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> Precisely> predicted. When predicting the number of medals in the Olympic Games, the host country needs to pay considerable attention to predictive an*lysis because it is expected to have a better performance compared to the previous competition with the advantage of home ground. Before the start of the tournament, it was predicted that US data would be obtained for the medal of the host country. Therefore, it is a better result than the athletes and data an*lysis companies mentioned above only when the medals of host countries are predicted. The results of the total number of medals by country of PyeongChang Winter Olympic Games predicted from the previous article are as follows. Graph of Medal Predictions for 92 Countries. The closer the red dot is to the straight line, the more accurate the prediction power is. The results of the forecasting model for the 25 countries in which more than 2 of the 92 participating countries are expected are as follows. To see how meaningful the results of my forecasts are, I compared my results with the results of Gracenote, a subsidiary of research firm Nielsen. Grace notes predicted medals from 27 countries that are expected to win one or more medals before the start of the competition. (See the table below.) As a result of comparison, I can see that grace notes averaged 0.29 better than my prediction model. For a more detailed comparison, we have also compared the number of countries by the number of errors. I can see that the results of my model and Grace notes are very close. In my model, it was difficult to predict the abnormal values ​​in Norway and Germany, while Gracennon needed additional an*lysis to improve the predictive power of doping ripple in Russia and host country. It was Russia that caused a systematic doping ripple. Russia is the last Olympic Winter Games in Sochi