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Amid expansion into 12-team era, why College Football Playoff needs modified system to evaluate contenders

As college football gears up for the expanded College Football Playoff (CFP) format in 2024, there’s a lot of buzz about how teams will be selected. While in the past, picking the top four teams seemed relatively straightforward, the new 5+7 model adds layers of complexity to the decision-making process.

With the expanded playoff field, the responsibility of the selection committee becomes even more critical. Their choices not only determine which teams get at-large bids but also influence whether a team will play at home or away in the playoffs. This heightened level of responsibility requires a more refined approach to selecting teams.

One of the challenges faced by the committee is how to determine the best teams among a competitive field. While the committee sticks to its established process, recent controversies, like Florida State’s exclusion despite being a 13-0 conference champion, highlight the need for improvements.

A key aspect of the selection process involves evaluating teams based on their performance against opponents ranked in the previous week’s top 25. However, using this approach has its limitations, as the number 25 is somewhat arbitrary and may not accurately reflect the true strength of teams in today’s college football landscape.

To address these limitations, there’s growing support for adopting objective metrics similar to those used in college basketball, such as the NCAA’s NET ratings. These metrics provide a more comprehensive assessment of a team’s performance beyond just top-25 wins, reducing subjectivity in the selection process.

Models like ESPN’s SP+ offer a balanced approach by considering both predictive and resume-based metrics. While these models shouldn’t replace the committee’s decision-making process entirely, they can provide valuable supplementary data for evaluation.

As the CFP expands, it’s crucial to enhance the evaluation process to ensure fairness and transparency. Incorporating objective analysis can help address concerns about bias and inconsistency, ultimately bolstering the credibility of the selection process.

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