Opponent-Adjusted Team Success Rate

Offensive and defensive Success Rate (SR) have been available on the advanced team stat pages all year. And recently I've been calculating opponent-adjusted team SR. Now I've been able to fully automate it, so it's always available following each wave of weekend games.

I like to look at SR for a couple reasons. First, it correlates well with winning. And second, it correlates well with itself, meaning it is relatively stable throughout the season. These are the two attributes we want in a stat for it to be predictive of future outcomes. For a couple weeks I've promised some hard numbers, but I haven't had time to wrap everything in a bow.

SR does not, however, tell the whole story. Teams that rely on high risk/reward plays, such as the Steelers this season, tend to be undervalued. SR is really a measure of consistency.

Opponent-Adjusted Team SR rankings are available here.

Going into week 9, the top teams in terms of AdjSR are NYG, SD, PHI, NO, and KC.

HST, MIN, and TEN have faced the toughest opponents so far in terms of SR.

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6 Responses to “Opponent-Adjusted Team Success Rate”

  1. DSMok1 says:


    I've been pondering the utility of SR vs. adjusted Yards/play. I think I'm beginning to understand why SR is important: the bimodal nature of pass plays. If both runs and passes followed a normal distribution, then adjusted yards/play would capture most of what we need to know (stdev would be useful also). However, passes do not. So far I'm not sure what to do about that--SR gets at it somewhat; so does the Y/Play. But I think in order to get an even better understanding of the effects of the distribution, we must (basically) measure what each distribution looks like.... and do something with that. Perhaps a monte carlo simulation.

  2. Anonymous says:

    How exactly do you adjust for opponent? Is it the same way you handle strength of schedule in the win prediction model?

  3. Anonymous says:

    Hi Brian. How much of the outcome Can be explained by SR? Your Efficiency stat counts for about 80% right?

    Also SR=DVOA?

    Thx Juri

  4. JMM says:

    "Teams that rely on high risk/reward plays, such as the Steelers this season,"


    Is this based on numbers or observations?

  5. Brian Burke says:

    Opponent adjustment is accomplished by looking at the average SR of each team's opponents, except when playing the team of interest. The difference between the opponent avg SR and the league avg SR is simply added to the team's unadjusted SR.

    Juri-Yes, you can get up over 80% r-squared with an efficiency stat model, but that's a retrodictive, explanatory model. For example, knowing a teams fumble rate explains a good deal of their past wins, but it doesn't predict future wins very well.

    No SR is not the same as DVOA. DVOA starts with a simple SR, but then adds lots and lots of modifiers.

    JMM-It seems kind of obvious to me, but since you mentioned it, I compared WPA and EPA to SR, and you can see the deep-throwing offenses are underrated in terms of EPA and WPA by SR.

  6. Anonymous says:

    is there anyway for you to combine your SR rankings into you prediction model, as between the 2 seems to gove a reasonable ranking, for example.

    raiders 7th on the SR, yet 22nd(30th last week), somewhere in between seems to be about there actual play from what we see.

    saints 4th SR, 18th efficiency, somewhere in the top 12 teams or so.

    although hard to explain the chargers, 1st in efficency and 2nd in SR, yet sitting at 3-5.

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