The World Ultimate Championships take place every four years. In 2016, they were held in St Albans, UK, and hosted the largest number of teams in the event’s history.
There has never been any real analysis performed on the results and statistics recorded at Ultimate tournaments, so I wanted to see what could be discovered and communicated to the ultimate-playing world that was never possible to see before.
I used Processing.js to map all goals scored in the tournament (over 10,000) in a timeline, and show which of the five divisions they related to. It is clear to see the gaps between game slots (typically games started at 9:30, 11:30, and so on), and also the drastically reduced number of games that took place on Thursday, due to terrible weather rendering the majority of the fields unplayable.
In Ultimate, all teams score their opponents on how well they embodied the “Spirit of the Game”, or fair play, that defines our sport. Keeping record of this allows the governing bodies to reward those teams that are consistently rated highly, and to work with those with lower scores to find out whether there are any problems.
Scores are given on five criteria:
I used Processing.js to plot all teams’ spirit scores against their finishing position in the tournament, to see if there was any correlation between the two. Ideally, there would be no correlation; however it is sometimes the case that teams finishing lower down the order receive a higher spirit score from each other, particularly in the Positive attitude category. In this case, there was no solid correlation between finishing position and spirit score.
The green blocks in the centre show which teams received an above-average score for each of the five scoring categories.
In Mixed Ultimate, men and women play on the same team, with 4 of one gender and 3 of the other from both teams playing on the field at the same time. This means that there are four ways for a mixed team to score a goal:
I decided to plot the breakdown of all mixed teams’ goals and see which teams spread their goals out between all four methods, and which relied more heavily on one method of scoring. It is a commonly held belief that teams who vary the way they score goals are more successful, and those who rely on one method are more predictable, and therefore easier to defend against.
It is clear that the majority of goals are scored by the male to male method, and although there is no evidence to suggest that teams who spread the scoring around perform better, there is definite correlation between performance and the number of goals scored by the female to female method.
Visualising 10 years of entry/exit data about the London Underground.
Analysing the four sample-heavy albums of one of my favourite bands to see what’s going on.
What happened when? Who changed what? Where did everybody go? I decided to find out.
500 major events from throughout history, displayed on concurrent timelines.