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76 | 76 | with a generative or static model. |
77 | 77 | <ahref=https://amplitude.com/blog/2017/01/19/causation-correlation>Causal analysis</a> |
78 | 78 | and<ahref=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996805/>big data approaches</a> |
79 | | -are used for tactical analysis.</p></li><li><p><strong>Data Visualization:</strong> Data graphing and<ahref=https://towardsdatascience.com/advanced-sports-visualization-with-pandas-matplotlib-and-seaborn-9c16df80a81b>visualization</a> provide useful insights into relationship between various datasets.</p></li></ul><h2id=summary>Summary<aclass=headerlinkhref=#summarytitle="Link to this heading">#</a></h2><p>Sports Analytics is a game changer when it comes to how professional games are |
| 79 | +are used for tactical analysis.</p></li><li><p><strong>Data Visualization:</strong> Data graphing and visualization provide useful insights into relationship between various datasets.</p></li></ul><h2id=summary>Summary<aclass=headerlinkhref=#summarytitle="Link to this heading">#</a></h2><p>Sports Analytics is a game changer when it comes to how professional games are |
80 | 80 | played, especially how strategic decision making happens, which until recently |
81 | 81 | was primarily done based on “gut feeling" or adherence to past traditions. NumPy |
82 | 82 | forms a solid foundation for a large set of Python packages which provide higher |
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