How did my college football predictions do in 2014? Here, I look at not only my posted numbers for all games but also the forecasts made on this site and other outlets such as Grantland, Deadspin and Bleacher Report.
It’s 2015, and I’m making a full effort to track and report on all of my predictions. It started with baseball this spring, and it will continue through football and basketball.
Let’s get started.
Before the BCS title game, I wrote on Deadspin about how Ohio State presented a terrible match up for favorite Oregon. Ohio State had a vicious rushing attack that had just mauled a strong Alabama defense. Oregon had an average rush defense.
During the game, Ohio State RB Ezekiel Elliott gashed Oregon for 246 yards on 36 carries (6.8 yards per carry). Despite 4 turnovers, Ohio State won 42-20.
In the comments of the Deadspin article, a reader wrote this:
It is the start of the fourth, and it is creepy how on point your predictions are.
Two of my preseason predictions make honorable mention.
Auburn to regress
Auburn had a dream season in 2013, as they rose from the ashes of the SEC West to win the conference and play in the BCS championship game. However, they got the benefit of a few lucky plays (a tipped hail mary completion against Georgia, a field goal returned for a touchdown against Alabama).
In August, I wrote about how Auburn would have a tough 2014 season because of their schedule and the small chance they benefit from those lucky type plays again. Auburn fans didn’t like that I called them lucky.
@thepowerrank Luck? Really? You wanna talk about "luck". You are "lucky" to have a job writing about sports. Lazy journalism.
— Blake Atwater (@BlakeWater) July 30, 2014
Auburn couldn’t reproduce those plays in 2014. After a magical 12-2 season in 2013, they fell to 8-5 last season. Part of their demise was a tough cross division game at Georgia that they lost.
TCU to win the Big 12
My other favorite preseason prediction was that TCU would win the Big 12.
I actually went against my numbers on this one as Oklahoma had a higher win probability. However, no one gave TCU a chance, and I had them ranked 14th in the preseason.
TCU had a tremendous season as they went 12-1 and finished as co-champions with Baylor of the Big 12.
Grantland asked me to predict the Heisman winner during the preseason. I don’t make player predictions, so I had some fun and picked Stanford QB Kevin Hogan.
I thought I had some strong reasoning, but Hogan came no where near the Heisman conversation. He led a Stanford offense that made red zone stalls a season long habit. This led to a disappointing 8-5 season.
Halfway through the season, Grantland gave me a do over and asked for another Heisman prediction. This time I go with Bo Wallace, the quarterback of a 6-0 Ole Miss team. Part of my reasoning was his improved completion percentage the first half of the season, an oh so huge sample size to make a judgment.
I wrote the following about my Wallace pick.
It’s hard to deny a blond quarterback from an unexpected SEC contender.
Then Wallace had a terrible second half of the season. He couldn’t make a play in a close game against LSU, and Ole Miss lost their first game of the season. The once mighty Rebels lose two more SEC games before getting blown out by TCU 42-3 in a bowl game.
Don’t ask me about the Heisman.
The Ohio State season end surge
For predictions based on my numbers, I was disappointed to not predict Ohio State’s surge at the end of the season. Before the Big Ten title game, they were 13th in my team rankings. Their loss to a bad Virginia Tech team at home pulled them down.
Then Ohio State plays the 3 best games any college football team has ever put together. They become the first national champion in the playoff era.
Members get access to my best predictions for spreads and totals.
The member predictions with the most value are the college football totals, which were posted from week 6 to the end of the season in 2014. These predictions went 53.3% against opening totals (273-239-4) and 51.5% against closing totals (260-245-9).
However, these numbers do not tell the entire story. When the predicted total differed from the opening total by more than 4 points, the market total moved in the direction of the prediction 90.4% of the time (122-13, with two totals that didn’t move).
On average, the final total moved 3.5 points in the direction of the model prediction. Some refer to this as closing line value.
For the entire 2014 season, spread predictions for members were 50.1% against the opening line (367-366-19) and 48.6% against the closing line (357-378-8). Modifications will be made to this model for 2015.
To learn more about becoming a member of The Power Rank, click here.
On the predictions page, I posted a margin of victory for each college football game.
These predictions got the game winner correct in 70.4% of games (539-227). It’s interesting that my preseason model, which doesn’t use data from the regular season, predicted a higher percentage of game winners (71.1% on 482-196 with no predictions on the other games).
Against the markets, the public predictions won at 49.9% against the opening line (370-371 with 18 pushes) and 48.5% against the closing line (363-385 with 9 pushes). It’s tough to beat the markets on every game.
The public predictions will be reworked this season. There’s room for great improvement, especially since these predictions were 53.8% against the opening spread through week 8 of the season.
Playoff probabilities on Bleacher Report
On Bleacher Report, I predicted which teams would make the four team playoff based on the committee rankings. To learn more about these simulation methods, click here.
Overall, I thought the predictions did pretty well. Mississippi State was first in the committee’s first rankings. However, my numbers thought they wouldn’t make it due to tough games at Alabama and Ole Miss. Mississippi State lost both games and didn’t make the playoff.
By week 12 of the season, Alabama, Oregon and Florida State had the highest chance to make the playoffs by my calculations. Eventually, all 3 of these teams made the playoff.
However, the predictions were off the last week of the season as my numbers had TCU instead of Ohio State for the last spot. As I mentioned earlier, it was difficult to predict Ohio State’s surge at the end of the season based on their previous numbers.
However, my methods also need work. I had no way of knowing how the committee would value a conference championship. For 2015, I’ll account for this in my model.
Even with this improvement, there are still human factors out of my control. Though the committee placed an emphasis on a conference championship, Big 12 commissioner Bob Bowlsby still presented them with co-champions in Baylor and TCU. It might make more sense to crown Baylor the champion as they beat TCU.
My other decent predictions
Some of my other predictions had the right idea but didn’t nail it.
- Before their October 18th game, I predicted neither Florida State nor Notre Dame would make the playoff despite their undefeated records. Notre Dame fell off a cliff after losing the game. However, Florida State won close game after close game to make the final 4. I would definitely make the same prediction again.
- I had my doubts whether Chris Peterson could bring his success at Boise State to Washington. Boise State had a long history of winning which transcended Petersen’s time as coach. Washington went 8-6 in 2014 with a rank of 40th in The Power Rank. However, the jury is still out on this one.
- In the preseason, my numbers gave Wisconsin the best chance to win the Big Ten. They weren’t better than Ohio State but had a favorable schedule. Ohio State stomps them in the Big Ten title game on their way to a national title.
Thanks for reading.
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