Oakland's Slide: Regression to the Mean or the Cespedes Trade?

The Athletics were up 2 games on the Angels in the AL West on July 31, when Billy Beane dealt Yoenis Cespedes to Boston for Jon Lester and Jonny Gomes. Since then, they have been passed by the Angels and now sit 10.5 games back, facing an inevitable one-game wild card playoff, while the Angles have clinched the division. The Cespedes trade has been panned as the reason for this "collapse". I figured something more innocent was the reason for their slide in the standings: regression to the mean. The Athletics still have the best run differential in baseball (+150), although the Angels have significantly caught up (+149).

I calculated the Pythagorean-expected records for the Athletics and compared them with their actual records since the trade deadline:

As seen above, the A's actually have been unlucky (with respect to their expected record) the entire time, but this luck has gotten considerably worse since the trade. They've actually regressed farther from the mean, the opposite of what I expected.

I then compared the Angels's luck to that of the Athletics. As seen above, they're trending in opposite directions, and the wins above/below expected currently stand at LAA: +3.03, OAK: -9.63. The total difference between these is 12.66. So, if both teams were playing to their (considerably high) Pythagorean-expectations, Oakland would be up 2 games: exactly where they were on July 31. 

So is the absence of Cespedes the cause of this slide, since the team has actually continued to play worse? This article from CBS Sports provides more accurate reasoning as to why the A's have fared so poorly in the last month and a half: 

Did trading Cespedes weaken the A's offense? Absolutely. Is one man responsible for the club suddenly scoring 1.29 fewer runs per game? Not a chance. Even if you fully buy into the idea of lineup protection and all that, slumps like this take a total team effort.

Parsing Data in Google Sheets

I figured I would give a rundown how I parse data on Google Sheets (which can be translated to use in Microsoft Excel).

To start, I import data from an external site; it has to be in a table or .csv format. In this example, I'm importing from ESPN's schedule for the Tampa Bay Rays.

Projected ACC Standings

I've finished simulating every ACC team's season, and can now project the conference standings from those results.

Projected bowl teams: 10

Atlantic
1. Florida State   11-1 (7-1)
2. Clemson         8-4  (6-2)
3. Louisville      8-4  (5-3)
4. Boston College  6-6  (3-5)
5. Syracuse        5-7  (3-5)
6. NC State        6-6  (3-5)
7. Wake Forest     5-7  (2-6)

Coastal
1. Virginia Tech   8-4  (5-3)
2. Duke            7-5  (4-4)
3. North Carolina  7-5  (4-4)
4. Georgia Tech    7-5  (4-4)
5. Pitt            7-5  (4-4)
6. Miami (FL)      7-5  (4-4)
7. Virginia        4-8  (2-6)

Note: Notre Dame is not considered part of the ACC

Bonus (Alternative) UNC Season Predictions

The following was penned by "Stan Hooper"

ACC media days this week. (Quick immediate analogy. SEC media days are the trailer park meth. It'll have you up for days straight trying to figure out the madness going on there. It is the real college football stuff for real college football people. ACC media days is the methadone. Its the cheap imitation knockoff. It leaves the user in a zombie like state, however you appetite for meth is temporarily curbed until the next relapse and subsequent binge. ACC football turns you into a zombie, SEC makes you an addict because it is real.)​ Nothing interesting happened. But one thing did happen. UNC got picked fourth in the ACC coastal. 4th! 4th! Not 4th in the ACC, 4th in the Coastal. Behind Miami, behind VT, behind d00k. Gutless. Spineless. Brainless. They know not of what will happen this season. What kind of crackpots are voting in the ACC media poll?

Never mind what these bozos pick. 15-1 is what will happen. Before you try to go counting number of games and such, here is in great detail what will happen this year.

Simulating UNC's Season

I (once again) adapted my Monte Carlo simulator, this time to simulate the entire regular season of any given Division 1 FBS college football team. Its input was my roster-adjusted MDS preseason NCAAF rankings, and each season was simulated 10,000 times. Naturally, I've only done it so far for North Carolina.

An alternative, more optimistic preview can be found here.

North Carolina (Rank: #36)
Average record:      6.80-5.20 (4.27-3.73 in conference)
Most likely record:  7-5 (4-4)

Chance of making a bowl game (6-6 or better):  79.31%
Chance of going undefeated (12-0):             0.05%