![]() ![]() In 1995, against those same expansion Jaguars, the old Browns were 13.5 point favorites coming off of a bye. ![]() Tampa Bay would finish the year 11-5.Īnd finally, we have the Browns. ![]() This was the last game of the regular season, and the host Bucs scored a late defensive touchdown to cover, 27-13. In 2005, in a game against the Katrina Saints with backup Todd Bouman, the Bucs were 13-point favorites. That is the largest points spread the team has had since ’78, and the playoff-bound Lions won 44-0. ĭid you know: Detroit, Tampa Bay, and Cleveland have never been 14-point favorites in any game since 1978? In December 1995, facing the expansion Jaguars quarterbacked by backup Steve Beuerlein, the Lions were 13-point favorites. Using the iterative SRS process, and because the transitive property of point spreads applies, we can generate team ratings based on the 272 point spreads involved. For example, when the Jets are 4.5-point underdogs to the Panthers in Carolina, we can imply that Carolina is viewed as 2 points better than the Jets (I am using 2.5 points for home field advantage). The way to generate team ratings is to take the point spread in each game, adjust for home field (except for the two international games), and then determine by how many points Vegas thinks Team A is better than Team B. Hence the title of today’s post: we can use the Vegas point spreads in each game to derive the implied ratings by the oddsmakers (in this case, Action Network) for each team. Every year ( or at least the years where I remember to do so), after Vegas releases the point spreads for every game, I take those weekly “ratings” to derive the Vegas ratings are for each team. My preferred way to come up with NFL team ratings and NFL strength of schedule ratings is to trust the experts: in this case, the Vegas oddsmakers. ![]()
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