Of course, everyone knows this. Turnovers mean you aren’t getting shots on cage, which means you aren’t scoring. Depending on where the turnovers occur, they can easily become fast-breaks or goals for the opponent. So turnovers are bad, obviously.
But saves can easily turn into fast breaks the other way too. And in reality, the problem with turnovers is 80% the loss of possession and 20% the risk of a counter-attack. So whether you lose possession because of a turnover or a saved, or otherwise missed, shot, you have experienced a negative outcome.
The contradiction here is that turnovers get such a bad rap compared to missed shots. And there is an empirical basis for that: missed and saved shots lead to goals for the offensive team far more often than turnovers do. This is why offensive players get positive EGA credit for a missed or saved shot.
But what if there is a downside to low turnover rates? After all, not all turnovers are created equal. Some come from a failed clear, where the opponent is gifted an easy opportunity to score. Others come from a scrum in the crease after a long possession ended in a failed attempt to thread a pass to the doorstep for a slam dunk goal.
In the same vein, some saved shots are great feats by the goalie to stuff a point-blank attempt that results in a marker 90% of the time. Others are easy saves on shots from 20 yards at the very end of the shot clock.
So it stands to reason that a team with a high-risk, high-reward offensive strategy may end up with very few possessions ending in a missed or saved shot. They could have a high turnover rate relative to a more cautious attack. But if the high-risk approach leads to greater offensive efficiency, (which of course, is the goal here,) then lots of turnovers may not be such a bad thing.
To this point, we are in hypothetical land. So let’s use this post to dive into the numbers and see if there are any trends or insights we can draw.
As I write this paragraph, I have not looked at the data yet, so it’s very possible that we’ll end up with a bunch of muddled data and no insights. That would be fine; publishing your failed studies is still a contribution to lacrosse science.
First, let’s define a few terms. First is the “third outcome”. This represents possessions that end with neither a goal nor a turnover. So basically possessions that end with a shot that either misses the net, is saved, or hits the pipe or a player and is picked up by the defense. As a percentage of the total possessions, this is the Stop Percentage or the Third Outcome Percentage.
If you add up the Stop Percentage, Offensive Efficiency, and Turnover Rate, you’ll get 100% for each team.
The next term we need to define is the “turnover gap”, which is the Turnover Rate minus the Stop Percentage. This is a measure of how many more possessions end in a turnover vs a defensive stop. You would imagine that excessively cautious teams would have a negative turnover gap (more missed shots, fewer turnovers). Our high-risk, high-reward team might have a positive turnover gap because the possessions that don’t end in goals are more likely to be turnovers than missed shots.
With that done, we can try and tackle this problem by asking a few questions. We have used the entire 2019 season as the data set here.
So question number one is, are there large variations in this turnover gap? Do we see evidence that offenses tend to fail for different reasons?
These are the 6 teams with the largest and smallest turnover gaps. Clearly, there is a large variation.
And many of the teams with the highest turnover gaps had some of the least efficient offenses. But so did High Point, which had a top-30 offense and scored some of the biggest wins of the year.
On the flip side, Sacred Heart, who had the 11th most efficient offense last year, had the second smallest turnover gap. But then, so did Bryant and Hofstra.
Do better offenses have a different turnover gap?
Another question we can ask is: do more effective offenses demonstrate any common tendencies with respect to turnover gap? If a high-risk, high-reward approach tends to lead to better outcomes, then we might expect the better offenses to have a higher turnover gap.
Interestingly, that is exactly the opposite of what we see in this table. The better offenses have a lower turnover rate, which is not surprising. Hard to score if you are constantly giving the ball to the other team. And those lower turnover rates translate into a lower turnover gap. As you go up the efficiency ladder, the percentage of possessions that end in a turnover falls 3 times faster than the number of possessions that end in a missed or saved shot.
Of course, there is one large exception: Penn State. The lone team to crack the 35% efficiency mark last year had a 4.4% turnover gap. In fact, the Nittany Lions had the lowest percentage of third outcomes of any team. And you know who had the second smallest? Cornell, the 2nd most efficient team from last season had a turnover rate of 36.1% and a rate of third outcomes of 29.8%. Their turnover gap was even higher than PSU at 6.4%
So in general, the better the offense, the lower the turnover gap. But the absolute best offenses had some of the highest turnover gaps. I think it would be fair to say that better offenses do not necessarily have to mean lower turnover gaps.
Does turnover gap predict anything?
The next question is whether teams that have similar turnover gaps demonstrate any other similar tendencies? If turnover gap contains any information, we might expect to see some trend in one of the other outcome variables.
As expected, the smaller turnover gaps are associated with a greater percentage of possessions ending in a saved or missed shot and smaller turnover rates. That is the formula for turnover gap after all.
From above, we saw that the best offenses tended to have the lowest turnover gaps (noting the Cornell and Penn State exceptions of course), but here we see that the highest average efficiencies are actually not in the lowest turnover gap buckets. Instead, offensive efficiency peaks in the bucket where turnover rate is between 0 and 7% lower than the third outcome rate.
Is turnover rate just the best predictor of efficiency?
This perhaps should have been the first question we asked; consider it the null hypothesis: do high turnover teams have lower efficiencies? If the turnover gap doesn’t mean anything, then we would probably expect turnover rate to be the best predictor of efficiency. After all, a turnover cannot become a goal under any circumstances, where even the worst shots sometimes find their way into the back of the net.
By and large, the more turnovers that you cough up, the worse your efficiency. But there is one big exception: the 5 teams with the lowest turnover rate did not have the best efficiency. That distinction was held by the next highest turnover bucket.
It is at least plausible that this gives us a glimpse of the balance needed between aggressive playmaking and poor offense.
If you seek to minimize turnovers, you can find yourself in the first bucket, with an ok degree of efficiency and a very small turnover gap. Consider this the conservative offense mindset.
The best efficiency, on the other hand comes from a slightly higher tolerance for turnovers. Remember, at the end of the day, it’s really about the percentage of possessions that end in a goal. There is no real reason to prefer a failed possession to come as the result of a diagonal pass getting intercepted or a shot intercepted by the goalie.
Because I created this table too…
I am skeptical that looking at teams by the Stop Percentage will yield any insights, but I created the table already, so might as well show it.
There is actually more here than I expected. The trend is clear, the more possessions you have that end in a missed shot or a saved shot, the lower your offensive efficiency. The fact that the trend is clearer here than in the turnover buckets chart bolsters the idea that turnovers get a bad rap. According to the stats from 2019, the best offenses are not the ones that turn the ball over the most, they are the ones that have the fewest possessions end in a saved or missed shot.
This goes back to the Penn State and Cornell examples. Neither of those teams had an absurdly high turnover rate, but they also didn’t have the lowest turnover rate. Where they really stood out was the very small percentage of their possessions that ended in a saved or missed shot.
At the end of the day, the average data tells one story and the exceptions tell quite another. Turnover gap and turnover rate tends to fall in line with efficiency. But the best offenses from 2019 completely flipped that script with higher turnover rates than 3rd outcomes.
To be a good offense, you can focus on reducing turnover rate, even if it means more possessions end in a missed or saved shot. To be a great offense, it would seem that you need to aggressively hunt great shots, such that your missed/saved shot percentage is minimized.
And bottom line, if the coaching staff is focused too much on turnovers at the expense of finding great shot opportunities, the offense is probably going to suffer.
From an evaluation perspective, this can mean a few things. First of all, having the lowest turnover rate is not necessarily a good thing if it means you are getting poor shots off. So having the #1 smallest turnover rate is not necessarily a good thing.
Second, this probably deserves some more work to understand why the best offenses have turnover rates higher than their 3rd outcome rates. It’s possible that a very aggressive strategy that relies on trying to find goal scorers in the absolute best position to score, even if it risks a higher turnover rate is the optimal strategy…if you have the offensive players to execute it (read: Grant Ament and Jeff Teat).
Lastly, we have the un-examined part of all this. What is the defensive implication of all this? It may be that the high-risk/high-reward strategy does help boost offensive metrics while also boosting the defense’s susceptibility to counter-attacks.
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