Beyond the Basics: How We Think About Saved Shot Rate

Welcome to Beyond the Basics!

My name is Zack Capozzi, and I run LacrosseReference.com, which focuses on developing and sharing new statistics and models for the sport.

The folks at USA Lacrosse Magazine offered me a chance to share some of my observations in a weekly column, and I jumped at the chance. Come back every Tuesday to go beyond the box score in both men’s and women’s lacrosse.

Save percentage is not just a goalie stat. Like almost every stat, the skill of the offense and the defense interact to determine the final result. A great goalie can easily have a lower save percentage if he plays against a bunch of teams who are able to avoid saves.

And make no mistake, this is a skill. For an offense to operate at peak efficiency, shot-on-goal rate has to be balanced with saved shot percentage. I touched on this in a previous Beyond the Basics piece; one of the biggest statistical differences between top teams and the rest is the percentage of on-goal shots that end up as saves.

Given the importance of this stat, I wanted to do a deeper dive and see where the different offenses fit and demonstrate why we should think about saved shot rate the same way we think about shooting percentage.

SHOT ON CAGE? SO WHAT?

But before we start, let's get one thing straight. Shot-on-goal rate is not the type of stat where more is better. Knowing how many shots a team put on goal is not particularly helpful in determining how well they played. Take a look at the matrix below and write down the teams that are along the vertical midline.

You’ve got Ohio State. You’ve got Duke. You’ve got Georgetown. You’ve got … Hampton? Clearly, SOG rate is not highly correlated with offensive success.

Think of it another way. Shot-on-goal rate, like time-of-possession, can be gamed. I can have the highest time of possession in the country by simply incurring a shot-clock violation on every possession. You can have a high shot-on-goal rate and a terrible shooting percentage if every shot is getting saved. Let’s take two teams to see how this plays out in practice.

Drexel and North Carolina have very similar shot-on-goal rates. 61.9 percent for the Heels. 62.4 percent for the Dragons. But Drexel has the seventh-best shooting percentage in the country (32.7 percent); UNC is 55th nationally at 26 percent. The reason is that just 46 percent of Drexel’s on-goal shots result in saves (54 percent are goals). For UNC, 54 percent of their on-goal shots are saved and just 46 percent are goals.

Lacrosse is unique in goal-based sports in that how you miss is really important. And I hope that this has demonstrated that shot-on-goal rate is not so much.

PLAYER SHOOTING DECONSTRUCTED

We can apply this same analysis to individual players as well. The chart below shows the offensive players who were recently named to the Tewaaraton Award Watch List.

In general, higher shot-on-goal rates are correlated with higher saved-shot rates. But remember, these are some of the best offensive players in the country and there is still quite a bit of variation.

The size of the player’s bubble reflects their shooting percentage. Take the three guys on the right side. John Piatelli has a pretty standard saved-shot rate given his shot-on-goal rate, and his shooting percentage is fairly standard too (32 percent; 65th percentile). Ryan Lanchbury is a bit better. Despite having almost the same shot-on-goal rate, his shooting percentage puts him in the 86th percentile.

And then there is Logan Wisnauskas. Same shot-on-goal rate, but his shooting percentage, at 48 percent, puts him in the 97th percentile overall. And that has consequences for the offense overall. Fewer saved shots going the other way means less transition for the opponent. Shots that are missed rather than saved give you a second crack at scoring. Misses are fine. How you miss matters.

If I was trying to find ways to increase my offensive efficiency, this is the kind of thing that is critical to be aware of. Offensive efficiency is made up of components: shooting percentage, turnover rate and shots-per-possession. In the same vein, it’s not enough to just know what a player or a unit’s shooting percentage is. You need to know how they are missing when they do. It’s hard to coach a kid to shoot better; it’s easier to make progress when we can be specific in what we want to improve.

THE IMPLICATIONS ARE SERIOUS

Now, you may be thinking: are saved shots really that bad? Don’t we hear all the time that the offense needs to get shots to the goalie. Get shots on net and you’ll see them fall eventually. And there may be elements of truth in that, I’m pretty certain that it’s not a strategy that we should measure offenses against. Like goals-per-game as a measure of offensive success, hearing analyses that fawn over high SOG rates is getting to be a pet peeve of mine.

But that’s pretty fuzzy for a Beyond the Basics article, so let’s dig into the numbers a bit. To do this, let’s look at how often the various types of misses lead to goals the other way. Specifically, how often does a miss, a save or a pipe lead to a goal for the opponent within 20 seconds?

Missed Shot: 0.68% of all missed shots lead to a goal
Pipe Shot: 1.42%
Saved Shot: 2.40%

This data is taken from all 2022 Division I men’s lacrosse games ,and it’s pretty clear, a save is over three times more likely to result in a transition goal the other way than a missed shot. Admittedly, the 20-second cut off may be a factor here since missed shots that are backed up by the shooting team would not end up as goals the other way within that time frame. But even if percentages are closer if you were to limit this to late shot-clock attempts, we know from watching transition goals that clean saves can ignite a rush the other way.

But if you want a more direct way to think about the importance, we can just look at how these metrics relate to the thing we care most about: offensive efficiency. Simple correlation has its place, and I think this is a question that it’s well suited to answer. If offensive saved shot rate didn’t matter, we’d expect to see great offenses with bad ratings and bad offenses with great ratings. That’s not what we see. The correlation between offensive saved shot percentage and offensive efficiency is just as strong as the correlation between shooting percentage and offensive efficiency. As you might have guessed, offensive shot-on-goal rate has almost no correlation with offensive efficiency.

Let me say that again. If you want to be a good offense, the percentage of shots that become goals is just as important as the percentage of on-cage shots that are saved. The best offenses have a high shooting percentage AND a low saved shot rate. You can’t be great without both.

OK, SO WHAT?

This goes back to the idea of what statistics should be for. If I’m a team, I want to know where my strengths and weaknesses really are. If I have a practice slot that I’m trying to fill, I have a lot of choices about how I can fill that time. If I’m focusing on raising one player’s performance, there are lots of different things that I can emphasize for that specific player. Smart teams are using their limited resources (time) in the places where their efforts will result in the largest payoffs.

If shooting is an area of interest for me, I can be more effective if I know where the biggest gaps in my shooting are. Does my team have a high saved shot rate? Am I emphasizing shot-on-goal rate as something to be desired? If not, which players are contributing the most saved shots? Is there something that I can do to help those individual players increase the percentage of shots that miss the cage while not reducing the percentage of shots that find the back of the net?

As I mentioned above, saved shot rate and shooting percentage are distinct components of shooting effectiveness. If a player’s year to year shooting percentage doesn’t change, but his saved shot rate goes down, he’s made real progress because his contribution to offensive efficiency has gone up.

Stats should be a tool that you use to help guide that directs your program’s activities. It’s hard to do that with high-level stats. Splitting shooting percentage into its component parts is a way to focus on what matters.

LACROSSE STATS RESOURCES

My goal with this column is to introduce fans to a new way to enjoy lacrosse. “Expand your fandom” is the mantra. I want you to walk away thinking about the players and stories presented here in a new light. But I also understand that some of these concepts can take some time to sink in. And part of the reason for this column is, after all, to educate.

To help this process along, I have several resources that have helped hundreds of lacrosse fans and coaches to internalize these new statistical concepts. The first is a Stats Glossary that explains each of my statistical concepts in more detail than I could fit here. The second is a Stats 101 resource, which provides context for each of my statistics. What is a good number? Who’s the current leader? That’s all there.