{"id":15419,"date":"2019-07-15T11:58:35","date_gmt":"2019-07-15T15:58:35","guid":{"rendered":"http:\/\/studentwork.prattsi.org\/infovis\/?p=15419"},"modified":"2019-07-16T20:36:37","modified_gmt":"2019-07-17T00:36:37","slug":"nba-all-stars-and-their-relationships-2000-2016","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/visualization\/nba-all-stars-and-their-relationships-2000-2016\/","title":{"rendered":"NBA All Stars and their Relationships, 2000-2016"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

Introduction<\/strong><\/p>\n\n\n\n

The National Basketball\nAssociation (NBA) is the premiere and most watched professional basketball\nleague in the United States. Over the past two decades, there have been dozens\nof superstars in the NBA whose superior athleticism, will to win, and ability\nto garner support of fans worldwide is unprecedented. This network\nvisualization demonstrates both the biggest stars of this period, the\nrelationships between NBA all stars and the players who they have teamed up\nwith in an all star game, and the shifts over this era among who are the\nbiggest stars in the league. <\/p>\n\n\n\n

As a fan of the NBA who\nwas born in 1995, these players have played a pivotal role in shaping this\nleague drastically over the years of which I have followed it closely. I have\nwatched in awe as Bryant, Garnett, Shaq and Wade dominated; as Duncan, Pierce,\nPaul, and Gasol led; as LeBron single-handedly changed the way in which NBA\nstars, and athletes at large, negotiate their contracts and their agency as\nshapers of culture.  <\/p>\n\n\n\n

Materials<\/strong><\/p>\n\n\n\n

I was inspired by the Les\nMis\u00e9rables Character Network Visualization by previous Pratt Institute\nvisualization student nfesta. This visualization impressed me in that it very\nbeautifully demonstrates a complex web of interaction between a large number of\ncharacters, and the classification between groups allows for easy dissemination\nof who most regularly interacted with whom. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

I gathered my data from\nData World, which was uploaded two years ago by Gabe Salzer. The data lists all\nNBA all stars from 2000 to 2016, with additional information such as the team\nthey played on that season, their position, their height and weight, as well as\nwhen they were drafted and what country they are from. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Methods<\/strong><\/p>\n\n\n\n

Using code language\ncreated by Professor Chris Alen Sula, I brought the dataset into R as a CSV\nfile and converted each player to a string; based off which and how many all-star\nteams they played on. These strings became the basis of the nodes of this\nvisualization, each all star player in this era and the number of teams they\nplayed on; as well as the edges, which are the teammates they played with. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

As you can see above,\nGephi populates each string as a player (the target) and plots each player who\nthey played on an all-star team with as the source. The relationship is\nundirected as the dynamic between two players is a two way street: because one\nplayer is selected to an all-star team does not mean another one is chosen too\n(at least in theory, one would hope). <\/p>\n\n\n\n

Results<\/strong><\/p>\n\n\n\n

I was pleasantly surprised\nto see both expected and unexpected results from the Gephi visualization. While\nsome stars have obvious weight that they pull, such as Kevin Garnett and Tim\nDuncan, the presence of Ray Allen and Kevin Love as central characters sharing\nteammates from many teams and years is more surprising. What is also\ninteresting is the ways in which the groupings formed, with distribution of\nstars from the Western Conference all-star teams along the left side of the viz\nand stars from the Eastern Conference along the right side of the viz. Players\nwho are strictly to one of these sides likely played all their all star games\nduring this period on one conference, whereas those in the center split time\nbetween teams on the east and west coasts, and thus had the opportunity to play\nwith all stars from both conferences. For instance, Kevin Love (represented as\nthe top most center circle), has a smaller circle size than Parker, Wade or\nBosh on the edges, but has a central placement for his years as an all star\nboth as a Minnesota Timberwolf (Western Conference) and as a Cleveland Cavalier\n(Eastern Conference). <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

A very interesting pattern\nthat is made visible from this visualization is the difference among star\nchanges in the Eastern and Western Conferences. Whereas the Western Conference\nhas fewer overall players represented with a larger circle size overall and\nplacement closer together, the Eastern Conference seems to have more smaller\ngroupings of stars within this time frame, with many more one-off stars who\ngravitate around players who played in a few all star games over a smaller\nperiod. While the west has generation-defining stars like Kobe Bryant, Tim\nDuncan, and Dirk Nowitzki who were selected for many, if not most, of the all\nstar games during this period and collectively played with nearly every Western\nConference all star, the Eastern Conference has more isolated periods of star\ndominance, stretching the right side of the viz further out. Similarly, when\none zooms in further to the small pockets of one-off stars on the edges of the\nviz, they can notice patterns of time changes, with the lower most circles\nreflecting all stars in the early 2000s, the central outer circles displaying\nthe latter 2000s, and the highest outer circles showing the most recent new all\nstars. These one-off players gravitate around larger stars who bridged eras\ntogether, somewhat like planets. It is also interesting to see which stars pull\nclose together, such as LeBron James, Dwyane Wade, and Chris Bosh who shared\nmany years on the Eastern Conference all star team, as they were drafted the\nsame year to east coast teams, played together for years on the Miami Heat, and\nall remained in the east their whole careers (besides James, who has played for\nthe Los Angeles Lakers since 2018, which is after this data was collected). <\/p>\n\n\n\n

Lastly, it is important to\ncaution viewers that this visualization does not represent who is the biggest\nstar, the best player, or who had the most beloved following in the league.\nThis data reflects who played in the most all star games in a given time frame,\nwho they played with, and if they played in one of the two conferences\nthroughout their tenure or if they switched teams. That should explain why Ray\nAllen, a consistent but not universally recognized star, has a larger circle\nthan globally known stars like LeBron James and Kobe Bryant. If this\nvisualization were to represent players\u2019 star recognition or other intangibles,\nthey would surely be in the center drawing large amounts of smaller stars\naround them. <\/p>\n\n\n\n

Future Directions<\/strong><\/p>\n\n\n\n

In future studies, I am interested to learn\nhow to make a network visualization that demonstrates changes over time through\nanimation, so a viewer can see how over years star dominance changes \u2013 allowing\ncircles to move and change shape as their prominence changes. Similarly, I\nwould like to integrate more information about the players, where a viewer can\ninteract by clicking a circle and finding out more about their career\nstatistics, information about their background, and other intangible\ninformation that fans may want to know that could illuminate their role in this\nvisualization overall. <\/p>\n","protected":false},"excerpt":{"rendered":"

Introduction The National Basketball Association (NBA) is the premiere and most watched professional basketball league in the United States. Over the past two decades, there have been dozens of superstars in the NBA whose superior athleticism, will to win, and ability to garner support of fans worldwide is unprecedented. This network visualization demonstrates both the…<\/p>\n","protected":false},"author":666,"featured_media":15425,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[149,342,1],"tags":[48],"coauthors":[436],"class_list":["post-15419","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-labs","category-networks","category-visualization","tag-networks"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infovis\/wp-content\/uploads\/sites\/3\/2019\/07\/NBA_AllStars_Network_notextatbottom.jpg?fit=2480%2C3507&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paBdcV-40H","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/15419","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/users\/666"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/comments?post=15419"}],"version-history":[{"count":3,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/15419\/revisions"}],"predecessor-version":[{"id":15570,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/15419\/revisions\/15570"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media\/15425"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media?parent=15419"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/categories?post=15419"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/tags?post=15419"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/coauthors?post=15419"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}