Football:

http://thedailyviz.com/tag/nfl/

This line chart or line plot shows the Cowboys average penalty yards per game in comparison with the rest of the NFL’s average from 2003 to 2011. I find the color scheme of this chart appealing since navy is used for the Cowboys and orange is used for the NFL average. These colors are vastly different even at first glance which makes it easy for the viewer to differentiate between the two averages. The title and the labels on the x and y axis of this plot are clear and concise. In this chart, we see that as time goes on, the Cowboys received more penalty yards per game while the rest of the NFL had a vast drop in penalty yards per game from 2006-2008, with their penalty yards per game later increasing in 2009.

Basketball:

https://www.r-bloggers.com/competitive-balance-and-home-court-advantage-in-the-nba/

This bar graph represents nine different NBA teams and their number of championships. Although this graph uses all the same colors for each team I still find it easy to use and understand. The x and y axis are clearly marked with labels that are simple and concise. However, I do think that using different colors for each team would make this graph even more appealing. If the graph were to use dark blue for the Mavericks, silver for the 76ers, red for the Rockets, light blue for the Pistons, maroon for the Heat, green for the Celtics, grey for the Spurs, black for the Bulls and purple for the Lakers, this chart would produce more visual appeal.

Baseball:

https://blogs.fangraphs.com/dont-blame-hitters-for-all-the-strikeouts/

This scatterplot represents the relationship between fastball velocity and strikeout rates since 2002. I like this graph because it is not cluttered, as scatterplots can sometimes become. Also, the labels make it easy to understand what is being calculated. I can see that the lower the fastball velocity, the lower the strikeout rate. However, when the fastball velocity is high, the strikeout rate greatly increases. I think it’s important for scatterplots not to have too many data points because once the chart gets crowded, it becomes harder to understand and comprehend the information being presented. One thing I think could be better is the color used. While the pale blue is an appealing color, I think the chart would benefit from using a bolder color, such as dark red, green or blue.

Hockey:

http://slatekeeper.blogspot.com/2011/06/201011-nhl-age-histogram.html

This histogram shows the relationship between the number of NHL players and the year they were born for the 2010 and 2011 season. For starters, the title is simple and to the point. The labels on the x and y axis correlate with the title and are clearly marked. I also like the spacing between each of the bars which makes it easy to comprehend each stat on its own. Yet, this histogram also captures the wide variation between players born in the early and late years compared to players born from ’84 to ’87, which is the most common.

Soccer:

https://www.sportskeeda.com/football/shocking-stats-why-lionel-messi-poor-atletico-madrid

This heat map represents Lionel Messi’s location in a F.C. Barcelona vs. Atletico Madrid game. I like looking at heat maps because they put a visual in your head of the actual game rather than just looking at numbers and stats. In this heat map, we see that Messi spent most of his time on the opponent’s side, which makes sense considering he is a forward. All the red marks are the spots he spent most of his time at. One thing I find confusing about this map is the location of the team names and the arrows. I think it would be more effective and visually appealing if the name of each team was written in the center of their side of the field.