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This is my first time to actually record the draft results. I can go back and record but the data won't be accurate. I was also under the impression that drafts would be better the higher up you advance but I figured it would not be that dramatic of an increase in talent. I think the higher up you advance, however, the less significant the draft becomes as your rely more and more on the transfer list.

My theory is that lower level teams rely on the draft early as well as purchasing cheap trainable players off the transfer list. As the players progress and the teams progress along as well, then they sell them high in hopes of acquiring better talent that allows them to compete at their new levels.

With each draft consisting of 48 players, that would give you 480 subjects to study. Before you begin your study though, you need to clarify your objective of this study. After pulling the data from this draft, I've concluded that I really did not gather anything more than facts and at this point I have no idea why I am studying this data other than the fact that I was interested in the actual results of our draft and wondering who pulled the best draft class in my division.

I do agree that you would need to gather data from quite a few of the major countries and quite a few minor countries. Then I'd compare the two samples of data with each other and see if the major countries are pulling strong draft classes than the minor countries. That would be something I'm curious in.

As far as standard deviation, I only learned about it during my years as a maintenance analyst for the USAF. I've been out for nearly 6 years now so I am not current with any changes in statistical analysis. The only thing standard deviation does is determine the average deviation between data. In this case, I was comparing the salaries in the draft class and trying to determine the relationship between their actual draft position (which I've determined that draft position has no effect on the actual salary as they are apparently pre-determined ... which I'm pretty sure had already been figured out by a lot of others here).

To calculate standard deviation, you'll need no less than 30 samples. Thankfully there are 48 samples in a draft class. To calculate the Standard Deviation in Excel, it's actually quite simple:

=stdev(selection of cells) <--- Only 1 column, cannot be a group of cells
=stdevp(selection of cells) <--- Only 1 column, cannot be a group of cells

The two numbers will have a slight variance but it won't be by much. Honestly, I have a hard time determining when I should use STDEVP and STDEV.

To determine the Z-Score, subtract an individual sample from the average and divide by the standard deviation. To understand the importance of the Z-Score, I recommend reading up on Wikipedia.

first leagues don't get better draft, the bb said it and i could say it too ;)

because i normally i check 10-20 draft in our country in search for new NT talents.

My theory is that lower level teams rely on the draft early as well as purchasing cheap trainable players off the transfer list. As the players progress and the teams progress along as well, then they sell them high in hopes of acquiring better talent that allows them to compete at their new levels.

I wanted to clarify my theory.

All draft classes are roughly the same talent pool across the board. You will not find a better draft class in Division NBBA than you would in Division II just because Division NBBA is a higher division. Two examples:

Ice Store BC, NBBA (Season 10 Champs)
Total Salary: $461,588
Avg Salary: $28,849
High: $69,213
Low: $2,320
Rookies: $3037 (#16 Pick), $2030 (#32 Pick), $2362 (#48 Pick)

My theory is that teams in the higher leagues have little use for their draft picks outside of training purposes. The Ice Storm BC in the NBBA League have 9 of 16 players with five-digit salaries, ranging from $69,213 to $27,339. The next player to fall below that range is sitting at $7,165/week. With 9 players (1 being sold off) hitting those high salaries, draft picks serve little use outside of playing scrimmages so they receive training so they can be shipped off later.

Dangerous Viperz, USA Div V.125 (Season 10 Champs, promoted to Div IV.63)
Total Salary: $79,953
Avg Salary: $3,476
High: $5,369
Low: $1,650
Rookies: $5028 (#16), $3011 (#32 Pick), $3038 (#48 Pick)

The Viperz managed to luck out with some of the best picks in their draft class. However, notice that their draft picks are on the same level as their average salary. My theory proposes that while they may be active participants on the transfer list, when it comes to a lower leagues draft, they are pretty much receiving younger players that are on the same level playing field as their current players.

The higher the league, the less likely you'll keep those players you draft unless you plan on training them. Therefore, I theorize that the transfer list is their best friend in terms of keeping their team competitive because it will take several seasons for a rookie to be on the same playing field as that team's current group of stars. Therefore, the only reason they should/would keep a rookie is if they are good enough for training purposes so that they can later sell them for high profit so they can boost their bank account for either hitting the transfer list, purchasing cheaper staff members, upgrading arena, etc.

Last edited by kaygdanimal at 12/16/2009 10:19:24 AM

how do you guys look this up i cant even find this years draft anyplace , i was able to break down the order i wanted my picks before the draft but i cant find the draft anyplace


Rusty

league site, and the drop down menu in the top there should be a point draft.

Your league > Draft History (in the drop down list).

Just for say that this guy: http://www.buzzerbeater.com/player/11772141/overview.aspx was one of the best rookies in the draft this season

Nice player, wonder if he has some inside skills too at that height he is a little short to train as a pure big man but would be perfect height for SF training.