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Governor School Junior Research Paper

For each, their efficiency trend and mean, were calculated to determine a final efficiency value for their career. The touchdown-to-sack- efficiency equation was used to display the trends in how many total touchdowns were scored by the quarterbacks compared to how many times they were sacked. The higher values based on the data, were approximately around 8 to 16. 2, Daunted Clapper having the highest value. The overall data in this research was varied since the quarterback played for different teams and played with different styles of offense.

This study could also be seed for future determination in deciding a fixed salary for the players based on performance or can be a derivative in determining quarterback performance. Keywords: TEST, African American Quarterbacks, performance, NFG Introduction Statistical analysis is an important aspect when it comes to sports (Stimuli, 2009). Numbers or statistics can sometimes determine how many yards were gained or lost, or how many points were scored (Sober, 2009).

In American football, team efficiency is critical in scoring and winning a game, especially for an offense (Berry, 2012). If your offense cannot score on a consistent basis, you cannot win. On a football team, a good offense and an efficient quarterback is pivotal, especially if there is an African American quarterback at the helm (Ingram, 2005). In the case of African American quarterbacks, some analysts are skeptical in determining black quarterback success in the NFG, because they were projecting whether that this race of quarterback would draw more fans to the stadiums or not.

That led to some successful African American quarterbacks in college to change positions in the NFG or were deliberately drafted in later rounds or played Canadian Football (Buffing, 2005). For example, In April of 1999, three African American quarterbacks were chosen in the first round of the Neff’s annual draft. Up to that point, only four African American quarterbacks had been first round draft picks in the draft’s entire history (Buffing, 2005). This experiment will hopefully change the standpoint of black NFG quarterbacks potential success to the NFG by comparing current African American NFG quarterbacks.

This study was conducted based on ten NFG African- American quarterbacks based on a created TEST (touchdown-to-sack efficiency rating) equation. In this study, based on ten African- American NFG quarterbacks, study tested, whether a certain TEST Value (10. Or higher) based on the TEST Value Scale, can determine if they can earn a possible Hall of Fame selection. This information hopefully will display the varied efficiencies of the quarterbacks and can determine their efficiency success rating based on the T SEER Value Scale. This also showed African American quarterbacks should not be overlooked in the NFG Draft (Simmons, 2009).

Methods This study was conducted by using ten African American NFG quarterbacks from different decades, ranging from the early 1 sass to the late 201 So. The determination of the quarterbacks was based on overall career statistics with aspect to number of times sacked and approximately 1 00 touchdowns scored. The quarterbacks who were selected were: Cornell Stewart (KS), Daunted Clapper (DC), David Gerard (DC), Steve McCain (SMS), Donovan McCann (DAM), Aaron Brooks (Ad), Doug Williams (DO), warren Moon (WHIM), Randall Cunningham (RCA), and Jeff Blake (JAB). African -American Quarterbacks were also used because there was a limited number of them in the NFG who started and there were very few successful ones with a significant amount of statistical data with respect to number of times sacked and touchdowns scored. These statistical data available were aired based on the decade they played in and the team’s style of offense. The data came from Pro-Football-reference and Database Football. Also, for further reference, The Official NFG Fact and Record Book was also used (NFG editors, 2009, 2008, & 2007).

The yearly TEST values of the quarterbacks were compiled in order to be compared and their career T SEER value was calculated to determine their overall efficiency success. The equation for all the data sets to determine the T SEER value was T ASS + TEST. The TTL value was used in the numerator to represent the number of total touchdowns by the earthquake and the S + NP in the denominator represented how many times quarterback were sacked plus the sixteen game season. With these values, standard deviation and other central tendency data values were calculated.

The years in which the quarterbacks played less than 7 games were not totaled into the career TEST value, but they were still calculated to show any trends. The data sets were numbered 1-17, representing the number of years played and only one Warren Moon, played 1 7 years. All the quarterbacks were set to 1 7 years, even if they did not play that long and because it stay constant throughout the study. The players did not play that corresponding year received a N/A or not applicable symbol and that data was calculated in their TEST value.

Meta-Chart was also used to develop a box and whisker plot and a scattered. Also, a scale range called the T SEER Value scale was created to determine their efficiency success according to their TEST 3 Value.. This a randomization of numbers in the scale. This scale can be further illustrated in the results in table 1. Rest Its In this study, The quarterbacks’ values fell between 5. 00 and 18. 99 on the TEST Value Scale, which means that their efficiency success correlated to either an average or good career. The scale determines their efficiency success under certain categories which coincides with the values.

Table 1 : This is the T SEER Scale, which indicates where the quarterback’s value falls under which category and what is their efficiency success rating, whether it is either great, good, average, below average or horrible. Figure 1 displays the career TEST values of the NFG quarterbacks. Daunted Clapper and Donovan McCann have the highest values with 16. 2 and 12, respectively. On the other hand, Cornell Stewart (KS) and Jeff Blake B) have lower values of 8. 66 and 8. 29 respectively. No quarterback was over 1 9, suggesting that they were either average or good. 4 Figure 2 displays the values from figure 1 in a histogram. Figure 3 represents the quarterbacks’ career TEST Values. The average is 1 1. 06 which shows most of the quarterbacks were average or had a good career. Quartile 1 or 25% Of the data fell under or at 8. 63. Quartile 3 or 75% Of the data fell under 12. 4. Figure 4 displays the yearly progression of the quarterbacks’ TEST values. The quarterbacks with the most years played, stayed around the 5-20 range. Warren Moon (WHIM) for example played the longest from all the subjects, 17 ears. His hall of fame potential is high, and he stayed consistently around the 5-20 range per season.

Randall Cunningham (RCA) had the highest value of 35 in one season. One great season does not determine a career, consistency and longevity are the two main factors. 6 Figure 5 Illustrates the T SEER equation that was used to determine TEST values. The TAT is the total touchdowns squared. The S represents sacks plus NP which is number of games played. Only the seasons in which quarterbacks played a minimum of 8 games, were calculated which determined their overall career efficiency value. 7 Discussion/Conclusion The lowest value recorded in the data was David Gerard, with a career TEST value of 8. 8 and the highest was by Daunted Clapper with a value of 16. 2. In Data set , the quarterbacks’ TEST values, fell between 0. 00-5. 40, because it was the their rookie seasons and they lacked the experience. After their first year, their TEST values showed significant increase due to experience at the position and playing more games. Donovan McCann, Doug Williams, Aaron Brooks, and Daunted Clapper had the highest TEST values for data set Their values increased to 1 1. 9, 17. 4, 1 1, and 32, respectively. Warren Moon and Donovan McCann were the most consistent longevity wise.

Warren Moon was the only quarterback to reach a TEST value of twenty or above three times (data set# 5, 7, and 12). On the other hand, not all the quarterbacks stayed consistent throughout their career, some fluctuated significantly. David Gerard had only two T SEER values above ten twice, but he only played seven significant years, due to injury. In seven significant years, Cornell Stewart had only one TEST value above twenty, and his values declined after the third year, due to increase lack of confidence. Also, after Daunted Sleeper’s second year, his TEST Value dropped 23. TEST points, due to a crucial knee injury and holding onto to the ball too long.. There was about a +/of 3 touchdowns scored, that could have affected the values of the quarterbacks. Randall Cunningham had the highest seasonal value of 35. 0 in data set #13, due to a change in teams and offensive line play. Cunningham values were mainly dictated by his offensive linemen because TEST values would have been consistently higher if he played with better support. In Cunningham second season, he had the lowest TEST value of 1. 94, due to eating sacked seventy-two times that year.

As far as Jeff Blake, he had similar issues comparable to Randall 8 Cunningham. Even though Blake was a superb runner, which boosted his TEST values, his inconsistency in his TEST values was due to poor team performance and lack of a strong receiving corp.. Doug Williams and had similar results like Randall Cunningham: lack of team performance. Steve Maniac’s values were consistent to a certain degree, but injury skewed his TEST points. The TEST values overall supported the stated hypothesis. Comparing touchdowns to sacks determined the overall performance. The values are not just representative of quarterback performance, but also team success.

The ability to make good decisions and the ability to be a dual-threat (the ability to pass and run effectively) could increase the values of the quarterbacks. Also, great pass protection and great team performance affected the values as well by observing the team’s offensive ranks per Season and their overall record. Avoiding injury is another pivotal factor that affected performance. These values were indirectly proportional. If a quarterback was sacked more than he scored, then his value was lower Although, if a quarterback scored more than e was sacked, then his value was higher.

Finally, this study may help to change opinions on how analysts view black quarterbacks because the TEST index could be used in college to predetermine their success. The T SEER index could be used for future determination in deciding a fixed salary, based on performance. The index can also be used as a derivative in order to determine a quarterback performance rating, which then could be adjusted to compare to other performance algorithms. The probability of team success- how well a team could perform that season- could be calculated by using this index.

The TEST value scale and the index could also be used in college football and by NFG draft analysts to determine the most efficient quarterbacks. Finally, the TEST values could be used as a validation check of their 9 actual performance, by comparing their stats from that season and concluding on their performance level. Acknowledgements will like to thank my father, for being a great mentor and helping with this arduous project of mine. Literature Cited Berry, D. J. , & Simmons, R. (2009). Race and the evaluation of signal callers in the National Football League.

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