Elevating MLB Model: Huddle’s Edge in a Pitcher-Dominated MLB Season

This MLB season, in its current state, is all about pitchers. Batting averages are historically low. Run scoring is down across the league. As recently as July 6th, the MLB-wide batting average was .242, the lowest it has been in a season since the late 1960s. Hits are down. Home runs and runs scored are down. Even walks are down. 

Even with nearly $1B worth of pitchers on the injured list, pitchers have dominated batters this season. And what is surely driving the commissioner of MLB crazy is this isn’t supposed to be happening. They instituted a pitch clock, bigger bases, and no shifts with the sole purpose of increasing offensive outputs, producing higher steal rates and more explosive offenses.

So what happened?

In my opinion, you can attribute some of this to young pitchers breaking out. Paul Skenes, who recently became the first player to be selected No. 1 overall in one draft and then make the All-Star Game in the subsequent season, has electrified. He’s got at least 7 strikeouts in all but one outing that he’s pitched. Meanwhile, the Chicago White Sox have benefitted from the services of Garrett Crochet, this year’s absolute breakout star who has dominated as a lefty on the mound. Shota Imanaga, whom the Cubs signed from Japan, has dominated batters to the tune of 7-2 record (as of July 3rd), 92 strikeouts and a 3.16 ERA. Through his first nine starts, Imanaga went 5-0 with a 0.84 ERA. 

Where does Huddle play into this?

Pitching markets are, to no one’s surprise, increasingly popular. Huddle’s MLB model enables an offering of micro and player performance markets, fully out-of-the-box ready for Same-Game Parlays (SGPs). Additionally, Huddle’s machine learning model rigorously evaluates the quality of every pitch thrown in a game. Through advanced algorithms and pattern recognition techniques, we can assess the effectiveness and potential outcomes of each pitch with a high degree of accuracy.

What's new this season is a clean and intuitive user interface (UI) that allows semi-automated control of the markets, with an automated lineup updating in real-time based on event state. Nearly everything is customizable - including templates that offer full control over the market lifecycle and risk management - a dream for a sportsbook!

Let’s look at the potential outing of the Orioles and Yankees on July 12th. Gerritt Cole is a star pitcher, with two consecutive seasons of 200 innings pitched, 200+ strikeouts and a combined record of 28-12 with a ERA hovering around 3.00. However, in four games this season, Cole has struggled, with his ERA ballooning to 6.75 and a record of 1-1 in 4 starts. The Orioles are rolling out Cade Povich, who is 1-3 in 6 starts with a similarly rough ERA of 6.51. However, Povich is a rookie who has two games allowing 6+ runs and two games allowing 1 run or fewer (including a 4 inning outing against the Yankees where he allowed 1 hit and 1 ER). 

So how would Huddle price this particular situation? Using Player-Level models and Pitch Quality Evaluations. We offer sophisticated analysis of individual player abilities, including pitchers and relievers. Multiple inputs, even for the bullpen, mean precise late-game scenario pricing. Our model assesses every pitch using advanced algorithms and pattern recognition and provides detailed insights into pitcher performance for strategic decision-making.

One notable enhancement we have implemented is the dynamic adjustment for air pressure and the ball's estimated bounciness, also known as the coefficient of restitution. By accounting for these factors, our models can more accurately analyze and predict the trajectory and behavior of each pitch, offering a comprehensive understanding of its potential impact on the game.

That’s what stands out for Huddle. Even when the league might be experiencing a downturn as pitchers dominate… Huddle comes out on top. 

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