CollegeFootballWinning.com

This early 2013 college football betting preview comes just after the Cal Bears concluded their spring football season. Please read The Cal Bears 2013 Spring Football Game Analysis for an assessment of the football itself (as opposed to this preseason college football betting analysis). Knowing that it is profitability and not football success that guides this study, let us examine what was, what should be, and what might be for the 2013 California Golden Bears football team, from our sports investment perspective.

As an acceptable college football betting oversimplification, teams that meet expectations have average against-the-spread (ATS) seasons, teams that exceed expectations will have good ATS seasons, and teams that perform below expectations will have bad ATS seasons. Wins and losses, both ATS and straight up (SU), are comparatively easy to quantify; it is assigning a quantity to expectations that makes for the real challenge. However, we have unearthed three important correlations to Cal’s ATS success: season-to-season changes in SU wins, preseason poll rankings, and prior season ATS results. For the last 11 seasons, the Golden Bears were coached by Jeff Tedford. Since coaching staffs and styles are real football variables, having the head coach as a constant for 11 years is a luxury for college football data collection. Armed with our three metrics and many years of historical data, we will attempt to determine Cal’s 2013 ATS destiny.

Table 1: Cal Under Coach Jeff Tedford + 2001

Straight-up Wins

Based on the data from Table 1, there is a correlation between SU season win totals and ATS winning rates. Cal’s greatest positive increase in ATS results from one season to the next occurred from 2001 to 2002 (an increase of 39.4%), from 2007 to 2008 (an increase of 38.46%), and from 2005 to 2006 (an increase of 22.73%). That coincided with increases in season-to-season SU wins: six more wins from 2001 to 2002, two more wins from 2007 to 2008, and two more wins from 2005 to 2006. Conversely, the greatest decrease in ATS results from one season to the next occurred from 2011 to 2012 (a decrease of 28.85%), 2008 to 2009 (a decrease of 27.56%), and 2004 to 2005 (a decrease of 22.73%). That coincided with decreases in season-to-season SU wins: four fewer wins from 2011 to 2012, one less win from 2008 to 2009, and two fewer wins from 2004 to 2005. Simply put, SU wins in the previous season affected expectations for Cal in the very next season, as evidenced by their ATS results.

Intra-season ATS Results

In each of the two seasons that Cal won 10 SU games (2004 and 2006), they only finished 50% ATS. However, looking within those two seasons provides more evidence for our thesis that expectations correlate to ATS outcomes: Knowing, in retrospect, that Jeff Tedford’s Cal teams of 2004 and 2006 would have their best SU seasons, we can assume that there was a positive surprise (an exceeding of expectations) in each of those years. How, then, did Cal finish each of those seasons just 50% ATS? In 2004, Cal won four of their first six games ATS (expectations were exceeded right from the start of the year); then they lost four of their last six games ATS that season. (Expectations were too high for the second half of the season.) In 2006, Cal won five of their first six games ATS. Once again, expectations were exceeded from the beginning of the year. Then Cal lost five of their last six games ATS. Just like in 2004, for the second half of their season, the Bears failed to live up to the unreasonably high expectations built during the first half of their ATS season.

Preseason Rankings

Another way that season expectations can be measured is by preseason polls. When Cal was given a high preseason ranking, we can assume expectations were high. When the Bears received no preseason votes, we can assume low (or lower) expectations. Looking at their standing in the Final AP Poll helps confirm or deny those preseason expectations. As Table 1 indicates, in all four of Cal’s seasons when they finished better than 50% ATS (2002, 2003, 2008, and 2011), they received no votes in the preseason poll. Expectations were low. In three out of Cal’s four seasons when they finished worse than 50% ATS (2005, 2007, and 2009), the Bears’ final AP ranking was worse than their preseason rank. In other words, they performed below expectations.

Market-driven Regression and Progression

The betting market influences point spreads. Not only does the public betting market help to dictate an opening betting line, but point spreads can and usually do change from the opening to the closing number. When expectations are extreme enough (either too high or too low), point spreads become inflated or deflated accordingly. Over time, wagering on teams with inflated point spreads will prove unprofitable, while wagering on teams with deflated point spreads tends to be more profitable. Therefore, another gauge of expectations is knowing how teams have performed, ATS, in their immediate or recent past. Judged year-on-year, teams that had extremely successful ATS years tend to do worse (ATS) the following season, while teams that had extremely poor ATS years tend to do better (ATS) the following season. Cal is a good example of this phenomenon. The breakeven point in typical, American point spread betting scenarios is 52.38%; winning at any rate above that denotes a profit, and winning at any rate below that denotes a loss. Therefore, Cal had four profitable (ATS) seasons under Jeff Tedford (2002, 2003, 2008, and 2011). In three out of the four seasons immediately following those profitable ones, Cal had losing ATS seasons. Conversely, Table 1 shows four extremely unprofitable ATS seasons (2001, 2005, 2007, and 2012). In two of the three seasons immediately following those extremely bad years, Cal was profitable. (Obviously, we have no results from the 2013 season yet, to measure the effect of 2012’s results.) The one outlying year was 2006. As written under ‘Intra-Season Expectations’ above, 2006 had Cal winning five of their first six games ATS; so coming off of that extremely unprofitable 2005, the market had exceedingly low expectations for Cal to start their 2006 season.

Combining Expectations

Based on the above arguments, we might predict profitable ATS years for Cal when there is an (anticipated) increase in SU wins from the preceding season, low or no preseason poll rankings, and entering a season immediately following an extremely poor ATS year. At the same time, we might predict losing ATS years for Cal when there is an (anticipated) decrease in SU wins from the preceding season, high preseason poll rankings, and entering a season immediately following an extremely profitable ATS year. Searching for something predictive of Cal’s 2013 ATS season, we look to last year’s SU win total, which was just three games. Although the Preseason AP Poll is still months away from being released (at the time of this writing), we can be fairly certain that the Cal Golden Bears will receive no votes. Finally, Cal had their worst ATS season in more than a dozen years, last year. If history is any guide, then these converging factors suggest a profitable ATS year for Cal.

Sonny Dykes and the LA Tech Effect

The conclusion above was drawn from a Cal football team that had one head coach for 11 years. Now that Sonny Dykes is the papa Golden Bear, how might that affect expectations? As this is being written, the Bovada sportsbook has Cal at 200-to-1 to win the 2014 BCS National Championship. About this time last year, Cal was at 125-to-1 to win the 2013 BCS National Championship. While that early indicator suggests lower expectations for 2013 than those for Cal entering the 2012 season, 200-to-1 still might be considered higher-than-expected for a team who only won two games (SU) against FBS competition the prior season. The public knows that Coach Dykes is coming from three years as the head coach at Louisiana Tech where his 2012 squad led the nation in scoring and total offense. Might that raise expectations?

Sonny Dykes’ tenure at Louisiana Tech provides another good illustration of what happens to teams, ATS, based on expectations. [See Table 2 below.] His first year, 2010, was a 5-7 ATS year for the Bulldogs. Why was it unprofitable? There was a modest increase in SU wins (from four to five), there were no preseason poll rankings, but 2009 (the year immediately prior to Dykes’ first season with the Bulldogs) was an extremely profitable ATS year. Per our market-driven regression theory, there was an unusually high expectation for LA Tech’s ATS results based on their ATS success the prior year. Consistent with that theory, the Bulldogs lost their first four out of five games ATS to begin their 2010 season. Even though LA Tech won four of their final seven games ATS in 2010, in toto, it was an unprofitable season. That set the near-perfect stage for a profitable 2011: LA Tech would experience a large jump in SU wins (from five to eight), there we no preseason poll expectations, and the Bulldogs had a losing ATS season one year earlier. Coach Dykes and Louisiana Tech were an amazingly profitable 11-2 ATS in 2011. So what happened in 2012? After winning the last seven games in a row ATS in 2011, oddsmakers were ready to inflate Louisiana Tech’s point spreads in 2012 (i.e. expectations for the Bulldogs in 2012 were extremely high). The Bulldogs only had a modest increase in SU wins (from eight to nine), they appeared (by voting) in the 2012 preseason AP Poll, and they were coming off of an extremely profitable prior season. Consequently, LA Tech went from being a double-digit favorite just three times in 2010 and 2011 combined, to being a double-digit favorite six times in 2012 alone. So, even though Louisiana Tech finished 9-3 SU with the best scoring and total offense in the nation, expectations were so high that they finished just 5-7 ATS in 2012.

Table 2: Louisiana Tech Under Coach Sonny Dykes + 2009

Early Preseason Conclusions

Considering the ATS results of Cal’s last dozen years, we have good reason to think that Cal will have a profitable ATS 2013 season. Perhaps mitigated by high expectations for what Sonny Dykes can bring to the Golden Bears, we need to monitor the public perception of his arrival. One way of quantifying public perception is seeing which direction Cal’s BCS National Championship odds take. Another helpful metric will be the ‘prop’ bet for Cal’s 2013 season win total. That prop will not come out for months, but last year, Cal’s win total was set at 6.5. If 125-to-1 to win last year’s BCS National Championship (later) correlated to 6.5 wins, then we can expect that 200-to-1 to win this year’s BCS National Championship will correlate to slightly fewer wins than six. After the season begins, we will have to take note of any extreme ATS start to Cal’s year. Bearing those issues in mind, at this point in time, it is reasonable to conclude that the expectations for the 2013 California Golden Bears are fairly low. Consequently, Cal backers could see a profitable 2013 season.

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