So, a little while back I compiled some data on how the "home" wildcard did at the four majors. By "home wildcard", I mean a wildcard entry who is from the same country that the tournament is hosted in. So, I went back and looked at how these main draw wildcards performed in the tournament they were given a wildcard into. I will be removing "home" wildcards who played each other in the First Round from the data, but will be using "home" wildcards who played a different wildcard not from the host country. And while this article may seem a bit repetitive given how much attention I have given wildcards on this blog, especially recently, I hope that this post is very informative.
For the sake of this post, let's give each round a point value. So, for instance, if a wildcard lost in the First Round, their result would be given a value of "one", while if a wildcard lost in the Final, they would be given a point value of "seven". Because I want to be complete in my specifications, despite it not occurring in the data, if a "home" wildcard wins the tournament they would be given a score of "eight". Therefore, you could look at a player's "score" as what round they lost in, correlated to a numerical value.
There are many different ways to group the data, which runs from the 2013 Australian Open through the 2016 French Open, but let's start with grouping the "home" wildcards by major. Let's look at the Australian Open first. There were 36 "home" (eligible) wildcards to be used in this analysis. The range of scores ranged from a home wildcard losing in the First Round (and, thus, receiving a score of one) to those losing in the Second Round (and, therefore, receiving two "points"). The Australian Open has a mean score (rounded to two decimal places) of 1.17. Meaning that the vast majority of home wildcards lose in the First Round at the Australian Open. With the range being so small, this is not surprising from a data standpoint, but given the larger ramifications of what this means, given that 1.17 is a shockingly low number, it seems as if the local players given these wildcards were, for the most part, not ready for the big scene.
Now, let's take a look at the data for the French Open. There were 46 home (eligible) wildcards given at the French Open during the timespan previously mentioned, which is much higher than the number given out at the Australian Open. The range of scores went as low as one and as high as four. The French Open had a mean score of 1.39. While this is still a shockingly low score, it is a tiny bit higher than the Australian Open, which shows, perhaps, that better home players were given wildcards at Roland Garros. However, one could also make the case that a larger sample size led to a larger chance of a home wildcard making a run, and also that, had the Australian Open given 50 home wildcards away, that their score could have been even lower since, perhaps, France is more of a tennis "hotbed" than Australia.
Wimbledon (data only 2013-2015) gave out 22 home wildcards. This number is significantly less than the two previously mentioned majors because, at the time of the writing of this article, the 2016 wildcards haven't been given out yet and because Wimbledon just seems to give out less home wildcards than the other majors anyways. Wimbledon had a range of scores from one to three. The mean score for Wimbledon is 1.18, just barely above the Australian Open's mean score, but below the French Open's mean point total. Although I have not collected all wildcard data, I am speculating (the latter due to conjecture from Men's Tennis Forums) that this low score, and low number of home wildcards given, could be due to a combination of a lack of professional-level talent in Great Britain and the LTA just deciding to award wildcards to more worthy foreigners who have done well that season on grass.
Finally, in terms of this specific analysis, let's take a look at the data for the US Open. The US Open (2013-2015) has given out 37 home wildcards, significantly more than Wimbledon gave out in the same time frame. This is even more than the Australian Open has given, but with a year less of data! The number of wildcards, in a four year increment, would be 49.33, slightly greater than the number of wildcards (both eligible and non-eligible for analysis) at the French Open (48). The US Open's range of scores went from as low as one to as high as four. The mean point total for the US Open is 1.43, the highest of any major. And while this shows that, roughly, home wildcards do generally still fall in the First Round, it shows home wildcards at the US Open, in the sample size collected (although smaller than the French Open and Australian Open) does do a better job with picking out home wildcards that can go further in the draw. And while this could be due to the deep talent pool that the USTA has to work with, this definitely gives me a little bit more confidence in the wildcard selection process at the US Open.
The other angle I want to take when exploring this data is what the difference in scores for female home wildcards as opposed to male home wildcards. I will start with female home wildcards. In total, from the 2013 Australian Open to the 2016 French Open, 73 home (eligible) female wildcards were given. The scores of these wildcards ranged from one to four. The mean score for female home wildcards is 1.29. This number, once more, shows us that the vast majority of female home wildcards are losing in the First Round. Now, let's see if the same can be said for the men.
In total, there are 68 male home (eligible) wildcards to be used in this analysis. The range of scores varied from as low as one to as high as three. The mean score for male home wildcards is 1.32. This means that, while the majority of male home wildcards did lose in the First Round, perhaps the grand slams were slightly better at choosing male home wildcards, as opposed to female ones. However, it would take many more majors' worth of data before we could really make any definitive conclusions or takeaways in regards to the relationship between female vs. male data.
So, with all of this said, we cannot really takeaway much from the data, as it was mainly constructed for my readers' enjoyment and intrigue. However, if we are to say that this is a representative sample, which I think it is, we can say that all majors, whether selecting male or female wildcards, are not selecting players who are making deep runs in these majors, unfortunately. Why this is, exactly, is not known, but the data does paint an interesting picture regarding home wildcards at majors.
Obviously more research is needed, and with no margin of error analysis, there is not much I can say with certainty regarding the data, so take all of this analysis with a grain of salt. However, that doesn't mean we should totally disregard the data either. Because, really, with as low as the numbers are, maybe less home wildcards should be given out.
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