If we stipulate that the actual players did not change but that only their visible ratings changed during the migration, then we can use the Migration Graphs to determine where an individual player is on the percentile continuum to a more accurate degree than just "he's got a 5 in power."
Suppose that a player was rated 6 in power in OOTP 24 but immediately after the migration he is now rated 5. Look at this graph:
From the graph we can see that he must be in the range between the lower bound of OOTP 24 six (green) and the upper bound of OOTP 25 five (purple). Thus, his actual percentile is somewhere between 62 and 73. This is useful information. This places him roughly in the third best octile, i.e., between 5/8 and 3/4. One quarter of hitters have more power, but 5/8 of hitters have less.
Using the Migration Graphs to Derive More Accurate Ratings Information for Your Players
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Using the Migration Graphs to Derive More Accurate Ratings Information for Your Players
Bob Breum
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- Bob Breum
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Re: Using the Migration Graphs to Derive More Accurate Ratings Information for Your Players
Let's use a real world example. Take our starting pitcher, Todd Schroeder. Erik traded for him because he thought he would perform well as a SP for us, given his 8 stuff / 10 movement / 7 control and three pitches all rated 8. He did indeed, starting 20 games, throwing 117 innings to a 3.31 ERA with a 1.23 WHIP. After the migration, he does not look like the same player. I am trying to allay Erik's concerns.
Todd's stuff post-migration is a pedestrian 5. But given what we know about pre-migration Todd, let's use our graphs. Here's the Stuff graph with Todd's information superimposed:
We now confidently locate his Stuff between percentiles 58 and 71. It's clearly above average, not at all in the 30-58 percentile range that the rest of the new 5 rating encompasses.
His Movement has plummeted from 10 to 6. On the face of it, this is a ghastly change, especially given the Blazers' emphasis on keeping the ball in the park when we are on the road. Let's see what we can learn from the Migration Graph:
Whew! It looks like his movement is between the 89th and 96th percentile. This is rarefied air, and certainly no cause for concern.
Finally, let's consider his control, which dropped from 7 to 5.
Our graph places his control between the 71st and 73rd percentiles, the very tippy-top of the 5 range. This is very good news.
Perhaps Todd can still be a useful rotation piece for our Blazers.
Todd's stuff post-migration is a pedestrian 5. But given what we know about pre-migration Todd, let's use our graphs. Here's the Stuff graph with Todd's information superimposed:
We now confidently locate his Stuff between percentiles 58 and 71. It's clearly above average, not at all in the 30-58 percentile range that the rest of the new 5 rating encompasses.
His Movement has plummeted from 10 to 6. On the face of it, this is a ghastly change, especially given the Blazers' emphasis on keeping the ball in the park when we are on the road. Let's see what we can learn from the Migration Graph:
Whew! It looks like his movement is between the 89th and 96th percentile. This is rarefied air, and certainly no cause for concern.
Finally, let's consider his control, which dropped from 7 to 5.
Our graph places his control between the 71st and 73rd percentiles, the very tippy-top of the 5 range. This is very good news.
Perhaps Todd can still be a useful rotation piece for our Blazers.
Bob Breum
Co-GM (Position Players)
2057 Johnson League champions
2057 Johnson League GM of the Year
Montreal Blazers
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2057 Johnson League champions
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Montreal Blazers
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Re: Using the Migration Graphs to Derive More Accurate Ratings Information for Your Players
Neat
Rob McMonigal
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