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College football advanced stats glossary: How to use today's metrics in sports betting

College football advanced stats glossary: How to use today's metrics in sports betting

Here at BetChicago, we love to reference advanced metrics when handicapping college football. This article attempts to simplify these numbers to help you become a mores successful bettor.

Joe Rodgers
Senior Staff Writer
BetChicago
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@RodgersBC
Joe Rodgers is a sports analyst specializing in betting odds and fantasy. He has spent time with Perform Group Media, earned a master's degree, and is even a certified pace car driver.
Here at BetChicago, we love to reference SP+ and Football Outsiders' advanced metrics, among others, when looking "inside the numbers" to evaluate college football teams or matchups. Understanding these statistics and how to apply the numbers can improve your success betting college football. In this article, we attempt to simplify some advanced stats commonly used by experienced sports handicappers, while providing examples as a guide. ## SP+ introduction Let's begin with an introduction to our favorite data set, SP+. The SP+ rankings are a data set of tempo- and opponent-adjusted components of the five factors of college football: Efficiency, explosiveness, field position, and finishing drives. Per [creator Bill Connelly](https://twitter.com/ESPN_BillC), a fifth factor, turnovers -- which are largely based on luck -- are informed marginally by sack rates. Why those five components? Connelly found if teams win the explosiveness battle, they win 86% of the time. Similarly, college football analyst Collin Wilson [found that](https://www.actionnetwork.com/ncaaf/college-football-betting-explosiveness-big-plays-teams-to-watch-2019) since 2015, teams that rank better in IsoPPP (a measure of explosiveness) have been more likely to cover the spread than non-explosive offenses. __Big Ten betting guide:__ [Notes on all 14 teams, in order of our power ratings](https://www.betchicago.com/2019-big-ten-football-betting-handicapping) Connelly [also found](https://www.footballstudyhall.com/2018/2/2/16963820/college-football-advanced-stats-glossary) that if teams win the efficiency battle (using Success Rate), they win 83% of the time. Win the drive-finishing battle and win 75%; win the field position battle, win 72%; and win the turnover battle, win 73% of games. SP+ is [presented](https://www.espn.com/college-football/story/_/id/27466530/preseason-sp+-rankings-alabama-tops-clemson) in an adjusted points per game figure. For example, if Team A’s SP+ rating is +22.0, that means it is 22 points better than the average college football team. If Team B’s rating is -17.0, it is 17 points worse than average. And if Team A and B were playing on a neutral field, SP+ would favor Team A by 39 points (22 minus -17). Several metrics make up each of SP+'s five factors. If you have seen Connelly's [advanced statistical profile](https://docs.google.com/spreadsheets/d/e/2PACX-1vQ2e9xV7-ClihFVJ3kla0ZDxzFCQ7-WXvQRur-nK6gOzo333PqSetw52kEGgbXKb6viGZSbYuJugvRR/pubhtml#) for teams, you'll realize dozens of stats are used, but we list some of our favorites below. The key to using these stats when handicapping is to find matchups where one team excels and one team struggles. ## College football advanced stats glossary __Adjusted pace:__ A good [metric to know](https://www.footballoutsiders.com/stats/ncaaoff/2018) when betting a total. More effective than a plays-per-game measure, adjusted pace compares a team's plays per game to its expected plays per game. Last season, Houston was second in adjusted pace and went 9-4 to the OVER with an average total of 68.3. __Adjusted sack rate:__ An opponent-adjusted measure of sack rates. This stat can be used to rank offensive line pass protection and defensive pass rush. For example, Rutgers' defense ranked 125th in sack rate on passing downs (second-and-8 or more, third-and-5 or more or fourth-and-5 or more) last season, giving opposing QBs plenty of time to find an open receiver. Offensively, Utah State had the third-best adjusted sack rate last season, one of the reasons Jordan Love completed 64% of his passes and also why the Aggies nearly upset Michigan State. __Adjusted turnover margin:__ Based on national averages for fumble recovery rates and the ratio of interceptions to passes broken up, teams have a projected turnover margin. If their actual turnover margin is much higher or lower than average, it suggests a team’s luck was particularly good or bad. The metric can be used to identify teams bound for positive or negative regression. __Efficiency:__ Presented by SP+ using success rate, which simply measures whether every play of a given game was successful or not. The terms of success in college football, per Football Outsiders: 50% of necessary yardage on first down, 70% on second down and 100% on third and fourth down. Inefficient offenses are tough to trust, especially if they are not explosive. __Explosiveness:__ Isolated Points Per Play (IsoPPP) is an explosiveness measure derived from determining the equivalent point value of every yard line, looking at only the per-play value of a team's successful plays. IsoPPP answers the questions: How consistently successful were you; and when you were successful, how potent were you? As stated above, big-play teams are important targets against the spread. __Havoc:__ This metric is defined as plays in which a defense records a tackle for loss, forces a fumble or defends a pass. Havoc rate is broken into unit-specific defensive line, linebacker and defensive back measures. Defenses that create more havoc increase the probability of forcing turnovers. [Michigan State](https://www.betchicago.com/2019-college-football-betting-win-totals-michigan-state) was No. 4 in Havoc last season, and with eight returning starters on defense, the Spartans will continue to be a tough defense to beat in 2019. __Opportunity rate:__ The percentage of carries in which the offensive line produces at least five yards of rushing for the ball-carrier, or a defensive line allows five yards. Mismatches in opportunity rate are often a good indicator of who will win the trench battle during run plays. __Second-order wins:__ This metric accounts for single-game win expectancy compared to the actual result of the game. Related to [Pythagorean expectation](https://captaincalculator.com/sports/baseball/pythagorean-expectation-calculator/), second-order wins comes up with what a team’s postgame win expectancy “should” be based on the metrics of a given game. For example, Texas had a postgame win expectancy of 8% in a win over Oklahoma last season, which contributed to the Longhorns having a second-order win total of -1.7 last season, meaning they should have lost nearly two games it ended up winning. It's one of the reasons why [we like Texas to fail](https://www.betchicago.com/texas-longhorns-football-betting-point-spreads-win-total) to live up to expectations this season. __Standard Down run rate:__ How often a team runs the ball when it is expected to. Standard downs are defined as first down, second-and-7 or fewer, third-and-4 or fewer and fourth-and-4 or fewer. It's an important stat to consider when betting totals. __Stuff Rate:__ Percentage of runs where the ball-carrier is tackled at or behind the line of scrimmage. Since being stuffed is bad, offenses are ranked from stuffed least often (No. 1) to most often (No. 125); for defenses, the opposite is true. __MORE:__ [Odds to make 2019 College Football Playoff](https://www.betchicago.com/odds-2019-college-football-playoff-betting-notre-dame) ## Other college football data sets SP+ is just one of many college football data sets, and the field is growing each season. Other metrics such as [ESPN's FPI](http://www.espn.com/college-football/statistics/teamratings), [CFBAnalytics.com](https://www.cfbanalytics.com), [CFB Professor](https://www.patreon.com/cfb_professor) and [CollegeFootballData.com](https://collegefootballdata.com) are also good references. [SportsSource Analytics](http://cfbstats.com/) is a good place to begin if you are interested in creating your own power ratings using play-by-play data. For more of a grassroots approach, [r/CFBAnalysis](https://www.reddit.com/r/CFBAnalysis/) on Reddit is always brainstorming creative ideas on how to analyze college football. __MORE:__ [Alabama/Clemson combined losses prop sees big odds adjustment in Vegas](https://www.betchicago.com/alabama-clemson-prop-combined-losses-odds-las-vegas)
2019-08-28T15:43:36.954Z2019-08-28T11:43-04:00
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