영어1 YBM 박준언 3과 본문 빈칸 넣기

When the Oakland Athletics, a Major League Baseball team, won 20 ____ in a row in 2002, the professional sports industry was shocked.

The Oakland Athletics ____ a small team with limited funds, which made it difficult for them to attract elite players.

____ did they do it?

The key to their success was adopting sabermetrics, a statistical model used ____ making decisions in baseball.

____ was created in the late 1970s.

It tries to use large amounts of information to discover ____ trends, and insights that are difficult to find with traditional ways of studying statistics.

Normally, coaches and managers prefer players who can hit the ball hard and far, for such players tend to hit more home runs ____ extra-base hits.

Sabermetrics suggests that players’ offensive skills can be better measured by the frequency with ____ they safely reach base.

It does not matter whether this is achieved through hits, ____ or hits by pitch.

Sabermetrics had ____ been widely used until the Athletics adopted it in 2002.

With sabermetrics, the Athletics were able to identify underrated players ____ significant contributions to winning and built a strong team on a small budget.

The success of the Athletics prompted other teams to quickly adopt ____ sparking a movement to utilize data not only in baseball but also in other sports.

Thus, sports data ____ emerged as a systematic approach to predict game outcomes.

In soccer, the Liverpool Football Club of the English Premier League is similar to the Oakland Athletics ____ baseball.

In ____ Liverpool underwent a change in ownership.

While data analysis was already prevailing in the Premier League at that time, the new owner of the club, who also owned a baseball team in the United States, aimed to push data ____ in soccer to new heights.

So he demanded that the club form a ____ data team.

The new team included a ____ from Cambridge, a nuclear scientist from Harvard, and a former chess champion.

What they had in common was ____ expertise in data.

The team started to apply data analysis in key ____ of club management, including player recruitment, injury prevention, and strategy during the game.

The team analyzed large amounts of data to recruit players who fit the team’s style ____ play.

In training, they collected data on players’ movement patterns, heart rates, and vital signs by using GPS trackers and sensors ____ prevent injuries.

____ games, they used live data to make tactical decisions such as substitutions and formations.

The data ____ was praised for its efforts when the Liverpool Football Club won the league championship for the first time in 30 years in 2020.

The emergence of sports analytics did not go unnoticed by the Korean sports ____

____ notable example of success is the Korean women’s curling team.

Following its debut at the Winter Olympic Games ____ 2014, the team recognized the need to enhance its sweeping technique.

Sweeping melts the ice and makes the stone ____ faster.

If too much ice melts, however, the stone moves too fast and misses the ____

On the other ____ if not enough ice melts, the stone stops before reaching the target.

The amount of ____ melting depends on the sweeping speed and pressure.

Applying too much pressure slows down the sweeping speed, and ____ only on speed makes it hard to transfer enough force to the broom.

Finding the right balance between speed and pressure is important to ____ the right amount of ice.

To identify the most effective technique, the Korean team ____ a sweeping measurement device.

The ____ consisted of infrared cameras and sensors attached to the players’ bodies, shoes, and brooms.

Through the device and motion-capture screens, foot pressure values and other data were obtained for ____

After monitoring changes in the temperature ____ the ice surface, the team concluded that speed was more economical than strength for sweeping.

____ use of data analysis was critical in the team’s winning of a silver medal at the 2018 Pyeongchang Winter Olympics.

The ____ use of sports analytics was not limited to the curling team.

The Korean women’s archery team had dominated the sport for ____

However, the team turned to sports analytics to maintain its edge over its rivals in preparation ____ the 2020 Tokyo Olympics.

The team developed a system ____ monitor players’ heart rates by using advanced visual computing technology to convert facial color variations into heart rates.

____ data was used for psychological training to help players maintain stable heart rates during crucial moments.

The team also created an AI coach that helped adjust shooting ____

The team managers requested that the AI coach edit training videos of the players ____ assist with practical analysis.

Players and ____ used the edited videos to analyze the players’ usual habits or weaknesses.

The active use of data analysis by the Korean women’s archery team handed them their ninth Olympic gold ____ in a row in Tokyo.

There are ____ limitations to what data analysis can capture in games.

Factors ____ as team chemistry, which is related to how well people get along, will likely remain difficult to measure.

Similarly, predicting player performance in ____ match cannot be entirely accurate as players are humans and not machines.

Still, sports analytics ____ undeniably elevating the level of play across various sports, and fans are enjoying this development.