영어1 YBM 박준언 3과 본문 빈칸 넣기

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

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

How ____ they do it?

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

Sabermetrics was created in the late ____

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

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

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

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

Sabermetrics had not been widely used until the Athletics adopted ____ 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 sabermetrics, sparking a movement to utilize data not ____ in baseball but also in other sports.

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

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

In 2010, Liverpool ____ a change in ownership.

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

So he demanded that the club form a new data ____

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

____ they had in common was significant expertise in data.

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

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

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

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

The data team was praised for its efforts when ____ 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 ____ industry.

One notable example of success is ____ 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 ____ the ice and makes the stone move faster.

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

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

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

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

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

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

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

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

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

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

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

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

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 to monitor players’ heart rates by using advanced visual computing technology ____ convert facial color variations into heart rates.

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

____ team also created an AI coach that helped adjust shooting form.

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

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

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

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

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

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

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