This is my favorite time of the year to watch sports. The NFL is back in action, but more importantly, October brings us the MLB Playoffs. We’re huge baseball fans here at Mullooly Asset Management, and this year is particularly exciting for us because our New York Mets are back in the post season after nine long years.

I’ve always found the playoffs to be funny in any sport though. We often hear the cliche during post game interviews that, “The better team won”, but is that always true? It depends on what time frame we’re talking about and how we choose to define “better”. In a playoff series, the team who wins was undoubtedly the better performer over however many games they played. Are they really the better team as defined by longer term statistical evidence though? We’ve all seen the regular season juggernauts crumble in the postseason. Does that make them statistically worse than the team that got hot and beat them in the playoffs?

If we’re measuring superiority in a statistical sense, the better team does not always win in the playoffs; just ask Billy Beane. Billy Beane has been the GM of the Oakland A’s since 1998, and most people recognize his name from Michael Lewis’ book Moneyball that was made into a movie, starring Brad Pitt. Billy Beane, Bill James, and Sandy Alderson are a few of the biggest names who have been credited with introducing statistical player analysis to the MLB.

Although each practitioner has their own personal input regarding which statistics are the most significant determinants of baseball prowess, they’re all attempting to accomplish the same goal: objectively measure a player’s worth. They want to eliminate emotions, feelings, and other conflicts from the equation, and it’s certainly caught on. Bill James said in 2008 that every team was using some form of statistical analysis, and Billy Beane is on the record saying:

“The people that we’re hiring and other baseball teams are hiring, we’re competing with the Apples and the Googles of the world.”

These evidence based methods of player selection remind me of rules based factor investing. Implementing evidence based investment factor strategies in a systematic fashion have shown impressive results over time. Common investment factors that people like to target include value, momentum, and low volatility. Over at GestaltU they recently wrote about these factors, stating:

“Factor tilt portfolios are consistent with the systematic, rules-based nature of passive indexing, but are constructed to take advantage of well-known and intuitive market inefficiencies to yield excess returns over time. These excess returns are highly significant; more significant even than the equity risk premium itself. Factors appear to exist because of universal behavioural or risk based phenomena across global markets, and have persisted since the dawn of markets.”

In addition to offering excess returns above the equity risk premium, they most certainly offer better returns than relying on the star mutual fund manager and their “secret sauce” or “great intuition” for picking securities. While we need experts to create systematic models and help us understand why factors ...