In this paper I consider a statistical analysis of basketball shooting in a controlled (practice) setting, with special interest in the hot-hand. In Section 2, I review and critically examine the two seminal papers on this topic: Gilovich, Vallone, and Tversky (GVT) , and Tversky and Gilovich (TG1) . A simulation study of power is presented in Section 3. Finally, in Section 4, a case study of 2,000 trials is analyzed. In GVT and TG1, three additional topics appear which are beyond the scope of this paper: 1. Modeling game free throw shooting,
2. Modeling game shooting, and
3. Opinions and misconceptions of fans.
Readers interested in the first of these topics should refer to Wardrop  for a further analysis of the free throw data from the papers.
Several researchers have considered the second topic; the interested reader is referred to Larkey, Smith, and Kadane (LSK) , Tversky and Gilovich (TG2) , Hooke  and Forthofer . For related work in baseball, see Albright , Albert , Stern and Morris  and Stern . Topic 3 is considered briefly in Section 2 of this paper.
Finally, readers interested in statistical research in sports are referred to Bennett . The chapters on basketball and baseball should prove to be of special interest to readers of this paper. 2 Review of Literature
GVT appeared in 1985 in a “psychology journal.” Four years later the same research was restructured as TG1 and appeared in a “statistics journal.” For the most part the papers present identical analyses and interpretations of the data, with the earlier paper generally providing more detail. Twenty-six members of the Cornell University varsity and junior varsity basketball teams generated the data that are examined. The players are labeled M1 (for male one) through M14, and F1 through F12. Each player provided two sequences of shot attempts: the shooting data and the prediction data. I will begin with an examination of the shooting data.
The plan was for each player to provide a sequence of 100 shots, but three of the players, M4 (90 shots), M7 (75), and M8 (50), fell short of the target number.
Twenty-six null hypotheses are tested; namely, for each player the null hypothesis is that his or her shots satisfy the assumptions of Bernoulli trials. Below is one summary of the data obtained by M9. Previous Current Shot
Shot S F Total
S 38 15 53
F 16 30 46
The researchers describe these data in two ways. First, note that M9 made 72 percent of his shots after a hit, but only 35 percent after a miss; a difference of 37 percentage points. Second, the researchers compute the serial correlation and obtain 0.37.
The researchers analyze each player’s data with three test statistics. The first two are a test of the serial correlation and the runs test. They summarize their...