Run_Pass Time Analysis : 2016 Part 1

by John Bush

Run_Pass Time Analysis Introduction.

Key questions for a fantasy football drafter can include the team’s run and pass balance, the time of possession, and a team’s efficiency in offensive activities of both rushing and passing.

While this information may be of differential importance, the following data presents information very useful in choosing between closely ranked players. I use this also to key into certain team’s players as a whole vs teams to avoid. This concept applies especially as you get deeper into the “poor” team’s depth charts. Take chances on deeper players from the teams that have shown better historical metrics.

I suggest this information be highlighted in your draft sheets. I go over this data and try to ingrain my tendency of drafting within the better teams. In your mock drafts, when you have a tougher decisions use these data to may your choice.
I also think my series previously published on team biases is worth blending in to this data.

Positional and Team PPR Analysis Part 1

Positional and Team PPR Analysis Part 2

Positional and Team PPR Analysis Part 3


Run vs Passing Percentages within Team 2016 Total Plays

The data shown in Figures 1 to 3, divides all 32 NFL teams into 3 groups based on their overall 2016 game scripts. I divide the teams as either :

  • RUN Dominate
  • PASS Dominate

The RUN type of teams from 2016 are shown in Figure 1. The table highlights the game scripts, total plays, pass attempts, % of passing activity vs total plays, rushing attempts and the % of rushing plays vs total attempts. (Color Coded – Green High vs Red Lower)

The top run based team in 2016 was the Bills. They were 51% run vs 49% passing. That out of context seem as balanced but these data are based on the league data. The NFL is a passing based game now. The league % pass average is 58% vs 42% run. Thus in my analysis I have used these averages to define each team into one of three types.

Thus McCoy looms large as a nice early pick in your drafts especially in non-ppr leagues. A great running back on a run biased team. Your homework then is to look with each of these run based teams and highlight the running depth charts especially deeper than in the pass based teams (Figure 3).

Note that I will not do all of your homework and tease out all the conclusions to be drawn. As I tell my students chop the wood then get the fire. They want the fire then they promise to chop the wood. No, if you are handed material and conclusions then you will just scan and move onto the next article etc. If you invest the time in my data with your analysis you will benefit.

Figure 1.  2016 Run Based Teams

Run_Pass Time Analysis Slide01

The balanced teams are shown in Figure 2. These teams are into the middle of both run and passing activities. Their game script form 2016 may have been their plan or not. The danger lurking here is no strength in any aspect of the game. These will require more digging to seem if 2017 will lead them toward run or pass!

Figure 2. 2016 Balanced Teams

Run_Pass Time Analysis Slide02

Finally we have the Pass based teams. Note this is the game script for a majority of the teams. These team’s quarterbacks, wide receivers, pass catching running backs and tight ends deserve your extra attention even deeper into the depth charts.

The highest passing % team was the Ravens. Their issue is the QB position. They have nice WRs but need a powerful QB to light up the offense. Flaco is hurt and that is a concern in 2017. I have drafted the Ravens WRs but tried to get a nice ADP price.

The Lions, Saints, and Packers are all solid, I think Stafford is a good late round QB! I have focused this year on Washington’s Cousins as my main QB as they were a nice passing based team.

Figure 3 Pass Based 2016 Teams

Run_Pass Time Analysis Slide03

Another metric that I used to frame my decisions is shown in Figure 4. The league average for total seasonal plays run was 987. I subtract that number for each team’s total plays. That gives you a range metric of above and below average teams in their activity. Teams that run a lot of plays will have better opportunities to generate fantasy points for us.

The Saints ran 91 plays above the league average (nice), along with Eagles at 60 plays above average and the Ravens at 59 plays run above average. The bottom teams include the Dolphins at a minus 105 plays below average as well as the Rams at a poor minus 76 plays. the Browns were third worst as well. I am not turning away for players on these team but I will not reach for them as “bargains”

Figure 4 Spiral Graph of 2016 Team’s Total Plays Scaled to the League Average. 

Run_Pass Time Analysis Slide04

I end this article with Figure 5 and 6  and a beginning of my look into the time aspects of team metrics! Teams that can produce points in a shorter time give us a higher chance for our drafted players to rank up those victory points to crush our leagues!

Figures 5 and 6 present data that introduces time in the points per min of offense played. These figures give us, team total time played, plays per minute, % of possession, Points generated, points per minute and my “new” time based metric  I call EFFICIENCY. These data are color coded with Green and Red. Note that depending on the data the color is “good” or “not good”. The two figures show those teams above the 37% efficiency league average and those below this number.

For example the 49ners generated 2.43 plays per minute but were not efficient with those extra plays. They were the 5th worst in 2016. Lots of fruitless plays is not what we were looking for. My EFFICIENCY metric catches this issue.

The highest 4 teams in 2016 EFFICIENCY were the Falcons, Saints, Cowboys and Patriots. The Superbowl teams were in this elite group! Scan down the list starting in Figure 5 of the high to low EFFICIENCY Teams. Nice players from these teams are will desired in the 2017 drafts. Look at players deeper on these team for some sleeper types.

The lowest teams were Rams, Jets, Browns, and Texans. I have fear in taking many players from these teams in 2017. I would not stretch to draft players from these low efficiency teams.

Figure 5. 2016 Above Average Efficiency Teams

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Figure 6. 2016 Below Average Efficiency Teams

Run_Pass Time Analysis Slide06

This last figure concludes Part 1 of Run_Pass Time Analysis. Part 2 will go deeper into the time metric with estimated passing and rushing yards per minute of play. Please come back for that plus extra good things!

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