Projected Top 100 Scoring transfers

[sittingon50]

(courtesy of the BYU board)

http://www.si.com/college-basketball/2016/10/13/marcus-foster-austin-nichols-top-100-transfers

[seacatfan]

Huh. It claims they ran projections, but it seems more like they pulled numbers out of their butts. Some high scorers from previous stops they have their average cut in half, some non-productive guys they have doubling or tripling their scoring averages. Doesn't really seem to be based on much. I might put my money on Marcus Foster. I saw that guy light it up his Fr. year at K-State, he slumped a bit as a soph.

[MontanaCoyote]

Huh. It claims they ran projections, but it seems more like they pulled numbers out of their butts. Some high scorers from previous stops they have their average cut in half, some non-productive guys they have doubling or tripling their scoring averages. Doesn't really seem to be based on much. I might put my money on Marcus Foster. I saw that guy light it up his Fr. year at K-State, he slumped a bit as a soph.

Maybe so. Still 3 ZAG's in top 20. I'll take it!

[WallaWallaZag]

Huh. It claims they ran projections, but it seems more like they pulled numbers out of their butts. Some high scorers from previous stops they have their average cut in half, some non-productive guys they have doubling or tripling their scoring averages. Doesn't really seem to be based on much.

have no idea what their methodology is, but what you are questioning is actually perfectly reasonable...high scorers from small schools moving on to big time programs will likely have their averages drop, and bench/role players from big schools moving in the other direction will likely see the inverse.

what's interesting is that gonzaga for all the transfers has yet to pick up one of these small school stars...came close the past two years with lee last year and pryor this year...not sure about pryor, but lee would have made a huge difference.

[seacatfan]

have no idea what their methodology is, but what you are questioning is actually perfectly reasonable...high scorers from small schools moving on to big time programs will likely have their averages drop, and bench/role players from big schools moving in the other direction will likely see the inverse.

That's way oversimplified. Quite a few of them look like more or less lateral moves, but still some change in scoring numbers. For one thing they are absolutely guessing about how much bigger/smaller of a role or how many more or less shot opportunities these various players are gonna get. How can there possibly be an accurate methodology to determine that? There isn't. It's guesswork.

I'll highlight a few. Canyon Berry is moving from a smaller school to a bigger school, but he averaged almost 20 points/game at Charleston. The dude is a scorer. They have him at 10 ppg at Florida. That's a big decrease. I don't think Florida is exactly bringing back a bunch of studs from last year. Why wouldn't a guy that has proven he can score the rock average more than that?

Anton Gill averaged 2.5 ppg at Louisville. I don't care how few minutes per game he got, that's not productive by any definition. They have him at 9.8 ppg at Nebraska. Based on what? Nebraska is Big 10, it's not like it's a significant change in competition level from the ACC.

How about Katin Reinhardt, 11.4 at USC last year. Projected as 8.5 at Marquette. So...USC was a better team than Marquette last year, Marquette lost their leading scorer from last year, Reinhardt's a gunner, but his scoring average is gonna drop 3 ppg? Based on what?

Whatever their methodology is, I'm not buying it.

[WallaWallaZag]

For one thing they are absolutely guessing about how much bigger/smaller of a role or how many more or less shot opportunities these various players are gonna get. How can there possibly be an accurate methodology to determine that? There isn't. It's guesswork.

with the amount of data and how advanced statistical analysis is these days, i would say a model could easily be created that absolutely isn't guesswork...whether or not they actually did this or did it well is a different story.

[seacatfan]

with the amount of data and how advanced statistical analysis is these days, i would say a model could easily be created that absolutely isn't guesswork...whether or not they actually did this or did it well is a different story.

Okay, take the Zags for example. Lost 4 starters from last year, including 2 bigtime scorers in Wiltjer and Sabonis. Get back one double figure scoring starter from last year in Perkins, plus Karnowski who has averaged double figures in previous seasons. Add 3 transfers from Big 5 conference schools who all averaged double figures previously. Then you've got a couple touted freshmen, plus some freshmen who are wildcards due to playing overseas and not having as much scouting done with them. And then a few other holdovers who didn't score much last year, but maybe potentially could up their average significantly. And there are metrics somebody can run that can predict who is going to be taking the shots and scoring for the Zags? I simply don't believe it. How can you predict the unpredictable? Zags might have 6 guys average between 10-12 points, or they might have a couple average around 14 or 15 and everybody else scoring less. There's no way to know until the season starts. There are too few givens, too many new pieces being added at once.

[WallaWallaZag]

Okay, take the Zags for example. Lost 4 starters from last year, including 2 bigtime scorers in Wiltjer and Sabonis. Get back one double figure scoring starter from last year in Perkins, plus Karnowski who has averaged double figures in previous seasons. Add 3 transfers from Big 5 conference schools who all averaged double figures previously. Then you've got a couple touted freshmen, plus some freshmen who are wildcards due to playing overseas and not having as much scouting done with them. And then a few other holdovers who didn't score much last year, but maybe potentially could up their average significantly. And there are metrics somebody can run that can predict who is going to be taking the shots and scoring for the Zags? I simply don't believe it. How can you predict the unpredictable? Zags might have 6 guys average between 10-12 points, or they might have a couple average around 14 or 15 and everybody else scoring less. There's no way to know until the season starts. There are too few givens, too many new pieces being added at once.

i'm no sabermetric pro, but i think one could project the returning zags even with the transfers because nowadays you know their usage rates, personal and team efficiency stats/rankings, and the tempo numbers of the teams they were on previously...enough data to draw a reasonable conclusion on the numbers that they might produce.

high schoolers and internationals obviously don't have much data, so accuracy with them probably isn't going to be particularly high, but i would think there's at least a decent correlation between an incoming freshman's stats + composite recruiting ranking combined with the known scoring returning and incoming(transfers) to get a projected contribution...i'm guessing the hardest part of freshmen is trying to adjust their prior stats for level of competition (something relatively easy to do with transfers, even from small to big conferences and vice versa).

[seacatfan]

i'm no sabermetric pro, but i think one could project the returning zags even with the transfers because nowadays you know their usage rates, personal and team efficiency stats/rankings, and the tempo numbers of the teams they were on previously...enough data to draw a reasonable conclusion on the numbers that they might produce.

high schoolers and internationals obviously don't have much data, so accuracy with them probably isn't going to be particularly high, but i would think there's at least a decent correlation between an incoming freshman's stats + composite recruiting ranking combined with the known scoring returning and incoming(transfers) to get a projected contribution...i'm guessing the hardest part of freshmen is trying to adjust their prior stats for level of competition (something relatively easy to do with transfers, even from small to big conferences and vice versa).

Would those metrics have accurately predicted that Pangos and Bell would both have career low scoring averages their Sr. year, that Wesley's scoring average would nearly be cut in half from his previous year at USC and that Wiltjer's average would nearly double from his previous season at Kentucky? I seriously doubt it.

Trying to extrapolate a player's previous usage rate or efficiency numbers when he transfers is kinda dicey, since it's a different system and he could be used in an entirely different manner. And if he has better talent surrounding him his efficiency might increase due to less defensive pressure facing him. Too many variables. Computer models aren't infallible (for proof of that look at weather forecasts).

[NumberCruncher]

Interesting stuff. Thanks for posting, 50.

Their methodology looks pretty good to me. I also agree with seacatfan in that there are too many variables to be perfectly accurate. But it still seems worth trying. I've noted their list and intend to check how they did after the season.

Their projections for Nigel, J-Mat and J-Wil seem very reasonable. Three Zags in the top 20 is pretty cool.

[WallaWallaZag]

i agree completely that college basketball is too unpredictable with too many variables to be able to accurately project...especially compared to say the nba...i was objecting to seacat's suggestion that it was all guesswork and pulling from one's rear end when in fact a decent model wouldn't be too difficult to create if you had the resources.

[WallaWallaZag]

Would those metrics have accurately predicted that Pangos and Bell would both have career low scoring averages their Sr. year, that Wesley's scoring average would nearly be cut in half from his previous year at USC and that Wiltjer's average would nearly double from his previous season at Kentucky? I seriously doubt it.

i actually think a well constructed system might have come close with pangos, bell, and especially wesley (his per 40 scoring only dropped from 20.5 to 15.9 -- very reasonable and seemingly projectable going from a poor usc team to strong zag team)...but probably not wiltjer. doesn't mean the projection system is flawed or based on faulty data, just that no model can account for the power of the olynyk clinik...doesn't invalidate the model...there are always going to outliers in any projection system even if you could account for all the variables. who knows, with another 10 years of data maybe a system could accurately predict the effect of the olynyk clinik for highly skilled white guys who need to work on their body =).

[Zagdawg]

Gonzaga Guru @ZagsGuru 6m6 minutes ago
Nigel Williams-Goss & @JordanMathews22 are top 10 impact transfers. Backcourt scoring shouldnt be an issue @ Gonzaga

10 impact transfers to watch for this college basketball season

"Nigel Williams-Goss, Gonzaga
After scoring 996 points and tossing out 217 assists in two seasons at Washington, Nigel Williams-Goss opted to seek a new home. Now at Gonzaga, Williams-Goss will be asked to produce and fill a couple of different roles for Mark Few’s team. The 6-3 guard is versatile and can facilitate, which is evident by his 5.9 assists a game as a sophomore in the Pac-12, but he’s also a more-than-capable scorer. The Bulldogs plan to use two primary ball handlers quite often and Williams-Goss should excel in that setting."

"Jordan Mathews, Gonzaga
After a very productive three seasons at California, Jordan Mathews opted to end his college career at Gonzaga. As mentioned above, the Bulldogs plan to play a variety of guards, plus they lost their top three scorers from last season, so Mathews is sure to be a big part of their attack.

Mathews averaged 13.6 points a sophomore and 13.5 as a junior and proved to be a major threat from 3-point range, averaging a combined 42.7-percent from there the last two seasons. He will surely help Few in the scoring department."

[seacatfan]

I'm glad you made a reference to Olynk, Wallawalla, that's exactly the kind of unpredictability I'm going on and on about. New Mexico had a stretch 4 a few years ago, did pretty much nothing for 3 years, then exploded into a 20 ppg scorer his Sr. year (had to google it--Cameron Bairstow). I've seen that quantum leap plenty enough times over the years to know that players don't necessarily follow a linear progression during their college career. It might be a bit of an exception, but it happens often enough. How about Kemba Walker? Good, productive player for 3 years, then became an unstoppable scorer who carried his team to a National Championship his Sr. year. Jason Terry at Arizona was a complimentary player for 3 years, then 20+ ppg his Sr. year. Khalid Reeves was similar at UA.

[seacatfan]

i agree completely that college basketball is too unpredictable with too many variables to be able to accurately project...especially compared to say the nba...i was objecting to seacat's suggestion that it was all guesswork and pulling from one's rear end when in fact a decent model wouldn't be too difficult to create if you had the resources.

fair enough