ART of W.A.R Q1 2024 Check-in

We thought it would be useful for us to create a short piece of writing to give a company update on Art of W.A.R. We have been fairly busy over the past few months and would like to share what we have been up to. There is some exciting news and even more good stuff to come soon. First, Art of W.A.R, had the opportunity to attend two sports analytics conferences recently. We attended and presented at the annual SABR Baseball Analytics Conference in Phoenix, Arizona. This was a great opportunity for us to share our Pitching + Model. We received great feedback and advice from some leaders in the baseball analytics industry. This event gave us great ideas on the direction of our company going forward.  We also attended the MIT Sloan Sports Analytics Conference in Boston, Massachusetts. We heard from some of the most influential names in the sports business. These two events helped us gain great experience and advice that we feel can help us properly direct our company with our next steps.

The first of those major steps for Art of W.A.R has been creating our first full software product: The Art of W.A.R Pitching + Server. The purpose of this server is to create a large database of statistics for a team, using our Pitching + model and a computer charting system. This database includes a variety of stats, ranging from traditional stats such as Innings Pitched to advanced statistics such as Location + and FIP. Our hope is that this database on its own could be useful to both coaches and players. This database can serve a similar purpose to proprietary databases used by teams across the Major Leagues, but at an affordable price. Additionally, we have compiled a set of supplementary writings from across the web. These are some of the best online resources out there and are another good resource for development. We plan to further develop our app through the incorporation of AI and machine learning to the databases. We plan to get the server in a place where one day it could act as a sort of computer pitching coach or analytics advisor.   

To elaborate on our app, the most important feature is the three quantitative models we have developed: Stuff +, Location +, and Pitching +. These models attempt to quantify various aspects of a pitcher’s abilities: specifically, their nastiness (movement, velocity, etc), location (ability to throw quality strikes consistently), and their overall pitching ability, which looks at both stuff and location. We calculated Stuff + by first developing a “Stuff Constant,” which is a composite of various stats that can be considered success for a pitcher, such as whiff rate and groundball rate. After calculating these “Stuff Constants'', we used Boruta, a feature selection algorithm to determine which ball flight metrics contributed most to a pitcher’s success, as measured by the “Stuff Constant.” Finally, we used XGBoost, a gradient boosted decision tree, to determine precisely how to weight the various ball flight metrics.

As time has progressed following our initial model, this process has stayed consistent. Our app enables us to collect vast amounts of data efficiently, helping us to refine our models. The main changes in our model have been behind the scenes, with various different weights changing. We have greatly increased the quantity of our data, and this increased quantity has helped our model become even more predictive. We are continuing to refine our model as we gather more data. We are currently working with a few partner schools to beta-test our app in exchange for increased data access. This increased access from a variety of playing levels will help our model continue to become more predictive, further enabling teams to help evaluate their pitching staff.