a dot plot where the y-axis is fantasy points per game (PPR) & each dot represents a different WR. The size of the circle is based on total TDs & the color is based on targets per game (blue is good & orange is bad). The median amount of fantasy points per game is 5.94 & the grey area represents 2 standard deviations from the median.
Fantasy Points Per Game Outliers (PPR): Mike Evans | Chris Godwin | Cooper Kupp | Michael Thomas
The purpose of our next visual is to show what WR are outliers when looking at targets per game & red zone targets. This was executed utilizing a scatter plot where the y-axis is targets per game & the x-axis represents red zone targets. Each circle represents a different WR, the size of the circle is based on total TDs, & the color is based on fantasy pts per game (PPR) – blue is good & orange is bad. The median amount of targets per game is 5, the median amount of red zone targets per game is 4, & the grey shaded area represents 2 standard deviations from the median.
The 4 pts per game outliers from the previous viz (Mike Evans, Chris Godwin, Cooper Kupp, & Michael Thomas) are also outliers in this scatter plot. This is a good indication that red zone targets & targets per game leads directly to fantasy points.
Julian Edelman is a monster in the red zone & the safest bet to put up numbers each week. The combination of red zone targets(17) & targets per game(10) makes Edelman easily the safest pick week in and week out. The addition of Mohamed Sanu to the Pats may cut into Edelman’s red zone targets – but Edelman is as safe as they come. Look for Edelman to pick up where he left off once he comes off a bye in week 11.
Michael Thomas can produce regardless of the QB situation. When Drew Brees went out – I assumed Thomas would have a major drop-off. That has obviously not been the case & with Brees back and producing – Thomas could make a run at the top WR spot. For now, I think Evans & Edelman are safer choices – but Thomas is in that same upper echelon.
I’m surprised there is this many ‘short’ WRs on this list (Edelman, Lockett, Jarvis Landry). When I started this exercise I did not expect these WRs to be such a force in the red zone. Obviously my bias against short people is shining through but the stats show that I was incorrect for thinking this.
I wish Allen Robinson was on a different team. Robinson is the real deal but will never unlock the full potential with such poor QBs throwing his way. Robinson should be a top 5 WR but in reality he puts up less than 10 pts per game.
Jarvis Landry is heavily targeted but does not put up fantasy points. Landry may be the biggest anomaly among the group – putting up only 7.9 fantasy pts per game. With his volume – we would expect nearly 5 pts per game more. This may fall on the coaching staff or Baker but either way Landry does not put up the points expected.
Chris Godwin & Mike Evans are the best duo in the league. Now imagine the outlandish numbers they would be putting up if Jameis was actually competent. Either way – due to the style of play & raw talent – these WRs are putting up ridiculous numbers.
Cooper Kupp is not a flash in the pan. Kupp unfortunatyel got hurt last year which provided us little sample size when analyzig Cupp. Now through 9 weeks of the season – it is clear he is a stud. Cooper not lonly has high targets per game & red zone targets but he also turns those into TDs with relative ease. Kupp will be a force the remainder of the season and for seasons to come.