Strength of Opposition and Fantasy Points Allowed

When I got involved in fantasy football a few years ago I quickly became aware of the “fantasy points allowed” (FPA) statistics that are readily available from different sources. Almost equally quickly I started to dislike them.

At first I happily relied on them in setting my line-ups, and unhappily had some poor results. Now that was partly down to me being a fantasy rookie, but there was something else to it as well. They don’t take account of the strength of opposition faced, or whether a team is generally outperforming or underperforming versus opponents.

This article is the first in a two-part series looking at how taking account of the strength of a team’s performance in comparison to their opponents can give greater depth to FPA statistics.

In reality, when do you use FPA statistics? You may well be playing your star players week in, week out, regardless of the matchup. When you want some extra help, is when you need to find value from your bench or on waivers, due to byes, injuries, or perhaps streaming at a position.

In that situation FPA statistics don’t necessarily help you that much.

While, on the surface, they give an indication of defensive strength/weakness, they don’t show you whether a particular team has had an easy or hard schedule, or whether that team has performed better or worse than their schedule would suggest they should. Plus they only look at defense.

I wanted to be able to spot the teams that allowed more fantasy points than expected, especially when they are facing teams that achieve more fantasy points than expected.

So how did I do it?

Firstly let me clarify some terminology. When I use the term ‘FPA’ I mean fantasy points allowed on defense and fantasy points achieved on offense. When I refer to FPA from the passing game, I mean the points in respect of a wider receiver, standard scoring; one point per 10 yards, six for a touchdown.

My plan can be broken into four main parts:

1. For each team I wanted to know what an average week looked like from an FPA perspective – pass offense, pass defense, rush offense, rush defense.
2. Then, determine what each team’s average opponent looked like in those same categories, based on who they had faced during the season so far.
3. Compare the results above (a team’s pass offense versus their average opponent’s pass defense, rush offense versus rush defense, etc.) to see if a team was outperforming or underperforming versus opponents on average.
4. Use all of this to make projections of whether a team’s next matchup looks favorable or unfavorable from a fantasy pass and/or rush perspective.

Below I provide the detail on how I sourced the data for my analysis and the calculations I went through in manipulating it into the projections I wanted.

1. Each team’s average fantasy week

I wanted to keep it simple – I didn’t have the time to do deep analysis of box scores. Therefore, my starting point was to see what value I could derive from the freely available team statistics on NFL.com.

There is one table each for pass offense, pass defense, rush offense and rush defense. They include the total yards and touchdowns each team has achieved and allowed so far during the season.

They are quickly updated after matches so I could use them each week after Monday night football to update my statistics and see what the next week held.

I simply took a copy of each table and pasted them into a spreadsheet.

Using the total yards and touchdowns for each team, I calculated the total fantasy points allowed and achieved for passing and rushing, by using the one point per 10 yards, six for a touchdown formula.

Dividing the results by the number of games each team had played gave me what an average FPA week looked like for every team in each of the four categories (pass offense, pass defense, rush offense, rush defense).

2. Average opponent

Once I knew what an average week looked like for every team it was relatively simple to calculate what each team’s average opponent looked like. I just needed to know who each team had faced so far, and that is easily obtained from the season schedule.

So if I was looking at Arizona after week five of the 2014 season, I know they have faced the Charges, Giants, 49ers and Broncos, with a bye in Week 4. If I am calculating their average opponent’s pass defense, I simply add up the pass defense FPAs for those four teams and divide by four.

To do this, I set up four spreadsheets, one each for pass offense, pass defense, rush offense and rush defense. The pass offense spreadsheet, for example, would be used to compare each team’s pass offense FPA versus their average opponent’s pass defense FPA. Each spreadsheet contained every team’s schedule, and would pull through all the comparative FPA information from the spreadsheets produced in point 1, up to the current week of the schedule.

3. Assess outperformance or underperformance

Using the spreadsheets from point 2, I simply compared the four categories for each team versus the opposing categories for their average opponent. On offense, a higher FPA than their average opponent’s defense FPA means outperformance. On defense a higher FPA than their average opponent’s offense FPA means underperformance.

So if, for example, Arizona’s average pass offense FPA was 31.68, but their average opponent’s pass defense FPA was 32.11, then Arizona’s pass offense is underperforming by 0.43 fantasy points per week, on average.

4. Matchup projections

Once I know how a team has performed versus their opponents, to calculate a projection for the next game I can simply apply the outperformance or underperformance to their next opponent’s scores.

Click on the image to the left to see the calculations in step 2 to 4 for Arizona up to week 17 of the 2014 season, with explanatory notes.

Here you can see that based on the calculations, Arizona are, on average, underperforming a little on pass offense. Their next opponent, San Francisco, on average give up 32.95 fantasy points on pass offense, so Arizona’s projection (due to their underperformance) reduces that to 32.51.

This same passing matchup could be looked at in the opposite direction by checking the calculations for San Francisco to see if they outperform or underperform on pass defense and look at what their pass defense FPA projection is for the Arizona matchup.

Comparing the projections for all the matchups, and looking for the highest values in any particular category, gives an idea which matchups are projected to yield the most fantasy points.

That is what I do in the second article, where I look at the projections in action and what can be learned from them.