Gaining an edge over the bookmaker using NFL HFA data

Gaining an edge over the bookmaker using NFL HFA data

By Mark Taylor Sep 4, 2014

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Every bettors aim is to gain an edge over the bookmaker, one way to do this is to calculate handicap points more accurately than the oddsmaker. This NFL betting article highlights which teams have the biggest HFA since 2002, giving you a starting point to build an edge in your favour.

When looking to calculate HFA we need to look at the differential in performance at home compared to away. We are looking for team where the combination of factors that contribute to their performances at home and away, give the largest disparity in figures.

The simplest method is to look at the average margin of victory or defeat at home and on the road. The gap between these two figures can be thought to represent the HFA of the team and the average HFA of their opponents over that timeframe.

The average HFA of the league as a whole (2.64 points since 2002) can be used as an approximation for the latter figure and the HFA for the side may be calculated by subtracting this from the gap.

Bettors should read this article to understand the factors which contribute towards a HFA in the NFL.

Home Field Advantage since 2002 in the NFL

Team

Points differential at Home

Points differential on the Road

Gap between the two

HFA (previous column – 2.64)

Seattle

7.1

-2.8

9.9

7.3

Arizona

1.1

8.7

9.8

7.2

Baltimore

8.0

-1.1

9.1

6.4

San Francisco

3.1

-5.1

8.2

5.6

Minnesota

3.8

-4.1

7.9

5.2

St. Louis

-1.9

-9.4

7.5

4.9

Buffalo

0.5

-6.5

7.0

4.3

Detroit

-2.1

-8.8

6.8

4.1

Dallas

3.4

-2.7

6.2

3.5

New York Jets

2.9

-3.2

6.1

3.4

Kansas City

1.7

-4.2

5.8

3.2

Houston

0.1

-5.6

5.8

3.1

New Orleans

5.8

0.2

5.7

3.0

Green Bay

7.3

1.6

5.6

3.0

Indianapolis

6.7

1.2

5.6

2.9

Chicago

3.0

-2.5

5.5

2.8

Atlanta

2.8

-2.1

4.9

2.2

Pittsburgh

6.9

2.0

4.8

2.2

San Diego

6.5

1.6

4.8

2.2

Denver

3.7

-1.1

4.8

2.2

Jacksonville

-0.2

-4.8

4.6

2.0

Tennessee

1.3

-3.3

4.6

2.0

Cleveland

-2.7

-6.6

3.9

1.3

Oakland

-3.7

-7.3

3.6

1.0

Tampa Bay

0.6

-2.9

3.5

0.8

Cincinnati

0.6

-2.4

2.9

0.3

New York Giants

2.1

-0.6

2.7

0.1

New England

10.0

7.5

2.5

-0.2

Philadelphia

4.3

2.0

2.3

-0.3

Washington

-1.6

-3.8

2.3

-0.4

Miami

-0.3

-2.4

2.1

-0.6

Carolina

0.5

-0.5

1.1

-1.6

Around half of the teams are clustered around the league average for HFA – 2.64 – but it’s no surprise to see Seattle, the home of the Twelfth Man, as the side having the highest HFA.

Of the potential causes, crowd noise, in a stadium built to allow sound to reverberate rather than be absorbed, would seem to be at its most potent in Seattle and their trips to the East Coast should also exaggerate the gap between their home and road performance.

So from a betting perspective an appreciation of home field effects is essential – this article will help.

Seattle have still been under estimated at home, even when their fine home form has been such public knowledge. They are 62-41 (60%) since 2002 and 29-13 (69%) against the spread at home since 2009, beating the spread by an average of over 5 points per game.

Trends carry much more weight if they can be backed up by plausible reasons, especially when extreme outcomes are to be expected in sport simply through random variation within relatively small sample sizes.

For example, each year a few Premier League soccer teams appear to show unusually better form at home compared to their away form, but rarely does this trend persist. Without the factors that are present in the NFL, such as domes and time zones, these Premier League splits almost always return to more expected levels in subsequent years. They are most likely naturally occurring fluctuations seen in a limited sample.

The NFL will have cases where randomness may contribute towards unusual splits, but there are also real, repeatable factors at work as well, which don’t apply equally to all teams.

Isolating these niche circumstances, which may be mistaken for random noise when the betting lines are set or may be initially ignored by bettors, could result in an exploitable betting edge.

The six sides with the biggest and most persistent differential between home and away results each experience factors which may legitimately alter their success rates either at home or on the road, but may not have been wholly accounted for in the handicap lines.

Seattle, San Francisco and Arizona, 1st, 4th and 2nd, respectively in terms of HFA, make frequent trips from west to east for early matches which depress their away results compared to a more typical NFL road trip.

Seattle, especially have an overall losing ATS record of 41-54 (43%) on the road since 2003, which may be partly down to their inability to cover early games in the Eastern time zone. In addition, Seattle have their home crowd and own geographical isolation to potentially boost home performance.

St Louis and Minnesota, 6th and 5th respectively in the HFA standings, play indoors, as do Arizona and the performance of dome teams, especially when travelling to cold weather opponents, is particularly unimpressive, but the extent of this decline is perhaps poorly understood when applied to a handicap line.

And 3rd placed Baltimore has benefitted from covering the spread in a large number of their early home games against west coast sides. They have also had an extremely aggressive, testosterone fuelled defensive unit, typified by the recently retired Ray Lewis.

By isolating these many intertwined factors which contribute towards each team’s home and away differential, along with attempting to gauge the size of each influence on individual games, it may provide a vital betting edge over the traditionally applied 3 points that is invariably used to account for home field advantage.

Especially when Pinnacle Sports often price handicapped NFL matches as an enticing 1.952 each of two.

Mark Taylor is a freelance soccer and NFL writer who, along with producing expert content for Pinnacle Sports, also runs his own soccer analytics blog, the Power of Goals.

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