This article done by the Washington Post entitled "The Wizard Shooting Stars" is an interactive data visualization charged with helping Washington Wizard fans compare the type and success rate of the shot selection their team took in 2013.
The article begins with showing us a rather stimulating graph that has 6,920 lines (1) heading towards a basketball hoop. Each line illustrates where each shot was taken on the court by the Washington Wizards in 2013. The use of these lines to correspond to each shot in this graph is both a strong way to show each piece of data/shot attempt in that it follows the same route aesthetically as a ball going towards a hoop as opposed to a chart that shows no similarity to a literal basketball shot. These lines follow in line with the data visualization rule of simplicity in that no extra detail is put in to detract readers from the actual data. What this chart lacks is being able to distinguish made field goals and attempts in this chart for there is no explanation as to what the varying colours of the lines mean. We see a clutter of colour varying from white to orange and no way of distinguishing which is which.
Once viewers have chosen a player, ((2) We picked John Wall in our case) we see a similar graph but now with just the shots John Wall has taken. On top of the updated graph we saw before, we now have two extra graphs (4, 5) that give us a birds eye view of where the data/shots take place rather than just the length away from the hoop. Specifically in chart (4), this is a very accurate way of showing exactly where the player is shooting from with each tiny red and white circle symbolising a shot. As well as little bagels to break down how the specific player was taking his shot ie. Jump shots, layups and/or dunks. This is effective because we can definitely tell the difference between the 3 bagels in chart (4). Chart (5) is helpful in comparing the specific player to the average player in the NBA and does a good job in showing the data's specificity; however, it brings in new information that isn't directly relevant to the team. A good comparison but perhaps not one that needs to be there.
The static nature of graph (5) is not a failing per say, but probably would have been more effective if it was some data that changed with the different options like the two other graphs.
The truly impressive thing is how many ways they have made the data available to be viewed and while the colours seemed cluttered and complicated before, now very simplistic and easy to maneuver. Overall the interactive part of the data visualization is very easy to use.
The article then goes into trying to visualize the trend of John Wall's shooting by trying to symbolize the writing "58 percent of Wall's shots came from the 15 to 29 feet range" (8) in the varying degrees of circles corresponding with where he's shooting from the floor. This is a little too complicated in that the only way of connecting the information being portrayed in (8) by careful inspection. As well as the failure of the cardinal rule of bubble graphs not needed, as the numbers are powerful enough statistics. Or perhaps even if they put the numbers in the bubbles. If they had highlighted (8) with a greyish background it would have been easier to connect.
Lastly, all the labels of graphs are labeled in full words and not acronyms but here in (9) we see it used here. For a basketball fan these acronyms would be easily discernible as FGM = "field goal made" and FGA = "field goals attempted" but may be too cryptic for the average sport fan.
URL: http://www.washingtonpost.com/wp-srv/special/sports/wizards-shooting-stars/
