The analysis does not say that a steal is worth 9.1 points. Although I have some problems with the methodology employed, saying that it equates a steal to 9.1 points is fallacious.
What he is saying is that, proportionately, getting 1 steal has the same impact on the final box score as getting 9.1 points. It is a subtle difference, but an important one.
Look, an NBA team averages somewhere between 5 and 9 steals per game. Let's just take the middle ground and say 7. So if a player on that team averages 1 steal per game, on average they are responsible for just over 14% of the team's output in steals.
Similarly, an NBA team averages between 93 and 108 points per game. Again, let's use the middle ground and say 100. A player would have to average 14 points per game to be responsible for 14% of the team's output in steals.
Now, this isn't EXACTLY how they got the 9.1 percent number. The math they used was more sophisticated and weighted to take into account a variety of factors (including team averages in team transition offense/defense and other important considerations). But the logic is essentially the same. It is just a parametric description of the relative impact of a statistic with respect to overall team performance. It doesn't say that 1 steal will produce 9.1 points.
Now, you can debate whether you agree with this number. Certainly it is a very brute-force approach to modeling relative statistical impact; in my mind, a more rigorous approach would be a Bayesian method using distributions of prior probabilities (e.g. Lance Stephenson driving into the paint is more likely to result in a turnover that counts as a steal for the opposing team than Chris Paul; etc.), but this isn't a trivial calculation, and requires knowledge that isn't accessible without access to the Sports VU camera data. However, that does not mean that the 1 steal/9.1 points comparison is inherently meaningless, either. It is actually a very important statistic to understand, it just requires proper contextualization.
This statistic does not tell you that a steal is more important to winning a basketball game than points. It merely tells us that, taken into account the total production an NBA team tends to produce regardless of whether the game is a win or a loss, you have to score 9.1 points to share the same proportional impact as getting 1 steal. That is all. This should be intuitive: when you look at the box score, any team is going to have at minimum 70 points (usually closer to 100), but will tend to only have about 1/10th as many steals. Another way to think about it is that there is greater variability in points than there are as steals (which, again, should be pretty intuitive if you've ever watched basketball). The ability to produce steals is more consistent than the ability to produce points.
(In fact, this type of analysis is how most smart people build their fantasy football rosters. Essentially, getting a really good TE is a higher value draft pick than getting a really good WR, because there are fewer really good TE's in the league. That is, the expected deviation from league average production is greater for a good TE than for a good WR, because if you pick a random WR they are on average going to be a more productive player than a random TE. Heck, this type of analysis is how most private equity firms make their money. The absolute value of a given measurement isn't nearly as meaningful as that value's relationship with wider trends and averages; when you are investing in a product or industry, you don't just look for something with high profits, you look for something with high profits relative to the average profit level of other companies in that sector.)
It has nothing to do with "regression analysis", by the way. And it has nothing to do with breaking down the expected outcome of a steal as some people in this thread have tried to do. Those are different ways to look at steals, and are both valid within the right situations, but aren't relevant to this specific comparison.
Topic: Steals, Scoring and Scoring Impact: Marcus Smart and Russ Smith (Read 5072 times)