Modeling Basketball Shooting Patterns Using Markov Chains: A Longitudinal Analysis of the Hot Hand Phenomenon
ADTM 2026 Conference · SCE Beer Sheva · supported by IEEE
My academic work spans probabilistic and statistical modeling, algorithms, network analysis, Torah & Science, and applications where mathematical structure meets messy real-world data.
Probabilistic modeling, forecasting, Markov chains, statistical inference, and dependence.
Approximation algorithms, optimization, broadcasting problems, and algorithmic problem solving.
Social network analysis, graph-based methods, empirical data science, and sockpuppet detection.
Probabilistic and statistical modeling of menstrual-cycle patterns and forecasting questions.
Mathematical and statistical research at the interface of Jewish law, traditional sources, and empirical science.
Academic work where statistical methodology, empirical validation, and financial markets overlap.
B.D.D. 38–40, 59–74
B.D.D. 36, 77–104
Functional Differential Equations 26(1–2), 1–13
ADTM 2026 Conference · SCE Beer Sheva · supported by IEEE
ADTM 2026 Conference · SCE Beer Sheva · supported by IEEE
Graduate Research Seminar · Shenkar · May 27, 2026
This lecture presented a data-driven analysis of NBA shot sequences using first- and second-order Markov-chain dependence tests. The study models shots by outcome and shot type, uses a two-decade NBA dataset, and finds some short-term dependence without evidence for a strong or consistent hot hand effect.
Selected capstone and research projects across quantitative finance, NLP, network analysis, navigation, algorithms, and software systems, with abstracts, methods, visuals, demos, and research outcomes added as materials are consolidated.
Explore supervised projects →First- and second-order Markov-chain models for longitudinal basketball shooting behavior.
Developing structural measures that complement classical Sharpe/Sortino/Calmar-style evaluation.
NLP, network analysis, and higher-order response structures for identifying coordinated identities.
Geometric and directional awareness in agent-based pursuit and tag environments.