<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/65ff3262f6e44a9698841bb513c4d3f2&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/65ff3262f6e44a9698841bb513c4d3f2-e59196d4a6121606.gif</thumbnail_url><duration>116.033</duration><title>Cricket Match Analysis: Key Winning Factors</title><description>This Loom presents an analysis on what most influences match outcomes, challenging the belief that cost alone decides the result. The author finds cost contributes about 50 percent overall, reaching up to 44.3 percent when batting first, but rising to 53.7 percent when choosing to field. They emphasize that win chances increase most in the death overs, growing by up to 27.3 percent, particularly during the 17 to 20 overs. They also mention top grand scorers as Virat Kohli, R G Sharma, Dhawan, and K L Rahul, and top wicket takers as Jehan, Kumar, Nareen, Shabla, and Doberman, along with the use of pandas, numpy, and matplotlib in code shared on GitHub.</description></oembed>