The NBA regular season is one heck of a marathon. Starting from the end of October and running all the way through the middle of April, NBA teams are tasked with competing in eighty-two 48-minute basketball contests—41 in their hometown venue and another 41 in a range of various road cities and stadiums. Out of this, a natural “home-court advantage” tends to materialize. Teams, for as long as the Association has been around, have been more successful at home than on the road.

Indeed, this idea of a home-court advantage in the NBA is widely acknowledged to be an incredibly important factor towards the general outcome of games. Home teams, in any one season in league history, have never won less than 54% of their games, and have even managed to establish single season winning percentages as high as 67% in the past forty years.

Despite this, however, the manner in which individual players’ performances wax and wane given home or road venue remains largely uninvestigated. For instance, many assume that star players, those at the absolute height of the NBA game, are less dependent on their surrounding environment(s) than less-heralded players. Bench players—on a general scale–, meanwhile, seem to carry the reputation that their quality of play is far less reliable on the road, where fans are more hostile, hotels and strangers replace homes, families, and friends, surroundings become unfamiliar, and otherwise uniform schedules fall prey to all kinds of unforeseen circumstances.

As such, to further explore and clarify the public’s understanding of home-court advantage and the manner in which it influences not only teams but also individuals in the NBA, I decided to tailor an investigation to this very end. My study will revolve around a particular metric created by John Hollinger, game score, which is calculated as such: (pts+0.4*FG-0.7*FGA-0.4*(FTA-FT)+0.7*ORB+0.3*DRB+STL+ 0.7*AST+0.7*BLK-0.4*PF-TOV). This value is calculated on a per-game basis and pools the aforementioned statistics via basic NBA box scores (available on any of,, etc), weights them, and provides a method with which to measure individual players’ composite per-game productivity.

With this in mind, I will chronicle the name of each player who qualified for statistical achievements in any of the past five NBA seasons (minimum 70 games played for 2010-11, 56 games for ’11-12, 70 games for ’12-13, and 58 games played for each of ’13-14 and ’14-15). Then, I will categorize each, depending on whether he started or came off the bench for the majority of games, as either a starter or a bench player. From here, I will add up each of these players’ “game scores” (via for a composite “home” value, do the same for all road games, then divide each by the total number of home or road appearances for an average value. Upon doing so, I will divide each player’s per-game road statistic by his corresponding home game score value, and this number (something like, say, 0.95) will serve as one of many such data points. Essentially, if one of such values is sub-1.00, it is fair to surmise that the player for whom this is the case tended to perform better at home than on the road—at least as far as ‘game score’ is concerned. On the other hand, if this number proves to be greater than 1.00, the opposite is true. I will repeat this process for every qualified player and for all of the past five NBA seasons (this amounts to tens of thousands of individual game score values added, divided, and parsed) from which I have data.

Upon finishing this particularly lengthy and extensive data collection process, I will have a home-road statistic for each qualified player for each NBA season since 2010-11. This information will allow me to compare home-road discrepancies amongst any particular players of interest, to determine the typical distributions of this data across entire seasons, and the like. Ultimately, however, it will allow me to answer this fundamental question: “How does the discrepancy in home vs road performance for NBA starters compare to the discrepancy in home vs road performance for NBA bench players?” Accordingly, in my quest to find a statistically evident answer to this query, I will have a pair of hypotheses. My null hypothesis will state the following: There is no difference in home vs road performance between starters and bench players in the NBA. On the other hand, my alternate will pontificate that there is, in fact, a statistically significant difference in home vs road performance between starters and bench players. Ultimately, using game score data provided by, I will be able to identify evidence in support of one of two initial hypotheses, make corresponding observations and conclusions about the variability of player performance in the NBA, and broaden my (and the reader’s) understanding of this subject as a result.

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