VOA文化艺术2024--US Sports Fans Hope AI Will Help with March Madness Brackets

US Sports Fans Hope AI Will Help with March Madness Brackets

　　The American college basketball tournaments known as "March Madness" begin this week. College basketball, or National Collegiate Athletic¹ Association (N.C.A.A.) basketball, is very popular in the United States. In parts of the country it is even more popular than professional basketball.

　　And, many people like to try to guess who will win the many games played over the next few weeks of competition. Sixty-seven games will be held for both men and women.

　　A chart that shows the sequence of games is called a bracket. Thousands of fans in the U.S. compete with each other to correctly predict the most outcomes of each game.

　　Today, more people are using artificial intelligence, or AI, to help them fill their brackets. Using AI for bracketing in the tournament is not so new. Even so, the yearly bracket competitions still provide many surprises for computer science experts who have spent years creating their models using past tournament results.

　　The researchers have found that machine learning alone cannot quite solve for the limited data and unpredictable human elements of the tournament.

　　A normal fan may spend a few days this week deciding which team might win a few games in the tournament. But some computer experts are going after even more detailed² information. They are using complex math to find the best model for predicting success in the tournament. Some are using AI to perfect their codes or decide which qualities of the team can best predict their competitive future.

　　The chances of creating a perfect bracket are extremely low for any competitor, however advanced their tools may be. An "informed fan" making choices based on past results has a 1 in 2 billion chance at perfection, says Ezra Miller³. He is a mathematics professor at Duke University.

　　Artificial intelligence is likely very good at determining the probability that a team wins, Miller said. But even with the models, he added that the "random⁴ choice of who's going to win a game that's evenly matched" is still a random choice.

　　For the 10th straight year, the data science community Kaggle is hosting "Machine Learning Madness." In traditional bracket competitions, people simply write each team they think will win. But "Machine Learning Madness" requires users to enter a percentage representing their level of confidence that a team will advance.

　　Kaggle provides a large data set from past results for people to develop their algorithms. That includes information on a team's free-throw percentage, turnovers⁶ and assists. Users can then turn that information over to an algorithm to find the statistics most predictive of tournament success.

　　"It's a fair fight. There's people who know a lot about basketball and can use what they know," said Jeff Sonas. He is a statistical⁷ chess analyst⁸ who helped found the competition. "It is also possible for someone who doesn't know a lot about basketball but is good at learning how to use data to make predictions."

　　No method will include every element at play on the court. There is a balance between modeling and intuition, said Tim Chartier, a Davidson University bracket expert.

　　Chartier has studied brackets since 2009. He developed a method that largely depends on team success on home court and away, performance in the second half of the season and difficulty of schedule. But he said the NCAA Tournament's historical results provide an unpredictable and small sample size. That is a difficulty for machine learning models, which use large sample sizes.

　　Chartier's goal is never for his students to reach perfection in their brackets. His own model still cannot account for Davidson's 2008 unexpected admission into the "Elite⁹ Eight" level of the tournament.

　　In that mystery, Chartier finds a useful reminder¹⁰ from March Madness: "The beauty of sports, and the beauty of life itself, is the randomness¹¹ that we can't predict."

　　Words in This Story

　　chart — n. information in the form of a table, diagram, etc.

　　sequence — n. the order in which things happen or should happen

　　advanced — adj. beyond the basic level

　　probability — n. the chance that something will happen

　　random — adj. chosen, done, etc., without a particular plan or pattern

　　algorithm — n. a set of steps that are followed in order to solve a mathematical problem or to complete a computer process

　　turnover⁵ — n. the amount of money that is received in sales by a store or company

　　intuition — n. a natural ability or power that makes it possible to know something without any proof or evidence

　　schedule — n. a plan of things that will be done and the times when they will be done

　　sample — n. a group of people or things that are taken from a larger group and studied, tested, or questioned to get information

1 athletic   

adj.擅长运动的，强健的；活跃的，体格健壮的

参考例句：

• This area has been marked off for athletic practice.这块地方被划出来供体育训练之用。
• He is an athletic star.他是一个运动明星。

2 detailed   

adj.详细的，详尽的，极注意细节的，完全的

参考例句：

• He had made a detailed study of the terrain.他对地形作了缜密的研究。
• A detailed list of our publications is available on request.我们的出版物有一份详细的目录备索。

3 miller   

n.磨坊主

参考例句：

• Every miller draws water to his own mill.磨坊主都往自己磨里注水。
• The skilful miller killed millions of lions with his ski.技术娴熟的磨坊主用雪橇杀死了上百万头狮子。

4 random   

adj.随机的；任意的；n.偶然的(或随便的)行动

参考例句：

• The list is arranged in a random order.名单排列不分先后。
• On random inspection the meat was found to be bad.经抽查，发现肉变质了。

5 turnover   

n.人员流动率，人事变动率；营业额，成交量

参考例句：

• The store greatly reduced the prices to make a quick turnover.这家商店实行大减价以迅速周转资金。
• Our turnover actually increased last year.去年我们的营业额竟然增加了。

6 turnovers   

n.营业额( turnover的名词复数 )；失误（篮球术语）；职工流动率；（商店的）货物周转率

参考例句：

• However, one other thing we continue to have issues with are turnovers. 然而，另外一件我们仍然存在的问题就是失误。 来自互联网
• The Shanghai team took advantage of a slew of Jiangxi turnovers. 上海队利用江西队的频繁失球占了上风。 来自互联网

7 statistical   

adj.统计的，统计学的

参考例句：

• He showed the price fluctuations in a statistical table.他用统计表显示价格的波动。
• They're making detailed statistical analysis.他们正在做具体的统计分析。

8 analyst   

n.分析家，化验员；心理分析学家

参考例句：

• What can you contribute to the position of a market analyst?你有什么技能可有助于市场分析员的职务？
• The analyst is required to interpolate values between standards.分析人员需要在这些标准中插入一些值。

9 elite   

n.精英阶层；实力集团；adj.杰出的，卓越的

参考例句：

• The power elite inside the government is controlling foreign policy.政府内部的一群握有实权的精英控制着对外政策。
• We have a political elite in this country.我们国家有一群政治精英。

10 reminder   

n.提醒物，纪念品；暗示，提示

参考例句：

• I have had another reminder from the library.我又收到图书馆的催还单。
• It always took a final reminder to get her to pay her share of the rent.总是得发给她一份最后催缴通知，她才付应该交的房租。

11 randomness   

n.随意，无安排；随机性

参考例句：

• The randomness is attributed to the porous medium. 随机性起因于多孔介质。 来自辞典例句
• Einstein declared that randomness rather than lawfulness is the characteristic of natural events. 爱因斯坦宣称自然现象的特征为不可测性而不是规律化。 来自辞典例句