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We discovered last week that it hasn't been so simple for teams to turn strong expected goals share metrics into playoff success.
The 2023 Golden Knights had the 16th-best xG% during the regular season and only marginally improved that rate in the playoffs, and all they did was win the Stanley Cup.
Instead, Vegas scored on its even-strength high-danger chances (ES HDC) at a ridiculously opportunistic rate: 21.2%. Was something like that predictable? No, but if a team shows it has the high-end talent to turn a chance - estimated at a fraction of an expected goal - into an actual goal during the regular season, bettors may be inclined to believe an above-average conversion rate can be predictive.
Some teams boast more talented scorers than others. For example, an Auston Matthews shot from close range has a better chance of going in than almost anyone else's.
A team's best measurable scoring opportunity is an ES HDC or power play (league average: 20.8%). The teams with the most talent have a good power play (PP) and are also likely to score at an above-average rate on ES HDC (league average: 12.5%).
Adding PP and ES HDC goals together and dividing them by power-play opportunities and high-danger chances gets you a metric we call SNIPES percentage.
The league average for SNIPES is 14.5%. Here's how the last 12 teams to make a conference final fared during the regular season and then in the playoffs:
Is there a correlation to playoff success?
Eleven of the 12 teams in the above table were above average in SNIPES percentage during the regular season. Only last year's Hurricanes came into the playoffs below average. Carolina had the best regular-season xG% and was third during the playoffs, which can make up for low conversion rates for two rounds.
While some teams saw their efficiency drop, just three fell below average: the 2021 Canadiens, 2021 Golden Knights, and 2023 Panthers. Later this week, we'll see how those three managed to thrive in the postseason when we look at how teams keep the puck out of the net.
The lesson? If any of the above teams score more often relative to how many chances they get in the playoffs, it shouldn't come as a total surprise.
The cheat sheet
The dirty little secret in the betting world is that while there are no bad bets at the right price, the discovery process of what a good price looks like is hidden.
Each week, we balance market information from regular-season point totals and in-season advanced metrics - with an even-strength focus - to determine the win probability for each team and the moneyline needed to bet on either side. The idea is to remove the cognitive bias of win-loss records, which can be skewed by outliers like special-team results, poor goaltending performances, and other unreliable events.
You can use whatever parameters you like to decide how much of an edge you need to trigger a bet, but here are mine:
- True line favorite of -111 or longer: 1%
- True line between -110 and +110: 2.5%
- True line underdog of +111 or longer: 4%
I also have a 5% win probability consideration for a team playing in the second game of a back-to-back with travel and a 3% consideration for the second leg of a home back-to-back. When it comes to injured players, an estimation is made on the player's impact on their team's win probability.
When the betting markets open up the night before, you can compare those prices with our "price to bet" column to see if you're getting any value with either side's moneyline. There's a possibility that a moneyline moves into a bet-friendly range at some point between the market opening and puck drop.
DATE | GAME | WIN PROB. (%) | PRICE TO BET |
---|---|---|---|
Apr. 8 | PIT@TOR | 39.5/60.5 | PIT +182/TOR -147 |
VGK@VAN | 50.4/49.6 | VGK +109/VAN +112 | |
Apr. 9 | WSH@DET | 46.9/53.1 | WSH +133/DET -109 |
OTT@FLA | 40.2/59.8 | OTT +176/FLA -143 | |
PHI@MTL | 50.9/49.1 | PHI +107/MTL +115 | |
TOR@NJD | 46.2/53.8 | TOR +137/NJD -112 | |
NYR@NYI | 52.4/47.6 | NYR +100/NYI +122 | |
CBJ@TB | 31.4/68.6 | CBJ +265/TB -208 | |
CAR@BOS | 55.6/44.4 | CAR -120/BOS +148 | |
BUF@DAL | 31.5/68.5 | BUF +263/DAL -207 | |
WPG@NSH | 48.4/51.6 | WPG +118/NSH +104 | |
MIN@COL | 41.9/58.1 | MIN +164/COL -133 | |
ARI@SEA | 36.3/63.7 | ARI +210/SEA -168 | |
LAK@ANA | 72.1/27.9 | LAK -246/ANA +318 | |
Apr. 10 | CHI@STL | 36.0/64.0 | CHI +213/STL -170 |
VGK@EDM | 38.1/61.9 | VGK +194/EDM -156 | |
ARI@VAN | 29.0/71.0 | ARI +300/VAN -234 | |
Apr. 11 | NJD@TOR | 40.8/59.2 | NJD +172/TOR -139 |
WSH@BUF | 40.4/59.6 | WSH +175/BUF -141 | |
PHI@NYR | 31.9/68.1 | PHI +259/NYR -204 | |
DET@PIT | 34.1/65.9 | DET +232/PIT -185 | |
OTT@TB | 45.2/54.8 | OTT +143/TB -117 | |
CBJ@FLA | 26.5/73.5 | CBJ +345/FLA -264 | |
MTL@NYI | 33.3/66.7 | MTL +241/NYI -191 | |
WPG@DAL | 35.3/64.7 | WPG +220/DAL -176 | |
SJS@SEA | 25.5/74.5 | SJS +365/SEA -278 | |
CGY@LAK | 39.2/60.8 | CGY +184/LAK -149 |
Matt Russell is the lead betting analyst for theScore. If there's a bad beat to be had, Matt will find it. Find him on social media @mrussauthentic.
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