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  • Hi, everyone. Today we're going to talk about the Basketball Economics.

  • Hear about basketball, what's your first thought?

  • Jersey? Basketball shoes? Or...

  • yes, the topic is about the market of the NBA basketball players

  • First of all, we will start from 1989

  • when FIBA, the Fédération Internationale de Basketball

  • voted to eliminate the distinction between amateurs and professionals.

  • This ruling meant that international players could play in the NBA

  • without being disqualified from representing their countries in the world competitions

  • and thus started the flow of international players into the NBA

  • But due to the limited time and the lack of stats, under the condition of information asymmetry

  • it would make the players' salaries are not consistent with their performance

  • It means the salaries are higher than the players should have been

  • after accounting for their personal characteristics and on-court performance in the previous season.

  • The best example is Kwame Brown.

  • And this phenomenon is called thewinner’s curse

  • The winner's curse appears when the player's value can't be accounted properly.

  • Because of excessive optimism or the lack of stats,

  • the team will overestimate the player’s value, and then suffers loss

  • Another possible reason is when the player’s value is not easy to account.

  • If estimate correctly, the team may lose the bid

  • and if overestimate, the team may win the bid, but also get some loss.

  • The disappearance of the premium paid is attributed to estimate the Marginal Revenue Product

  • The team can look at the performance to evaluate the players.

  • For example, a team might look at the points scored, total rebounds, and assists.

  • And plus the experience, age, height, and etc.

  • Further, a team might also look at how the public will embrace a given player as a predictor of his drawing power.

  • But in this video we will focus on the player's performance in the seasons.

  • Divide all the players into two parts

  • the first we call it the backcourt which includes the guards, and the small forward

  • The second is called the frontline including the power forward and the center.

  • And then we will determine which stats are the most relative with the playerssalaries

  • In our research, we choose some of the stats, which are influential to wages.

  • There are six stats when it comes to the backcourt, and five stats for the frontline.

  • Before we start our analysis and discussion

  • we first inquire of the fans which factor correlate to wages the most.

  • For the backcourt players, top three are PTS, AST and 3P%.

  • And for the frontline players, REB, BLK and FT% stands out.

  • Then, let’s move on to see if the results to our research and the perspectives from the fans are identical.

  • First of all, we list the top 100 players who got the highest salary during the years 2003~2014 individually

  • And we rank and classify those players by the amount of their wages, the backcourt and the frontline

  • Next, we apply correlation coefficient to check the impact on each other.

  • That is, we calculate the relevant level between each datum and wages by EXCEL.

  • And conduct a hypothesis test to clarify if there is actual relation between wages and each datum.

  • Well do so by using a t-test with a confidence level of 95%.

  • Then we can find that both stats and wages are related.

  • Lastly, well draw a proper conclusion.

  • For the backcourt players, in the subjective viewpoint,

  • the top three stats which are influential to the wage are PTS, AST and 3P%.

  • And in the objective viewpoint, PTS, AST and +/- stands out.

  • We can find that the 3P% is the most different thing

  • between the subjective and the objective data.

  • We infer that the Golden State Warriors went viral caused three point field goal prevails in the NBA.

  • For the fans, competition of three point field goal between the players

  • definitely adds more excitement to the games.

  • However, the three point field goal didn’t prevail in the period of the data we test.

  • For the frontline players, in the subjective viewpoint,

  • the top three stats which are influential to the wages are REB, BLK and FT%.

  • And in the objective viewpoint, PTS, +/- and REB stands out.

  • We can infer that the fansexpectation of a worth watching game,

  • which will reflect on their anticipative performance of a player.

  • So, they believe that the rebounds are important to the frontline.

  • However, NBA is a professional but commercial league.

  • In order to attract more spectators to create more business opportunity,

  • the team will take the data correlate to score into consideration primarily

  • After all, the win and lose of a game are result from the point.

  • Therefore, the objective stats indicate some differences against the subjective viewpoint.

  • Thanks for your watching.

Hi, everyone. Today we're going to talk about the Basketball Economics.

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パンダ - バスケットボールの経済学 (中国語/英語字幕) (The Panda - Basketball Economics (Chinese/English Subtitles))

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    汪小豪 に公開 2021 年 01 月 14 日
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