I claim that anyone with a math background and a love of baseball has at one time given serious thought whether they could be “the one” to unlock the equations that make Moneyball a reality. I am no different. This is the story behind the inspiration of my mid-career vision quest in search of the holy grail of sports-tech.

我声称，任何具有数学背景并且热爱棒球的人都曾一次认真考虑过他们是否可以成为“解开使Moneyball成为现实的方程式的人”。 我也一样 这是我在职业中期愿景探索中寻求体育技术圣杯灵感的故事。

June 2017. Frankfurt, Germany. A hot, sweaty, un-airconditioned ballroom with about a 1000 supercomputer guys. I was one of a handful of women (and an engineer, to boot!) in a sea of male PhDs. I felt invisible, alone, and my monumental case of jet lag was not doing me any favors!

2017年6月。德国法兰克福。 一个热气腾腾的，无空调的宴会厅，大约有1000名超级计算机人员。 我是一群男性博士学位中的少数几个女性之一(也是工程师！)。 我一个人感到无形，而我的时差React性的巨大案例并没有给我任何帮助！

The 3rd cup of bitter, strangely thick coffee was no help at all. I soon found myself drifting off and daydreaming of baseball. 2017 was the perfect year to be into baseball back home in Houston. (I never heard the infamous trash-can banging, but our math did uncover anomalies.) My lack of attention went beyond boredom and jet lag, though. I was mentally taking a break from an unaccepting and exclusionary environment to one that I knew would always welcome me with open arms: the world of being a sports fan! It should be no mystery why I was mulling over Jose Altuve’s 350 batting average instead of the latest product on the Intel roadmap.

第三杯苦味浓浓的咖啡根本没有帮助。 我很快发现自己正漂流而去做白日梦。 2017年是进入休斯敦棒球之乡的完美之年。 (我从未听过臭名昭著的垃圾桶撞击声，但是我们的数学确实发现了异常现象。)不过，我的注意力不足，不仅是无聊和时差。 我在精神上从一个无法接受和排他的环境中休息了一下，我所知道的将永远张开双臂欢迎我：成为体育迷的世界！ 我为什么要考虑何塞·阿尔图夫(Jose Altuve)的350次击球平均值，而不是英特尔路线图上的最新产品，这并不是什么神秘的事情。

Then, the next speaker changed my whole world!

然后，下一位演讲者改变了我的整个世界！

Enter Dr. Eng Lim Goh, the new CTO for the High-Performance Compute (HPC) group of my organization. A speaker that forces audiences to perk up by making a lot of eye contact and asking for audience agreement, nodding, and hand-raising; his secret power that day was an insistence that we all ‘get’ the philosophy of AI. Imagine the eye rolls amongst the crowd that was anxious for deep mathematical concepts. But the philosophical approach got my attention. “AI/Deep Learning/Machine Learning is all about letting the data tell us the story and generating the right equations to solve problems. Forget the equation first method. Work the data.”

输入我组织的高性能计算(HPC)组的新CTO Eng Lim Goh博士。 演讲者通过与观众进行大量眼神交流并征求他们的同意，点头和举手来迫使他们振作起来； 那天他的秘密力量是坚持我们所有人都“了解”人工智能的哲学。 想象一下那些渴望深入的数学概念的人群中的视线。 但是哲学方法引起了我的注意。 “人工智能/深度学习/机器学习就是让数据告诉我们故事，并生成正确的方程式来解决问题。 忘记方程式优先方法。 处理数据。”

These concepts were not new to me, but with baseball on the brain, I started to wonder. Can we apply deep learning to sports data and make better sense of stats and trends in baseball? To better understand the game? In every sport? Oh my! It was not lost on me that EVERY other person around me wanted to use these mathematical tools to solve complex weather problems, cure cancer, make jet engines, and manage nuclear stockpiles. Me? I just wanted to see whether deep learning could help me enjoy and better understand baseball.

这些概念对我来说并不陌生，但由于脑中有棒球，我开始怀疑。 我们可以将深度学习应用于体育数据并更好地了解棒球的统计数据和趋势吗？ 为了更好地了解游戏？ 在每项运动中？ 天啊！ 我周围的每个人都想使用这些数学工具来解决复杂的天气问题，治愈癌症，制造喷气发动机和管理核库存，这对我来说并没有使我迷失。 我？ 我只是想看看深度学习是否可以帮助我享受和更好地了解棒球。

It was that day that I began my lonely quest to use math to crack the world of sports. And Oh! The stories I can tell from then on!

那天是我开始孤独的探索，希望使用数学来打破体育世界。 哦！ 从那时起我可以讲的故事！

Before I do, I must thank Dr. Goh.

在我这样做之前，我必须感谢吴医生。

PS — Like any ‘proud parent’ here is a snapshot of our live dashboard that tells the story of the game in real-time with each pitch and each down! Isn’t she pretty? I will have a lot more to say about this in the future & how it is different than anything else in the industry! The way we do the predictions is new to the industry and something I’d love to share!

PS-就像任何“骄傲的父母”一样，这是我们实时仪表板的快照，实时记录每个球场的俯冲情况！ 她不是很漂亮吗？ 将来，我将有很多话要说，这与行业中的其他事物有何不同！ 我们进行预测的方式是业内新手，也是我很乐意分享的东西！