Comments on Vegas Watch: Finding The Happy Medium

Wish I could add something as lucid as those comme...

2008-04-27T18:24:00.000-04:00

Wish I could add something as lucid as those commenters above, but all I have is a request to keep us updated at the 40 game mark.

Great work.

What I would want to do if we incorporated strengt...

2008-04-25T14:28:00.000-04:00

What I would want to do if we incorporated strength of schedule is take the PECOTA predictions and figure out how difficult each team's schedule has been so far. Then, incorporate it either as a separate variable, or to help figure out how much weight to give to Pythag W%.

If you have the MLB schedule in a database, it is ...

2008-04-25T08:55:00.000-04:00

If you have the MLB schedule in a database, it is not that hard to implement chuckdickens's approach. But would it really be more predictive? The sample size for a single team v team matchup is vanishingly small, especially for interdivisional (or even interleague) matchups, and hence especially prone to results very deviant from the mean. Would the deviations even out over an entire schedule? Perhaps, but isn't that a tacit admission that the value of Pythag prediction is in the aggregate?

"It would be a nightmare to compile all of the nec...

2008-04-24T21:23:00.000-04:00

"It would be a nightmare to compile all of the necessary data, but I wonder if weighting the pythagorean projections based upon the schedule a given team has already played versus the schedule a given team has yet to play would provide more accurate predictions."

I think it probably would be more accurate. I also think it'd probably take hundreds of hours to do that. I'd like to incorporate some kind of schedule component, but have yet to figure out some kind of reasonable way to do it.

Interesting article. It would be a nightmare to co...

2008-04-24T21:16:00.000-04:00

Interesting article.

It would be a nightmare to compile all of the necessary data, but I wonder if weighting the pythagorean projections based upon the schedule a given team has already played versus the schedule a given team has yet to play would provide more accurate predictions.

For instance, the Twins have played the Royals 6 times thus far. In those games, they scored a total of 19 runs and allowed 15. The pythagorean expectation would project them to win about 62% of their remaining 12 games against the Royals. Given that they have 140 games left, you could give .62 a weight of 12/140. Rinse and repeat for the rest of the teams, applying the overall pythagorean projection towards any teams that they haven't played. Then, sum up the respective pythagorean shares to determine a weighted pythagorean expectation.

Then again, that's a lot of work. In any case, great article.

"That's a concern of mine, but it's not the only o...

2008-04-23T13:51:00.000-04:00

"That's a concern of mine, but it's not the only one. You are also using Pythag based on actual RS/RA, rather than AEQR/AEQRA (expected RS/RA via the batting lines produced, adjusted by SOS)."

I wanted to use that, but figured I wouldn't be able to find it for the past data.

What I did is essentially the same thing as combining Davenport's original Playoff Odds, and his PECOTA Playoff odds. For example, the original odds have the Diamondbacks winning 95.4 games, and PECOTA has them winning 90.9 games. My prediction of 93.3 comes down right in between- it's higher than (90.9+(95.4-90.9)*.1) because he is regressing to .500 to get that 95.4 number; if he was using straight Pythag or straight AEQR/AEQRA, I'd assume they would be expected to win more than 95.4 games at this point.

"My only concern is that the PECOTA numbers alread...

2008-04-23T10:00:00.000-04:00

"My only concern is that the PECOTA numbers already account for SOS, so teams that play hard schedules would be getting penalized twice."

That's a concern of mine, but it's not the only one. You are also using Pythag based on actual RS/RA, rather than AEQR/AEQRA (expected RS/RA via the batting lines produced, adjusted by SOS). Both of these concerns relate to #2 on my list of things needed to do a Monte Carlo sim.

Davenport's solution is to regress the AEQR/AEQRA Pythag to .500, then take a random sample from a normal distribution around the regressed WPCT. The flaw in that, IMHO, is that teams do not regress to .500. Your work above indicates that teams regress strongly to their PECOTA projections. And that's exactly what Davenport does in his PECOTA-adjusted Playoff Odds. Perhaps we should find out if he is using regression values similar to the ones you derived.

"These take into account the team's record so far;...

2008-04-22T21:46:00.000-04:00

"These take into account the team's record so far; the W% column is their expected winning percentage the rest of the way."

Actual record is what is used for games already played. The Pythag record is only used to help determine their winning percentage from here on out.

You should be using actual record, not pythad. If...

2008-04-22T21:41:00.000-04:00

You should be using actual record, not pythad. If you are trying to predict what the actual record of the team is going to be at the end of the season at this stage, just take their actual record and pro-rate the rest of the season using whatever projection system you want. Pythag tells us how many games the team should have won up until this point, but frankly, we don't care how many games the team should have won since we KNOW how many games the team has won. Whether a team is 21-1 by winning all 1 run games or 21-1 by blowing out their opponents, I don't care. I know the team won 21 games. I don't need to, nor should I correct for that. The proration of the projection system over the next 140 games is going to take care of that regression to the mean in luck.

Fastness, Evilmonkeycma, DCThrowback, Passive Voic...

2008-04-22T18:07:00.000-04:00

Fastness, Evilmonkeycma, DCThrowback, Passive Voice, and Bobby S- Thanks for the insightful comments. (I'm kidding, I'm glad you like the post.)

Sky- Looking at Matchbook, the ones that jump out are ATL O85.5 +125, and KC U72.5 +150. I'm not sure where else win totals are still posted.

Skoor- This would be fun. My only concern is that the PECOTA numbers already account for SOS, so teams that play hard schedules would be getting penalized twice. I could do #1, although it would take awhile unless there is something like that freely available.

Awesome.Now, how do those projected win totals com...

2008-04-22T17:52:00.000-04:00

Awesome.

Now, how do those projected win totals compare to current online odds? Can we make some money by taking advantage of others' overreactions?

"I am not smart enough to run a Monte Carlo simula...

2008-04-22T13:50:00.000-04:00

"I am not smart enough to run a Monte Carlo simulation."

Hogwash. If you are smart enough to do regression analyses, you are twice smart enough to do a Monte Carlo. Take your projected wpct and run through the remaining schedule an arbitrarily large number of times. (BP does one million.) The log5 method is a quick and effective way to get a result for each game based on the two team's wpct.

All you need:
1) A database with the 2008 MLB schedule.
2) Your projected wpct for each team for the remainder of the schedule.
3) A program to read the database and your projections, run the simulations, and report the results.
4) A snack to munch on while the program runs.

If you are saying you are not smart enough for #3, I still say hogwash. But if you'll give me (or point me to) #1, I'll make you #3.

Excellent, excellent post. Thanks.

2008-04-22T13:26:00.000-04:00

Excellent, excellent post. Thanks.

Check-plus.

2008-04-22T12:54:00.000-04:00

Check-plus.

2nd to evil monkey. muchas gracias

2008-04-22T12:10:00.000-04:00

2nd to evil monkey. muchas gracias

Excellent post. Nothing else needs to be said

2008-04-22T10:40:00.000-04:00

Excellent post. Nothing else needs to be said

Good work. It's interesting how pecota is still w...

2008-04-22T06:07:00.000-04:00

Good work. It's interesting how pecota is still weighted much more heavily even late into the season.

I'm surprised pct3 is the same. On the bottom of the pecota adjusted postseason odds page, it says they are taking the aeqr pythag wpct and regressing that toward the pecota projections, but they obviously aren't.

One more thing - the pecota adjusted playoff odds page says it is regressing performance toward the pecota predicted winning percent, then running a simulation of the rest of the season using the log5 method to determine who wins the game, but the pecota projected winning percent is based on simulations of the entire season. So the pecota projected winning percent is not an approximation of a team's adjusted winning percent (like for example, the kenpom.com pythag wpct), but an approximation of their winning percent given their schedule. So it would then assume the cubs and red sox (both projected to go 91-71) are equal by pecota, while pecota actually finds the red sox better, but having a harder schedule.

This post is the kind of stuff to shove up Rick Re...

2008-04-22T03:10:00.000-04:00

This post is the kind of stuff to shove up Rick Reilly's ass. Good stuff.