2022 NBA Draft Thread

[A Better DJ & Photographer 456]

1 hour ago, CTMagicUK said:

*Chet and Jalen... :) 

No sticks! 0--->----<

What if we draft him and he's injured as often and severely as JI? Wasted pick! The boy is all skin and bones. Grown men will crush him.

*(Anybody but) Chet, and Jalen...

[CTMagicUK 1,480]

7 minutes ago, A Better DJ & Photographer said:

What if we draft him and he's injured as often and severely as JI? 

What if we don't draft him and he isn't? 

[A Better DJ & Photographer 456]

3 minutes ago, CTMagicUK said:

What if we don't draft him and he isn't? 

Then we'll have a different great player that helps us get better. How many stick figures built like Chet have long healthy careers? 

[CTMagicUK 1,480]

9 minutes ago, A Better DJ & Photographer said:

Then we'll have a different great player that helps us get better. How many stick figures built like Chet have long healthy careers? 

We'll have a different player if we don't draft Chet yes that is correct. Whether that player will be "great" is not assured and whether that player will be as impactful as a healthy Chet is up for debate. 

I've previously posted a pretty solid list of guys who came into the league skinny and succeeded. 

[jmmagicfan 301]

19 minutes ago, A Better DJ & Photographer said:

Then we'll have a different great player that helps us get better. How many stick figures built like Chet have long healthy careers? 

This is about the closest comparison I could find for height/weight to have a long, (mostly) healthy career; and even Garnett was 10 pounds heavier (and a couple inches shorter at the time, he was about 17). But as with most of the tall, skinny comparisons; most have wider shoulders to make you think their frame could fill out. Chet scares me more because of his frame than his actual weight. He just looks skinny through the shoulders. 

[CTMagicUK 1,480]

Yet to hear/read/see any actual science that suggests skinny = more injuries. Only anecdotal evidence. 

[CTMagicUK 1,480]

This is an older paper but:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3445097/

Key quote: "No correlations were found between injury rate and player demographics, including age, height, weight, and NBA experience."

This is based on a 17 year sample of data. 

 

[CTMagicUK 1,480]

6'6, vastly improved shooter as a junior. Fits this FO mould. Definitely a 2 way guy though rather than a draft pick, he's not even in ESPNs top 100. 

 

 

[CTMagicUK 1,480]

I somehow didn't know this (and it doesn't really matter with respect to the draft just interesting) but Mike Miller is an agent and he represents Paolo Banchero (and he also represents RJ Hampton).

[jmmagicfan 301]

1 hour ago, CTMagicUK said:

This is an older paper but:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3445097/

Key quote: "No correlations were found between injury rate and player demographics, including age, height, weight, and NBA experience."

This is based on a 17 year sample of data. 

 

Interesting find, but it does tend to lump together quite a few diverse injury types, and it doesn't differentiate between guys playing 30-35 minutes/game, and those playing 1-10 minutes/game. The formulation for their data seems far too simplistic to actually generate much useful analysis. It's conclusions seem to be too generic to support any demographic specifics.

For example, a guy who only is playing 8 minutes a game gets injured near the beginning of the season, is out for 12 games, and is then cut. Based on their formula, those 12 games of injury counts the same as a guy who plays 34 minutes/game, and misses 12 games during the entire season from accumulated bumps/bruises. The fact the 8mpg guy actually missed 70+ games doesn't factor in once he is off an active roster. Now someone like Isaac wouldn't even count for 2021-22, because he wasn't hurt during that season. 

"For the purposes of this study, an athletic exposure was defined as 1 athlete appearing in 1 game. Game injury rates were calculated per 1000 athlete exposures. No distinction was made in the database between athletes who played all 48 minutes of a contest versus athletes who played 1 minute. During a single game, the maximum athlete exposures would be 24, when all 12 players from each team participate in the contest. This method describes the total number of athletes appearing in regular and postseason games. The incidence rate (per athletic exposure) for practices and preseason games was not calculated owing to unreliable reporting methods and lack of a standardized protocol. However, the frequency data for injuries and illnesses sustained during these activities were still included and analyzed.

Incidence rates for a particular injury were defined as number of injuries per 1000 athlete exposures, as calculated with the following formula:

 

total number of injuries×1000/total number of game exposures"

 

[CTMagicUK 1,480]

9 minutes ago, jmmagicfan said:

Interesting find, but it does tend to lump together quite a few diverse injury types, and it doesn't differentiate between guys playing 30-35 minutes/game, and those playing 1-10 minutes/game. The formulation for their data seems far too simplistic to actually generate much useful analysis. It's conclusions seem to be too generic to support any demographic specifics.

For example, a guy who only is playing 8 minutes a game gets injured near the beginning of the season, is out for 12 games, and is then cut. Based on their formula, those 12 games of injury counts the same as a guy who plays 34 minutes/game, and misses 12 games during the entire season from accumulated bumps/bruises. The fact the 8mpg guy actually missed 70+ games doesn't factor in once he is off an active roster. Now someone like Isaac wouldn't even count for 2021-22, because he wasn't hurt during that season. 

"For the purposes of this study, an athletic exposure was defined as 1 athlete appearing in 1 game. Game injury rates were calculated per 1000 athlete exposures. No distinction was made in the database between athletes who played all 48 minutes of a contest versus athletes who played 1 minute. During a single game, the maximum athlete exposures would be 24, when all 12 players from each team participate in the contest. This method describes the total number of athletes appearing in regular and postseason games. The incidence rate (per athletic exposure) for practices and preseason games was not calculated owing to unreliable reporting methods and lack of a standardized protocol. However, the frequency data for injuries and illnesses sustained during these activities were still included and analyzed.

Incidence rates for a particular injury were defined as number of injuries per 1000 athlete exposures, as calculated with the following formula:

 

total number of injuries×1000/total number of game exposures"

 

That's a valid criticism I was aware of from reading it but I can't see how that would affect correlation between weight and injury in any meaningful way. 

[jmmagicfan 301]

Again, I'm not saying I hate Holmgren as a pick, and if the team has done it's due diligence - looked at all his medical, had the doctor's do a complete examination, worked him out against guys with some beef, etc; then I would be okay with the pick. I just have reservations about his ability to be a superstar in the NBA based on a "less than imposing" frame and body-type. I get that he's very talented, and has a lot of potential, but the NBA is much faster, more physical, and puts a lot of wear and tear on big men's bodies. The fact that Holmgren hasn't had any major injuries that I am aware of is definitely a positive in his favor. Many of the other guys 6'10" and over who seem injury-prone did have some history. 

3 minutes ago, CTMagicUK said:

That's a valid criticism I was aware of from reading it but I can't see how that would affect correlation between weight and injury in any meaningful way. 

If I'm reading it correctly, injuries that "carry over" between seasons aren't counted in the subsequent seasons, so if there were an injury like Isaac's or Kawhi Leanord's that ended a player's season, and cost them the entire next season, it would not be accounted for in that second season. It might not actually move the numbers in a meaningful way, but it might. Their analysis eliminates what could be impactful data, so it increases the uncertainty; that uncertainty calls into question some of the conclusions drawn from analyzing the data - sort of a corollary of the GIGO principle. (Garbage In, Garbage Out), this one being what might be termed IIIO (Incomplete In, Incomplete Out).