Statistics

More on NFL Scoring

lions-johnsonAs the Detroit Lions prepare for their first compelling Thanksgiving Day game in 15 years, I thought I would revisit my pre-season hypothesis that scoring in the NFL would be down in 2011 due to the new kickoff rule.

A quick recap of my argument:  the new kickoff rule will result in more touchbacks, which will reduce overall starting field position, which will result in fewer points being scored.  An elementary analysis suggested that per-game scoring would be down by about 2 points per game.

The first two weeks of the season saw record-setting offensive production:  scoring was actually up by 2.5 points per game!  But now, with more than half the 2011 NFL season in the books, the average points-per-game is 44.07.  During the 2010 NFL season, the average points-per-game was around 44.16.

A TV analyst recently suggested that scoring decreases as the season progresses, due to factors like weather and injury.  Not only does this give me another idea for a math and sports analysis, it also gives me hope that perhaps my pre-season prediction may still come true!

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By patrick honner, ago

Google Public Data Explorer

Google’s Public Data Explorer is a great, free resource for students and teachers interested in data science and statistics.

http://www.google.com/publicdata/home

The site allows you to create custom graphs of available data sets, making it easy to experiment with different representations and explore the meaning of data.

There are several data sets available to play around with.   The OECD Factbook alone provides a wealth of raw data on education, energy, employment, population and migration, and many other categories.  There are also data sets available from the U.S. Census and the U.S. Bureau of Economic Analysis.  There appears to be support for using your own data sets, as well.

The data can be represented in a variety of ways:  histograms, line graphs, and even dynamic time series are all available.  It’s a great way to play around with data, and to build skill and intuition in data analysis, interpretation, and representation.

By patrick honner, ago

Bike Data Visualization

This is a cool visualization of bicycle usage in London:

http://www.digitalurban.org/2011/02/london-cycle-flows-sociable-physics.html

On October 4th, 2010, there was a public transit strike in London, which maximized bike usage in the city.

The creators claim that the flashes of light that represent the bikes move in accordance with the actual speed and path of the bikes they represent.

An innovative representation that puts me in mind of graph theory and networking!

By patrick honner, ago

Applications of Government Data

This is a nice resource from The Guardian that highlights some of the ways developers are making government data accessible to citizens.

http://goo.gl/00jmo

The projects include housing price analysis, roadway usage, government spending, and aggregation of community information.

The site wheredoesmymoneygo.org is especially interesting:  slide the bar to your yearly income, and see just how much of your salary is spent on education, health services, defense, and other categories.

Lots of applications to play around with, and plenty of food for thought!

By patrick honner, ago

A One-in-a-Million Baseball Play

As the 2011 MLB season winds down, there is a slim chance of something very unusual happening:  a three-way tie for the wild card playoff birth!

https://www.espn.com/mlb/story/_/id/7005248/three-way-tie-american-league-wild-card-race-cause-logistical-nightmare

It seems highly unlikely that the Red Sox, Rays, and Angels will actually all finish in a dead-heat, but if they do, it will pose a lot of problems for playoff scheduling.

This is a fun, if complicated, math question to think about:  what are the chances that after a 162-game season, three of the eleven teams ultimately vying for the wild card end up with identical records?

To investigate, the first thing I’d do is simplify the situation.  I’d reduce the number of teams and the number of games, give every team a 50/50 chance to win every game, and then see what happens.  After I’d explored a bit, I’d then consider complicating matters by using more teams, more games, and more realistic winning percentages.

A math challenge that any Strat-o-matic player could love!

By patrick honner, ago
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