[marshall]

We had a radically different approach this year and it paid dividends. As soon as we got back to the lab after kickoff we took the game apart using statistical analysis and mathematical modeling.

We realized on day one that the key to a high score was a short cycle time. We also proved that you could reach high scores with high scoring cycles but would end up with less of them and we predicted it would be hard to achieve those scores while maintaining control of the ball. At any rate, we spent the day taking the game apart until we had some nice graphs and charts to look at. We then chose our strategy based on that analysis of the game.

After that, we spent the first week working on the mathematics of the mechanics of the strategy. Basically, feasibility studies of different design ideas. By the end of the week we had a prototype built and were testing.

Overall, this approach lead to a couple of interesting observed behaviors. Breaking down the game mathematically made it so that pretty much everyone agreed unanimously on a strategy which made the design process easier. Performing the mathematical modeling on the game made it so that everyone could see the strategy even though not everyone fully understood the analysis behind it (it wasn't necessary for everyone to).

Performing the calculations of the various designs also made it so that everyone saw the pros/cons and we could easily make a decision about how to move forward.

As a mentor and someone who has been doing this for nearly 10 years, having a group of students that all agree is something that is rare and special. Using math and analysis forced us to all come to an agreement and do it sooner rather than later so we were more focused on what needed to be accomplished sooner in the build season.

It was a good first week for us and a good season overall. I can highly recommend this approach.