In European club football, decision makers often rely on recent match outcomes when evaluating team performance, even though short-term results are heavily influenced by randomness. This can lead to systematic misjudgments. In this article, we propose a complementary approach for performance evaluation. We build upon the concept of expected goals based on quantified scoring chances and develop a chart that visualizes situations in which a team’s true performance likely deviates from the performance indicated by match outcomes. This should prevent clubs from making flawed decisions when match outcomes are misleading due to the influence of random forces.
Existing evidence shows that decision-makers' social ties to internal co-workers can lead to reduced firm performance. In this paper, we show that decision-makers' social ties to external transaction partners can also hurt firm performance. Specifically, we use 34 years of data from the National Basketball Association and study the relationship between a team's winning percentage and its use of players that the manager acquired through social ties to former employers in the industry. We find that teams with "tie-hired-players" underperform teams without tie-hired-players by 5 percent. This effect is large enough to change the composition of teams that qualify for the playoffs. Importantly, we show that adverse selection of managers and teams into the use of tie-hiring procedures cannot fully explain this finding. Additional evidence suggests instead that managers deliberately trade-off private, tie-related benefits against team performance.
Using representative and geocoded data from the Swiss Household Panel and the Swiss Business Census, we estimate the effect of sports activity on health care utilization and health. Because sports activity is likely correlated with unobserved determinants of health care utilization and health, we use the number of sports facilities within 6 miles of the individual's residence as an instrument. We find that doing sports at least once a week significantly reduces the number of doctor visits, overweight and sleeping problems. The magnitudes of these effects are larger in the IV estimations than in OLS estimations, which are biased toward zero due to reporting errors in sports activity and an omitted variable bias. To know the magnitudes of the causal effects is crucial for any kind of cost-benefit analysis of promoting individual sports activity.
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