The question of player combinations has fascinated me for some time. The topic is predicated on the belief that a team is, more than anything else, the aggregation of its players. Coaches have an impact, but it is the players on the field. More than individual players, even, I have been looking for ways to understand the results of player combinations.
Several years ago, I wrote about the importance of continuity in a team’s lineup over the course of the season. The piece has since been taken down (it will soon be republished on this site), but the thrust of the argument was that the most successful teams in Major League Soccer were able to identify a core group of players who played a significant amount of a given season together. Teams that couldn’t, or didn’t, coalesce around such a core were less likely to be successful.
Over the past several weeks, I’ve been re-visiting that thesis using some alternate strategies to see if they continue to hold true.
I started working with a new type of impact plot tonight, looking specifically at playing time compared against team goal difference. Dots representing each player are plotted along two axes: the horizontal axis records how much of the season the player has seen, while the vertical axis indicates the team’s goal difference during the player’s time on the field. Continue reading Plotting individual playing time against goal difference
This chart presents the attendance figures for Columbus Crew SC home openers since 1999, when MAPFRE Stadium opened. In the 16 year history of the stadium, crowd sizes have ranged between 10 and 25 thousand. The low point was 2011, while the high was unsurprisingly set in the stadium’s first year.
Attendance shows some correlation with game day temperature, as depicted above. This is not surprising, although the math – an R2 value of 0.3264 – indicates that temperature alone does not explain the variation. It appears that attendance varies by about 163 people for every degree of temperature gained or lost.
Other possible factors that could influence attendance include precipitation, opponent, competitive prospects, and the sales efforts by the front office. This last factor is particularly important, as shown by the attendance growth since 2011 after the team restructured their sales team.
Sometimes, creativity needs to be bounded. This is a lesson I’ve been learning (or perhaps re-learning) lately, and can be seen specfically in the display of players on this site.
When MRData launched, and through even today, the list of all time players has been rendered using a platform based on Isotope – which renders items in a grid:
This is very clever, but as time wore on, it became clear that “players as elements, rosters as a periodic table” isn’t a very useful metaphor. One of my goals for this year is to improve on this design, and the changes so far are looking awfully familiar: Sometimes, it isn’t necessary to completely rethink a display. Sometimes, the traditional method of displaying a set of information (in this case, a table) is generally okay, and only simple tweaks are needed (in this case, depicting a player’s career using a visual timeline).