Expectations and Realities: Week 4 AP Top 25 College Football Teams

Welcome to the 4th week of breaking down the top 25 teams’ performance compared to their expectations as predicted by vegasinsiders.com. Results from previous weeks can be found at the bottom.

This week Louisville and Virginia Tech fell out of the top 25 and will not be included in this week’s results. Instead they will be replaced with Nebraska and Oklahoma State.

Week 4 Results

In the Table 1 and Figure 1 below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected, or covered the spread, while teams with a negative percent error underperformed, or did not cover the spread. Note: this is not a measure if a team won or lost a game, rather a measure of how well the team won or lost the game.

Rank Team Opponent Spread Actual %Error
1 Florida State Clemson -9.5 -8 -16%
2 Oregon Washington State -23.5 -7 -70%
3 Alabama Florida -14 -21 50%
4 Oklahoma West Virginia -8 -12 50%
5 Auburn Kansas State -7.5 -6 -20%
6 Texas A&M Southern Methodist -34.5 -52 51%
8 LSU Mississippi State -7 5 -171%
11 Michigan State Eastern Michigan -43.5 -59 36%
13 Georgia Trojans -41.5 -66 59%
14 South Carolina Vanderbilt -22 -14 -36%
18 Missouri Indiana -15 4 -127%
19 Wisconsin Bowling Green -26.5 -51 92%
20 Kansas State Auburn 7.5 6 20%
21 Brigham Young Virginia -15 -8 -47%
22 Clemson Florida State 9.5 8 16%
24 Nebraska Miami-Florida -8 -10 25%

Baylor, Notre Dame, Ole Miss, UCLA, Arizona State, Stanford, USC, and Ohio State each had bye weeks. They are not included in the Table 1 or Figure 1. Wisconsin beat the spread by the largest margin at 92%. LSU did not beat the spread with the worst margin at -171% after being upset by Mississippi State. Week 4 was important for the SEC rivalry between Alabama and Auburn. Week 4 was the first week that Alabama beat the spread at a 50% error and the first week that Auburn did not beat the spread at -20% error.

Weekly Summary

Now that we are past the 3rd week of college football we have enough data for some statistics. Every team has played at least three games, which is the minimum amount of data required for statistics. A single factor analysis of variance (ANOVA) reveals that there is no statistical difference in mean percent error across the first four weeks of play (p=0.829). The results of head to head Tukey multiple comparison statistical matchups can be found here. This means that, on average, all teams have performed in a similar manner relative to their expectations. This isn’t unexpected due to the variable nature of the data.

While there may not be any differences now, there might be some practical information to be taken from the data. Below are five boxplots to aid in understanding the data. Each boxplot contains five of the top 25 teams in order to reduce crowding.

Figure 2 reports the percent error for the first five teams. As stated earlier, this is the first week that Alabama has beaten the spread. Will they continue or revert back to their previous three weeks? Will Auburn continue to beat the spread after failing to do so for the first time this season? Baylor had a bye week but expect them to continue their trend of beating the spread this week vs Iowa State. Arizona State and Brigham Young are not consistently beating the spread.

Figure 2 – Boxplots of Percent Error for Alabama, Arizona State, Auburn, Baylor, and Brigham Young.

There are three important details in Figure 3. Firstly, Florida State has yet to beat the spread this season. However it should be noted there percent error for Florida State has increased over their three games indicating they might beat the spread in the near future. The performance of Clemson, Georgia, and Kansas State has been too variable. This is the first week that LSU did not beat the spread.

Figure 3 – Boxplots of Percent Error for Clemson, Florida State, Georgia, Kansas State, and LSU.

The data in Figure 4 is more straightforward. This group of teams has a variable percent error. Michigan State is scoring close to the spread each week. Missouri and Notre Dame are mostly beating the spread. Ohio State beat the spread in two of their three games, but the week they didn’t beat the spread was by a large margin (-240%) skewing their plot.

Figure 4 – Boxplots of Percent Error for Michigan State, Missouri, Nebraska, Notre Dame, and Ohio State

Figure 5 has two groups. Oklahoma, Ole Miss and Oregon have performed consistently each week. Meanwhile, Oklahoma State and South Carolina have performed inconsistently. Oklahoma has beaten the spread the past three weeks while only not beating the spread during week one with a -4% error. Ole Miss has beaten the spread by 52% or more this season.

Figure 5 – Boxplots of Percent Error for Oklahoma, Oklahoma State, Ole Miss, Oregon and South Carolina.

Figure 6 is an interesting group. Firstly, Stanford beat the spread in weeks one and three but fell short of the spread in week two by 200%. Texas A&M has beaten the spread by 51% or more in every week but week three. UCLA has not beaten the spread this season. Furthermore, UCLA hasn’t surpassed the -58% mark. USC beat the spread by more than 100% in weeks one and two but failed to beat the spread by more than 200% in week three. Wisconsin failed to beat the spread by -14% and -17% in weeks one and two, but after coming off a bye in week three smashed the spread by 92% in week 4.

Figure 6 – Boxplots of Percent Error for Stanford, Texas A&M, UCLA, USC, and Wisconsin.

This week’s takeaways: If Baylor, Oklahoma, and Ole Miss keep the same pace, expect them to beat the spread. UCLA won’t cover the spread if they continue the same pattern. Auburn and Alabama have broken their streak. The rest of the top 25 teams are not demonstrating any patterns after four weeks.

 

Important notes:

  1. Spreads can be found at vegasinsider.com.
  2. Percent error is calculated as (Spread-Actual)/Abs(Spread)
  3. I understand that spreads are typically used for gambling purposes and that the lines move. However, it is important for the spreads to reasonably accurate in order for the house or bookie to make money. Lines are a consistent source of weekly predictions.

 

Previous results – week 1 week 2 week 3

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