Very few have been able to avoid being caught up in the Lin-credible wave of Lin-sanity that has swept New York City, the nation and the world. Jeremy Lin is a fascinating inspirational story of perseverance and triumph over adversity. Lest we forget, just a few short weeks ago he was without a contract, sleeping on his brother’s couch, and riding the pine. His current status as a basketball “phenom” who succeeded against all odds, however, is perhaps more a reflection of inherent biases within professional sports and our society as a whole than the ability of a third-string bench warmer to dig deep and seize an opportunity to shine. If you live by the truth in numbers, there is much to suggest that Lin was always one of the most promising potential stars in basketball—hindered more by biases about the types of people who rise to the pinnacles of the sport than by a lack of ability to perform at the highest level of it.

According to a recent Adventures in Capitalism post, a group of basketball “stat heads” (think the basketball equivalent of Jonah Hill in Moneyball) used analytics to predict Lin’s success way before he shamed Kobe and exceeded the rookie stats of greats like Michael Jordan. When Lin went undrafted by the NBA, pure statistical analysis ranked him #10 out of all players and #1 among the undrafted. Based purely on his numbers, Lin should have been a top prospect and easily worthy of sharing the court with the likes of Carmelo Anthony and Kobe Bryant. Instead Lin was cut, shipped to the D-league and left on the bench until a series of unfortunate events for the Knicks left coach Mike D’Antoni with no choice but to put Lin in the game. Since, Lin has performed in every way consistent with what his stats predicted.

For those of us who make a living analyzing data, Lin is as much a cautionary tale as he is an inspirational one. Lin reminds us of the importance of remaining mindful of our own biases, which can obscure how we interpret data and lead us to discount statistics that don’t fit our preconceived notions of how certain populations should act and what they should value. Should an Asian-American Harvard grad with a degree in economics be dominating a professional sport that has rarely included people of Asian descent or Harvard grads among its ranks?

This is particularly important to keep in mind given the general makeup of the public relations industry compared to the populations with which we are typically asked to communicate. PR professionals are generally better educated, more affluent, more exposed to news and culture and less ethnically diverse than the general population. Given this, it is in our best interest to check our preconceived notions at the door and let data and analytics be our guide. If we don’t lead with data driven decisions, we risk repeating the mistakes of the Golden State Warriors and 28 other NBA teams that are kicking themselves and wondering how they found themselves on the wrong side of the Lin-sanity wave.