Merit wrote:CPT wrote:Raps in 4 wrote:
What the **** is this fool talking about? He ranked Walter #6 but doesn't know why, so he's giving us a B+? Sports analysts are **** morons.
It does sound kind of dumb, but he's clearly referring to some kind of statistical projection. He feels it doesn't match with the eye test or his overall perception of Walter.
Sports analysts as a whole are morons, especially as they are steered more towards hot takes for engagement, but Givony is solid. He absolutely knows more about each and every prospect than any of us would even know about one. This is not SAS being put at a desk to say "I have never seen this man before in my life."
I rate givony’s honesty, but it does make one wonder how he came up with his spreadsheet formulas that rank players.
Of course, there’s more to life than the projections alone - the eye test + work ethic + character etc. Consider me curious as to what’s on his sheet and what’s rated where.
Regardless, in a flat draft we went in. I’m definitely content with that.
first of all this grade is by pelton
second he links his projections and how his projections work in the article
his stats based projections list
https://www.espn.com/nba/insider/story/_/id/40394709/nba-draft-2024-pelton-updated-top-30-prospects1 reed sheppard
2 donovan clingan
3 sarr
4 edey
5 furphy
6 jacoby walters
41 Jonathan Mogbo
46 Jamal Shead
https://www.espn.com/nba/insider/story/_/id/16235135/explaining-kevin-pelton-nba-draft-projection-systemits long written article but some points
my projections start with translating what players have done before with what they will do in the NBA for 14 core statistics: 2-point percentage; 3-point percentage; free throw percentage; offensive and defensive rebound percentage; assists; steals and fouls per 100 team plays; blocks per 100 2-point attempts; percentage of individual plays devoted to 2-point, 3-point and free throw attempts; turnovers; and usage rate.
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this process also adjusts for strength of schedule to put players who faced different levels of competition on a level playing field.
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Utilizing multiple seasons of data yields better projections than looking solely at the most recent season. In fact, for college players I've found that earlier seasons tend to project NBA performance better than more recent seasons because older prospects no longer have the same experience advantage in the NBA. So the player's most recent season is weighted two times, the season before that (if available) three times, and two seasons before that five times. The weights are opposite for international prospects, who haven't demonstrated the same pattern because they are playing against older opponents.
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I introduced consensus projections that also include the league's assessment of a prospect's talent
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