Latest Cubs prediction: 110-54 (0.362 team OBP, 3.66 team ERA, underlying equation). (Previous predictions: 112-50, 113-49, 90-62)

We’ll have to see how Soriano’s broken finger affects the Cubs’ team OBP and thus the prediction.

The balloon tooltip appears to be a Windows tooltip common control with the TTS_BALLOON style.

To replicate this functionality, I decided to write a function called ShowMsgBalloon() which, given a control and the various balloon tooltip parameters, creates and shows the balloon tooltip below the control.

The key insight to making ShowMsgBallon() work as intended was to use the TTF_TRACK option to create a tracking tooltip. This will immediately show the tooltip without requiring the user to position the mouse over the control. The main downside to using TTF_TRACK is that the tooltip will not move with the control if the window is moved; you need to manually move the tooltip using TTM_TRACKPOSITION as required. One could probably make this automatic by subclassing the tooltip’s parent control and handling WM_WINDOWPOSCHANGED messages.

Here is the source code to ShowMsgBalloon(). When you are done with the balloon, call DestroyWindow() on the returned HWND. Note: you may want your application to use comctl32.dll version 6 as it will lead to a nicer visual style, including a close button.

In XPath, strings must be delimited by either single or double quotes. Given a quote character used to delimit a string, one can’t represent that same quote character within the string. This means that if you decide to use single quotes to delimit your XPath string, you couldn’t represent the string O'Reilly; use double quotes, and you can’t represent "Hello".

However, given a quote delimiter, you can represent the other quote character. We can use this observation along with the concat XPath function to devise a general quoting rule for XPath strings. It’s easiest to show this via a series of examples:

Below is a piece of C++ code which implements these quotation rules:

Usage looks like:

Latest Cubs prediction: 112-50 (0.368 team OBP, 3.73 team ERA, underlying equation). (Previous predictions: 113-49, 90-62)

To contrast, a simple extrapolation of their current 28-19 record predicts 97-65. 97-65 seems a lot more realistic than 112-50.

The problems with my regression which “predicts” a baseball team’s win-loss record are the following:

1. The regression is extremely sensitive to the input parameters, many of which are quite unstable throughout the year. For example, one extra point (0.001) of team OBP results in 0.6 extra predicted wins.
2. The standard error of the prediction is quite high (4.68).
3. The regression doesn’t seem to be much better than linearly extrapolating a team’s current win-loss record to the entire season.

To demonstrate my point, a run of the regression against the current Cubs team statistics (0.371 team OBP, 3.81 team ERA) now predicts a record of 113-49, a swing of 23 wins in a matter of 15 days. This record would put them 3 wins shy of the regular season win record—first achieved by the 1906 Cubs (in a 152-game season) and again by Lou Piniella’s 2001 Seattle Mariners.

It’s clear that this new prediction is the consequence of the Cubs’ hot streak. Let’s hope they can keep it going.

Until recently, for instance, the Lincoln Navigator offered 128 options on its console alone.

“You know what 128-factorial is—it’s a lot of combinations,” Mr. Mulally joked at a conference recently, mocking the number of designs theoretically resulting from mixing-and-matching the options. (Answer: 3.85620482 x 10 to the 215th power.)

Spector, Mike. “Ford Eyes More Cuts as Recovery Advances; Earnings Improve”. The Wall Street Journal 23 April 2008: A1, A14.

128-factorial is the correct number of combinations of options only if the order in which you pick the options is important. It almost certainly is not. Instead, assuming each option is independent and can be either on or off, the correct number of combinations is 2^128—3.4 x 10^38. Mr. Mulally was off by a factor of 177.

The business of assigning a rating to a mortgage security is a complicated affair, and Moody’s recently was willing to walk me through an actual mortgage-backed security step by step. I was led down a carpeted hallway to a well-appointed conference room to meet with three specialists in mortgage-backed paper. Moody’s was fair-minded in choosing an example; the case they showed me, which they masked with the name “Subprime XYZ,” was a pool of 2,393 mortgages with a total face value of $430 million.

…

Moody’s did not have access to the individual loan files, much less did it communicate with the borrowers or try to verify the information they provided in their loan applications. “We aren’t loan officers,” Claire Robinson, a 20-year veteran who is in charge of asset-backed finance for Moody’s, told me. “Our expertise is as statisticians on an aggregate basis. We want to know, of 1,000 individuals, based on historical performance, what percent will pay their loans?”

…

In the frenetic, deal-happy climate of 2006, the Moody’s analyst had only a single day to process the credit data from the bank.

…

Mortgage-backed securities like those in Subprime XYZ were not the terminus of the great mortgage machine. They were, in fact, building blocks for even more esoteric vehicles known as collateralized debt obligations, or C.D.O.’s.

We built a financial house of cards on ratings agencies’ models, and these models turned out to be disastrously wrong.

Yep, that’s right, Nick Nolte.