- Analytics can give you a better idea of what to look out for in an upcoming game or season. Just as many coaches use statistics to inform the way they watch film, stats can give you a great starting point to try to understand just what might happen in a game.
- It gives something concrete to back up arguments you might have with various non-Bruin friends or coworkers. Think the final score failed to show the dominance UCLA had over Kansas State last year? You’re probably right, and the Bruins averaging nearly 3 yards per play more than the Wildcats helps back up that assertion. Think the UCLA-Arizona game was an incredible defensive effort? Right again—the Bruin defense allowed only 0.5 Points Per Drive and under 20 Yards Per Stop to an Arizona offense that had been averaging 2.93 PPD and 65.81 YPS going into the game.
- Unlike the polls, which do a pretty terrible job of predicting future events (Hello there, #9 South Carolina! Good to see you, #4 Oklahoma! Your Dadaist rankings truly deserve to be their own installation at MOCA, Jon Wilner!), advanced analytics can do a much better job of properly rating teams and giving warning about teams that are ready to take the leap. Ohio State failed the eye test for much of last season, but the 59-0 detonation of Wisconsin put them easily in the top 4 in many of the top analytical ratings that we follow, and the Buckeyes went on to roll to the national championship. Likewise, Florida State was the undefeated defending champ, but many analytics said that they did not deserve to be in the playoff. We all know what happened next.
- You’re already hopelessly addicted to BRO, and we’re writing two of these babies a week, so you might as well learn to enjoy it.
Invariably, when a football commentator brings up a team’s offensive or defensive ranking, they are using the metric of total yards or total points, yet those statistics actually do a pretty poor job of telling the real story of how a team has played. Mike Bercovici threw for 488 yards last year against UCLA, while Brett Hundley only managed a relatively paltry 355. Just taking the total yards, it looks like Bercovici outplayed Hundley, but that’s not how it worked out.
Even ignoring the interceptions (NOTE: Never actually ignore turnovers. They’re really important, if relatively random), Bercovici only managed a good-not-great 7.1 Yards Per Passing Attempt. Hundley, on the other hand, ripped the Sun Devils for a ridiculous 15.4 Yards Per Passing Attempt. ASU outgained UCLA 626-580 (if you include garbage time stats, which we will not in our actual analyses), but while the Madonna Headsets averaged 6.0 yards per play (a very solid number), the Bruins averaged 10.0 yards per play (a ridiculously high Oregon with healthy Mariota against an FBS team number). We call these per-play or per-drive stats Tempo-Adjusted stats. If you take one thing away from these articles, let it be to ALWAYS USE TEMPO-ADJUSTED STATS. We are still in negotiations in hopes of making the use of total, non-tempo-adjusted stats on the board a bannable offense.
As with last year, we will be using stats based on Bill Connelly’s “Five Factors” of Football Success. We want to measure:
- EFFICIENCY—How well can a team stay on schedule and put itself into 2nd and 3rd and short (and keep the opponent from doing so)
- EXPLOSIVENESS—How well can a team make big plays (and stop the opponent from making them)
- SCORING—How well can a team finish drives with touchdowns (and hold its opponent to a field goal or no points)
- FIELD POSITIONHow well does a team give itself a short field (and give its opponent a long one).
- TURNOVERS—How well does a team create opportunities for turnovers (and not give its opponent the opportunities)
- Yards Per Stop: This will be our measure of efficiency, and is the total yardage a team earns in a game divided by the number of times the offense was stopped short of the end zone (turnover, field goal attempt, punt, safety, or turnover on downs).
- Yards Per Play: This will be our measure of explosiveness, and is the total yardage a team gains divided by the number of plays they run.
- Points Per Drive and Points Per Trip Inside the 40: These will be our measures of scoring proficiency. PPD measures the total number of points an offense scores by the number of drives they have, while PPTI40 divides the total number of points an offense scores by the number of times they get inside their opponent’s 40 yard line.
- Field Position Margin: This measures the difference in mean starting field position between a team and their opponents.
- Turnover Margin: This measures the number of turnovers a team forces minus the number of turnovers a team coughs up. Analytics have shown turnovers to be pretty random, but we have a few tools at our disposal to do checks throughout the year to find whether the Bruins and their opponents have been especially lucky or unlucky.
If you would like to help us chart UCLA’s Pac-12 opponents this year, drop us a line on twitter or as a direct message on the BRO message board. Coming up later this week: some interesting stats to consider going into the season.
Questions? Comments? Meet us on the Premium Football Forum or tweet us @Bruinalytics.