A Model-Recommended Win Total for Your Consideration

Fun fact: I have never bet on a season win total before. I admittedly always thought they were a bit pointless. Even if I thought a team’s win total over/under had value, why would I tie up my money for an entire season when I could just leverage my disagreement from game to game? It’s a legitimate critique that I wouldn’t fault any bettor for expressing. But given my relatively recent foray into predictive sports modeling, I’ve had the opportunity to evaluate team win totals in a more concrete way.

Seeing in hindsight the profit I could have accumulated with my NFL model by taking action on large model disagreements gives me the assurance that doing that exact thing with the MLB model I’ve built for the upcoming 2019 season should have positive expected value. And I figured with you guys waiting for my impending announcement of what my plans will be with the MLB model, I thought I’d share some of that information with you and give you something to chew on.

As a Cubs fan, seeing that the Cubs were the most overvalued team in the team totals market hurt quite a bit, but it’s really not that hard to see how and why this team would be overvalued. In terms of offseason moves, the Cubs did absolutely nothing of substance whereas the rest of the NL Central did their best to ensure this year’s divisional race is a bloodbath. The Cardinals added Paul Goldschmidt and Andrew Miller; the Brewers added Yasmani Grandal and Mike Moustakas; and the Reds added Tanner Roark, Yasiel Puig, Sonny Gray, and Matt Kemp (while getting rid of Homer Bailey).

On top of that, they have a bunch of talent that is either already regressing or are prime regression candidates (Jon Lester, Cole Hamels, etc.). Javier Baez in particular is due for regression in the biggest of ways this season. Last year he batted .290 for 34 HRs and led the league with 111 RBIs, which was a massive improvement over his 2017 campaign in which he batted .273 for 23 HRs and 75 RBIs. Granted Baez did have 27% more plate appearances in 2018, but the bump in his counting stats production vastly outpaced the rate of his opportunity increase.

That production increase came despite maintaining a similar and abnormally high BABIP (.345 in 2017, .347 in 2018), and can be best explained by his increase in power (.207 ISO in 2017, .265 in 2018) which then led to the massive jump in his slugging percentage (.480 in 2017, .554 in 2018) and HRs. Despite those spikes, his BaseRuns only jumped from 3.8 to 3.9 across those two seasons and it’d be much more likely for Baez to have a 2019 that looks more like 2017 than 2018.

And while the Cubs have a ton of talent trending downwards, the rest of the NL Central has budding talent. The Cardinals have Marcell Ozuna, Jack Flaherty, and Alex Reyes; the Brewers have Ben Gamel and Keston Hiura; and the Reds have Luis Castillo, Nick Senzel, and a Sonny Gray without a non-destructive pitching coach. Considering 35% of the Cubs’ games will be against the Cardinals, Brewers, and Reds, they have a tough task to get wins as-is.

Another 20% of their games will be against the NL East, which is full of playoff contenders (ATL, PHI, NYM, WAS). A look at the supporting data doesn’t make their case any better, as the model projects this team to only be a top ten team in starting pitching while ranking league-average in run production, tenth-worst in relief pitching, and near the bottom third in fielding. That doesn’t sound like a team that should be tied for the seventh-hightest win total, and the model agrees. Take the Chicago Cubs to go under 88.5 wins.

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