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Earlier versions of OOTP: Technical Support Do you have a copy of OOTP Baseball 2006? Are you in need of help and assistance in running the game or do you have errors that you need help in resolving? This is your place! |
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04-27-2006, 10:34 PM | #41 |
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Just a confirming bit to the above. I've done quite a bit of testing the past two days to try to understand exactly how park factors influence those in other parks (in other words, to determin how league totals and park factors interact). I ran a controlled replay leauge with eight teams (two leagues of two team division) through multiple park factor scenarios like:
All park factors = 100 All League 1 factors = 125, All League 2 factors = 100 All League 1 factors = 150, All League 2 factors = 100 All League 1 factors = 75, All League 2 factors = 75 etc, etc, etc. The resounding answer is that it works as Andy theorized above. The totals are a constant baseline that each park's factors are then applied to individually. In other words, dialing up all the park factors in one league made no difference to results in the other league. Hence park factors are essentially a localized league total mod, and can alter a league's output in strange ways if they aren't applied evenly...or at least if they aren't applied evenly and someone is actually expecting the output of their league to follow the totals. Hope that made sense. Here's some partial data from V6. Note that it also confirms the lack of Hits adjustment. Note, I can confimr the V5 adjusments all work, so the error was induced in v6. (Though the v5 adjustments make a huge impact at the upper/positvie ends). I think it would be great to have a beta tester run through these same kinds of studies to prove the OOTP2006 park factors actually work as expected. Code:
All Park Factors = 100 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 1 0.276 796 3501 22871 6327 954 126 2439 4263 0.347 0.434 0.781 507 25310 League 1 0.276 798 3505 22695 6275 908 147 2510 4275 0.348 0.435 0.783 490 25205 League 1 0.275 807 3604 22630 6224 956 130 2492 4342 0.347 0.436 0.783 503 25122 League 1 0.274 791 3573 22784 6249 949 150 2501 4354 0.347 0.433 0.78 511 25285 League 1 0.272 796 3507 22818 6227 949 147 2511 4467 0.346 0.432 0.778 520 25329 Average 0.275 797.6 3538.0 22759.6 6260.4 943.2 140.0 2490.6 4340.2 0.347 0.434 0.781 506.2 25250.2 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 2 0.267 789 3440 22632 6065 963 142 2507 4250 0.342 0.428 0.77 511 25139 League 2 0.272 804 3510 22754 6207 940 166 2531 4375 0.346 0.435 0.781 492 25285 League 2 0.273 848 3572 22911 6266 1017 125 2536 4377 0.347 0.44 0.787 542 25447 League 2 0.265 820 3428 22589 5994 924 118 2430 4398 0.338 0.426 0.764 532 25019 League 2 0.269 775 3563 22843 6149 956 155 2533 4394 0.343 0.426 0.769 506 25376 Average 0.270 807.2 3502.6 22745.8 6136.2 960.0 141.2 2507.4 4358.8 0.343 0.431 0.774 516.6 25253.2 League 1 Park Factors = 125 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 1 0.273 927 3626 22594 6171 1175 141 2488 4326 0.346 0.461 0.807 477 25082 League 1 0.271 896 3670 22750 6183 1197 165 2591 4371 0.347 0.457 0.804 486 25341 League 1 0.273 950 3766 22856 6255 1199 152 2476 4253 0.346 0.464 0.81 494 25332 League 1 0.275 894 3739 22848 6286 1188 141 2544 4364 0.349 0.457 0.806 499 25392 League 1 0.270 856 3718 22809 6162 1273 154 2528 4324 0.343 0.452 0.795 468 25337 Average 0.273 904.6 3703.8 22771.4 6211.4 1206.4 150.6 2525.4 4327.6 0.346 0.458 0.804 484.8 25296.8 % Baseline -0.834 13.415 4.686 0.052 -0.783 27.905 7.571 1.397 -0.290 -0.231 5.576 2.996 -4.228 0.185 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 2 0.266 784 3378 22419 5979 898 120 2567 4224 0.343 0.422 0.765 512 24986 League 2 0.269 845 3480 22733 6130 946 144 2536 4299 0.344 0.435 0.78 573 25269 League 2 0.276 839 3633 22703 6273 1007 123 2516 4319 0.349 0.442 0.791 524 25219 League 2 0.269 769 3482 22864 6170 960 121 2534 4347 0.344 0.423 0.767 538 25398 League 2 0.271 798 3384 22743 6164 922 142 2405 4390 0.342 0.429 0.771 534 25148 Average 0.271 807.0 3471.4 22692.4 6143.2 946.6 130.0 2511.6 4315.8 0.344 0.430 0.775 536.2 25204 % Baseline 0.350 -0.025 -0.891 -0.235 0.114 -1.396 -7.932 0.168 -0.987 0.350 -0.186 0.077 3.794 -0.195 League 1 Park Factors = 150 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 1 0.270 1041 3961 22796 6175 1437 241 2503 4336 0.344 0.492 0.836 471 25299 League 1 0.270 1006 3923 22864 6174 1443 241 2629 4389 0.346 0.486 0.832 460 25493 League 1 0.266 1001 3788 22735 6051 1400 233 2578 4383 0.341 0.48 0.822 472 25313 League 1 0.266 988 3867 22648 6043 1395 232 2523 4409 0.342 0.48 0.822 463 25171 League 1 0.270 996 3898 22874 6180 1486 237 2593 4370 0.344 0.486 0.831 444 25467 Average 0.269 1006.4 3887.4 22783.4 6124.6 1432.2 236.8 2565.2 4377.4 0.343 0.485 0.829 462.0 25348.6 % Baseline -2.271 26.179 9.876 0.105 -2.169 51.845 69.143 2.995 0.857 -1.037 11.705 6.095 -8.732 0.390 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 2 0.268 835 3517 22680 6087 971 143 2500 4314 0.341 0.434 0.775 501 25180 League 2 0.266 805 3334 22473 5981 930 138 2543 4243 0.341 0.427 0.768 542 25016 League 2 0.270 829 3407 22772 6171 954 129 2410 4398 0.341 0.433 0.775 568 25182 League 2 0.272 804 3488 22753 6202 988 127 2460 4293 0.345 0.433 0.778 528 25213 League 2 0.272 808 3606 22679 6183 991 129 2546 4364 0.347 0.435 0.781 526 25225 Average 0.270 816.2 3470.4 22671.4 6124.8 966.8 133.2 2491.8 4322.4 0.343 0.432 0.775 533.0 25163.2 % Baseline -1.785 2.332 -1.911 -0.388 -2.166 2.502 -4.857 0.048 -0.410 -1.153 -0.369 -0.717 5.294 -0.345 League 1 Park Factors = 75 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 1 0.277 705 3354 22987 6377 725 121 2466 4420 0.348 0.411 0.76 488 25453 League 1 0.275 715 3357 23043 6355 697 120 2495 4322 0.347 0.41 0.757 500 25538 League 1 0.276 701 3376 22843 6327 733 147 2459 4331 0.347 0.414 0.761 514 25302 League 1 0.279 697 3471 23031 6430 741 124 2451 4455 0.348 0.413 0.761 501 25482 League 1 0.275 771 3468 22997 6335 725 152 2536 4265 0.348 0.421 0.769 545 25533 Average 0.277 717.8 3405.2 22980.2 6364.8 724.2 132.8 2481.4 4358.6 0.348 0.414 0.762 509.6 25461.6 % Baseline 0.692 -10.005 -3.754 0.969 1.668 -23.219 -5.143 -0.369 0.424 0.173 -4.654 -2.484 0.672 0.837 League AVG HR R AB H 2B 3B BB K OBP SLG OPS SB PA League 2 0.266 801 3411 22732 6058 931 146 2433 4331 0.338 0.426 0.764 516 25165 League 2 0.271 780 3388 22807 6199 913 143 2579 4448 0.347 0.427 0.773 539 25386 League 2 0.275 821 3647 22733 6259 1002 152 2497 4364 0.348 0.441 0.789 538 25230 League 2 0.265 775 3305 22457 5957 941 142 2475 4218 0.339 0.423 0.762 540 24932 League 2 0.266 760 3390 22620 6037 948 142 2493 4356 0.341 0.422 0.763 518 25113 Average 0.269 787.4 3428.2 22669.8 6102.0 947.0 145.0 2495.4 4343.4 0.343 0.428 0.770 530.2 25165.2 % Baseline -0.224 -2.453 -2.124 -0.334 -0.557 -1.354 2.691 -0.479 -0.353 -0.175 -0.742 -0.517 2.633 -0.348 Last edited by RonCo; 04-27-2006 at 10:47 PM. |
04-28-2006, 01:18 PM | #42 |
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Not really sure I even agree that is how it should work. I'm assuming when you said "two leagues", that you set one .lg file in an AL/NL kind of situation, and not two separate .lg folders.
What about interleague play? What if all the AL parks are more offense heavy than the NL parks, why should two equal ability players, one in each league, produce the same stats? I'm pretty sure you agree with those sentiments as well, just throwing those questions out there to make sure. I'd hate to have to calculate the average park factors in the AL/NL/other leagues as yet another modifier on performance when comparing two players in two different leagues. The onus should be on the editor of park factors to ensure it balances to 100, or at least, consider all teams in the major leagues when balancing park factors, not just isolating each AL/NL type league and balancing locally, because interleague play happens and trades between leagues happen.
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04-28-2006, 01:32 PM | #43 |
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Great findings guys, and as was sad, thankfully it's just AVG
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04-28-2006, 01:45 PM | #44 |
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Where'd the thread go that displayed how the split park effects (LH/RH AVG/HR) affect pitchers' ability based on their hand as much as it affected batters?
That is, when park effects are 125 HR LHB and 75 HR RHB, you'd expect a LHP vs RHB matchup to give you 75% of the HR output of that same matchup in an all 100s park. What you actually get is 100% of the HR output because the LHP is equally handicapped in avoiding HR by the 125 LHB as the hitter is handicapped by the 75 HR RHB. Seeing jeheinz's comment reminded me that AVG being broken was only the tip of the park effects iceberg.
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04-28-2006, 03:25 PM | #45 | |
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Quote:
Really accurate, real life park factors are hard to calculate for just the reason you're discissing here. BBREF has a tutorial on how they do it. But remember, I don't think we're talking about the same thing. Park factors in real life are a result of the players who play in the parks, and the parks themselves. They are calculated based on runs scored by all collection of players in all parks. OOTP park factors are not that. I don't think they are, anyway. OOTP park factors are modifiers on how often a specific player will achieve a specific kind of hit in a specific at bat. As such, they are an attempt to model the physical impact of the park only. In order to get an OOTP league's park factors, I think you would have to run the data through BBRefs, formulas... I think all the above is true, anyway. It is up to the league editors to ensure their parks add up to/average out to 100 for what ever player pool that exists. I'm not suggesting how anything _should_work here, I'm just saying that essentially, park factors in OOTP today act in a local fashion, and do not affect the other league in any way. So, in your example, the NL player who moves to an AL with more offensive parks will see their stats adjust appropriately. What I'm saying, though, is that the park factors interact with the league totals as a direct modifier...as localized league totals modifications. So, if you set your league totals to a baseline, and then modify every park up 10% or down 10% for a specific factor, it results in stats that look like a fundamental league totals change. So, if your league is allowing wanton changes in the league's parks (like most seem to), then you are essentially changing the league totals. The specific change that occurs due to the localized change is different in v5 than in v6. (as you discovered in your study) V6 doesn't budge in hits, seems to track for doubles (meaning a 125 park setting results in 25% more doubles), and seems to be about half-strength for HR. V5 tracks directly for each park factor change, but changing multiple items (HR and hits, for example) results in a multiplication of the effect on HRs or doubles or triples. Whatever, the park effect is localized to the individual park, which lends some credence to my expectation that Marks is realy trying to model park dimensions by these factors...note, park dimensions in real parks can and do result in different ballpark factors over the years. Let's not confuse those. I'm speaking only of the mechanics of OOTP at present. Of course, it could be that I'm just over-analyzing what you're trying to say, too. |
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04-28-2006, 03:35 PM | #46 |
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Haha, yeah, you might be overanalyzing it a bit. I think park factors are definitely a physical representation that doesn't take into account particular hitter styles in particular parks, as covered in the OOTPBB threads on hitter types (pull, spray, normal) and how those aren't really meaningful at this time.
But, as far as the AL/NL thing. Let me try to play out an example: I have a park thats all 125 park ratings. The average AL park is 140 park ratings. I trade a player who has an .800 OPS in my park to an NL team. The NL team park is all 75 park ratings, but the average NL park is 90 park ratings. My non-OOTP logic says this guys OPS will drop like a rock moving from a hitter's park to pitcher's park. What I'm asking, is that does your 2-league study actually suggest this batter will continue to put up .800 OPS, because his previous team and new team both have park effects 15 below their respective league averages?
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04-28-2006, 04:50 PM | #47 |
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The study says he will drop like a rock, just as you would expect.
All my study really does is confirm the process works like Andy suggested it did. --each park as a stand-alone entity unto itself that creates it's statistical output as a unique adjustment to league the basic league totals. |
04-28-2006, 04:59 PM | #48 |
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Oh, ok. I didn't really understand your study, then, on my first pass.
I get it now, all you're saying is that you can't expect your league to produce stats in line with your league totals if the average park effect across your major leagues is not 100. But, this has nothing to do with AL/NL kind of leagues and being treated differently within the same major league system. I think the term "League" was just confusing me.
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04-28-2006, 05:31 PM | #49 |
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Yes.
My reasoning for looking at it as I did was that if the park factors were subservient to the League Totals, then the totals would stay the same over the entire league, and that offense that got kicked out of one park would be absorbed by another (or visa versa). That's not the case. So League totals are the foundation, and park factors make changes from that point. It's as you would expect...but I've come to not expect things to work as I expect. Have I confused you enough for one day? |
04-29-2006, 12:53 PM | #50 |
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Just for kicks and grins, I also confirmed the common knowledge that OOTP park dimensions are not meaningful in statistically significant any way in either V5 or V6.
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