Guinness World Records for housing

Here is a roundup of some of the 2014 Guinness World Records in housing:

Knapp, who died in 1988, lived in the same house in Montgomery Township, Pa., for 110 years. And for that feat, she earns the title as the person who has lived the longest time ever in one residence, according to the 2014 edition of the “Guinness World Records.”…

While we’re at it, a nod to the world’s tallest real estate agents: Laurie and Wayne Hallquist are 6’6″ and 6’10”, respectively. She’s a full-time agent with Prudential California Realty in Stockton, Calif., while he’s a part-timer with the company…

The skinniest house on record is in Warsaw. It is three feet two inches wide at its narrowest point and just about five feet at its widest. It contains a floor area of 151 square feet, and instead of stairs, occupants climb a ladder to reach the bedrooms above…

The tallest resident-only building is in Dubai. Princess Tower is 1,356-feet high, with the highest occupied floor at 1,171 feet. But the title of tallest residential apartments belongs to Burj Khalifa, also in Dubai, which combines a hotel, offices and apartments. There, the highest residential floor—the 108th—is at 1,263 feet.

Houses, their furnishings, and apparently, their agents, come in all shapes and sizes. However, when I think about these records, it strikes me that most housing in the United States is relatively uniform. I don’t mean that the housing is uniform – this is a common criticism of suburban housing and I don’t think it is particularly fair – but that most housing is within a standard deviation or two from normal. Give or take a few rooms, a few decades, and some furnishings and decorations, most housing is “normal.” The housing cited in Guinness tends to be unusual and extreme outliers.

Denver Broncos scoring at 3.13 standard deviations above the NFL average

Bill Barnwell puts the scoring of the 2013 Denver Broncos in statistical perspective:

That brings us to z-score (or standard score), the measure that analyzes a figure’s distance from the rest of the data set using the mean and standard deviation from the set. By comparing each team’s points scored to the league average (and calculating the standard deviation) for the points scored of each team from that given season, we can get a measure of how much better or worse it was than the average team from that season. Fortuitously, that measure also allows us to compare teams across different years and eras. It’s not perfect, since it can’t account for things like strength of schedule or whether a team let up late in games or not, but it’s a much better measure than raw points scored.

As it turns out, even after we make these adjustments, the 2013 Denver Broncos have still scored points at a higher rate through four games than anybody else since the merger. The Broncos are scoring points on a per-game basis at a rate of 3.13 standard deviations over the mean, which is unmatched over that 43-year run. No team has ever scored more frequently, relative to its peers, than the Broncos have done relative to the rest of the league in 2013.

Because these are standardized figures, it’s possible to translate each team’s scoring rate in 2013 figures and see how close it is to Denver. In this case, after we account for the different populations, a bunch of teams move closer to Denver’s throne. Chief among them is the 1991 Super Bowl–winning team from Washington, which scored 146 points through four games in a league whose teams averaged a mere 72 points through their first four tilts. Washington’s figure placed it 2.85 standard deviations above the mean and translates to 170.9 points scored in 2013, just 8.1 points behind the Broncos. Other famous teams follow: the 2000 Rams, 1992 Bills, 1996 Packers, 1981 Chargers, 2005 Giants …

And you thought standard deviations were good only for statisticians. If you know your normal distribution, that’s way above the league average. I can only imagine how Sportscenter anchors might try to present this information…

Actually, this is quite useful for two reasons: (1) it allows us to look at the Broncos compared to the rest of the league without having to rely on the actual points scored; (2) it allows us to standardize points scored over the years so you can compare figures over a 43 year stretch. Both advantages are part of the wave of new statistical analysis taking over sports: don’t just look at the absolute value of statistics but put them in comparison to others teams or players and also provide statistics that allow for comparisons across time periods.