Thinking about the Grizzlies Cubs, Part 3: Mike Conley

A little while ago, I introduced my Grizzlies Cubs series, in which I ran some stats to project how good the young Grizzlies players can end up being in the immediate future and at the peak of their career.

Last time we did Quincy Pondexter, and today we’re going to do Mike Conley.

Before we start, I’m going to do a quick reminder of how this works:

May 21, 2013; San Antonio, TX, USA; Memphis Grizzlies guard Mike Conley (11) reacts in game two of the Western Conference finals of the 2013 NBA Playoffs against the San Antonio Spurs at AT

How it Works:

What I did, using the average peak age and experience data (the average player peaks after 5.8 seasons in the league and around the age 27), is I plugged the players’ growth from one year to another, along with the probable peak season, into my calculator to get a basic equation describing the players’ growth. Using that equation, I could then do just a little bit of calculus to get a projected career performance arc.

I did this for PER, Net Efficiency in Points per 100 Posessions (Points scored per 100 possessions minus Points allowed per 100 possessions), and Win Shares per 48 minutes. I used those three because they’re all “comprehensive” metrics to tell us how good a player is, but they all tell us slightly different things.

PER tries to tell us how good a player is, objectively, but is still remarkably bad at accounting for defense. As well, because PER doesn’t really take minutes into account, it’s bad at telling us the impact a player has on a team. Net Efficiency, on the other hand, does tell us about defense and impact, but since it’s basically just an upgraded +/- system, it does a very poor job of telling us just how good the player is, isolated on his own merits. Win Shares is a nice mix of the two, really.

If you go back to the original article, I tried this technique on an already-retired player, Mark Aguirre, and included the results for you to see.

To be able to say that these all of these pairs of graphs are describing the same relationship, the correlation coefficient for each would need to be at least 40%. To be able to say that these two graphs are definite, absolute projections, the correlations would need to be above 90%.

For PER, the correlation was 70.79%. For Efficiency, it was 71.70%. For Win Shares, it was 83.69%.

It’s flawed, but it has some pretty darn good value as a predictor of peak production.

The Rising Star: Mike Conley

One of the main things I learned in my research for this analysis is that players typically peak between 5 to 8 years in the league and from age 26 to 30. Right now, Conley is in the middle of both of those periods; he’s near or in his prime. He’s a little young to be in his athletic prime, still, but one other thing the analysis brought out is that experience seems to have a greater correlation with a player’s prime than age.

The average time in the league before hitting the prime is 5.8 years. Conley has been in the league for 6 years, now.

As a result, between Conley’s age and his experience, his prime is likely to be in the next year or two, which is really unfortunate for Grizzlies fans who were hoping for Conley to really blow up in the next year or two. On the bright side, these are still just odds, and odds can be broken. They are all the time. Conley certainly seems like he’s still growing, which is great.

So now, without further ado, here’s the projections, with the real stats for reference:

As I mentioned earlier, this projection predicts that Conley peaks in his 8th season in the league, and he doesn’t get significantly better in the next 3 years. He does, however, get a little better, and he keeps up his borderline All-Star level performance over the next 3 seasons, which is still pretty great for Grizzlies fans. I, for one, am pretty happy with the idea of Conley maintaining a PER near 18 for the next three years.

The correlation coefficient between the two graphs up through his 6th season, by the way, is 78.41%, which is a pretty great percentage.

 The Efficiency predictor graph seems a little low, to me, but I think it’s perhaps a good reminder to temper expectations. 7 more points scored than allowed per 100 possessions is certainly not bad by any measure, it’s pretty good. It is also not astounding, which is fine.

As I’ve mentioned before, too, the Grizzlies’ defense is likely to slack a bit next season due to most of the bench additions, so it wouldn’t be unreasonable to expect Conley’s efficiency to drop from his 11 more points scored than allowed per 100 possessions from last season. 7 might be perfect, in fact, for the next couple seasons.

The Correlation Coefficient for these two graphs is 79.29%.

The Win Shares projection works in basically the same way as the efficiency graph, I think. It seems a little low, but it might actually be more accurate in the long run. And, while it does seem a little low, the numbers are still really good. 17 win shares per 48 minutes is actually a way above average number, so even if he’s not improving readily, that’s a great number for him to be logging.

The correlation coefficient for this graph is 78.41%.

The lesson, here, is that Mike Conley is a really great player. He’s not quite a superstar, but he is a fantastic player, and he’ll still be a fantastic player going forward…he just won’t be much more.  Really, that’s fine. Conley is phenomenal, and I, for one, will happily take a phenomenal player like Conley on any day of the week.