Introduction
In 1988, Steffi Graf was the first tennis player in history to win the Golden Slam Award. In order to recieve this award, a player must win all four Grand Slam singles tournaments and the Olympic gold medal in tennis. Only three other players have won this prestigious award to date: Serena Williams, Andre Agassi and Rafael Nadal. Out of these four Golden Slam winners, I was curious to see if the two women had more of an affect on baby names during their professional career compred to the two men.
Hypothesis
Professional female tennis players who have won the Golden Slam Award have more of an influence on baby names during their careers compared to male tennis players who have also won this award.
Methodology
Steffi Graf
#babynamesPct <- mutate(babynames, pct = (prop*100))
#babynamesPct <- select(babynamesPct, -prop)
#steffi <- babynamesPct %>% filter(year > 1970 & name == "Steffi")
#ggplot(steffiplot, aes(year, pct)) + geom_line(color='darkgoldenrod1') + ggtitle("Steffi Plot") -> SteffiPlot
A variable titled ‘babynamesPct’ was created which calculated the percentage of babynames for a given year. For interpretation purposes, the percentage was calculated instead of using the proportion. Then, a variable called ‘steffi’ was created that was a subset of the babynames dataset. It filtered the data by years beyond 1970 with the name equal to ‘Steffi’. An additional term could have been added to ensure that only females were included in the plot (sex == ‘F’), however it is less common that a male would be named Steffi and therefore did not have a significant affect on the plot. The babynames dataset came from R Studio, which is also where the plots are created. Between 1980 and 1990, Steffi dominated women’s tennis. She first received international notice in 1975 when she lead her team to victory in the Federation Cup. In 1978 she was ranked number 1 after winning the Virginia Slims championship along with the Wimbledon women’s singles final. One year later, she was ranked the undisputed top player. The chart below shows a large spike in the name ‘Steffi’ in 1989. The ‘babynames’ dataset came from the US only, which was interesting because Steffi is originally from Germany and did not become a U.S. citizen until 1981. She received national attention as a female tennis player which seemed to have influence on baby names in the 1980s-early 90s in the U.S.
Serena Williams
#serenawilliams <- babynamesPct %>% filter(year > 1970 & name == "Serena")
#ggplot(serenawilliams, aes(year, pct)) + geom_line(color='brown1') + ggtitle("Serena Plot") -> SerenaPlot
A similar process was used to create the chart for the popularity of the name Serena. Serena Williams was the most recent Golden Slam winner. In 2002, she was ranked number 1 for the first time and later in 2004 won the Golden Slam. Serena’s father was a professional tennis player as well as her sister Venus. In the chart below, Serena’s name peaked in popularity in 2000. I thought it was interesting that her name peaked a couple of years before she was ranked number 1. Strangely, nothing tremendous in her career happened in the year 2000. She was ranked number 6 at the time, but she started off this year with a couple of losses. Ever since 2000, the name Serena has decreased, but the popularity is higher now compared to before Serena’s fame.
Andre Agassi and Rafael Nadal
#andreplot <- babynamesPct %>% filter(year > 1970 & name == "Andre" & sex == 'M')
#ggplot(andreplot, aes(year, pct)) + geom_line(color='darkorchid2') + ggtitle("Andre Plot")
#rafaelplot <- babynamesPct %>% filter(year > 1970 & name == "Rafael" & sex == 'M')
#ggplot(rafaelplot, aes(year, pct)) + geom_line(color='darkorchid2') + ggtitle("Rafael Plot")
Interestingly enough, the graphs of Andre Agassi and Rafael Nadal look very different from Serena Williams and Steffi Graf. The same process was used to create the each name variable, except a term was included (sex == ‘M’), which indicated that only males named Andre and Rafael are in the chart. In this case, it was more common that both sexes had the names Andre and Rafael, which made the graph look considerably different without the extra term to differentiate sex. Andre’s plot is stedily decreasing, which is normal due to the fact that there is a wider range of names today than there was in 1970. Between 1994 and 1997, Andre won the Olymic Gold for singles mens tennis. There is a slight peak around 1994 which was one year before he was ranked number 1 in the world. Rafael’s plot increases and then decreases more recently. Again, this trend is normal due to the proption of babies named Rafael being smaller because of the vast amount of names today. In 2006, there seems to be jump in the percetange of ‘Rafael’ names. He was ranked number 2 overall tennis player a year before which explains the peak in popularity of Rafael’s name during this time.
Results
All four charts had different patterns, but the females seemed to have greater and more distinct peaks compared to the males. Arguably, the names Andre and Rafael are more common than Serena and Steffi which explains why there is not a clear peak in either of Andre and Rafael’s charts. There is less data for Serena and Steffi’s names which is why the peaks for their charts look considerably larger compared to both the males. Additionally, it seems like each individual’s respective name peaked in popularity when they were ranked as one of the top 10 professional tennis player during their time. This is a common thread between the male and female athletes. In most charts the popularity in baby names peaked when they were high in world ranking, and it wassn’t until years later the individual’s received the Golden Slam Award. This makes sense considering winning the Golden Slam is extremely difficult so anyone who is lucky enough to win this award is bound to have dedication and skill. Another important point is that spelling variations for these names also should be taken into consideration. If someone was named Steph, which would be considered a variation of Steffi, the results would look very different.
Conclusion/Further Research
Billie Jean
#billie <- babynamesPct %>% filter(year > 1970 & name == "Billie")
#ggplot(billie, aes(year, pct)) + geom_line(color='cadetblue') + ggtitle("Billie Plot") -> BilliePlot
The question remains: whether or not the actual Golden Slam Award affects or the high performance ranking affects the popularity of babynames during that time period. Although Billie Jean did not win a Golden Slam, she was a very influential women’s tennis player. In 1973, at age 29, Billie Jean won the “Battle of the Sexes” tennis match against 55 year old Bobby Riggs. The match attracted an estimated 90 million people around the world. Jean’s win was considered a milestone in public acceptance of women’s tennis. The graph below shows the name Billie peaking at around the same time she beat Riggs. This event in history could explain why female tennis players had a greater percentage of babies named after them compared to males. Regardless, for males and femlaes professionalism seems to be a common theme in popularity of baby names. There is room for further research here. It would be interesting to see if other sports had different outcomes. Would a predominately ‘male sport’ have an influence in male baby names? For example, is there a correlation between the peak in a professional football players career and influence on male babynames? Or is there a correlation bewteen the peak of a gymnasts professional career and influence on female babynames?
