nfl alphas 2016-2017

ANALYTIC INVESTORS NFL ALPHAS 2016-2017 P a g e | 1

Back on the Horse

LAST YEAR’S BIG GAME saw the Denver Broncos upset the Carolina Panthers 24-10 in a game that was notable for many reasons. Not only was this the first one without a Roman numeral, it also marked a fitting end to a great career for Broncos quarterback Peyton Manning, who won one last ring before embarking on his next career as a crooner of insurance company jingles. But more importantly, the result meant that Analytic ended a two-game skid and has now correctly predicted 10 of the last 13 games.

2016 was a year of tumult and oddities, with the NFL being no exception. It began with New England Patriots quarterback ending his legal battle with the league, and serving a four-game suspension for his role in the “Deflategate” scandal. But just when Commissioner Roger Goodell thought he was in the clear, San Francisco 49ers QB Colin Kaepernick began kneeling during the National Anthem to protest police brutality and racial inequality, with other players following suit. Then, the league saw its TV ratings decline for the first time in 4 years, down 8 percent from 2015. And as if that wasn’t enough, the San Diego Chargers announced they would be leaving their longtime home to head north and become a tenant of the new stadium being built by the Los Angeles Rams, with no one in Los Angeles, even seeming to notice or care. To put a cherry on top, in a union almost as perfect as Kim Kardashian and Kanye West, the Oakland Raiders filed papers to relocate to Las Vegas.

The good news? On February 5th in Houston, we will see two of the highest-scoring offenses square off –

the New England Patriots against the Atlanta Falcons. The former will be vying for their fifth title, with the latter looking for their first. While we can only attempt to predict the outcome using our quantitative model, we do know one thing is fairly certain – the majority of football fans outside of New England will be pulling for the Falcons, especially those at league headquarters in New York, whose run-ins with the boys from Boston are well-documented.

But First, A Word From Our Alpha

At the core of our annual Big Game prediction is a calculation we create for each NFL team’s investment return versus wagering expectations during the 16-game regular season, called NFL Alpha (Table 1). To demonstrate the mechanics behind these alphas, let’s assume that a gambler in Las Vegas wagers $100 for his favorite team to win each of their 16 regular season games individually via what is known as a “money line bet.” If his team loses, he is out his $100; if he wins, he gets back the $100 plus an amount that is determined by the probability that the team will win, as determined by wagering markets. As one would expect, a favorite will pay out less for winning than would an underdog. At the end of the season, the bettor tallies his wins and/or losses for each game and computes a return on investment (ROI). To put it simply, any amount over his $1,600 in total wagers would result in a positive NFL Alpha, while anything below that amount produces a negative one.


Table 1 A L P H A S F O R A L L 3 2 N F L T E A M S


The 1993-1995 NFC Championship Games – Where Are They Now?

From 1993-1995, the Dallas Cowboys and San Francisco 49ers squared off in three epic NFC Championship games that some football analysts feel were those years’ “real” Big Games. But in 2016, these two teams had quite different fates. The Cowboys led the entire league with a 50.6% NFL Alpha, which was a whopping 94.8% improvement over 2015. Oft-injured QB Tony Romo got hurt yet again in a preseason game against the Seattle Seahawks, thrusting rookie Dak Prescott into the starting job. After a close loss in the opening game against the New York Giants, Prescott led the Cowboys to 11 straight wins, finishing with a 13-3 record. From an alpha perspective, the team outperformed throughout the season (Chart 1), even winning outright in four of the six games in which they were an underdog. But in typical Cowboys fashion and keeping with our postseason

mean reversion thesis, they lost a heartbreaker in the Divisional Round to Aaron Rodgers and the Green Bay Packers, 34-31. On the bright side, at least football fans won’t have to endure the ubiquitous shots of Cowboys owner Jerry Jones, New Jersey Governor/Cowboys cheerleader Chris Christie, or a clipboard-toting Romo. And then there’s the 49ers, who have fallen a long way from their last appearance in 2013. The team hired former wunderkind/Philadelphia Eagles head coach Chip Kelly – their third in three years – and managed to perform even worse with Chip at the helm. They finished with the second-worst NFL Alpha of -66.8%, for a year-over-year change of -60.5%. After upsetting the newly-relocated Los Angeles Rams on Monday Night Football, the Niners steadily underperformed throughout the season (Chart 1).

They only covered the point spread twice, and caused Levi’s Stadium Wi-Fi to be overloaded due to fans checking their fantasy football scores and desperately searching for diversions from watching the game. Before you Ram’s fans take too much pleasure in this statistic, it is worth noting that both 49ers wins came at the expense of your team. Some have theorized that the Kaepernick protests may have been a distraction, but in reality, the team really just lacked a true playmaker, or maybe 22 of them. In a classic scapegoating move that would make the late Al Davis proud, 49ers owner Jed York fired both General Manager Trent Baalke and Kelly (after just one season). But all is not lost, Bay Area fans – your team has the second pick in the upcoming NFL Draft, and the hapless Cleveland Browns have the pick right in front of you.

Chart 1 C U M U L A T I V E A L P H A S : Dallas Cowboys vs. San Francisco 49ers


Better Records Do Not Guarantee Higher Alphas

Could a 9-7 team be a better performer than an 11-5 team? Conventional wisdom would say no, but this is not the case when analyzing NFL Alphas. Case in point: the Tampa Bay Buccaneers and the Pittsburgh Steelers (Chart 2). Led by second-year QB Jameis Winston and a resurgent defense, the Bucs surprised the league and nearly earned an NFC Wild Card

berth. Even more impressive, they had a 40.4% NFL Alpha, which was fourth-best in the league. How did they do it? The Bucs were underdogs in 12 of their 16 games, including all eight of their road games. Add to that upset victories over three favored playoff teams: the Falcons, Kansas City Chiefs and Seahawks, and you have a recipe for significant

outperformance. Conversely, the Steelers won the AFC North and made it to the AFC Championship game, but had a significantly lower NFL Alpha of 7.1%. They were favored in 15 games and were only underdogs in a home game against the Patriots – a game which QB Ben Roethlisberger missed due to a knee injury. Consecutive losses to

the Miami Dolphins, Patriots, Baltimore Ravens, and Cowboys drove their Alpha to a season-low -29.6%, creating a hole that they struggled to dig out of until the last few weeks of the season. There’s no need for Steelers wide receiver Antonio Brown to broadcast this underperformance on Facebook Live; the numbers tell the story.

The Return of Low Volatility

Analytic has produced research showing that low risk (beta, in particular) securities tend to outperform their high risk counterparts over time. This is a thesis that we have incorporated into many of our equity investment strategies. We have also found this anomaly can be applied to sports wagering markets, such as the NFL. Case in point: “boring” bets on heavy favorites with more frequent, less-appealing payouts (i.e., low-risk) will tend to outperform the

more “exciting” longshot bets that occasionally produce higher payouts. To be fair, readers of this paper will remember that the 2015 season was an outlier in which the riskier wagers on heavy underdogs outperformed; a “Powerball effect” of sorts. This year, we are happy to report that the trend reversed course and returned to normalcy: low risk wagers returned 6.4%, while high risk wagers had a return of -46.4% (Chart 3). This was in stark contrast to the US Equity markets

in 2016, where risk was rewarded. Looking at risk (beta) quintiles for the Russell 1000 Index, we see that the opposite is true. High beta stocks (quintile 5) outperformed low beta stocks (quintile 1) by 9.3% (Chart 4). While this differs from our long-run expectations, this profile is not uncommon in years marked by a rally in equities. To put it in football terms, the more speculative longshots outperformed “safer” favorites.

Chart 2 C U M U L A T I V E A L P H A S : Tampa Bay Buccaneers vs. Pittsburgh Steelers


Chart 3 L O W V O L A T I L I T Y A N A L Y S I S 2 0 1 6 - 2 0 1 7 S E A S O N Chart 4 R U S S E L L 1 0 0 0 R I S K Q U I N T I L E R E T U R N Chart 5 C O R R E L A T I O N S B E T W E E N N F L A L P H A S A N D W I N S


Another Perspective on the Volatility Anomaly A final, unusual trend that we noticed while analyzing the results of this outlier of a season was the correlation between teams’ NFL Alphas and their win total. Typically, teams with the highest Alphas do not necessarily have the most wins. To illustrate, dating back to 1978 (the first year with a 16-game schedule), the sample average correlation was 0.73. In 2016, the correlation was a record-high of 0.94 (Chart 5) – the first time this figure has crossed 0.90, and the highest since a 0.89 in 1984. When you dig deeper into the top-ranked Alpha teams, eight of the top nine were playoff teams, with the lone exception being the Buccaneers, who narrowly missed the playoffs. In a way, this Upset Coefficient is an indirect measure

of the number of large upsets that occurred during each season. A higher Upset Coefficient would indicate fewer longshot victories occurred. While we at Analytic

enjoy analyzing the results of each NFL season and poking fun at notable events, it’s time to get down to business. Our thesis for predicting postseason and Big

Game outcomes is simple – there is a mean reversion across football seasons, in which teams with the highest NFL Alphas tend to underperform market

expectations in the following season, and vice versa. Interestingly, our research has shown that this reversion takes place as early as the post-season. Therefore, we forecast that teams with higher Alphas will actually underperform expectations in the playoffs, making the lower Alpha team in each matchup the best bet to cover the point spread. The anomaly held up again in 2016, as we went 6-4 with our playoff

selections (Table 2), bringing our historical success rate to 62% and marking the 13th consecutive year that we’ve hit at leastu50%.

Table 2 P O S T S E A S O N A N A L Y S I S ( 6 - 4 R E C O R D )


The Big Game LI

This year’s game will pit two high NFL Alpha teams: the third-ranked New England Patriots (40.5%) against the seventh-ranked Atlanta Falcons (29.2%) (Table 3). Ironically, the last game in Houston (2004) featured a high-Alpha Patriots team against an upstart NFC South team, the Carolina Panthers. We tipped the Panthers to be undervalued in that game, and they rewarded us by covering the point spread to give us our first of many wins to come. This Pats/Falcons Game could make history – if the Patriots win, it would be the first time a QB and a coach/QB combo has won five titles. Furthermore, the Pats have not lost a Super Bowl to an opponent named after an animal in the Belichick/Brady era, which doesn’t bode well for the Falcons. However, from a value standpoint, our model would argue to the contrary. With a relatively lower Alpha, the Atlanta Falcons are our pick. The higher-Alpha Patriots are currently favored by 3 points, so to clarify, we feel that the lower-Alpha Falcons will either win outright or lose by less than 3 points. And no, there isn’t any anti-Spygate/Deflategate bias factored into our prediction. Although, it would be fascinating to see Goodell forced into handing the Lombardi Trophy over to his nemesis Robert Kraft, wouldn’t it? Table 3 S U P E R B O W L R E S U L T S

*While in these games lower-Alpha teams did lose to the higher-Alpha teams, the predictions are correct because of the lower-Alpha teams covered their respective point spreads. The opinions expressed herein are those of Analytic Investors and are subject to change without notice. The research is prepared for general circulation and is circulated for general information only. It does not have regard to specific investment objectives, the financial situation and the particular needs of any specific person who may receive this report. NFL and Super Bowl are registered trademarks of the National Football League.

nfl alphas 2016-2017

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