The growing business of professional sports has lead to an increasing demand for effective metrics quantifying factors leading to team success, and evaluating individual player contributions to that success. In the sport of hockey the advancement of analytics has lead to a decline in the use of goal-based metrics, and an increased reliance on shot-based metrics. I tested assumptions behind this trend by using statistical modeling of 10 years of NHL data to directly compare the effectiveness of goal versus shot-based metrics at predicting team success, and comparative hypothesis testing to determine how well goals and shots quantify player contributions to team success. Goal-based models consistently outperformed their shot-based analogs. Models of team goal differential successfully predicted winning % during the 2015-16 season, while shot differential did not. Goal-based metrics (i.e. relative plus-minus/minute of ice time) were also better than shot-based metrics (i.e. relative Corsi/minute of ice time) for evaluating individual player contributions to team winning %. These results show that team and individual performance is not correlated with all shots, but only those shots effective enough to result in goals. These results will lead to more effective evaluation of individual players, and better understanding and prediction of those factors leading to team success.
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