Week 15:
BOWL HANDICAPPING: CAN STATISTICAL ANALYSIS LEAD BETTORS ASTRAY?
By Kevin O’Neill
www.ConsumerBet.com
College bowl games are a wildly popular dish on the wagering menu, and with as much as 5 weeks passing between a team’s regular season finale and their bowl appearance, there is plenty of time to analyze the games. Many bettors look for an anchor to base their bowl handicapping off of, and look to past bowl results for their cue.
Many analysts over the years have pointed to the power of the running game in determining bowl winners, both on the scoreboard and to the pointspread. Teams that outrush their opponents in bowl games are a far better than 70% proposition over the years. Since rushing yardage can be reasonably projected during the regular season it makes sense to study running stats, especially yards per rush, which is more valuable as a predictive tool than straight rushing totals, especially when games against 1-AA opponents are eliminated from the database.
Last New Year’s Day Utah entered the Fiesta Bowl averaging 5.5 yards per rush and allowing 4.0 yards per rush for net yards per rush differential of +1.5. Utah’s opponent Pittsburgh entered the game averaging 2.8 yards per rush and allowing 3.8, for a differential of –1.0. Utah enjoyed a huge +2.5 net yards per rush differential and sure enough, the Utes outrushed the Panthers 139-17, helping to key a 35-7 crushing of Pitt as a 14-point favorite. As you would expect, teams that outrushed their opponents went 17-9 last bowl season, and while that 65%+ mark is below historical standards, it still points to a valuable tool. Or does it?
In 2004-2005’s bowl season the team with the better net yards per rush numbers in bowl games went a staggering 5-22 (18.5%) against the pointspread, a monumental loser for those trying to isolate a rushing edge. The only game without a result was the Cotton Bowl, where Tennessee and Texas A&M had an equal yards per rush differential.
OK, so Louisville’s +2.3 YPR differential probably didn’t merit laying double digits into Boise State’s +1.9 differential. Certainly there are a lot of games in those 22 losses that involved narrow margins that would make basing a wager on them untenable. So how did the most obvious advantages do? Of the 11 teams that enjoyed an advantage in YPR differential of +1.0 or more, our example above of Utah over Pitt was the lone pointspread winners. These likely rushing dominators went a putrid 1-10 (9.1%) against the spread.
Why did these projected rushing dominators do so poorly against the pointspread, covering only one game out of 11? Let’s take a look at some potential reasons.
College YPR has structural weaknesses: QB sacks count as passing yardage in the NFL, not so in college football, so pass rush and pass protection weigh on the yards per rush ratings in a way that they don’t in the NFL. YPR is not entirely a measure of the running game.
Emotional Factors: LSU (+1.7) figured to enjoy rushing dominance over Iowa (-0.7), but the Tigers were distracted by the pending departure of Nick Saban to the Dolphins and weren’t sharp overall despite winning the rushing game. Their pass defense allowed a 55-yard TD pass on the game’s final play for an Iowa win but unfocused LSU never had the pointspread covered in the ballgame.
Style Differences: Cal (+3.5) had an enormous rushing advantage over Texas Tech (-0.3) and played to that projection, with a 221-77 advantage. But Texas Tech’s running game is meaningless and they had won 6 games while being outrushed, including 70-10 over Nebraska and 70-35 over TCU. The key factor in this game was Cal’s disappointment in not making the BCS and being relegated to the Holiday Bowl.
Game Planning: When Connecticut took a 17-0 first quarter lead over Toledo, the Rockets had to abandon their running game and throw, throw, throw to try to catch up. Then never did and the result was a 159-78 rushing edge for the Huskies in a game where Toledo figured to have a modest rushing edge.
The Big Break: With 4 to 6 weeks in between games, teams may lose their rhythm and stray from the characteristics that they have exhibited throughout the campaign, making projections more difficult. Some coaches who are conservative against conference foes may throw caution to the wind in bowl games and try to show different looks to confuse their opponents.
Passing Prominence: It is no secret that the passing game has become more important in recent years in the college game. A strong passing game can open up running opportunities when the defense has to focus more on slowing down the quarterback. Conversely, a defense that knows their opponent doesn’t have the weapons to hurt them through the air can load up to stop the run. So success passing or defending the opponents’ air attack feeds the running game.
Beware the Short Sample & Backfitting: The bowl results from last season are certainly extreme, and based on a very small sample. Bowls are by their very nature a short sample, and can change dramatically from year to year. But we’ve isolated the danger of trying to take statistical results, such as the strength of college teams that outrush their opponents in bowl games, and thinking it is easy to get positive results out via statistical projections, especially when it involves a bunch of college kids who have been sitting around for six weeks.
What’s the strongest bowl factor? We’ll follow up next week with a report to our email list on the strongest factor in bowl games. To be included on that email report as well as Kevin’s weekly Sports & Gaming News column visit
www.ConsumerBet.com/email.html. All the best to you this bowl season.
About the author: Kevin O’Neill is a writer, researcher, and sports handicapper. Kevin’s Strategic Sports Publishing selection service was documented with an incredible 74-34 (68.5%) record in 2004’s football season, earning the #1 college/NFL combined ranking from The Sports Monitor. Kevin had a solid, if less spectacular winning season in college football in 2005 but has been unable to overcome the avalanche of favorites in the NFL. Kevin has a documented 60% NBA record from the fall of 2002 to the present. Opt in to his email list at http://www.consumerbet.com/email.html
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