This is all fine and dandy, but you’re going off of hypotheticals, and I’m going off of facts.
I admitted as much as saying bottom 3 was an exaggeration. They’re one of only 5 teams that slots comfortably in that bottom sect in every splice of the data. I was off by ~a few~ position. They’re still bad at drafting.
Again, this doesn’t even get into their completely inability to draft star caliber players, which you admitted is concerning. This is just as much of an unquantifiable data point as all the hypotheticals you’re throwing out above. Like I said above, there’s arguments for and against at this point, but the line of scrimmage is so far back that it doesn’t change a whole lot.
But you can't cling to the facts of results, without acknowledging that you're comparing a very uneven field.
I could stand in a tree and state the fact that I am at a higher elevation than the person on the ground, but I can't leave out the fact that I'm in a tree. That contextual detail impacts the data I am presenting. Especially if my conclusion is that I must be a taller person because my head is higher from the ground. That's not an accurate conclusion because it is not comparing two subjects on equal footing.
So comparing the Rangers draft success, based on the number of games their picks have played or points they're scored, is going to be inherently skewed if we remove half the first round picks in the sample size, along with another 4 picks from the second and third round.
I mean how do you reasonably compare that to a team that had multiple top 10 picks? That's not a small differential --- especially concerning an event (the draft) where talent is not equally distributed across all rounds.
But let's even say what I proposed is hypothetical (it's a valid hypothetical). What if we reversed that? What if we didn't project what the Rangers did, but instead removed the same number of picks from other teams? What happens to the data when we remove "the tree" they are sitting in and even the starting point? I'm going to guess you probably end up with the the same result --- the Rangers climbing to more of that 13/14 range. And again, that still wouldn't necessarily account for their success picking in the 20s vs. teams who picked in the top 10 consistently (which is where I think they edge closer to that top 1/3 range I’ve mentioned).
Because even if we "level” the starting point, we still have a significant gap between draft positions.
I remove half the Rangers first round picks, they're still picking at around 20 on average.
I remove half the Oilers first round picks, they're still picking in single digits on average.
So for the data to be somewhat clean, you'd have to pursue a different approach, including, but not limited to:
Removing an equal number of samples from other teams to get a more accurate comparison of results,
and/or limiting the field to just drafts where the Rangers had a comprable number of kicks at the proverbial can.
Otherwise it's a flawed input and it's going to turn out flawed data.
Now, I think we're also confusing facts with interpretations.
It could be factual to say that since 2007 the Rangers rank 26 in the games played by draftees, 22nd in points by draftees, etc. etc.
But those numbers do not actually mean they were the 21/22 worst drafting team. Because that number would reflect missing data.
For example, every Ranger first round pick from 2008-2012 could've been in NHL regulars, but the cumulative totals for the team still would still lag behind because they are missing picks who could've played during the era in question. So Rangers could draft 10 guys who score 800 points in 800 games, but they would still lose in every one of those "statistical" categories to a team that took 15 guys, who scored 820 points in 1000 games. Never mind that the Rangers picks could’ve been better and scored at a higher point per game rate.
Factually, and by the numbers, the other team produced more players, those players scored more total points, and played in more total games.
But were those guys inherently better? And, subsequently, was the other team actually better at drafting?
That's one of the reasons why the other data was potentially more accurate, because it accounted for gaps --- albeit with some flaws.
And that's without us even getting into subjective measures.
For example, if you draft a guy who plays 1,000 games and scores 800 points, how do you value that compared to a guy who plays 900 games and scores 820 points. Does the 20 points win out, or does the 100 games win out?
What happens if your guy gets taken out by an injury and retires at 30? Is the guy who lasts longer and eventually eclipses his total the better pick? What criteria are we using and what value system do we assign to it?
Let's use the 1994 draft as an example.
Steve Sullivan played 1011 games, scored 290 goals and posted 747 points.
Chris Drury played 892 games, scored 255 goals and posted 615 points.
Which player was the better pick?
Sullivan leads in every statistical category, and yet I don't know if he's the clear winner in a survey of which player is viewed as being the "better" choice.
And what about value? Sullivan wasa 9th round pick, Drury a third. Was Sullivan technically a better value?
That's one example of many. How do we judge that?
Chris Kreider has less games played and less points than Marcus Johanssen as of this post.
Both guys were drafted in 2009.
Statistically speaking, the Rangers didn't do as well as Washington with their pick. Did Washington draft better in that first round?
Which player would you take?