As many know, I run a College Football analytics site called PerfectFall. On the site I use a model I created to measure every teams on-field performance and gives them an Overall, Offensive, and Defensive 's-values'. It also measures team talent, offensive tendencies, and strength of schedule/opponent. *Offensive tendencies is used to rate a team appropriately. A run heavy team shouldn't be penalized as much for having a poor passing game, but if they then have a poor rushing game, it should punish them more. And vice versa.
New this year, I'm using data created by my site to train a few machine learning models which can then predict future results (this feature is normally only available to Patreon members, but I'll post just the Purdue prediction here in this column each week).
Things like these rely on data, data, and more data. That means 2 things. For ratings, I do factor in preseason values for the first 4 weeks, but my entire models intention is to rate how teams are performing right now, this season and not overly rely on the past, so rankings early in the season may look somewhat weird for the first 3-4 weeks. And second, even more so on the reliance on data, I dont expect predictions to be any sort of reliable until at least week 5. So while I will post the prediction, if you use it to bet, it's your money, not mine #ThisIsNotFinancialAdvice
Statistical Analysis...
Read this post
https://purdue.forums.rivals.com/threads/a-statistical-look-at-wisconsin.217138/
@amarcott kills these posts. Not much more to add here. On paper, these are statistically 2 pretty similar teams. The difference mostly just that Purdue's offense has been on the lower side of mediocre, while Wisconsin's offense has been on the upper side of just really bad.
Purdue:
Wiscy:
Machine learning prediction:
I missed last week, but TLDR: the model didnt like us at all. Had an 8-32 Iowa win predicted. Understandable, but thats why we play the game and dont just go off predictions Here we have a prediction eerily similar to that of the Minnesota game. Let's hope this one is more accurate!
Last section I'll include is our scheduled opponents, where they currently sit in the ratings, and the predicted outcomes vs actual results:
**remember, these movement numbers are since I posted before 2 games ago, which 3 full games have happened since then.
Again, expect rankings and predictions to improve as the season goes as with ANY mathematical rating model, not just my own Though pretty happy in general with how they are looking right now! Let me know what y'all think!
New this year, I'm using data created by my site to train a few machine learning models which can then predict future results (this feature is normally only available to Patreon members, but I'll post just the Purdue prediction here in this column each week).
Things like these rely on data, data, and more data. That means 2 things. For ratings, I do factor in preseason values for the first 4 weeks, but my entire models intention is to rate how teams are performing right now, this season and not overly rely on the past, so rankings early in the season may look somewhat weird for the first 3-4 weeks. And second, even more so on the reliance on data, I dont expect predictions to be any sort of reliable until at least week 5. So while I will post the prediction, if you use it to bet, it's your money, not mine #ThisIsNotFinancialAdvice
Statistical Analysis...
Read this post
https://purdue.forums.rivals.com/threads/a-statistical-look-at-wisconsin.217138/ @amarcott kills these posts. Not much more to add here. On paper, these are statistically 2 pretty similar teams. The difference mostly just that Purdue's offense has been on the lower side of mediocre, while Wisconsin's offense has been on the upper side of just really bad.
Purdue:
Wiscy:
Machine learning prediction:
I missed last week, but TLDR: the model didnt like us at all. Had an 8-32 Iowa win predicted. Understandable, but thats why we play the game and dont just go off predictions
Here we have a prediction eerily similar to that of the Minnesota game. Let's hope this one is more accurate!
Last section I'll include is our scheduled opponents, where they currently sit in the ratings, and the predicted outcomes vs actual results:
| Week | Opponent | Current Ranking (Movement) | Predicted Outcome (Spread) | Actual Outcome (Spread) |
|---|---|---|---|---|
| 1 | Oregon State | 50 (down 15) | N/A | |
| 2 | UConn | 130 (still last lol no movement) | 43-3 Purdue (-40) | 49-0 (-49) |
| 3 | Notre Dame | 19 (down 13) | 27 - 45 Notre Dame (+18) | 13-27 (+14) |
| 4 | Illinois | 101 (down 7) | 32-15 (-17) | 13-9 (-4) |
| 5 | Minnesota | 53 (up 19) | 29-14 (-15) | 13-20 (+7) |
| 6 | Iowa | 22 (up 11) | 8-32 (+24) | 24-7 (-17) |
| 7 | Wisconsin | 47 (down 5) | 28-13 (-15) | TBD |
| 8 | Nebraska | 52 (up 2) | TBD | TBD |
| 9 | Michigan Sate | 5 (up 2) | TBD | TBD |
| 10 | Ohio State | 7 (up 14) | TBD | TBD |
| 11 | Northwestern | 82 (up 1) | TBD | TBD |
| 12 | Indiana | 71 (up 6) | TBD | TBD |
Again, expect rankings and predictions to improve as the season goes as with ANY mathematical rating model, not just my own
Though pretty happy in general with how they are looking right now! Let me know what y'all think!
