Perfect Game Expands Midwest Sports Reach Amid 93rd-Ranked Stock Surge and PG's 0.68% Decline

On September 15, 2025, The stock traded with a volume of 0.94 billion, ranking 93rd in market activity. Meanwhile, Procter & Gamble (PG) fell 0.68%.

Perfect Game, a leading youth baseball and softball platform, announced a partnership with the Cincy Flames tournament organization, expanding its Midwest presence. The collaboration integrates Cincy Flames’ events under Perfect Game’s brand, enhancing exposure for young athletes and solidifying the company’s national footprint. The Cincy Flames, known for hosting elite competitions, have historically drawn thousands of participants and college scouts, aligning with Perfect Game’s mission to elevate youth sports development.

The partnership aims to leverage Cincy Flames’ established reputation and network of collegiate venues, including the University of Cincinnati and Xavier University, to create more opportunities for players to showcase their talents. Perfect Game CEO Rob Ponger emphasized the strategic value of the Midwest expansion, while Cincy Flames owner Jay Basil highlighted the synergy between their organizations’ goals of fostering top-tier competition and player growth.

To run this back-test rigorously we need to clear up (and, in one respect, work around) a few practical issues: 1. Market universe • Should we limit the universe to U.S. listed common stocks (NYSE + NASDAQ + AMEX), or a broader / different market? 2. Weighting & rebalancing • Equal-weight across the 500 names each day? • Rebalance every day at the close, exit at next day’s close (i.e., one-day holding period)? 3. Trading frictions • Assume zero commissions / slippage, or add a cost (e.g., 2 bp per leg)? 4. Corporate-action treatment • Use split/dividend-adjusted prices? (industry default: “adjusted close”). 5. Tooling limitation • The back-testing engine currently integrated in this interface evaluates one ticker at a time; it is not yet capable of rebalancing a 500-stock cross-section. • I can still produce the analysis by running an external script, then present the results here (return curve, annualized return, vol, Sharpe, max drawdown, etc.). • Alternatively, we can narrow the task (e.g., look at how an ETF proxy such as SPY behaves when it’s one of the day’s top-volume names, or any other single-ticker question supported by the built-in engine). Please let me know your preferences on the above points (especially 1–4) and whether you would like me to: A) Proceed with the full 500-stock portfolio back-test via an external computation and show you the results, or B) Refine the question to something that can run completely inside the current single-ticker engine. Once I have your guidance I’ll move straight to execution.