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Ben Crissy
Ms. Tillery
AP Literature
18 November 2011
Sports Statistics
What is the correlation between a basketball team’s performance at a home and an away
game? Few people would know the answer or even how to solve for the answer. This question
could only be answered by thorough research from a sports statistician. Sports statistics are used
every day to represent teams’, players’, and coaches’ performances in sports. The ever expanding
realm of sports statistics is structured by the statistician’s responsibilities, statistical categories,
and the analysis of the statistics.
Most important to sports statistics is of course the statistician. The responsibilities of the
statistician can be grouped into eight different duties:
Recording statistics as events happen, auditing stats with play-by-play,
preparation of final stats for league records, serves as official scorer for both
teams, computer data entry, preparation of final and midgame summary reports
for the media, keep up to date on changes in statistical scoring rules, and
involvement in resolution of disputed calls (“Team Statistician”).
The most obvious duty of a statistician is to observe the game and periodically record statistics as
they occur. For example, basketball includes many statistics such as: field goals, blocks, steals,
fouls, assists, rebounds, and countless more. When sports were first introduced, statistics were
recorded by hand on a scorecard. In today’s world, some statisticians still prefer to manually
record statistics, while many have downloaded programs on laptops or other hand-held devices
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to minimize the time it takes to record so they can focus more on the game. Sports statisticians
need to be able to multitask and operate quickly in order to meet the demands of the press, the
teams, and the fans.
In the same way that statisticians report to the media, the media reports to the fans.
Fantasy sports have become increasingly popular as of late; they engage the fan by
accompanying points to real life statistics in separate stat categories. Although the fans do not
need to calculate the data, most of the statistics can be easily determined:
For most statistical categories - points, rebounds, blocks, steals - that's simple:
add 'em up. But for the percentage stats - most commonly field goal percentage
and free throw percentage - it's not that easy. For those categories - and any others
that consider a team's percentage as opposed to a team's total - you tally the
numbers that make up the percentage, and then divide (Zegers).
Statistics such as points, rebounds, and blocks should be commonplace to any basketball fan.
The already easy to observe statistics become even more user friendly with fantasy sports.
However, statistics can create a facade to disguise glaring defects, for example “[Juwan] Howard
was 10th in the league in scoring average, but fourth in minutes per game and third in field-goal
attempts. These numbers suggest that he wasn't really making the most of his time on the court,
something the Washington organization would have noticed if they had been looking at the right
metrics” (Turbow). At a glance, Howard would appear to be an outstanding player by viewing
his core stats that are recorded during the game. Upon further evaluation, it can be revealed that
many players, as in Howard’s case, are not always as successful as they may seem at first.
Evaluating all of a player’s statistics as a whole is the only true way to identify a player’s
strengths.
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Furthermore, there is more to sports statistics than what is on the surface. In a recent
study, Jaime Sampaio, Eric Drinkwater, and Nuno Leite studied the effects of season period,
team quality, and playing time on basketball players' game-related statistics:
While playing time was significant in almost all variables, errors were the most
important factor when contrasting important and less important players, with
fewer errors being made by important players. The trends identified can help
coaches and players to create performance profiles according to team quality and
playing time. However, these performance profiles appear to be independent of
season period.
After a devastating loss, teams can often wonder what they should have done to achieve victory.
With this discovery, coaches can better prepare their teams for games by adding focus to ball
handling, control, and passing. Evaluating statistics such as this can greatly affect future game
results and philosophies. Defeats can be demoralizing to players, coaches, and fans. On the other
hand, sports statisticians can use data from losses to expose areas that need improvement. “An
also important finding was that, in best teams, the nonstarters' performance was worse in the
games that the team lost, whereas in worst teams, it was the starters' performance that was worse
in the games that the team lost” (Gomez et al.). Not surprisingly, teams that are deemed bad lose
games mainly due to their starters’ lack of talent. On the contrary, coaches of talented teams may
be shocked to discover that losses can be a result of poor game play by players who do not start.
Normally, coaches are quick to place blame on the starters. Thanks to this detection by sports
statisticians, coaches can better prepare their teams as a whole to improve their game play.
Additionally, the specific statistics that are analyzed produce different insights. Sports
statistics have evolved over the years to include various perspectives of players. “The new math
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is not just for evaluating individual player value. It's also a useful tool in scouting team
tendencies” (Ballard). Advanced statistics such as player efficiency ratings can be extremely
helpful in deciding which player to start and who to bench. However, these statistics can also be
useful if they are used to scout the matchup and determine the opposing team’s strengths and
weaknesses. Statistics are commonly inspected to review past events. On the other hand, stats
can be used to forecast future results. “One of the dangers [of evaluating statistics] is to draw on
historical information that seems to be telling you something will happen and forget that’s why
they play the games. I know it’s a cliché, but things reach cliché status for a reason” (Peter
Hirdt). Statistics do not only display what happened in a game; they can also be used to predict
what will happen in a game. Companies such as the Elias Sports Bureau that have been in the
business for numerous years can predict the outcome in a game based on past games. Statistics
that display mind boggling information such as the probability of a basketball team winning
while down by 10 points in the fourth quarter frequently appear on the television to inform fans
watching of the rarity of such an event occurring. Statistics not only tell about the past, but they
can also determine the expected outcome of a game.
Thoroughly evaluating statistics after games can prove to be beneficial for preparation of
future games. Successive games can really take a toll on a team and affect their performance. “A
discriminant analysis allowed identifying the two point field goals made, the defensive rebounds
and the assists as discriminators between winning and losing teams in all three games” (Jaime
Sampaio, et al.). This study was compiled in an effort to study the recorded statistics of winning
and losing teams that played in consecutive games. With this information, a sports statistician
can conclude that shot selection, ball control, and passing are essential to a team’s performance
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when playing consecutive games. Analysis of statistics such as this can aid teams who are facing
successive games to perform better and achieve victory.
Many coaches are interested in what stat categories are the most likely to yield season-
long success. Sports statisticians have conducted studies to determine which of the core stats
produce successful seasons:
The results allowed discrimination between best and worst teams' performances
through the following game-related statistics: assists (SC=0.47), steals (SC=0.34),
and blocks (SC=0.30). The function obtained correctly classified 82.4% of the
cases. In conclusion, season-long performance may be supported by players' and
teams' passing skills and defensive preparation (Ortega).
While a lack of scoring may appear to be an obvious reason for a losing season, statisticians have
proven that this is not the only factor. The most successful teams of the ACB League had
significantly higher rates of assists, steals, and blocks as compared to teams with poor
performances. Coaches can utilize this data to improve their teams’ passing by sharing the ball,
and to produce more blocks or steals by revising defensive strategies. Likewise, statisticians have
studied data based on the location of games, the outcome, and the statistics produced.
“The multivariate analysis showed that winning teams differ from losing teams in defensive
rebounds (SC = .42) and in assists (SC = .38). Similarly, winning teams differ from losing teams
when they play at home in defensive rebounds (SC = .40) and in assists (SC = .41)” (Palao).
Teams may often be flustered when they leave their safe haven to play an away game. When in
the opponent’s building, teams often have to face the dreaded “6th Man”, the fans. Sports
statisticians have found that there is not much discrimination between stats for the away teams to
worry about. Teams have only seen small fluctuations in the defensive rebound and assist
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categories when playing away games. In order to be victorious on the road, coaches only need to
tweak their game plan a little to favor rebounding and assists.
In summary, sports statistics are the central component to the success of sports today.
Behind every single statistic is a dedicated statistician who works for the benefit of the fans and
the players. Sports statistics are based upon the statistician’s responsibilities, various statistical
categories, and the analysis of the statistics.
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Works Cited
Ballard, Chris. "MEASURE Of Success." Sports Illustrated 103.16 (2005): 60. Academic Search
Complete. Web. 15 Nov. 2011.
Gomez, Miguel et al. "Discriminative Game-Related Statistics Between Basketball Starters And
Nonstarters When Related To Team Quality And Game Outcome." Perceptual & Motor
Skills 103.2 (2006): 486-494. Academic Search Complete. Web. 15 Nov. 2011.
Hirdt, Steve and Peter. "Seven Questions with the Hirdt Brothers of Elias Sports
Bureau." Interview by Ryan Stellabotte. Fordham. Ed. Ryan Stellabotte.
N.p., n.d. Web. 15 Nov. 2011. <http://www.fordham.edu/images/whats_new/
magazine/fall11/sevenquestions.pdf>.
Ortega, Enrique et al. "Basketball game-related statistics that discriminate between teams'
season-long success." European Journal of Sport Science 8.6 (2008): 369-372. Academic
Search Complete. EBSCO. Web. 17 Oct. 2011.
Palao, José et al. "Differences In Game-Related Statistics Of Basketball Performance By Game
Location For Men's Winning And Losing Teams." Perceptual & Motor Skills 106.1
(2008): 43-50. Academic Search Complete. Web. 15 Nov. 2011.
Sampaio, Jaime, Eric J. Drinkwater, and Nuno M. Leite. "Effects of season period, team quality,
and playing time on basketball players' game-related statistics." European Journal of
Sport Science 10.2 (2010): 141-149. Academic Search Complete. EBSCO. Web. 17 Oct.
2011.
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Sampaio, Jaime et al. "Effects of consecutive basketball games on the game-related statistics that
discriminate winner and losing teams." Journal of Sports Science & Medicine 8.3 (2009):
458-462. Academic Search Complete. EBSCO. Web. 17 Oct. 2011.
"Team Statistician." Statistics in Sports. N.p., n.d. Web. 15 Nov. 2011.
<http://www.amstat.org/sections/SIS/Careers%20in%20Sports%20Statistics/
team.html>.
Turbow, Jason. "Settling The Score." Popular Science 273.2 (2008): 66-70. Academic Search
Complete. Web. 17 Oct. 2011.
Zegers, Charlie. "Fantasy Basketball 101: Understanding Percentage Stats."
About.com. N.p., n.d. Web. 15 Nov. 2011.
<http://basketball.about.com/od/fantasygames/a/percentage-stats.htm>.