This year's roster in advanced stats

2,464 Views | 18 Replies | Last: 1 mo ago by calumnus
calumnus
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Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com
bearsandgiants
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This is great, and all makes sense. Add the inevitable ~0.25 "Madsen" factor into every player rating, and we're looking at 20+ wins.
eastcoastcal
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Thanks for sharing! Anyone know what a reasonable win total in the PAC generally equates to a tournament berth? Is it usually a little above 20 (total wins) and 11 or 12 in-conference, or are the last couple years not representative?
BeachedBear
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bearsandgiants said:

This is great, and all makes sense. Add the inevitable ~0.25 "Madsen" factor into every player rating, and we're looking at 20+ wins.
This is precisely what my Cal Math & Engineering degree came up with!!
bluehenbear
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Sunshine pump priming in progress
dimitrig
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calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.


GMP
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dimitrig said:

calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.





Respectfully, I'm not sure you understand this stat (which, disclaimer, is not exactly science). But if we accept these numbers as a thought experience, you don't seem to get it.

For example. You say, "If .100 is average, then Cal has 4 of them." No. We have 4 ABOVE average players. We have one who is worth better than TWO average players. That's, again in this thought experiment, like having six players on the court vs your opponent's five. If you had 5 Aimak's playing the whole game, you'd be projected to be undefeated. We have another player who is worth nearly 1.5 players. And another who is worth 1.25 players. We have another a bit above average and then a few just below average.

As another example, you calculated the average. But as I noted, and as the OP undoubtedly understood when he made his calculations, minutes are not even so an average of all 12 is not remotely informative. You need to weight the minutes to the players who will play the most. The top 3, barring injury, can be expected to play the bulk of the minutes for 3 of the 5 positions. The 4th through 7th the bulk of the minutes for the final two, plus some minutes when the top 3 need to sit.

I'm not going to do the math because OP already did so, and I'll trust his assumptions on minutes. Regardless, that is why having 4 above average players (including three well above average players) leads OP to conclude we'll have an above .500 record.
dimitrig
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GMP said:

dimitrig said:

calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.





Respectfully, I'm not sure you understand this stat (which, disclaimer, is not exactly science). But if we accept these numbers as a thought experience, you don't seem to get it.

For example. You say, "If .100 is average, then Cal has 4 of them." No. We have 4 ABOVE average players. We have one who is worth better than TWO average players. That's, again in this thought experiment, like having six players on the court vs your opponent's five. If you had 5 Aimak's playing the whole game, you'd be projected to be undefeated. We have another player who is worth nearly 1.5 players. And another who is worth 1.25 players. We have another a bit above average and then a few just below average.

As another example, you calculated the average. But as I noted, and as the OP undoubtedly understood when he made his calculations, minutes are not even so an average of all 12 is not remotely informative. You need to weight the minutes to the players who will play the most. The top 3, barring injury, can be expected to play the bulk of the minutes for 3 of the 5 positions. The 4th through 7th the bulk of the minutes for the final two, plus some minutes when the top 3 need to sit.

I'm not going to do the math because OP already did so, and I'll trust his assumptions on minutes. Regardless, that is why having 4 above average players (including three well above average players) leads OP to conclude we'll have an above .500 record.

Thanks for the explanation. Sort of.

To me "Where .100 is an average player" means the average player is .100.

So having 1 average and 8 below average players is not a good thing even though we have 3 above average players.

The stat is listed as "win share per 40 minutes" so it is already accounting for minutes played.

Now, if he said that an average starter is .100 then I agree that we are looking good as 4 of our 5 projected starters are above that figure.

You are correct that I don't understand the stat. I am just going by what was written.


calumnus
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dimitrig said:

GMP said:

dimitrig said:

calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.





Respectfully, I'm not sure you understand this stat (which, disclaimer, is not exactly science). But if we accept these numbers as a thought experience, you don't seem to get it.

For example. You say, "If .100 is average, then Cal has 4 of them." No. We have 4 ABOVE average players. We have one who is worth better than TWO average players. That's, again in this thought experiment, like having six players on the court vs your opponent's five. If you had 5 Aimak's playing the whole game, you'd be projected to be undefeated. We have another player who is worth nearly 1.5 players. And another who is worth 1.25 players. We have another a bit above average and then a few just below average.

As another example, you calculated the average. But as I noted, and as the OP undoubtedly understood when he made his calculations, minutes are not even so an average of all 12 is not remotely informative. You need to weight the minutes to the players who will play the most. The top 3, barring injury, can be expected to play the bulk of the minutes for 3 of the 5 positions. The 4th through 7th the bulk of the minutes for the final two, plus some minutes when the top 3 need to sit.

I'm not going to do the math because OP already did so, and I'll trust his assumptions on minutes. Regardless, that is why having 4 above average players (including three well above average players) leads OP to conclude we'll have an above .500 record.

Thanks for the explanation. Sort of.

To me "Where .100 is an average player" means the average player is .100.

So having 1 average and 8 below average players is not a good thing even though we have 3 above average players.

The stat is listed as "win share per 40 minutes" so it is already accounting for minutes played.

Now, if he said that an average starter is .100 then I agree that we are looking good as 4 of our 5 projected starters are above that figure.

You are correct that I don't understand the stat. I am just going by what was written.





The stat is "Win share per 40 minutes" there are 200 minutes to allocate per game. It is a weighted average, not a simple average. You don't play everyone equally. You give your best players at the 5 positions the most minutes, 30 or 35 and then your back ups the residual.

So if Aimaq can play 35, his win share per game is .208 x 35/40 = .182 and over an average 32 game schedule would give you 5.8 win share. You allocate minutes for your presumed starters and backups and then do the math. Adding up all your Win Shares for your win total.

That said, 14-18 is a completely reasonable estimate based on the above. I assumed a tight 8 man rotation, which may take some time to get to if at all. I do think, that based on what the players have done previously, we are not quite a Tournament team. Maybe NIT.

However, as I said, basketball is not baseball where individual performance is largely independent. Basketball can create tremendous synergies between the players. Coaches can create strategies that maximize the effectiveness of players. As an example, Steve Kerr was a .099 his 4 seasons with Cleveland, then a .172 his 5 seasons with the Bulls, then went back to being a .107 his next 4 seasons with the Spurs. Turns out sharing the backcourt with Michael Jordan in his prime, running the triangle, really helps your stats: lots of assists, lots of wide open threes. So it is quite possible that this collection of players all playing for Madsen for the first time together will greatly exceed the sum of their previous play. Or maybe not. Also, players can improve their individual skill.

So it is by no means determinative. It is just a way to get an early look at and analyze the team that we haven't seen yet, I think it is fun and informative, but feel free to ignore it if you don't.
dimitrig
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calumnus said:

dimitrig said:

GMP said:

dimitrig said:

calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.





Respectfully, I'm not sure you understand this stat (which, disclaimer, is not exactly science). But if we accept these numbers as a thought experience, you don't seem to get it.

For example. You say, "If .100 is average, then Cal has 4 of them." No. We have 4 ABOVE average players. We have one who is worth better than TWO average players. That's, again in this thought experiment, like having six players on the court vs your opponent's five. If you had 5 Aimak's playing the whole game, you'd be projected to be undefeated. We have another player who is worth nearly 1.5 players. And another who is worth 1.25 players. We have another a bit above average and then a few just below average.

As another example, you calculated the average. But as I noted, and as the OP undoubtedly understood when he made his calculations, minutes are not even so an average of all 12 is not remotely informative. You need to weight the minutes to the players who will play the most. The top 3, barring injury, can be expected to play the bulk of the minutes for 3 of the 5 positions. The 4th through 7th the bulk of the minutes for the final two, plus some minutes when the top 3 need to sit.

I'm not going to do the math because OP already did so, and I'll trust his assumptions on minutes. Regardless, that is why having 4 above average players (including three well above average players) leads OP to conclude we'll have an above .500 record.

Thanks for the explanation. Sort of.

To me "Where .100 is an average player" means the average player is .100.

So having 1 average and 8 below average players is not a good thing even though we have 3 above average players.

The stat is listed as "win share per 40 minutes" so it is already accounting for minutes played.

Now, if he said that an average starter is .100 then I agree that we are looking good as 4 of our 5 projected starters are above that figure.

You are correct that I don't understand the stat. I am just going by what was written.





The stat is "Win share per 40 minutes" there are 200 minutes to allocate per game. It is a weighted average, not a simple average. You don't play everyone equally. You give your best players at the 5 positions the most minutes, 30 or 35 and then your back ups the residual.

So if Aimaq can play 35, his win share per game is .208 x 35/40 = .182 and over an average 32 game schedule would give you 5.8 win share. You allocate minutes for your presumed starters and backups and then do the math. Adding up all your Win Shares for your win total.

That said, 14-18 is a completely reasonable estimate based on the above. I assumed a tight 8 man rotation, which may take some time to get to if at all. I do think, that based on what the players have done previously, we are not quite a Tournament team. Maybe NIT.

However, as I said, basketball is not baseball where individual performance is largely independent. Basketball can create tremendous synergies between the players. Coaches can create strategies that maximize the effectiveness of players. As an example, Steve Kerr was a .099 his 4 seasons with Cleveland, then a .172 his 5 seasons with the Bulls, then went back to being a .107 his next 4 seasons with the Spurs. Turns out sharing the backcourt with Michael Jordan in his prime, running the triangle, really helps your stats: lots of assists, lots of wide open threes. So it is quite possible that this collection of players all playing for Madsen for the first time together will greatly exceed the sum of their previous play. Or maybe not. Also, players can improve their individual skill.

So it is by no means determinative. It is just a way to get an early look at and analyze the team that we haven't seen yet, I think it is fun and informative, but feel free to ignore it if you don't.

This helps.

So if the average player is .100 and you play all 5 of them 40 minutes then you have .500 where .500 is the winning percentage?

If we take our top 5 and play them all the minutes then our winning % would be :

.208+.144+.123+.107+.086 = .668 = 21 wins?








calumnus
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dimitrig said:

calumnus said:

dimitrig said:

GMP said:

dimitrig said:

calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com


If 0.100 is an average player then Cal has only 4 of them. Wouldn't we expect a .500 team to have 12 such players or at least the average to be 0.100 instead of 0.72-ish?

Or if you mean 0.100 is average for a starter then aren't we still below average?

How do you figure we will be above .500 with that criteria especially with a tougher than average schedule?

I am going to turn your record around and predict 14-18 and I would very glad to have that after the last few seasons.





Respectfully, I'm not sure you understand this stat (which, disclaimer, is not exactly science). But if we accept these numbers as a thought experience, you don't seem to get it.

For example. You say, "If .100 is average, then Cal has 4 of them." No. We have 4 ABOVE average players. We have one who is worth better than TWO average players. That's, again in this thought experiment, like having six players on the court vs your opponent's five. If you had 5 Aimak's playing the whole game, you'd be projected to be undefeated. We have another player who is worth nearly 1.5 players. And another who is worth 1.25 players. We have another a bit above average and then a few just below average.

As another example, you calculated the average. But as I noted, and as the OP undoubtedly understood when he made his calculations, minutes are not even so an average of all 12 is not remotely informative. You need to weight the minutes to the players who will play the most. The top 3, barring injury, can be expected to play the bulk of the minutes for 3 of the 5 positions. The 4th through 7th the bulk of the minutes for the final two, plus some minutes when the top 3 need to sit.

I'm not going to do the math because OP already did so, and I'll trust his assumptions on minutes. Regardless, that is why having 4 above average players (including three well above average players) leads OP to conclude we'll have an above .500 record.

Thanks for the explanation. Sort of.

To me "Where .100 is an average player" means the average player is .100.

So having 1 average and 8 below average players is not a good thing even though we have 3 above average players.

The stat is listed as "win share per 40 minutes" so it is already accounting for minutes played.

Now, if he said that an average starter is .100 then I agree that we are looking good as 4 of our 5 projected starters are above that figure.

You are correct that I don't understand the stat. I am just going by what was written.





The stat is "Win share per 40 minutes" there are 200 minutes to allocate per game. It is a weighted average, not a simple average. You don't play everyone equally. You give your best players at the 5 positions the most minutes, 30 or 35 and then your back ups the residual.

So if Aimaq can play 35, his win share per game is .208 x 35/40 = .182 and over an average 32 game schedule would give you 5.8 win share. You allocate minutes for your presumed starters and backups and then do the math. Adding up all your Win Shares for your win total.

That said, 14-18 is a completely reasonable estimate based on the above. I assumed a tight 8 man rotation, which may take some time to get to if at all. I do think, that based on what the players have done previously, we are not quite a Tournament team. Maybe NIT.

However, as I said, basketball is not baseball where individual performance is largely independent. Basketball can create tremendous synergies between the players. Coaches can create strategies that maximize the effectiveness of players. As an example, Steve Kerr was a .099 his 4 seasons with Cleveland, then a .172 his 5 seasons with the Bulls, then went back to being a .107 his next 4 seasons with the Spurs. Turns out sharing the backcourt with Michael Jordan in his prime, running the triangle, really helps your stats: lots of assists, lots of wide open threes. So it is quite possible that this collection of players all playing for Madsen for the first time together will greatly exceed the sum of their previous play. Or maybe not. Also, players can improve their individual skill.

So it is by no means determinative. It is just a way to get an early look at and analyze the team that we haven't seen yet, I think it is fun and informative, but feel free to ignore it if you don't.

This helps.

So if the average player is .100 and you play all 5 of them 40 minutes then you have .500 where .500 is the winning percentage?

If we take our top 5 and play them all the minutes then our winning % would be :

.208+.144+.123+.107+.086 = .668 = 21 wins?




Exactly, that is the way it works in its most simple form.

However;

1. Our 5 best in WS per 40 may not be realistic by position (I assumed Newell at the 4 for example).

2. We cannot play our best players 40 minutes and expect them to maintain the same WS per 40. Madsen does go with short rotations, but that is 8 players, not 5.

3. Our most productive returning player statistically was Wren Robinson, a walk on. He did not play a lot last year despite his good play when in and despite injuries at PG (that we were constantly updated on), so now that we are deeper at guard I did not include him, even though, partly as he is our only pure point, I am rooting for him.
wifeisafurd
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calumnus said:

Here are the players with D1 experience listed by "win share per 40 minutes" in their most recent full year:

1. Aimaq.208
2. Tyson .144
3. Kennedy .123
4. Cone .107
5. Meadows .086
6. Robinson .085
7. Celestine .075
8. Askew .039
9. Newell .030
10. Okafor .020
11. Bowser .006
12. Larson -.063

Where .100 is an average player so 5 average players would go ,500 against an average schedule.

The above is just presented for fun and discussion, to try to get a better handle on the team. Obviously the above has to be taken with a lot of caveats. Basketball is not baseball, good teams, good coaches make individual players better. Fox made everyone worse. There will also be freshmen who could become contributors.

That said, allocating 200 minutes among a possible 8 above I come up with .569 winning percentage versus an average schedule.

Based on a 32 game schedule we would go 18-14

Again, just an indicator, I think we could be significantly better than that, Madsen will make everyone better, but I also think our schedule will be significantly tougher than "average."

Will be fun and a huge upgrade from Fox in any case.

*WS per 40 from SportsReference.com
well done! thanks
calumnus
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Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.
bearsandgiants
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calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
Bobodeluxe
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bearsandgiants said:

calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
CoB?
concernedparent
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bearsandgiants said:

calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
The post is just for fun. Win shares are pretty useless for projecting how a bunch of transfers from very different teams might perform together. Some things about WS and WS40: the more wins a team has, the more winshares can be allocated to players on that team; it also doesn't account for level of competition. As a tool, it is probably best for comparing value across players on the same team. For example if you look at this year's stats, it ranks in order of importance to the team, Tyson, Fardaws, Celestine, Kennedy, Cone; which aligns with what we see with our eyes.

Fardaws' .208 is his last season at Utah Valley. Utah Valley won a lot of games (a lot of that was Fardaws of course, but he likely had a good team relative to the competition) and did not play a particularly hard schedule. There's no way you should project him to repeat that on our team. If he put up .208 WS/40 in a full season with us, he'd probably be Pac 12 player of the year because it would mean he's either putting up good stats on a very good team (getting a healthy portion of the high number of winshares allocated amongst the team), or he's putting up Wilt-like numbers (allocated a bigger proportion of the team's winshares).
01Bear
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concernedparent said:

bearsandgiants said:

calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
The post is just for fun. Win shares are pretty useless for projecting how a bunch of transfers from very different teams might perform together. Some things about WS and WS40: the more wins a team has, the more winshares can be allocated to players on that team; it also doesn't account for level of competition. As a tool, it is probably best for comparing value across players on the same team. For example if you look at this year's stats, it ranks in order of importance to the team, Tyson, Fardaws, Celestine, Kennedy, Cone; which aligns with what we see with our eyes.

Fardaws' .208 is his last season at Utah Valley. Utah Valley won a lot of games (a lot of that was Fardaws of course, but he likely had a good team relative to the competition) and did not play a particularly hard schedule. There's no way you should project him to repeat that on our team. If he put up .208 WS/40 in a full season with us, he'd probably be Pac 12 player of the year because it would mean he's either putting up good stats on a very good team (getting a healthy portion of the high number of winshares allocated amongst the team), or he's putting up Wilt-like numbers (allocated a bigger proportion of the team's winshares).

Agreed.

Also, Tyson was held out of a number of games at the start of the season. Had he played, Cal probably would've won them.
stu
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01Bear said:

concernedparent said:

bearsandgiants said:

calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
The post is just for fun. Win shares are pretty useless for projecting how a bunch of transfers from very different teams might perform together. Some things about WS and WS40: the more wins a team has, the more winshares can be allocated to players on that team; it also doesn't account for level of competition. As a tool, it is probably best for comparing value across players on the same team. For example if you look at this year's stats, it ranks in order of importance to the team, Tyson, Fardaws, Celestine, Kennedy, Cone; which aligns with what we see with our eyes.

Fardaws' .208 is his last season at Utah Valley. Utah Valley won a lot of games (a lot of that was Fardaws of course, but he likely had a good team relative to the competition) and did not play a particularly hard schedule. There's no way you should project him to repeat that on our team. If he put up .208 WS/40 in a full season with us, he'd probably be Pac 12 player of the year because it would mean he's either putting up good stats on a very good team (getting a healthy portion of the high number of winshares allocated amongst the team), or he's putting up Wilt-like numbers (allocated a bigger proportion of the team's winshares).

Agreed.

Also, Tyson was held out of a number of games at the start of the season. Had he played, Cal probably would've won them.
Kennedy missed 7 games, Tyson missed just 1. But I agree with Kennedy we would have won several more.
calumnus
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stu said:

01Bear said:

concernedparent said:

bearsandgiants said:

calumnus said:

Dimitrig predicted 14-18 and we went 13-19.

Kudos.

Can't wait until we see who will be on next year's roster.


The forecast was for 18-14, according to the post. So it looks like we significantly underperformed.
The post is just for fun. Win shares are pretty useless for projecting how a bunch of transfers from very different teams might perform together. Some things about WS and WS40: the more wins a team has, the more winshares can be allocated to players on that team; it also doesn't account for level of competition. As a tool, it is probably best for comparing value across players on the same team. For example if you look at this year's stats, it ranks in order of importance to the team, Tyson, Fardaws, Celestine, Kennedy, Cone; which aligns with what we see with our eyes.

Fardaws' .208 is his last season at Utah Valley. Utah Valley won a lot of games (a lot of that was Fardaws of course, but he likely had a good team relative to the competition) and did not play a particularly hard schedule. There's no way you should project him to repeat that on our team. If he put up .208 WS/40 in a full season with us, he'd probably be Pac 12 player of the year because it would mean he's either putting up good stats on a very good team (getting a healthy portion of the high number of winshares allocated amongst the team), or he's putting up Wilt-like numbers (allocated a bigger proportion of the team's winshares).

Agreed.

Also, Tyson was held out of a number of games at the start of the season. Had he played, Cal probably would've won them.
Kennedy missed 7 games, Tyson missed just 1. But I agree with Kennedy we would have won several more.


And we never got Meadows who was projected to start, plus the above included Robinson as a top 8, but he barely played. And as has been pointed out, we did not play an average schedule. All together 14-18 was reasonable which I said said at the time.

I also hoped there would be a "Madsen effect" but we didn't see one.
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