NHL Statistics That Can Be Misleading

The NHL continues to become more analytical as new technology, tools, and knowledge has allowed us to analyze just about every stat at every time, while also inventing some new stats. However, not all stats are created equal, and some stats are actually rather unreliable, or worse yet, even detrimental. Here is a list of some of the most notable statistics that should be analyzed further than face value due to their misleading characteristics.

Plus/Minus

Plus/Minus is a stat that showcases the net result of a player when goals were scored while that player was on the ice. If the player was on the ice when his/her team scored, the player will be awarded with one plus (+1). If the player was on the ice for a goal against, the player will be awarded with one minus (-1). The exception is the powerplay, where the team scoring on the powerplay does not result in a reward of a plus to any players, and penalty killers are not punished with a minus. If the penalized team scores a shorthanded goal, plus/minus will be applied, rewarding the penalty killers and penalizing the players on the powerplay. Additionally, plus/minus is always applicable during 6 on 5 empty net situations.

The benefit of this stat is that it’s a quick and easy way to see the net result of a players’ contributions to the team. Even if a player doesn’t score a lot of goals or factor in on assists, plus/minus is a stat that will still reward productive players that appear to be more helpful than harmful.

However, this is only in theory. In practice, this stat is heavily influenced by the success of the overall team. Teams low in the standings will naturally produce players with negative plus/minus stats, even if these players are objectively great players in numerous other areas. The opposite can also be true, where players who are not as productive will still have a high plus/minus by being on a team high in the standings. Additionally, on line changes between play, some players are deployed more often for defensive zone face-offs, and others are deployed more often for offensive zone face-offs. This is a subtle factor that could impact a players’ plus/minus. Even if a defensive zone player successfully exits the zone, or an offensive zone player fails to score or create sustained pressure, the chances of scoring the same shift after starting in the defensive zone is much lower than when starting in the offensive zone. This would mean plus/minus would create a slight imbalance, all else equal, depending on a players’ role on the team and how they are deployed by the coach.

Plus/minus does have its place. Despite its flaws, it is most useful when used for a smaller sample size. For example if a player was a -4 in one game, or a +3 in one game, it would likely be a good representative of a players’ production or contribution for that game. Additionally, plus/minus would also be better when transformed into a proportion variable, where it becomes a comparison amongst teammates, thereby eliminating one of the biggest flaws with the variable, that being the overall strength of a team. However, this would still not be a perfect approach, as again, some players are deployed for different purposes within the team. In recent years, the WAR statistic (wins above replacement) has risen in popularity, as it is an advanced stat that analyzes how impactful a player would be to the team based on the results of that player replacing or being replaced by another player.

Hits

The concept of a hit is straightforward, but the definition of it is arbitrary. A hit is commonly noted as a player who intentionally and forcefully checks another player, usually using their body. However, this is precisely where the issue with hits lies; the degree to what can be qualified as a hit is subjective. Adding onto this, hits are recorded by different people depending on the NHL arena that the game is played in, resulting in another layer on top of the already inconsistent stat.

However, assuming this is just a minor inconvenience, and that most people in charge of recording hits generally agree with what a hit is, the stat itself is not useful without context. On the surface, it is implied that a team with more hits would be more physical and harder to play against, and perhaps a tougher team built for playoff hockey. However, while this may be the case at times, it is not always true. In theory, hitting can only be done without taking a penalty if the opposing team has the puck. Because of this, if one team is outhitting another team by a wide margin, this may imply that the high hitting team struggled to maintain puck possession, and was chasing the other team around who didn’t need to hit because they had the puck often. This is why context is important, and that hits alone do not tell the full story. On the other hand, it could be true that one team was simply more physical than the other, and possession was relatively equal. Because of this, hits is a misleading stat on its own, and this variable should be taken into consideration with other variables such as puck possession metrics.

Giveaways

In hockey, there are essentially four ways to gain possession of the puck; off the face-off, off of a forced turnover such as a dump in, skillfully taking the puck away (takeaway stat), and lastly, off of an unforced turnover, which is referred to as a giveaway. Similar to hits, giveaways are slightly arbitrary, and may vary from scorekeeper to scorekeeper, which is one of its faults. Additionally, the idea of a giveaway would be that it would have an inverse relationship with winning games, as the more giveaways there are, the higher chance a team has of losing the game. However, as seen below by the combined giveaway numbers in the salary cap era since 2005-2006 (excluding the Golden Knights, Kraken, Coyotes, and Utah HC for simplicity purposes), the numbers don’t align with this hypothesis.

As seen, the Oilers have nearly twice as many giveaways than the Columbus Blue Jackets, while simultaneously, the Blue Jackets have accumulated the second lowest number of points in this time frame. Granted the Oilers had struggled for many seasons as well throughout the salary cap era, but the San Jose Sharks and Dallas Stars are both teams in the top 12 for cumulative point totals since 2005, yet are both within the top five for giveaways in that time frame. This leads into another factor, which is that giveaways don’t always mean a team made a costly mistake. Giveaways will naturally occur more often among teams that have more puck possession, or skilled players who are often carrying the puck or taking risks to make creative plays. In this context, giveaways don’t tell the full story, as not every giveaway is a costly defensive zone turnover.

What’s more, unlike hits, where a certain teams’ style of play can drastically impact their hit totals over a 20-year sample size if that core made up over 25% of that time period, giveaways is a statistic that all teams would theoretically want to minimize, and in the long-run all teams’ giveaways should be very similar. However, that is not the case, as the Oilers have nearly double the number of giveaways as the Blue Jackets, something that should theoretically not be possible over a sample size this long.

One could argue this stat would serve as a useful tool when used in comparison to teammates, or analyzing the number of giveaways per time on ice in order to adjust for confounding factors. However, due to the inconsistency in how giveaways are tracked, the entire statistic should be taken with a grain of salt.

Goals Against Average

Goals against average, often referred to as GAA, is the average number of goals that a goaltender allows per 60 minutes of play. Unlike hits and giveaways, GAA is a stat that is perfectly accurate, however, the issue comes with the qualitative characteristics of this stat. GAA is more of a team stat than a goaltender specific stat, as the defensive capabilities of the team overall has a large impact on the amount of goals allowed. Similarly, a goalie playing behind a team that limits high danger chances or shots in general will naturally have an easier time keeping the puck out of the net than a goaltender who plays behind a poor team that allows numerous high danger opportunities.

While GAA is correlated with save percentage, save percentage is objectively the better statistic, as it eliminates the confounding variable of shots on goal against. For example, a goaltender playing behind a great defence who saves 14 goals on 16 shots would have a better GAA but a worse save percentage than a goaltender who saves 36 out of 39 shots.

In recent years, there has even been an argument that the advanced stat of goals saved above average (GSAA) should be the superior goaltending stat, as this takes the danger of shots saved into consideration, something that save percentage is unable to do.

While theoretically GAA can be used when comparing multiple goalies within the same team, it is still ultimately an inferior stat when compared to save percentage and GSAA. As a result, GAA should be treated more as a team statistic, and never for an analysis of a specific goaltender.

There are certainly more statistics that have their quirks, but the ones outlined in this article are some of the most controversial statistics that are still being used to this day. This is why when utilizing analysis for predictions, it is important to receive guidance from a trusted analyst who understands the game of hockey in addition to the math and statistics behind the scenes. If you want to stay in the loop for future products that will help with betting decisions, subscribe for free below.