We've provided a number of research articles that look at some tips on playing the team season win over/under bets. Now we will take some of these methods and use them to fashion a sort of "consensus" selection for teams heading into the 2005 season. The tips we will be charting include:
- Win History -- the historical over/under rates of a certain prior year win number compared to the season number set for the team
- Line History -- the historical over/under rates of a certain line number
- Line minus Wins -- the historical over/under rates taking the Line minus prior year wins
- Bounce Effect (2004) -- the historical over/under rates of teams that had 3 more or fewer wins in the last season than the year before
- Draft Picks (2004) -- the historical over/under rates based on a team's number of first round picks
- Preseason Results -- preseason won-lost records can be good indicators of regular season performance
- Pro Football Prospectus book -- our friends FootballOutsiders.com have a model for season win expectancy
It should be noted that shopping for the best available line is always a smart strategy but particularly so with season win bets where you can find very significant differences!
| Team |
2000
Wins |
2001
Wins |
2002
Wins |
2003
Wins |
2004
Wins |
Line |
Price |
Win
Hist |
Line
Hist |
Line
v Wins |
Bounce
Effect |
Draft
Picks |
Pre
Seas. |
PFP
Book |
Consensus |
| Arizona |
3 |
7 |
5 |
4 |
6 |
7.5 |
-140 |
|
over |
under |
|
|
|
under |
|
| Atlanta |
4 |
7 |
9.5 |
5 |
11 |
9.5 |
+120 |
|
|
over |
under |
|
|
UNDER |
Under -131 |
| Baltimore |
12 |
10 |
7 |
10 |
9 |
9.5 |
-139 |
|
|
under |
|
|
UNDER |
|
Under +127 |
| Buffalo |
8 |
3 |
8 |
6 |
9 |
8.5 |
+142 |
|
|
over |
under |
under |
under |
over |
|
| Carolina |
7 |
1 |
7 |
11 |
7 |
9.5 |
+105 |
under |
|
under |
over |
|
under |
|
|
| Chicago |
5 |
13 |
4 |
7 |
5 |
6.5 |
-110 |
|
|
under |
|
|
|
|
|
| Cincinnati |
4 |
6 |
2 |
8 |
8 |
7.5 |
-213 |
|
over |
over |
|
|
|
|
|
| Cleveland |
3 |
7 |
9 |
5 |
4 |
4.5 |
-112 |
OVER |
|
under |
|
|
|
OVER |
Over -112 |
| Dallas |
5 |
5 |
5 |
10 |
6 |
8.5 |
-118 |
|
|
under |
over |
|
|
|
|
| Denver |
11 |
8 |
9 |
10 |
10 |
8.5 |
-131 |
|
|
over |
|
under |
|
|
|
| Detroit |
9 |
2 |
3 |
5 |
6 |
8.5 |
+127 |
|
|
under |
|
|
|
under |
|
| Green Bay |
9 |
12 |
12 |
10 |
10 |
7.5 |
-109 |
|
over |
over |
|
|
|
under |
|
| Houston |
|
|
4 |
5 |
7 |
7.5 |
+131 |
|
over |
under |
|
|
under |
over |
|
| Indianapolis |
10 |
6 |
10 |
12 |
12 |
11.5 |
-133 |
|
|
over |
|
|
|
under |
|
| Jacksonville |
7 |
6 |
6 |
5 |
9 |
8.5 |
-104 |
|
|
over |
under |
|
under |
UNDER |
Under -106 |
| Kansas City |
7 |
6 |
8 |
13 |
7 |
8.5 |
-182 |
|
|
under |
over |
|
UNDER |
|
|
| Miami |
11 |
11 |
9 |
10 |
4 |
6 |
+127 |
over |
|
under |
over |
|
|
|
|
| Minnesota |
11 |
5 |
6 |
9 |
8 |
9.5 |
-119 |
UNDER |
|
under |
|
|
|
UNDER |
Under +109 |
| N.Y. Giants |
12 |
7 |
10 |
4 |
6 |
6.5 |
-140 |
|
|
under |
|
under |
|
over |
|
| N.Y. Jets |
9 |
10 |
9 |
6 |
10 |
9.5 |
+157 |
under |
|
over |
under |
under |
|
|
|
| New England |
5 |
11 |
9 |
14 |
14 |
10.5 |
-120 |
under |
under |
over |
|
|
|
under |
|
| New Orleans |
10 |
7 |
9 |
8 |
8 |
7.5 |
-145 |
|
over |
over |
|
|
under |
|
|
| Oakland |
12 |
10 |
11 |
4 |
5 |
7.5 |
-132 |
|
over |
under |
|
|
|
|
|
| Philadelphia |
11 |
11 |
12 |
12 |
13 |
11.5 |
+128 |
under |
|
over |
|
|
|
over |
|
| Pittsburgh |
9 |
13 |
10.5 |
6 |
15 |
9.5 |
-126 |
|
|
over |
under |
|
|
|
|
| San Diego |
1 |
5 |
8 |
4 |
12 |
8 |
-138 |
over |
|
over |
under |
|
|
|
|
| San Francisco |
6 |
12 |
10 |
7 |
2 |
4.5 |
+117 |
|
|
under |
over |
|
|
|
|
| Seattle |
6 |
9 |
7 |
10 |
9 |
8.5 |
-149 |
|
|
over |
|
|
under |
OVER |
|
| St. Louis |
10 |
14 |
7 |
12 |
8 |
8.5 |
-137 |
|
|
under |
over |
|
|
under |
|
| Tampa Bay |
10 |
9 |
12 |
7 |
5 |
6.5 |
-180 |
|
|
under |
|
|
|
OVER |
|
| Tennessee |
13 |
7 |
11 |
12 |
5 |
6.5 |
+116 |
|
|
under |
over |
|
|
over |
|
| Washington |
8 |
8 |
7 |
5 |
6 |
7.5 |
+110 |
|
over |
under |
|
|
|
|
|
ANALYSIS: All of the above is based on following historical patterns with regards to this bet, which is always a somewhat shaky starting point.
We isolated those teams where there were a preponderance of factors pointing the same way with little if any conflicting information. Whether this is the best approach is certainly arguable. Again, in the interest of full disclosure, we will mention that our results from 2001 through 2004 with a similar type of analysis is 18-12 (at +105 average odds) -- hardly a convincing sample size.
As the patterns revealed in our research have shown, the best plan has often been to go Under on select high win totals (eg the expected good teams) and go Over on select low totals (the expected bad teams). Part of this theory is that injuries can quickly take their toll on even the best squad (who are often facing much tougher schedules than their previous season) while the lowly teams can benefit by "things going wrong" from the teams above them.
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