A week or so ago, I explained what might be a new method to quantify the strength of schedule of various college football teams by calculating the expected wins of each team using a normalized power ranking. At that point, I presented just the data for the Big Ten in conference play.
As a supplement to that piece, I expanded my analysis to include all FBS teams, both overall and in conference play. I also came up with a better way to visualize the data, I think. While I am not going to into too much more detail here, the results are interesting, so I thought I would do a data dump before the season really gets underway.
For my new visualization, I am plotting the expected win total (i.e. the sum of the individual game win probabilities) versus the preseason ranking for each team. I added a simple trend line for comparison, because my initial analysis showed that the higher ranked teams tend to grade out with easier schedules, in part because they don't have to play themselves. The new plot shows both a "raw" strength of schedule index (the y-axis) but the trend line also gives some idea of the deviation from the "mean." (Quantitatively, that is a little shaky, but qualitatively, I think it's fine.)
I also for each conference or grouping had to decide which benchmark fixed ranking to use to make the calculations. For the Big Ten and most Power 5 conferences, I used a ranking of 25. As a bit of review, the data for the Big Ten is shown below:
The ACC plot is shown below. Clemson and Miami have the easiest schedules, and NC State is on the easy side as well. Florida State, VA Tech, and especially Virginia have the toughest schedules of the likely contenders.
As a supplement to that piece, I expanded my analysis to include all FBS teams, both overall and in conference play. I also came up with a better way to visualize the data, I think. While I am not going to into too much more detail here, the results are interesting, so I thought I would do a data dump before the season really gets underway.
For my new visualization, I am plotting the expected win total (i.e. the sum of the individual game win probabilities) versus the preseason ranking for each team. I added a simple trend line for comparison, because my initial analysis showed that the higher ranked teams tend to grade out with easier schedules, in part because they don't have to play themselves. The new plot shows both a "raw" strength of schedule index (the y-axis) but the trend line also gives some idea of the deviation from the "mean." (Quantitatively, that is a little shaky, but qualitatively, I think it's fine.)
I also for each conference or grouping had to decide which benchmark fixed ranking to use to make the calculations. For the Big Ten and most Power 5 conferences, I used a ranking of 25. As a bit of review, the data for the Big Ten is shown below:
In general, this plot highlights the same basic conclusions that I talked about in my previous post: Minnesota has the easiest schedule, followed closely by Nebraska, with Purdue also having a light load. MSU's schedule is middle-of-the-road, as is Michigan's and Northwestern's. As for the contenders, Penn State and especially Wisconsin have the toughest road, but Ohio State, IU, and Maryland also have relatively tough schedules.
The same plot for the SEC is shown below. Notable is that Missouri's has a major, major schedule advantage of almost a full game of expected value! Auburn and South Carolina are the teams with the toughest schedules. Note as a general rule that the scales on all of these plots are different. The advantage that Missouri has over the SEC field looks to be about twice as large as the schedule advantage held by Minnesota and Nebraska.
Next is the Big 12. Oklahoma has a big edge, but watch out for Baylor. The shortest end of the stick goes to TCU.
Wrapping of the Power 5 is the Pac 12. Utah actually has a pretty good schedule, as does Stanford and ASU. Of the contenders, Washington State is at the biggest disadvantage. It also just sucks to be Cal and Colorado...
For the Group of Five conferences, I made the same calculations, but I used a lower benchmark ranking that was more consistent with the average strength of conference. For the AAC (shown below) I assumed each team was ranked #50. Interestingly, UCF has a fairly easy schedule, while my pick Cincinnati's road is relatively difficult.
Next is the Mountain West. Boise and SD State have the advantage here, while Utah State is at a big disadvantage. For the remaining Group of Five conferences, I backed off even more on the benchmark rating, dropping it to 75.
In the MAC, there is clearly a 3-tier system where Toledo, Ohio, Buffalo, and Akron have easy paths, WMU, NIU, Ball State, and BGSU have hard paths, and the rest are in the middle.
Next in C-USA, where North Texas, So. Miss, and UAB have the advantage and LA Tech and WKU do not.
Last (and least) is the Sunbelt, where Arkansas State seems to be the big schedule winner.
Finally, I also decided to run the numbers not just for conference play, but also for the full schedule. In this case, it seems fine to group together all of the Power 5 teams into one chart and all of the Group of 5 teams into another. Those comparisons are shown here:
For the Power 5, the teams with the easiest schedules overall appear to all be clustered in the ACC, with NC State, Syracuse, Miami, Clemson, and Wake Forest having the five easiest schedules. Baylor, Utah, Nebraska, Minnesota, and Pitt round out the next five. As for the toughest Power Five schedule, that trophy goes to South Carolina. Actually, SEC teams represent 10 of the toughest 12 schedules using this methodology. Auburn, Florida, Texas A&M, Ole Miss, Colorado, LSU, Arkansas, USC, and Georgia make up the Top 10. For reference, Michigan's schedule is the 21st hardest, and MSU's is the 41st hardest.
Finally, the chart below summarizes the Group of Five. Overall, Army's schedule is by far the easiest and BYU's is by far the hardest.
That is all for now. Until next time, Go State, Beat Tulsa!
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