Although hockey is one of the least popular major sports – both in terms of fans and dollars bet – some consider it a “money sport” because of the large number of games played. For example, the NFL is super-popular, but the regular season and playoffs generate a total of about 240 games a year. On the other hand – in just over one-third of the NHL season – hockey has produced about 400 games. This leads to many more potential “profit opportunities.”
We’ve recently had some chatter on our SportsInsights forums about the “New NHL” – so we thought we would take a peak at how the hockey season was shaping up. We DO read the forums – so please keep the ideas flowing and help to improve our community (and our bottom lines!). In this article, we’ll take a look at how this year’s moneylines have been working out – as well as study how “Betting Against the Public” is faring. The information on this site is for entertainment and educational purposes only. Use of this information in violation of any federal, state, or local laws is prohibited.
Due to all of the changes introduced by the NHL after the strike – we used data only for the current hockey season. Although this represents only a little over one-third of the season (less data that SportsInsights.com would normally like to include in a study), it DOES include 400 games – which is a reasonable amount of data.
The NHL is a different animal because it uses a “money line” for betting purposes (as opposed to a “point spread”). As a result, we show the actual number of “units won or lost” over the period we studied. We also computed a “return on investment” or ROI (return for each dollar put at risk), as we have discussed on our forums.
Results for Various NHL Moneylines
Some of our members have discussed hockey and results for betting on dogs and favorites. We thought it would be interesting to take a look at what’s been going on. Table 1 shows the results of betting on the Home team at various moneylines.
Table 1: Betting on Home Teams at Various Moneylines
|Moneyline Range||Units Won/Lost||ROI||Win %||Avg Odds||Notes|
|-999 to +999||-1.7||-0.4%||57%||-127||All home teams|
|-999 to -100||-1.5||-0.5%||62%||-162||All home favorites|
|-999 to -300||-0.0||-0.3%||77%||-359||Huge home favs|
|-350 to -250||+1.4||5.2%||78%||-284||Big home favs|
|-300 to -200||+4.7||8.1%||76%||-234|
|-250 to -150||+4.9||3.5%||67%||-182|
|-200 to -100||-7.0||-2.9%||57%||-143||Smaller home favs|
|-150 to -100||-7.0||-5.1%||53%||-127||Smaller range; home favs|
|+100 to +999||-0.3||-0.3%||44%||+133||All home dogs|
|+100 to +150||-4.7||-6.4%||43%||+119||Small home dogs|
|+150 to +200||+3.4||13.8%||44%||+167||Larger home dogs|
|+200 to +999||+1.0||51.0%||50%||+211||Not too meaningful (not enough data)|
Some interesting points to note:
As expected, the broad ranges, highlighted in yellow, show flat to slightly negative results. In fact, most of the narrower ranges don’t show any edge one way or the other.
SportsInsights also took a look at how “Betting Against the Public” was faring in the 2006 “New NHL” season. Table 2 presents the results for the range of moneylines between –170 and +170, where we had the most data – and where the data seemed most “robust.” (Based on the “smoothness” of data, the data seemed the most reliable for this range.) As more data becomes available, we’ll study the more complete picture.
Even for this relatively small sample size, the results are starting to tell a story: that “Betting Against the Public” DOES indeed work in hockey. Note that due to the relatively small sample size, we don’t have enough data for the larger extremes of Public Betting % (less than 35%).
Table 2: Public Betting Percentage and NHL
(Within –170 to +170 range)
|Public % (lower than X%)||Units||ROI||Win %||Avg Odds|
We do not guarantee that the trends and biases we’ve found will continue to exist. It is impossible to predict the future. Any serious academic research in the field of “market efficiencies” recognizes that inefficiencies may disappear over time. Once inefficiencies are discovered, it is only a matter of time before the market corrects itself. We do not guarantee our data is error-free. However, we’ve tried our best to make sure every score and percentage is correct