The maps on this page are based on data that is older than the March 2005 data.  They are included here because they suggest ideas of what one might wish for, using updated information.

The map below merges the databases for the 23 maps into a single file and calculates the mean at the national level (13.144 ACBL members per ZIP code area for the conterminous 48 states) and the classes on either side of the mean (at intervals of 0.5 standard deviations).

This National Map is derived from total "count" by ZIP code region.  Total count is useful for certain types of analysis; however, it gives a partially skewed picture of pattern--is Southern Idaho really more of a bridge hotspot than coastal Florida?  If not, then the reason for such distortion is that the total number in a large polygon in Idaho is about the same as the total number in a small polygon in Florida:  the large polygon of the same color is simply more visible.  Absolute measures, such as total count, have use in a variety of contexts but not in all contexts.

Maps that show total numbers in relation to another variable, such as to total land area or total population, may reduce effects of the sort described above and have additional utility.  The set of maps below shows maps based on introducing population and land area (darker shades of red show higher values; yellow means no members).   The datasets underlying these maps are partitioned into 5 "quantile" categories with roughly the same number of observations in each category (other methods of partitioning the datasets would produce spatial patterns different from these).  All maps have merits and drawbacks; the challenge is to select the map that best suits the need at hand--there can be no single "best" map.

In the "density" maps above, again large land areas with low population but high percentages of ACBL members tend to dominate the picture.  That domination may not be realistic in reflecting where national focus on bridge is highest; it may, however, suggest areas where recruitment of members in rural areas has been successful or a variety of other issues best analyzed by regional experts.  The first map in the sequence above shows US 48 state boundaries, for reference purposes.  The second map shows the same pattern with 48 state boundaries removed (as they can distract from visualizing national pattern).
In the "land area" maps above, the national picture that one might expect is reinforced.  Again, the first map in the sequence above shows US 48 state boundaries, for reference purposes.  The second map shows the same pattern with 48 state boundaries removed (as they can distract from visualizing national pattern).  The Boston-Washington corridor, with its high concentrations of urban population dominates the picture, as does (once west of the Appalachians) the central EW axis of scattered cities from Pittsburgh to Chicago together with the associated Great Lakes perimeter.   The large cities of the West Coast, of Texas, and of the coast east of the Appalachians are also evident, again, as one would expect from simply looking at US urban patterns.

In addition, the cities of the Southwest, and of Florida, emerged as strongholds of ACBL members--not necessarily expected from the general urban pattern, but certainly expected when one considers the location of the retired population.   This well-known observation suggests that maps that separate the population according to age (these require work to get US Census data, by County, into a form that is reasonable to use with ZIP code boundaries) might be of interest in studying the spatial aspects of the ACBL dataset.  The difficulty here is that many of the population datasets that are readily available are partitioned by county, whereas the ACBL dataset is partitioned by ZIP code area.  County boundaries and ZIP code boundaries do not mesh.  The map below shows one approach to this issue.  In it, counties in Florida are represented as pie charts:  the purple piece of the pie represents the population of Florida aged 50 or over.  The light yellow piece represents the population under age 50.  These pies are superimposed on the ZIP code polygon boundaries to suggest a general idea of age distribution in given regions.

Another strategy for viewing population patterns is the "dot density" map.  Dots are scattered, based on information from the underlying database, at the local level:  1 dot represents X people (or some such).  The scatter at the local level is random, so that one cannot infer that the position of any dot at this local level is "correct" positionally.  To make sense of the dot scatter, one must step back and view it at a more global level, where the local clustering begins to make sense.  Thus, the map below uses 1 dot to represent 1 ACBL member.  The dots are randomly scattered within ZIP code areas.  Then, the ZIP code area boundaries are removed and state boundaries are inserted.  The cluster of dots in southeastern Michigan (for example) represents a concentration of ACBL members in the Detroit metropolitan area; it does not show, however, where each individual is located within that metro area.  Dot density maps may also suggest means for looking at data sets that do not mesh.

District 12 Maps:  selection
first one shows number of District 12 members by ZIP Code;
second one shows population of ZIP codes within District 12
Link to interactive map showing great detail

Link to interactive map showing great detail

Click to see interactive map!

Maps of District 12 with demographic analysis by County, based on U.S. Census Bureau data and categories:
What patterns do these maps suggest:
Reasons to consider such patterns involve marketing of bridge for clubs, for tournament staff, and for the ACBL:  educational outreach might thus be considered of particular importance in university towns and in urban areas with high concentrations of African-Americans.

This Atlas of international, national, and regional bridge maps is designed for visualizing information about the broader bridge-playing population.  Selected problems are considered using the evidence of maps.  These maps are tied in the computer to various ACBL databases and U.S. Census databases.  Thanks to Jay Baum, ACBL CEO, Rick Beye, Carol Robertson, Richard Oshlag, and Ed Evers, ACBL, for providing the materials directly to Sandra Arlinghaus, who then created the map sets using GIS software (ESRI, ArcView 3.2) that forges a dynamic link between underlying database and outline base map.  Graphic adjusments of various kinds were made in Adobe PhotoShop or Adobe Illustrator.

The linked materials display data from the ACBL national data base.  If you are looking for local materials related to finding a bridge club, please go to maps created originally by Jim Lahey, former District 12 Webmaster, and maintained by Alan W. Bau, current District 12 Webmaster (http://www.d12bridge.org/).  If instead, you are looking for materials about the broader bridge-playing population, at the regional and national levels, you are in the right place!

Click here to send an email to Bill Arlinghaus
Click here to send an email to webmaster of this page