NormalizedDB Best All Time Players

arod23 · 04-30-2005, 03:48 PM

Ankit and I have created a DB of the best all time players. But, unlike other databases, all players stats have been normalized to a league standard, making cross-era simulations more realistic.

The DB should be available on Joe Rock's Download Center shortly: http://www.ootpdownloadcenter.com/

From the readme file:

Arod23 NormDB-v10
by Ankit and Arod23

Version 1.0
Last revision: 4/30/2005

OVERVIEW

This database includes the best players of all time. All players' statistics have been "normalized" to the same environment in order to allow for more accurate simulations using players from across different eras. In other words, deadball era batters hit homers and deadball pitchers give up homers. Modern day pitchers with ERAs inflated by playing in higher HR compare more favorably with low run environment counterparts.

A more detailed explanation follows, but in short:
All player seasons have been translated to a neutral park in a standardized league, that scores 4.5 team runs per game, with a .260 batting average, .330 on base average, and .420 slugging average, making for a nice even .750 OPS.

Players have been imported based on their normalized career totals. These figures have then been recalculated based on 500 AB for hitters and 250 IP for pitchers for ease of comparison. Note, this does not impact the simulation in any way, as OOTP is only concerned about ratios not actual totals. That is, there is no difference in OOTP's Power Rating in a player with 10 HRs in 150 ABs and a player with 40 HRs in 600 ABs.

Players fielding stats are based on the positions played during the course of their career. However, range and arm ratings are randomly assigned by OOTP.

PLAYER EXAMPLES

Addie Joss played in the deadball era, holds the 3rd lowest career ERA of all time, dominates cross-era simulations. Active star Clemens with a career ERA that doesn't rank in the top-50 all time, clear hall of famer, yet he gives up 7x more HRs in cross-era simulations. When normalized Clemens numbers look better than Joss'.

HTML Code:

Addie Joss 1902-1910
Played in the deadball era, 3rd lowest career ERA of all time
		ERA	H/9	HR/9	BB/9	SO/9	
Actual		1.89	7.3	0.1	1.4	3.6
Normalized	3.60	8.4	0.9	1.5	5.3

HTML Code:

Roger Clemens 1984-2004
		ERA	H/9	HR/9	BB/9	SO/9	
Actual		3.18	7.7	0.7	2.9	8.6
Normalized	2.74	7.1	0.6	2.4	9.1

Ty Cobb average falls a bit, but still a very high career average, yet he benefits from getting credited with some long balls, nearly hitting 500 over his career.

HTML Code:

Ty Cobb 1905-1928
		BA	OBA	SLG	OPS	HR	AB/HR
Actual		.366	.433	.512	.945	117	97.7
Normalized	.352	.420	.584	1.004	484	25.1

Hornsby had some deadball years as well as some years when the run environment was higher. His average suffers but his power increases, although not to the same extent as a player like Cobb.

HTML Code:

Rogers Hornsby 1915-1937
		BA	OBA	SLG	OPS	HR	AB/HR
Actual		.358	.434	.577	1.011	301	27.2
Normalized	.328	.415	.606	1.021	604	14.1

As great a player as Mantle was, his actual stats sometimes fall short of other greats because he played many years in a lower run environment. His average is now over .300 and he actually gets credit for another 85 HRs

HTML Code:

Mickey Mantle 1951-1968
		BA	OBA	SLG	OPS	HR	AB/HR
Actual		.298	.421	.557	.978	536	15.1
Normalized	.314	.427	.602	1.029	621	13.1

As dominant as Bonds is today, he is even better normalized. Why? He has played in a pitcher's park and still dominants his league, a league in a relatively high run era.

HTML Code:

Barry Bonds 1986-2004
		BA	OBA	SLG	OPS	HR	AB/HR
Actual		.300	.443	.611	1.054	703	12.9
Normalized	.312	.453	.644	1.097	774	11.6

Babe Ruth dominated the game by such an extreme that all normalization procedures have trouble dealing with him. Since he hit more HRs than some teams, in other normalizations, his annual HRs can exceed 100. In these calculations, Ruth doesn't hit more than 69 homers in any normalized year, although he does hit 60 or more seven times.

HTML Code:

Babe Ruth
		BA	OBA	SLG	OPS	HR	AB/HR
Actual		.342	.474	.690	1.164	714	11.8
Normalized	.330	.461	.702	1.163	932	9.4

LEAGUE SETUP

The players have already been imported into a league file. The file contains 8 teams, split into 2 leagues of 4 teams. The schedule is set for 162 games. All players have been set as rookies in year 1901 and are available for drafting. Obviously, you may modify the league structure as you fit, given the number of players that are available. The league settings will produce a close to modern day league, slightly better batting averages and less homers, but you should run test sims and adjust to your liking.

All current ratings have been set so they match talent ratings, so everyone initally performs as dictated by their stats. (For some reason, OOTP does have some disparities between actual rating and talent ratings even when each season in a career is identical). L/R splits have been included but they have been adjusted to more realistic, less extreme ratings than OOTP defaults. Contact, Eye, Avoid K's include L/R splits, but Gap and Power are not split by L/R. Lastly, pitcher L/R splits have been removed since these are accounted for in the hitter's ratings (otherwise it seems like we would be double counting).

HOW WE CHOSE THE PLAYERS

We began with Bill James' New Historical Abstract. Per James' all-time lists, we included:
1) The top-100 players of all time, any position
2) The top-100 pitchers
3) At least the top-25 players at every position: C, 1b, 2b, 3b, SS, LF, CF, RF
4) Additional players:
a) when normalized would be competitive with the top players, e.g., there is no need to include the 80th best SS of all time because he won't be used as a DH or PH, and his stats don't even come close to the 300th best OF
b) who are commonly known as greats; part of the fun of a database like this is to see how your favorite players compare
c) who are active but may have ranked low or not at all on James' lists because their career hasn't been long enough yet, e.g., If Albert Pujols stopped playing today, he's not getting into the Hall of Fame, but statistically, his first four years are up there with the best ever
d) who are active or played recently, viewed as "stars" but might not be considered one of the best of all time; again part of the fun is playing with your favorite players
5) Pre and early 1900s players whose normalized stats compare favorably with the top players

Invariably, we left someone's favorite out, but we hope you will find that we have compiled a comprehensive list of players. And, consider this version 1.0, so we can always update it later.

NORMALIZATION METHOD

Although we put this database together, the underlying statistical work is not ours and should be properly credited. This normalized database was compiled using Baseball Prospectus' Davenport Translations (http://www.baseballprospectus.com/dt/) developed by Clay Davenport.

Normalizing baseball statistics across history is arguably one of the most difficult exercises one can undertake in both computational complexity and philosophy. While there are several approaches, we feel that Clay Davenport has done the most comprehensive work. Basically, he has considered everything.

For those interested, here is a summary of what is accounted for in his translations (summarized from his own explanations):

- All player seasons have been translated to a neutral park in a standardized league:
Batting: .260 batting average, .330 on base average, and .420 slugging average, making for a nice even .750 OPS
Pitching: 4.50 ERA, 9.0 H/9, 1.0 HR/9, 3.0 BB/9, 6.0 SO/9

1) Park Adjustment

An adjustment made to account for the fact that some parks are easier to hit in than average, giving an advantage (in raw statistical terms) to hitters who play for that team. Park factors are always made relative to a league average of 1.00. The park adjustments in the BP are made only on the park factor for runs, averaged over five years.

2) Team Hitting Adjustment

An adjustment made for hitters, to account for not having to face their own pitchers. Using pitching stats, (league R * pf - team R), divided by (league IP - team IP), divided by park-adjusted league runs per inning.

3) Team Pitching Adjustment

An adjustment made for pitchers, to account for not having to face their own team's batters. Using batting stats, (league runs * pf - team runs), divided by (league PA - team PA), divided by league runs per plate appearance * pf.

4) Adjusted for season/league offense level

Corrections have been made for team's hitting or pitching level and the player's home park. The numbers have also been win-adjusted; this is equivalent to a correction for league offensive level.

5) League Difficulty Adjustment

Each league has been given a difficulty level, based on the performance of players in that league compared to the same players' performance in other seasons. The reference difficulty level was defined by the trend line of the National League from 1947 to 2002, and extended backwards to 1871. The difficulty adjustment is the ratio between the actual difficulty level and the reference level.

6) Adjustments have been made for pre-homer times

In the deadball era, doubles and triples were power. A player who had a lot of 2b and 3b in that environment would almost certainly hit a lot of home runs in a modern environment, e.g., Sam Crawford's 312 triples turn into home runs, and he ends up with 575 for his career. But that isn't always true; thanks to his speed, Ty Cobb ends up keeping a lot more of his triples, and even though he emerges as a 20-25 HR a year guy, he keeps a high average (.350) and daring baserunning (consistent double-digit triples, 50+ stolen bases).

Note: Since we compilied this database, the Davenport Translation's have changed slightly, so the figures in this DB won't exactly match. Most are within one point of batting average or 1/100th of ERA, so the differences do not impact anything.

JoeRockEHF · 04-30-2005, 06:21 PM

I have the file all set to go at the Download Center in the Rosters section. Thanks!

khucke · 05-02-2005, 02:16 AM

Very interesting project indeed! One thing I`d like to know : how did you translate the normalized stats into ratings? I know there is a utility to translate ratings into stats. Did you use that one backwards? And how did you assign potential ratings? Did you take a player`s best season for that?

rem · 05-02-2005, 02:28 AM

Looks awesome man, nice work!

Johnny99 · 05-02-2005, 09:02 AM

Is there any way to pluck indiv. players from this league into another league? If it was a database like Ankits, I know what to do, but here?

arod23 · 05-02-2005, 09:36 AM

Quote:

Originally Posted by khucke

Very interesting project indeed! One thing I`d like to know : how did you translate the normalized stats into ratings? I know there is a utility to translate ratings into stats. Did you use that one backwards? And how did you assign potential ratings? Did you take a player`s best season for that?

OOTP translates the stats into ratings, nothing different for this DB. For talent ratings, they are based on career figures, so we had to set up the initial database with 10 identical seasons based on each players career normalized stats. The talent and actual ratings should have been about the same, but OOTP doesn't always seem to do that. So, we simply modified the ratings so that all players started out on equal footing, that is, no increases or decreases in talent in their rookie year. We did this simply to avoid any player have an advantage or disadvantage over their actual stats, e.g., drafting a hitter with huge potential despite lower initial ratings. We wanted all the players to import based on their career stats not some random anomoly.

arod23 · 05-02-2005, 09:38 AM

Quote:

Originally Posted by Johnny99

Is there any way to pluck indiv. players from this league into another league? If it was a database like Ankits, I know what to do, but here?

I think you can use one of Pierre's utility to move players between leagues. I haven't done that in awhile, so not sure. Although, I am not sure why you would take players from here to play in another league. Unless you have a league of players with normalized stats, taking players from here would be like apples and oranges. There are several other DBs of players based on their real stats.

Johnny99 · 05-02-2005, 09:50 AM

Quote:

Originally Posted by arod23

I think you can use one of Pierre's utility to move players between leagues. I haven't done that in awhile, so not sure. Although, I am not sure why you would take players from here to play in another league. Unless you have a league of players with normalized stats, taking players from here would be like apples and oranges. There are several other DBs of players based on their real stats.

Actually, I like running a fictional league and bringing in real players as I see fit. Your league looks great, but if I'm not mistaken, it only has about twenty years of life in it. I like to run long term universes.

arod23 · 05-02-2005, 10:23 AM

Quote:

Originally Posted by Johnny99

Actually, I like running a fictional league and bringing in real players as I see fit. Your league looks great, but if I'm not mistaken, it only has about twenty years of life in it. I like to run long term universes.

You are correct, since there are limited players, there is no draft, so the league can last about 20 years, maybe more if you adjust the aging factor (?). In fact, that is one of the reasons why we have it set up for 8 total teams. We were really scraping the barrel to find this many. (If you have read James' Abstract, most people haven't even heard of the players ranked after 50 by position) There may be enough players to handle a few more teams, but not really enough stars to support having a rookie draft. If you cut down the league to 4 total teams, then you could hold some players in reserve for a draft but that may only add 10+ years to it. I have created a random rookie year file for draft purposes before and could do so with this DB, if there is enough interest.

Some friends and I have been playing 10-yr leagues with the same DB over and over. A DB of all time stars based on actual career stats. After each season, we claim our few "keepers" then throw everyone else back in the draft, so we get some movement. After 10 seasons, we redraft from the original file. It has been interesting to see who the stars are, b/c of OOTPs randomness in talent changes, there are always several players that become stars, and sooooo many pitchers that don't develop. It is fun to compare the 10yr results, see who the hall of famers are each league, and about half of the stars change.

targy · 05-08-2005, 12:18 AM

How would you do a career league, would you just run an amateur draft every year

arod23 · 05-08-2005, 09:34 PM

Quote:

Originally Posted by targy

How would you do a career league, would you just run an amateur draft every year

We have every player entering in 1901 at their rookie age, so the only draft you would hold would be in the first year. If you hold an amateur draft after the first season, only fictional players would come in. Otherwise, you could release players each year and redraft.

If you wanted to decrease the number of teams, you could hold out some players for entry in later years (have to edit the database), but the number of amateur drafts you could hold would depend on the size of your initial rosters.

rasnell · 05-09-2005, 12:34 PM

I must be missing something. The file is only 375 kb on Joe Rock and, when I open the league file, there are no players on any of the rosters. Most other league files at the download center are over 1 meg. What am I missing?

arod23 · 05-09-2005, 01:15 PM

Quote:

Originally Posted by rasnell

I must be missing something. The file is only 375 kb on Joe Rock and, when I open the league file, there are no players on any of the rosters. Most other league files at the download center are over 1 meg. What am I missing?

The file on Joe Rock's site is a zip file. Still, the files should be smaller than a full league file since there are less total players in the DB, supporting 8 teams rather than say 30. You are also correct that there are no players on any rosters. The lg file is set up with all players in the free agent pool and ready for a fantasy draft (or you can just have the computer draft to fill the rosters). It didn't make sense for us to fill up the rosters since each user's preferences would be different.

You should customize the lg file as you see fit. We have provided the players and a 162 game schedule. As with any custom league, you should feel free to change team city's, nicknames, ballparks, league settings, etc to your liking.

rasnell · 05-10-2005, 04:56 AM

There are no players on the free agent list, either. Do I have to do something to import the players. The teams are all set up, but there are no players to be found. I downloaded the file from Joe Rock's site.

jcurtis423 · 05-10-2005, 06:04 AM

try starting an initial draft and see if the players show up.

arod23 · 05-10-2005, 09:15 AM

Quote:

Originally Posted by rasnell

There are no players on the free agent list, either. Do I have to do something to import the players. The teams are all set up, but there are no players to be found. I downloaded the file from Joe Rock's site.

I just double checked the files, everything is there. You can view the players under Edit Free Agents in League Settings and Show All Players under the Misc tab. I do know that OOTP sometimes does not list all players as Free Agents who are in fact not on a roster and available. However, this file is set up for an initial fantasy draft, as shown on the opening screen. All players are available to be drafted.

rasnell · 05-10-2005, 01:13 PM

Something has obviously malfunctioned in my download then. When viewing all players in Misc tab, going to league settings to edit free agents, seeing free agents or releasing all to set up fantasy draft, all possible choices are blank. There are no players. I will download again and see if the glitch continues.

Edit: I found the problem. The lg folder contained a lg folder with the same name. It's now working.

arod23 · 05-16-2005, 03:28 PM

I didn't notice this before but the ballparks for each team are the defaults rather than a standardized park. My original file had each team in the same neutral park, i.e., park factor of 100, but when I made the last round of changes, I must have forgotten to change this. For a normalized league, I would recommend each home park be the same, but obviously edit your league to your particular taste.

arod23 · 06-14-2005, 02:45 PM

Since OOTP imports range and arm ratings randomly, I am editing the database to use more realistic defensive ratings. I will post an update soon.

04-30-2005, 03:48 PM	#1
arod23 Major Leagues Join Date: Apr 2004 Location: Philadelphia, PA Posts: 378	NormalizedDB Best All Time Players Ankit and I have created a DB of the best all time players. But, unlike other databases, all players stats have been normalized to a league standard, making cross-era simulations more realistic. The DB should be available on Joe Rock's Download Center shortly: http://www.ootpdownloadcenter.com/ From the readme file: Arod23 NormDB-v10 by Ankit and Arod23 Version 1.0 Last revision: 4/30/2005 OVERVIEW This database includes the best players of all time. All players' statistics have been "normalized" to the same environment in order to allow for more accurate simulations using players from across different eras. In other words, deadball era batters hit homers and deadball pitchers give up homers. Modern day pitchers with ERAs inflated by playing in higher HR compare more favorably with low run environment counterparts. A more detailed explanation follows, but in short: All player seasons have been translated to a neutral park in a standardized league, that scores 4.5 team runs per game, with a .260 batting average, .330 on base average, and .420 slugging average, making for a nice even .750 OPS. Players have been imported based on their normalized career totals. These figures have then been recalculated based on 500 AB for hitters and 250 IP for pitchers for ease of comparison. Note, this does not impact the simulation in any way, as OOTP is only concerned about ratios not actual totals. That is, there is no difference in OOTP's Power Rating in a player with 10 HRs in 150 ABs and a player with 40 HRs in 600 ABs. Players fielding stats are based on the positions played during the course of their career. However, range and arm ratings are randomly assigned by OOTP. PLAYER EXAMPLES Addie Joss played in the deadball era, holds the 3rd lowest career ERA of all time, dominates cross-era simulations. Active star Clemens with a career ERA that doesn't rank in the top-50 all time, clear hall of famer, yet he gives up 7x more HRs in cross-era simulations. When normalized Clemens numbers look better than Joss'. HTML Code: Addie Joss 1902-1910 Played in the deadball era, 3rd lowest career ERA of all time ERA H/9 HR/9 BB/9 SO/9 Actual 1.89 7.3 0.1 1.4 3.6 Normalized 3.60 8.4 0.9 1.5 5.3 HTML Code: Roger Clemens 1984-2004 ERA H/9 HR/9 BB/9 SO/9 Actual 3.18 7.7 0.7 2.9 8.6 Normalized 2.74 7.1 0.6 2.4 9.1 Ty Cobb average falls a bit, but still a very high career average, yet he benefits from getting credited with some long balls, nearly hitting 500 over his career. HTML Code: Ty Cobb 1905-1928 BA OBA SLG OPS HR AB/HR Actual .366 .433 .512 .945 117 97.7 Normalized .352 .420 .584 1.004 484 25.1 Hornsby had some deadball years as well as some years when the run environment was higher. His average suffers but his power increases, although not to the same extent as a player like Cobb. HTML Code: Rogers Hornsby 1915-1937 BA OBA SLG OPS HR AB/HR Actual .358 .434 .577 1.011 301 27.2 Normalized .328 .415 .606 1.021 604 14.1 As great a player as Mantle was, his actual stats sometimes fall short of other greats because he played many years in a lower run environment. His average is now over .300 and he actually gets credit for another 85 HRs HTML Code: Mickey Mantle 1951-1968 BA OBA SLG OPS HR AB/HR Actual .298 .421 .557 .978 536 15.1 Normalized .314 .427 .602 1.029 621 13.1 As dominant as Bonds is today, he is even better normalized. Why? He has played in a pitcher's park and still dominants his league, a league in a relatively high run era. HTML Code: Barry Bonds 1986-2004 BA OBA SLG OPS HR AB/HR Actual .300 .443 .611 1.054 703 12.9 Normalized .312 .453 .644 1.097 774 11.6 Babe Ruth dominated the game by such an extreme that all normalization procedures have trouble dealing with him. Since he hit more HRs than some teams, in other normalizations, his annual HRs can exceed 100. In these calculations, Ruth doesn't hit more than 69 homers in any normalized year, although he does hit 60 or more seven times. HTML Code: Babe Ruth BA OBA SLG OPS HR AB/HR Actual .342 .474 .690 1.164 714 11.8 Normalized .330 .461 .702 1.163 932 9.4 LEAGUE SETUP The players have already been imported into a league file. The file contains 8 teams, split into 2 leagues of 4 teams. The schedule is set for 162 games. All players have been set as rookies in year 1901 and are available for drafting. Obviously, you may modify the league structure as you fit, given the number of players that are available. The league settings will produce a close to modern day league, slightly better batting averages and less homers, but you should run test sims and adjust to your liking. All current ratings have been set so they match talent ratings, so everyone initally performs as dictated by their stats. (For some reason, OOTP does have some disparities between actual rating and talent ratings even when each season in a career is identical). L/R splits have been included but they have been adjusted to more realistic, less extreme ratings than OOTP defaults. Contact, Eye, Avoid K's include L/R splits, but Gap and Power are not split by L/R. Lastly, pitcher L/R splits have been removed since these are accounted for in the hitter's ratings (otherwise it seems like we would be double counting). HOW WE CHOSE THE PLAYERS We began with Bill James' New Historical Abstract. Per James' all-time lists, we included: 1) The top-100 players of all time, any position 2) The top-100 pitchers 3) At least the top-25 players at every position: C, 1b, 2b, 3b, SS, LF, CF, RF 4) Additional players: a) when normalized would be competitive with the top players, e.g., there is no need to include the 80th best SS of all time because he won't be used as a DH or PH, and his stats don't even come close to the 300th best OF b) who are commonly known as greats; part of the fun of a database like this is to see how your favorite players compare c) who are active but may have ranked low or not at all on James' lists because their career hasn't been long enough yet, e.g., If Albert Pujols stopped playing today, he's not getting into the Hall of Fame, but statistically, his first four years are up there with the best ever d) who are active or played recently, viewed as "stars" but might not be considered one of the best of all time; again part of the fun is playing with your favorite players 5) Pre and early 1900s players whose normalized stats compare favorably with the top players Invariably, we left someone's favorite out, but we hope you will find that we have compiled a comprehensive list of players. And, consider this version 1.0, so we can always update it later. NORMALIZATION METHOD Although we put this database together, the underlying statistical work is not ours and should be properly credited. This normalized database was compiled using Baseball Prospectus' Davenport Translations (http://www.baseballprospectus.com/dt/) developed by Clay Davenport. Normalizing baseball statistics across history is arguably one of the most difficult exercises one can undertake in both computational complexity and philosophy. While there are several approaches, we feel that Clay Davenport has done the most comprehensive work. Basically, he has considered everything. For those interested, here is a summary of what is accounted for in his translations (summarized from his own explanations): - All player seasons have been translated to a neutral park in a standardized league: Batting: .260 batting average, .330 on base average, and .420 slugging average, making for a nice even .750 OPS Pitching: 4.50 ERA, 9.0 H/9, 1.0 HR/9, 3.0 BB/9, 6.0 SO/9 1) Park Adjustment An adjustment made to account for the fact that some parks are easier to hit in than average, giving an advantage (in raw statistical terms) to hitters who play for that team. Park factors are always made relative to a league average of 1.00. The park adjustments in the BP are made only on the park factor for runs, averaged over five years. 2) Team Hitting Adjustment An adjustment made for hitters, to account for not having to face their own pitchers. Using pitching stats, (league R * pf - team R), divided by (league IP - team IP), divided by park-adjusted league runs per inning. 3) Team Pitching Adjustment An adjustment made for pitchers, to account for not having to face their own team's batters. Using batting stats, (league runs * pf - team runs), divided by (league PA - team PA), divided by league runs per plate appearance * pf. 4) Adjusted for season/league offense level Corrections have been made for team's hitting or pitching level and the player's home park. The numbers have also been win-adjusted; this is equivalent to a correction for league offensive level. 5) League Difficulty Adjustment Each league has been given a difficulty level, based on the performance of players in that league compared to the same players' performance in other seasons. The reference difficulty level was defined by the trend line of the National League from 1947 to 2002, and extended backwards to 1871. The difficulty adjustment is the ratio between the actual difficulty level and the reference level. 6) Adjustments have been made for pre-homer times In the deadball era, doubles and triples were power. A player who had a lot of 2b and 3b in that environment would almost certainly hit a lot of home runs in a modern environment, e.g., Sam Crawford's 312 triples turn into home runs, and he ends up with 575 for his career. But that isn't always true; thanks to his speed, Ty Cobb ends up keeping a lot more of his triples, and even though he emerges as a 20-25 HR a year guy, he keeps a high average (.350) and daring baserunning (consistent double-digit triples, 50+ stolen bases). Note: Since we compilied this database, the Davenport Translation's have changed slightly, so the figures in this DB won't exactly match. Most are within one point of batting average or 1/100th of ERA, so the differences do not impact anything.

04-30-2005, 06:21 PM	#2
JoeRockEHF All Star Reserve Join Date: Sep 2002 Location: Niles, MI Posts: 933	I have the file all set to go at the Download Center in the Rosters section. Thanks! __________________ PSN: JoeRockEHF

05-02-2005, 02:28 AM	#4
rem Hall Of Famer Join Date: Jul 2003 Location: College Park, Md. Posts: 5,024	Looks awesome man, nice work! __________________ OTBA: Washington Filibusters CLBR: Minnesota Twins 2005 Winner of LL's Pick the Loser Contest! - 15-0

05-10-2005, 01:13 PM	#17
rasnell Hall Of Famer Join Date: Jan 2003 Location: Frankfort, Kentucky Posts: 3,746	Something has obviously malfunctioned in my download then. When viewing all players in Misc tab, going to league settings to edit free agents, seeing free agents or releasing all to set up fantasy draft, all possible choices are blank. There are no players. I will download again and see if the glitch continues. Edit: I found the problem. The lg folder contained a lg folder with the same name. It's now working. Last edited by rasnell; 05-10-2005 at 01:21 PM.

05-16-2005, 03:28 PM	#18
arod23 Major Leagues Join Date: Apr 2004 Location: Philadelphia, PA Posts: 378	Ballparks I didn't notice this before but the ballparks for each team are the defaults rather than a standardized park. My original file had each team in the same neutral park, i.e., park factor of 100, but when I made the last round of changes, I must have forgotten to change this. For a normalized league, I would recommend each home park be the same, but obviously edit your league to your particular taste.

05-02-2005, 02:16 AM	#3
khucke All Star Reserve Join Date: Dec 2001 Location: Düsseldorf, Germany Posts: 657	Very interesting project indeed! One thing I`d like to know : how did you translate the normalized stats into ratings? I know there is a utility to translate ratings into stats. Did you use that one backwards? And how did you assign potential ratings? Did you take a player`s best season for that?

05-02-2005, 09:02 AM	#5
Johnny99 Minors (Triple A) Join Date: Sep 2004 Posts: 209	Is there any way to pluck indiv. players from this league into another league? If it was a database like Ankits, I know what to do, but here?

05-08-2005, 12:18 AM	#10
targy All Star Starter Join Date: Jan 2002 Location: Clearwater, FL Posts: 1,152	How would you do a career league, would you just run an amateur draft every year

05-09-2005, 12:34 PM	#12
rasnell Hall Of Famer Join Date: Jan 2003 Location: Frankfort, Kentucky Posts: 3,746	I must be missing something. The file is only 375 kb on Joe Rock and, when I open the league file, there are no players on any of the rosters. Most other league files at the download center are over 1 meg. What am I missing?

05-10-2005, 04:56 AM	#14
rasnell Hall Of Famer Join Date: Jan 2003 Location: Frankfort, Kentucky Posts: 3,746	There are no players on the free agent list, either. Do I have to do something to import the players. The teams are all set up, but there are no players to be found. I downloaded the file from Joe Rock's site.

05-10-2005, 06:04 AM	#15
jcurtis423 Banned Join Date: Oct 2004 Posts: 57	try starting an initial draft and see if the players show up.

06-14-2005, 02:45 PM	#19
arod23 Major Leagues Join Date: Apr 2004 Location: Philadelphia, PA Posts: 378	Defense Ratings Since OOTP imports range and arm ratings randomly, I am editing the database to use more realistic defensive ratings. I will post an update soon.