Betting Teams After Losses

This post is a chapter that was cut from my new book because the first draft was too long, but there were still some interesting conclusions worth reading. If I write my playoff betting manifesto next year, some of these conclusions will be expanded with a deeper dive.

In the meantime, my new book, The Hockey Economist’s Betting Prospectus is now available. It's a comprehensive commentary on the last 3 years of hockey betting, broken down by team, by category, by strategy, by season. There is plenty of useful information for bettors of all skill levels. It covers pre-pandemic, peak-pandemic, post-pandemic. What worked, what failed. Lessons learned, market trends, team-by-team analysis. What impact did the pandemic have on hockey betting? The market differences between these 3 seasons are discussed at length, and there's a lot to talk about. To read more, visit the Amazon store.

-------------------------------------

One day while flipping through some NHL gambling strategy sites, I stumbled upon an old technique called “zig zagging” which under normal circumstances is only used in the playoffs. The “Zig Zag Theory” is based on the observation that when teams play a series of consecutive games, the loser of the previous match is going to have a higher probability of winning the next contest. Why this phenomenon occurs is anyone’s guess, but it likely has something to do with motivation and losers giving a greater effort in the next contest (while winning could breed complacency). If you consider that the better team is more likely to win game 1, then the loser should hypothetically have a much smaller chance of winning the next game.

Normally in regular seasons, teams don’t play enough consecutive games against the same opponent to provide a meaningful number of zig zag opportunities. The pandemic season was different, as the NHL was squeezing more games into a shorter window with less travel, meaning, there was more zig zagging in 2021 than ever before (and possibly ever again). That scheduling format was scrapped for the 2021/22 season, which reverted back to a more standard scheduling distribution.

The first sample that I looked at upon discovering “zig zag theory” was the first 2 months of 2021, which produced a result that the loser was winning the next game 55% of the time. Over that particular window, betting $100 on the losers would have netted you roughly $2,000 of profit. The success of zig zagging in the first half of 2021 inspired me to start promoting this as a viable strategy, at which point the trendline reversed course and started tanking.

Any profits you would have made in the first half were paid back in the second half. This actually happened a few times during the pandemic schedule, where I would Tweet about a gambling trend and it would immediately shift in the opposite direction. Either there is a butterfly effect and my Tweets hold incredible power over the universe, or perhaps the trend was actually random, and I was reporting coincidences more than actionable observations.

Looking at the raw data from October 2019 to June 2021; there were only 23 zig zag games in the 2019/20 regular season, but 385 in the 2021 regular season with an additional 72 in the 2021 playoffs. That provides a sample of 480. Of those, 239 times the visitors had lost the previous games, and 241 times, the home team had lost the previous game. If you bet $100 on every game in each category, you lost -$2,534 on the visitors, and won $2,245 on the hosts. Ignoring the home-road splits, the loser of the previous game only won 230 out of 480 games (48%).

My investigation was even expanded to include long-term zig zags, like if you lost to a team two months ago, are you more or less likely to win the next meeting? The answer was no, at least within this sample in terms of rate of return. The more time that passes between games, the influence seems to wane. The revenge motive can fade over time. In a normal schedule, teams will play 31 different opponents, if 1 particular opponent beat you 2 months ago, is that going to provide a jolt of energy? It’s hard to say. Some coaches more than others may emphasize revenge to energize their players.

Playoff zig zagging will be discussed further in my Playoff Betting Prospectus, but for the purposes of this regular season experiment, zig zag opportunities are few and far between. However, it does open an interesting area of study about how teams in general respond to losses. The basis for “zig zag theory” is that teams give greater effort following losses, but only focuses on consecutive games between two teams.

If this is all a function of motivation and determination to recover from a defeat, then it’s also reasonable to assume that they might expel even greater effort when that loss is extra embarrassing. The first time I heard of this as a betting strategy was from R.A on the Spittin Chiclets podcast, who informed listeners that this was a widely known thing in hockey gambling circles. Early in my betting career, I would often make the mistake of betting against a squad that just got their asses kicked, thinking it shows a real talent disparity between the two opponents; only to be disappointed when history failed to repeat itself.

This “Blowout-Redemption Theory” belongs to the zig zag family of theories along with this notion that players will compete harder to win games following losses. For the purposes of this investigation, we’ll define a blowout as 4 or more goals, just to get a greater sample. If you had bet $100 (moneyline) on every team who lost by 4 or more goals from October 2019 to May 2022, you won $3,700, but all of that came post-Covid. I doubt the pandemic affected how motivated teams were to play after a bad loss, so perhaps 2019/20 was more of an outlier.

In 2019/20, betting on teams recovering from blowouts did not yield a significant profit. It was not a good strategy, but it wasn’t bad either. Where it gets interesting is both seasons after Covid, where it became very profitable from about day 30 to day 90, then levelled off. What can’t be answered at this time is why the 2nd and 3rd months of those seasons were so good, and the others mediocre or bad. Will that be replicated in future seasons? We’ll have to wait and see. 

One question worth investigating; if losses motivate teams to try harder next game, then is it a viable strategy to bet on teams that just lost? That disqualifies all the games where both teams lost their previous match, so the entire sample is betting teams that just lost against teams that just won. If winners get complacent and losers try harder, how much money would you make if you bet every loser to beat every winner? From October 2019 to May 2022, you would have lost -$10,971. If you bet $100 on every puckline too, then you lost an additional -$12,428. Okay, so simply being a normal loser doesn’t make you better.

There is evidence to support the theory that a bad performance in hockey can lead to an improved performance in the following match for certain circumstances, but it does vary from team to team. If certain bad performances can lead to good ones in the future, then the next obvious question becomes; who are the best teams to bet after losses? Blowouts are rarer events than the common loss. For this investigation, I decided to look at the raw totals rather than rates of return. When a team that hardly every loses gets defeated, they might win 100% of their next games; however, you’ll have few opportunities to make that bet. The objective here is identifying the team that also offers the most opportunities to make these bets.

 

Keep in mind, the league’s worst teams are more likely to get blown out, so they will get much more opportunities at redemption, providing a much larger sample size. We did get two bad teams on the ends of both extremes, the Buffalo Sabres responded very well to blowouts, while the New Jersey Devils did not. Can we blame the motivational skills of the coach? Probably not considering that both teams had multiple coaching changes over the 3 years of this book (both are on their 3rd coach since my Vegas vacation). It really is a mystery as to why one team responded well and the other did not. It could be partially attributable to scheduling variance, that Buffalo faced easier opponents following blowouts. I could actually check that, but I’m not. After all this chapter did get cut from my book.

Both the Edmonton Oilers and Winnipeg Jets finished in the best teams to bet after losses in 2019/20 and 2021. In the first draft of my book prior to the 2021/22 campaign, the big conclusion from this chapter was supposed to be bet Winnipeg and Edmonton to win games after they lose, but had this book been published back then and you took my advice, you would have lost a big pile of money. One of the big lessons I’ve learned is that not all lessons are necessarily transferable from one season to the next.

Also, it needs to be mentioned that the team who finished dead last in the NHL standings cracked the top 5 worst teams to bet after losses in all 3 seasons (hitting #1 twice). The 2020 Red Wings and the 2022 Canadiens specifically would have murdered you following this strategy. The Habs might have been a profitable bet to win in the second half, but a lot of that came from some mini-winning streaks assembled after Martin St. Louis became the coach.

 

What’s interesting here is that Washington, Winnipeg, and Edmonton also appeared on the list of top 5 best road teams, at least payout on the road moneyline. This implies that there may be a correlation between ability to win on the road and recovery from losses. Do the same psychological ingredients lead to both outcomes? Generally the worst teams to bet after losses were all really bad teams (for all our parts of this sample), so there’s not really any mystery there. If the last place team loses, nobody says “they should be fired up to win the next game, let’s bet on that”. But it does seem like the ability to overcome adversity is a key ingredient to both winning on the road and bouncing back from a loss.

If you’re interested in seeing how teams respond to losses, you may also want to know which teams were the best/worst to bet after a win. Teams that won their previous game will beat teams who lost their previous game 54.9% of the time, but betting on that every opportunity would have led to a loss during these 3 seasons. The exception being, if an underdog won their previous game and the favorite just lost, then betting the dog +1.5 goals would yield a positive rate of return.

Who was better to bet after wins? It actually varied significantly from one season to the next. There were teams who appeared on the worst list one season, only to crack the best list the next (and visa versa). On the best side, only Carolina cracked the top 5 in more than one season, both post-pandemic. Meaning, they played well following “storm surge” post-win celebrations. In 2020, the Blues played well after listening to Gloria. The Flyers and Ducks each cracked the 5 worst twice, with no other team appearing more than once.

 

When you break it down by each season, most of the worst teams to bet after either a win or a loss tended to be bad teams.  A large majority did not make the playoffs, and barely any made it past the first round. Whereas teams that responded well to either a win or a loss tended to be teams who won a lot of games and made the playoffs. The lesson there is don’t convince yourself that a really bad team is more likely to win the next game after winning the last one.

Keep in mind to, if you are looking at my past seasons to draw inferences betting after losses in future seasons, there are multiple examples of teams flipping from best to worst one season to the next. You got destroyed if you expected the Red Wings to bounce back from losses in 2019/20, but that same catastrophically bad decision in 2020 was a net winner in 2021. The Flyers were strong following a win in 2020, but not in either 2021 of 2022.