Introduction:
Welcome to our Information Visualization project. The main goal of the project was to create an interactive application to explore and enjoy the world of football transfers.
The viewer can explore the huge data on player transfers to find interesting data points, patterns and hidden structures.
Top:
For reference the club name and league are displayed in the top left together with a their logos.
The search bar enables the user to directly get information on a club they are interested in.
Main page:
Aside from the top view the page contains two key elements:
First a bar plot displaying the transfers of the current club, QPR, with other clubs or leagues
and Second a line plot showing a timeline of transfers since the year 2000.
All the transfers are split into to two categories, incoming and outgoing transfers.
The timeline helps the viewer to identify interesting years to explore in further detail with the bar plot and recognize trends in the data.
Up to 20 other clubs or leagues are displayed in the bar plot with various details in descending order.
Furthermore, by hovering a specific transfer the user can get more details, such as the involved player or season.
They can even click on it and are then transfered to the player information on transfermarkt.
Options:
Our data contains many different dimensions for exploration. Therefore, we added the option to select them individually.
The first dimension is Time - the year a transfer was done - (why is this interesting??)
The second dimension is the transfer entity - the club or league a transfer was done with - (why is this interesting??)
And last the transfer the transfer value - either in british pound or the total amount of players transfered - (why is this interesting??)
For the line graph the viewer can only change the transfer entity and value.
Also, the user can change the ordering of the detail graph.
All these options give the viewer the chance to explore the data as they wish, the can explore in high detail by focusing on clubs or zoom out and focus on the bigger picture and look at leagues.
Search:
The search bar makes real time suggestions on what the user might be searching for.
Additionally, if the user does not have to select a certain year from the options, but they can click on it in the line graph and get the details in the bar graph immediately.
Evaluation:
Our data visualization shows multiple interesting points.
For example. Some clubs, like Ajax Amsterdam consistently have much higher incomes from selling players to other clubs contrary to Arsenal, which consistently spent much more on new players than they earn on outgoing ones.
Another example is the result, that many clubs have few very high value trades each season, and many free or low value transfers.
Furthermore, some leagues like the spanish LaLiga, have much more internal transfers, regarding value and amount of players than others, e.g. the britsh Premiere League.
jan-gerling
commented
4 years ago
Introduction: Welcome to our Information Visualization project. The main goal of the project was to create an interactive application to explore and enjoy the world of football transfers. The viewer can explore the huge data on player transfers to find interesting data points, patterns and hidden structures.
Top: For reference the club name and league are displayed in the top left together with a their logos. The search bar enables the user to directly get information on a club they are interested in.
Main page: Aside from the top view the page contains two key elements: First a bar plot displaying the transfers of the current club, QPR, with other clubs or leagues and Second a line plot showing a timeline of transfers since the year 2000. All the transfers are split into to two categories, incoming and outgoing transfers.
The timeline helps the viewer to identify interesting years to explore in further detail with the bar plot and recognize trends in the data. Up to 20 other clubs or leagues are displayed in the bar plot with various details in descending order. Furthermore, by hovering a specific transfer the user can get more details, such as the involved player or season. They can even click on it and are then transfered to the player information on transfermarkt.
Options: Our data contains many different dimensions for exploration. Therefore, we added the option to select them individually. The first dimension is Time - the year a transfer was done - (why is this interesting??) The second dimension is the transfer entity - the club or league a transfer was done with - (why is this interesting??) And last the transfer the transfer value - either in british pound or the total amount of players transfered - (why is this interesting??) For the line graph the viewer can only change the transfer entity and value. Also, the user can change the ordering of the detail graph. All these options give the viewer the chance to explore the data as they wish, the can explore in high detail by focusing on clubs or zoom out and focus on the bigger picture and look at leagues.
Search: The search bar makes real time suggestions on what the user might be searching for. Additionally, if the user does not have to select a certain year from the options, but they can click on it in the line graph and get the details in the bar graph immediately.
Evaluation: Our data visualization shows multiple interesting points. For example. Some clubs, like Ajax Amsterdam consistently have much higher incomes from selling players to other clubs contrary to Arsenal, which consistently spent much more on new players than they earn on outgoing ones. Another example is the result, that many clubs have few very high value trades each season, and many free or low value transfers. Furthermore, some leagues like the spanish LaLiga, have much more internal transfers, regarding value and amount of players than others, e.g. the britsh Premiere League.