This article describes an analogical use of National Basketball Association (NBA) statistics in an extension of an analogy originally offered by Claude Steele, Jay Rosner and Lee Ross. This analogy challenges the utility of the preeminent use of the SAT in admissions decisions by linking the use of the SAT to the selection of an NBA team using strength in free throw percentage as the only selection criterion. Two pedagogical usages of NBA player performance data are described here. The first usage reflects use of descriptive data alone to explicate the analogy. With a special focus on the 2005 NBA All Stars, it becomes clear that the league’s most dominant players are extremely weak free throw shooters. The second usage describes an actual simulation of the analogy using a video game system. Students select players for a team that will compete against the instructor’s team. However, the students’ team must include only the players with the strongest free throw percentages while the instructor is not similarly bound. By requiring the students to select their players in this manner, the danger of using one criterion to make such decisions is demonstrated. The impact of the exercise on students is also reported.
The use of analogies in teaching has been engaged by a number of authors. Much of the literature in this area is found in science instruction (Treagust, Harrison, and Venville 1996; Coll, France, and Taylor 2005; Silverstein 2000, 1999; Donald Bauhs 1999). Despite the predominance of the sciences, other authors have examined the value of analogical pedagogy as well (Hulsof and Verloop 2002; Glynn 1996; Garner 2005; Gayles 2004). The interdisciplinary use of analogies reflects its pedagogical value. This article offers a description and assessment of a class demonstration that I developed to elucidate one aspect of the debate around the use of standardized tests in admissions decisions. This demonstration is an extension of an analogy offered by Claude Steele:
Suppose that you were obliged to select a basketball team on the basis of how many of ten free throws a player makes. You'd regret having to select players on the basis of a single criterion. You'd know that free throw shooting involves only a few of the skills that go into basketball--and, worse, you'd know that you'd never pick a Shaquille O'Neal (1999, 54).
I have found that this analogy successfully encourages students to critically examine the inherent dangers in making a decision based on one criterion when (1) many criteria are available and (2) this criterion does not necessarily reflect the broad spectrum of skills necessary for success in a particular domain.
The use of this analogy demystifies certain aspects of the standardized testing debate by providing students with a real-world point of reference that is not as politicized as the primary centers of the standardized testing debate (i.e. race, gender and class). Further, by using NBA statistics, issues related to competition, performance and prediction are directly engaged by students. Expanding the class discussion to include the actual debate on standardized testing is served well by the use of this exercise.
Using EA Sports’ video game, NBA Live 2005, I attempt to bring this analogy to life by constructing a simulation pitting two teams against each other that reflect the analogy offered by Steele. While some authors situate video games as a direct or indirect cause of an increasing orientation towards violence – especially among young men (Garbarino 2000; Grossman and Degaetano 1999), others consider the relationship, actual or potential, between video games and meaningful learning experiences (Gee 2004; Amory, Naicker, and Vincent 1999; Baker 2003). NBA Live 2005 is best described as a sports simulation game. The simulation is extremely detailed and player performances reflect the performance of the real players. In this exercise, one team is composed of the very best free throw shooters in the NBA and the other is composed of players that are (comparatively) much weaker free throw shooters. Forcing the students to select their team based on one criterion with the full knowledge that the selection of my team is not similarly constrained brings this analogy to life since the two teams will compete against each other. Watching the game unfold further reinforces the analogy.
Running the Numbers: The Analogy through Descriptive Statistics
A number of useful extensions of this analogy are available to the instructor using NBA statistics alone. While there are numerous statistical resources available, the data included in www.realgm.com is used here. This site is comprehensive and accessible. I simply copied the data into Microsoft excel in order to generate the descriptive analysis used and reported here. I focus on the 2005 NBA All Star roster because the NBA All-Star team should represent the very best players in the league. This provides an easily accessible analogy for critical examination of the dissonance between free throw percentage (FT%) and All-Star Status.
The use of percentile ranks instead of raw data is important because it mirrors that manner in which standardized tests are interpreted. As indicated above, selecting a team based on one criterion has potentially ominous implications for the quality of the team. If one were to select the team limiting the selection to players in the top 75 th percentile in FT %, only nine of the twenty-four All-Stars would be eligible. This would also eliminate the 2005 NBA playoff Most Valuable Player (MVP), Tim Duncan and the 2005 Defensive Player of the Year (DPY), Ben Wallace. If one were to expand the selection criteria to the top 50 th percentile in FT%, Tim Duncan, Shaquille O’Neal and Allen Iverson, winners of four of the last six MVP awards during 1999-2005, would still be excluded. Additionally, Ben Wallace, winner of three of the last four DPY awards remains excluded as well. Even if the instructor encourages only a cursory glance at this data, the fact that some of the NBA’s most dominant players in recent years are situated near or at the bottom of free throw percentile rankings is readily apparent.
Overall, the 2005 NBA All-Stars are comparatively stronger in areas other than FT%. FT% is the second lowest average percentile rank of all of the statistical categories reported here.
Using team performance as a reference point, the weak relationship between FT% and success is readily apparent as well. In terms of FT%, the highest ranked team of the four final teams competing for the NBA championship ranked only 22 nd out of 30 teams. The eventual NBA champions, the San Antonio Spurs, ranked only 26 th of thirty teams.
Use of this data provides the instructor with an important reference point for a rudimentary statistical application of the analogy. Using strength in only one criterion to select your team, such as FT%, would be disastrous.
Although presenting the data above is compelling, simulating a game between a team composed of the best free throw shooters and a team that does not include the best free throw shooters is particularly compelling. Following a discussion of the aforementioned data, I inform the class that I have selected a team that does not include any players that are among the top ten percentile free throw shooters. I then challenge them to select a team that will play my team – and win. The only instructional caveat is that their team must include players that are in the top ten percentile in free throw shooting. There are several options to accommodate the selection of the class’ team. The facilitator may make the performance data available to the entire class at once (via handouts or projection) and allow class discussion of the logic of their selections before voting. The facilitator may also divide the class into small groups and assign each group the responsibility of selecting the best player for a particular position. The data should be limited to qualifying players and sorted by position and FT percentile rank. It is important that other statistical categories are included so that students will come to understand that strength in one category does not necessarily correlate with strength in other categories. For this reason, 2005 NBA Stars that are eligible should also be identified. Eligible players at the center position are illustrative. While the eligible centers rank in 90 th percentile or above in FT%, their performance in other statistical categories is generally abysmal when compared to the remainder of the NBA.
In order to simulate an NBA roster, each team should include at least one point guard (PG), one shooting guard (SG), one strong forward (SF), one power forward (PF) and one center (C).
The paucity of All-Stars available to students is immediately apparent. At this point, some students may protest and suggest that it is unfair to select players based on one statistical category. For example, in the assessment of this exercise one student commented that we “ picked some sucky people for those with good free throw percentages, and it really wasn't fair.” Of course, I am unsympathetic to such protests. In response, I (with an attempt at convincing sincerity) extol the importance of the free throw and bemoan the fact that their team will have the best free throw shooters while my team will be composed of many players that have horrible free throw shooting percentages. Of course, most students will scoff of this protest – as they should.
After ten minutes or so, the class “drafts” its team. I announce each selection with great fanfare, writing each player’s name and position on the board and then matching each name with my own selection. Usually, my selections are met with pronounced moans of dread as the exercise plays itself out. Once both teams are complete, I create the teams using the gaming software. The process for doing so varies according to the game and gaming system so it is important to consult the instruction manual well before initiating the simulation. It is best to hold the draft on one day, create the teams outside of class, save the teams onto a memory device and simply load the teams and simulate the game in class during the next class session. This saves time, creates anticipation and allows for more preliminary and follow-up class discussion. Additionally, it provides the facilitator with an opportunity to prepare statistical comparisons between the teams to strengthen the impact of the analogy.
Results
Video games are now remarkably realistic. Most NBA video games include elaborate pre-game introductions with blaring music, screaming fans and chest-bumping players. The in-game announcing is also intense as announcers’ voices reflect the intensity of the action on the court. Of course, games include powerful dunks, vicious blocks and dramatic long-range shots. This makes for enjoyable viewing as the analogy comes to life. Depending on the time available, an entire game can be viewed or only one quarter. To increase and sustain student interest, it is also possible to ask students to predict the score.
The following two rosters were the result of the selection process:
My Team is exclusively composed of 2005 all-stars while the team selected by the class includes only two all-stars. While the class’ team clearly outperforms the rest of the league in FT%, my team outperforms the class’ team in many other statistical categories:
I share this data with the students prior to the simulation in order to frame the analogy in statistical terms. True to the implications of the analogy, my team wins. The results of the most recent administration of the simulation are reported here. The game results reflect the actual performance data. While the class’ team, true to form, had a higher free throw shooting percentage, it was outperformed by my team in five of six of the remaining statistical categories reported by the game.
Assessment
The results of the post-exercise assessment indicate that this exercise was positively received by students. Although a small number of students responded with “neutral” or “slightly disagree,” the overwhelming majority of the students indicated “strongly agree” to the prompts while no student indicated “strongly disagree.”
Several of the open-ended comments regarding the exercise are consistent with these results:
A small number of students did not report a similarly positive experience:
The open-ended comments indicate that the exercise was generally successful and that providing the students with an opportunity to guess the score of the in-class administration increased the value of the experience for some students. Still, care must be taken to insure that the implications of the analogy are made clear at the outset.
To be fair, the College Board is opposed to exclusive use of the SAT in making admissions decisions. Staying true to the analogy, it is ultimately inappropriate to suggest that team selection should be based on FT% alone. Indeed, ETS is clear in stating that “SAT scores are intended to supplement your child's record.” (College Board 2005). A problem remains however. When institutions establish minimum scores on the SAT (as many do), this eliminates many students regardless of the strength of their grade point average or coursework. Consequently, that which is intended to supplement high school performance supplants this performance. Similarly, setting a minimum FT% potentially eliminates very strong players. Considering this, does the use of free throws come at too great an expense pertaining to the selection of the strongest team? Does the use of SAT come at too great an expense in admitting students?
The strength of the exercise is the transparency of the analogy. Indeed, “students must be able to recognize the meaning that is being conveyed and its relevance to the issue at hand” (Garner 2005, 3). The moment that the students realize that the ability of their team to compete is critically hampered by using one criterion, the meaning becomes clear. Much of the debate about the SAT centers on its limited ability to predict performance and the troubling and persisting patterns regarding the relationship between race, gender, income and parental education. Additionally, the SAT is to be used to predict first-year performance alone – nothing further. Are college degrees earned during the first year? Just as FT% does not capture the wide spectrum of skills necessary to be a dominant NBA player (passing, blocked shots, ball handling, defense, steals, etc.), the SAT is not designed to capture the wide spectrum of characteristics necessary to succeed in college and eventually earn a degree.
It is impossible to consider all of the variables that impact a player’s ability and opportunity to score points while the static reality of the free throw provides us with “ a common and objective scale for comparison” (College Board 2005) for measuring performance. The purpose of this exercise is not necessarily to select one criterion over another but rather to critically examine the selection of one criterion that does not necessarily reflect the ability of a player to perform. Similarly, there is much debate as to whether or not the SAT meaningfully predicts the ability of test-takers to perform academically. This exercise explicates this debate.
Ultimately the outcome of the game is not central. The real strength of this exercise is found in the selection process. It engenders a number of provocative questions for class discussion:
Although there are certainly no easy answers to these questions, this exercise forces an answer upon students that should make them uncomfortable. The overwhelming majority of the strongest players are not the strongest free throw shooters. Forcing students to make their selection based on this particular criterion is counterintuitive. It makes it virtually impossible to select a team that will have the comprehensive set of strengths and skills to compete – not to mention win.
Steele’s analogy is important because it encourages critical examination of the dangers of allowing one mechanism to overwhelm admissions decisions. This exercise extends this analogy by forcing students to choose what should ultimately be a losing team. Although watching the game unfold is certainly compelling, the impact of the exercise is centered on the students’ struggle to select strong players when most of the strongest players are excluded by the criterion that they are forced to use – despite the fact that eligible players are particularly strong in this one area. Just as success in the NBA involves much more than expertise in shooting free throws, this exercise encourages students to recognize the fact that success in college involves a complex set of skills, characteristics and resources that cannot possibly be assessed by one measure. While the outcome of a videogame simulation structured as described is entertaining and instructive, it is important to remind students that the stakes are much higher in relation to the continued use of the SAT in admissions decisions.
The author would like to thank the reviewers and the editor for their comments. Additionally, the author expresses gratitude to Kenneth Stallings and Justin Babino for their sincere attention to the manuscript prior to its submission.
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