A Flaw in the System
By: Sam Henrichs
Tags: Betting, NFL, Sports Betting, Data Science, Football

Me and my family gathered together on Christmas day to watch as the Cleveland Browns attempted to win a crucial game in the enemy territory of Green Bay, Wisconsin. They were nearly successful, with a very close final score of 24–22 in favor of the home team. Unfortunately for the Browns and the Cleveland faithful, Baker Mayfield made some mistakes on Saturday afternoon. Four of them, actually.

Mistakes were commonplace in this game, just as any in the’s world’s craziest sports league. Baker threw four interceptions during the game, the Packers dropped several more, and Kevin Stefanski abandoned the run game on a final drive with several timeouts. But mistakes are what separate the bad teams from the good, and the good from the great. Apparently, they’re also what separates good bettors from great bettors.

For those who aren’t familiar, OBIWAN is the name I developed for my predictive NFL model, and I use it to bet NFL games. The acronym stands for Offensive Based Inference (and) Win Adjusted Net-pay.

Recently, I’ve noticed it predicting the over on total lines far too often, and this led to a nearly disastrous Week 15. Among other bets, it took the over for 83% of games, which is problematic, given a higher amount of under results occurring this season. This caused a 7–10 record on totals, and a loss of 14% investment on the week.

Not great.

Given that I use over-under bets as the basis for my portfolio each week, this is certainly troubling. I can no longer say with a reasonable confidence level that OBIWAN's total predictions will be profitable in the long run. So what was the issue?

I thought it would be an issue with the way the algorithm awards high-scoring drives to the offense following a turnover. The idea was the team on the good end of the turnover should have better field position, and as such should score more often. However, quick testing showed this wasn’t the case, and that this adjustment didn’t result in much more scoring for teams.

I then looked at the small nominal defensive adjustment applied to teams during each simulation and quickly determined the problem. By simply forgetting a minus sign, I was adding points in a few lines of code when I should have been subtracting.

For those who don’t code, this may sound pretty silly, and you would be completely correct. Just like leaving a single two-meter weakness that could destroy a moon-sized battle station, the Rogue One retcon notwithstanding.

I quickly corrected the issue for Week 16, which unsurprisingly went far better than Week 15.

Returns continue to be strong. 4 out of 6 positive weeks, and a total return of investment of $627.81 on $1,000 or 62.8%. Positive bets are stabilized by totals (other than that sizeable hiccup) and spreads, but the true driver of returns has been moneyline bets.

Moneylines, spreads, and totals have a total return of investment of 30.66%, 3.67%, and -1.98%, respectively. I hope that the total ROI will increase, and I am confident that it will for two reasons: it continues to hit above the break-even point of 52%, and the algorithm has just been fixed.

A look at distributions.

Totals are more densley clustered around the positive peak of 90.91% versus the negative -100%. This is promising, and should only improve. The current issue is weighting certain total bets more than the others, and a quick glimpse at a list of bets shows that OBIWAN favors heavy over bets, a result that makes a lot more sense following the revelation of the bug.

Spreads are essentially neutral, which follows with the 3.67% total ROI. I’m largely okay with this. As long as it remains positive, it remains a good bet. Although it would be great to have better returns, spreads are just tricky.

Moneyline has been the moneymaker. Although the negative peak is much larger than the positive, the wide spread towards high returns is what has caused the 30.66% ROI. OBIWAN almost exclusively bets underdogs, and yet has a winning percentage of 51.22%, a fact I’m quite proud of. Conventional betting wisdom tells you to bet underdogs, and the statistical analysis certainly supports this.

Let’s take a look at Week 17.

It’s funny that I just spent an entire blog post about fixing the large amount of over bets, but the lines are low this week. Vegas has spent the last two weeks losing money on unders, and as such have readjusted them back to lower lines.

As a Packers fan, I hate to see a Vikings moneyline bet in the portfolio, but hey, you always have to trust the math. See you next week.