Breaking Down an Opponent

Using specific data fields to find tendencies in your opponent.

My main responsibility at Baylor was to be in charge of our opponent scouting. To anyone that knows me, I am a breakdown nerd and am content sitting in a dark room all day inputting data. To me, there is nothing more exciting than objectively looking at an opponent and inputting data to mine for tendencies. There is an art to breaking down an opponent, and everyone has a different way of doing it. The objective for this article is to explain my process and to hopefully help a few coaches along the way. Not everyone enjoys the breakdown process like I do or even knows what to do with all the analytical data. I’ll try and show you a process that has worked for me and highlights tendencies within an offense. Like anything, to truly understand something you must know the “why” behind it. My goal is to explain the process in a way that makes sense to a novice.

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Use the breakdown data to create a visual representation of an offense like the one in the hit chart above.

The key to a great opponent scouting system is to approach it like a science and keep it concise. In order to get the most out of your breakdowns, you have to find a true medium between too little information and too much information. To find that perfect medium you have to understand the limitations of your staff and define what you need to know, so when you sit down to create a hit chart and cut-ups the information is easy to use. If you approach a breakdown like you are looking for a needle in a haystack (Ex. – creating a data column for every single data point possible), you can bog your staff down and get lost in data. During my three years at Baylor, I felt confident we developed that perfect medium for what our defensive coordinator, Phil Bennett, needed in order to be successful on the field. After being back the high school ranks for three years, I feel even more confident that I have found a way to break down opponents concisely while not losing myself in data points.

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