Sports Analytics Club: The Peak stat of the week

SPARQ and its role in the NFL combine

Illustration courtesy of Linda Shu

By: Dani Chu and Matthew Ryers

With yet another exciting Super Bowl behind us, National Football League (NFL) teams cross off the 2017–18 season and look towards the future. Many teams will need to reflect and rebuild this offseason and will look to the draft for help. Despite the drafting of many talented players, few of them truly become super stars in the NFL. Some predictions as to who will thrive can be based on college statistics, though league differences prevent college production from translating perfectly to NFL production. For this purpose the NFL Scouting Combine exists. Here, players perform a set of drills while scouts evaluate their technique and performance. The Combine consists of numerous activities ranging from powerful jumps to agile shuttles. Identifying which drills relate with consistent NFL production can be a challenge. Enter the SPARQ score a cumulative measure evaluating the Speed, Power, Agility, Reaction, and Quickness of a player.

Created in 2004 and bought by Nike in 2009, the SPARQ scoring system is designed to be a standardized test of athleticism. The metric aims to summarize the aforementioned attributes into one statistic through an athlete’s performance in five exercises the 40-yard dash measures speed, the power ball toss and the vertical jump measure power, the shuttle measures agility, and the Yo-Yo beep test measures reaction and endurance. An athlete receives a cumulative score based on their performances in these events.

Across sports, the SPARQ score places slightly different weights on the intermediate performance score from each exercise due to the differing demands of sports. For example, football is typically an anaerobic exercise that requires massive bursts of intermittent power. It’s SPARQ score will then place a heavier emphasis on the scores received in the power drills. On the other hand, soccer is typically an aerobic exercise requiring more endurance and agility and weights the agility and endurance scores more heavily. According to research by Daniel Lorenz et Al., a definition of elite endurance (aerobic) athletes remains challenging though elite anaerobic athletes are typically “more powerful and explosive” than their non-elite counterparts. Theoretically, SPARQ should detect elite NFL players, especially wide receivers and running backs. As data is only readily available for the previous few years, consider the following results from the 2015 draft class.

Of the 2015 running back draft class, the top two SPARQ scores belong to Ameer Abdullah (145.5) and David Johnson (139.7). Both of these players have held starting jobs since being drafted. Notably, Johnson made a name for himself in 2016, where he amassed over 2,000 yards on the season. The only player to achieve that mark this season was Todd Gurley, another player from the same draft class. He ranked 11th in SPARQ for that year (129.4). Other notable players from 2015’s draft class include Jay Ajayi (127.6), Melvin Gordon (125.7), Tevin Coleman (125.6), and Duke Johnson (124.2). Of course these are not the only high SPARQ players from the 2015 draft. Many other players with high SPARQ scores have made the NFL but have failed to make much out of their opportunity so far. The amount of success at the top of the SPARQ leaderboards, however, is encouraging. If the same draft class had been sorted by the best 40-yard dash times, Jeremy Langford, Karlos Williams, and Trey Williams would all edge out David Johnson for the top three of the Combine. These three players are by no means bad but have had significantly less success at the NFL level than the top SPARQ players.

Criticisms of SPARQ scoring come mainly from the view of commercialism. Through its partnership with Nike, SPARQ apparel and coaching sessions have become extremely profitable. Further the exact coefficients used to weight the drill scores when calculating the overall ranking is not public information, leading many to question how well the SPARQ score formula is designed. The analytical community has tried to reverse engineer the statistic and have derived what they believe to be an accurate set of coefficients. This process, however, would be much more accurate with the exact values. Finally, the application of SPARQ scoring can be suspect. Most NFL prospects have their SPARQ’s calculated from the results of the Combine. The problem here is that the Combine does not run some of the drills required for this statistic. Instead the SPARQ score must rely on substitute events to evaluate all of the necessary components. This leads to some inconsistency with the evaluation of players in what is supposed to be a metric that standardizes testing.

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