2. 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.

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Table 1 A L P HA S F O R A L L 3 2 NF L T E A M S

4. ANALYTIC INVESTORS NFL ALPHAS 2016-2017 P a g e | 3
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 UM U L A T I V E A L P H A S : Dallas Cowboys vs. San Francisco 49ers

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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 UM U L A T I V E A L P H A S : Tampa Bay Buccaneers vs. Pittsburgh Steelers

6. ANALYTIC INVESTORS NFL ALPHAS 2016-2017 P a g e | 5
Chart 3 L O W V OL A T IL IT Y A NA L Y S I S 2 0 1 6 - 2 0 1 7 S E A S O N
Chart 4 R US S E L L 1 0 0 0 R IS K Q UI NT IL E R E T U R N
Chart 5 C OR RE L A T IO NS B E T W E E N NF L A L P H A S A N D W I NS

7. ANALYTIC INVESTORS NFL ALPHAS 2016-2017 P a g e | 6
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 OS T S E A S ON A N A L Y S IS ( 6 - 4 R E C OR D )

8. ANALYTIC INVESTORS NFL ALPHAS 2016-2017 P a g e | 7
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 SUPER BOWL RESULTS
*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.