├── 2025_MCM_Problem_C.pdf ├── 2025_Problem_C_Data ├── data_dictionary.csv ├── figures │ ├── host_performance.png │ ├── medal_distribution.png │ ├── model_stability.png │ └── top5_consistency.png ├── gray.py ├── summerOly_athletes.csv ├── summerOly_hosts.csv ├── summerOly_medal_counts.csv └── summerOly_programs.csv ├── 2511431.pdf ├── LICENSE └── README.md /2025_MCM_Problem_C.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_MCM_Problem_C.pdf -------------------------------------------------------------------------------- /2025_Problem_C_Data/data_dictionary.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/data_dictionary.csv -------------------------------------------------------------------------------- /2025_Problem_C_Data/figures/host_performance.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/figures/host_performance.png -------------------------------------------------------------------------------- /2025_Problem_C_Data/figures/medal_distribution.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/figures/medal_distribution.png -------------------------------------------------------------------------------- /2025_Problem_C_Data/figures/model_stability.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/figures/model_stability.png -------------------------------------------------------------------------------- /2025_Problem_C_Data/figures/top5_consistency.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/figures/top5_consistency.png -------------------------------------------------------------------------------- /2025_Problem_C_Data/gray.py: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | import numpy as np 3 | from typing import List 4 | 5 | def medal_to_value(medal): 6 | """ 7 | 将奖牌类型转换为数值 8 | Gold: 15 9 | Silver: 14 10 | Bronze: 13 11 | No Medal: 12 12 | Not Participated: 11 13 | """ 14 | if pd.isna(medal): 15 | return 12 # No Medal 16 | medal = str(medal).strip() 17 | if medal == 'Gold': 18 | return 15 19 | elif medal == 'Silver': 20 | return 14 21 | elif medal == 'Bronze': 22 | return 13 23 | return 12 # No Medal 24 | 25 | def value_to_medal(value): 26 | """ 27 | 将预测的数值转换回奖牌类型 28 | 15: Gold 29 | 14: Silver 30 | 13: Bronze 31 | 12: No Medal 32 | 11: Not Participated 33 | """ 34 | if value >= 14.5: 35 | return 'Gold' 36 | elif value >= 13.5: 37 | return 'Silver' 38 | elif value >= 12.5: 39 | return 'Bronze' 40 | elif value >= 11.5: 41 | return 'No Medal' 42 | return 'Not Participated' 43 | 44 | def get_participation_value(participated_years): 45 | """ 46 | 根据参与年数确定未参与年份的值 47 | """ 48 | return 11 49 | 50 | def gm11(x: List[float], n: int) -> List[float]: 51 | """ 52 | 灰色预测模型 GM(1,1) 53 | x: 历史数据序列 54 | n: 需要预测的个数 55 | return: 预测结果 56 | """ 57 | # 数据预处理，至少需要4个数据 58 | x = np.array(x, dtype=float) 59 | if len(x) < 4: 60 | return [] 61 | 62 | # 检查数据是否全为0或只有一个非0值 63 | if np.sum(x != 0) <= 1: 64 | return [x[-1]] # 返回最后一个值 65 | 66 | # 为避免0值，对数据进行平移变换 67 | min_x = np.min(x) 68 | if min_x == 0: 69 | x = x + 1 # 所有数据加1，避免0值 70 | 71 | # 累加生成 72 | x1 = np.cumsum(x) 73 | 74 | # 生成矩阵B和矩阵Yn 75 | B = np.zeros((len(x) - 1, 2)) 76 | for i in range(len(x) - 1): 77 | B[i][0] = -(x1[i] + x1[i + 1]) / 2 78 | B[i][1] = 1 79 | Yn = x[1:] 80 | 81 | try: 82 | # 使用最小二乘法计算参数 83 | B_T = B.T 84 | B_inverse = np.linalg.inv(B_T.dot(B)) 85 | params = B_inverse.dot(B_T).dot(Yn) 86 | a, u = params 87 | 88 | # 检查参数是否接近0 89 | if abs(a) < 1e-10: 90 | return [x[-1]] # 如果a接近0，返回最后一个值 91 | 92 | # 预测未来值 93 | predictions = [] 94 | x1_hat = [] 95 | 96 | # 计算x1的预测值 97 | for k in range(len(x) + n): 98 | try: 99 | x1_pred = (x[0] - u/a) * np.exp(-a * k) + u/a 100 | x1_hat.append(x1_pred) 101 | except: 102 | return [x[-1]] # 如果计算出错，返回最后一个值 103 | 104 | # 计算x0的预测值（还原预测值） 105 | for k in range(1, len(x1_hat)): 106 | predictions.append(x1_hat[k] - x1_hat[k-1]) 107 | 108 | # 如果之前进行了平移变换，需要还原 109 | if min_x == 0: 110 | predictions = [max(0, p - 1) for p in predictions] 111 | 112 | # 只返回需要的预测值 113 | result = predictions[-n:] 114 | 115 | # 确保结果合理 116 | if any(np.isnan(result)) or any(np.isinf(result)): 117 | return [x[-1]] 118 | 119 | return result 120 | except: 121 | return [x[-1]] # 如果计算过程出错，返回最后一个值 122 | 123 | def summarize_team_medals(predictions_df): 124 | """统计每个队伍的奖牌数""" 125 | # 创建奖牌统计 126 | team_medals = predictions_df.groupby('Team').agg({ 127 | 'Predicted_Medal': lambda x: list(x) 128 | }).reset_index() 129 | 130 | # 计算每种奖牌的数量 131 | team_stats = [] 132 | for _, row in team_medals.iterrows(): 133 | medals = row['Predicted_Medal'] 134 | stats = { 135 | 'NOC': row['Team'], # 改为NOC 136 | 'Gold': medals.count('Gold'), 137 | 'Silver': medals.count('Silver'), 138 | 'Bronze': medals.count('Bronze') 139 | } 140 | stats['Total'] = stats['Gold'] + stats['Silver'] + stats['Bronze'] 141 | team_stats.append(stats) 142 | 143 | # 创建DataFrame并排序 144 | team_stats_df = pd.DataFrame(team_stats) 145 | team_stats_df = team_stats_df.sort_values(['Gold', 'Total'], ascending=[False, False]) 146 | 147 | return team_stats_df 148 | 149 | def allocate_medals_by_event(predictions_df): 150 | """ 151 | 为每个项目分配奖牌，考虑团体项目和个人项目的不同规则 152 | """ 153 | final_predictions = [] 154 | 155 | # 按项目分组 156 | for event, group in predictions_df.groupby('Event'): 157 | # 判断是否为团体项目 158 | is_team_event = 'Team' in event 159 | 160 | # 按预测分数降序排序 161 | sorted_athletes = group.sort_values('Prediction_Score', ascending=False).reset_index(drop=True) 162 | total_athletes = len(sorted_athletes) 163 | 164 | # 用于跟踪已分配的奖牌数量 165 | medals_count = {'Gold': 0, 'Silver': 0, 'Bronze': 0} 166 | # 用于跟踪已获得奖牌的队伍（团体项目使用） 167 | teams_with_medals = set() 168 | 169 | # 遍历运动员分配奖牌 170 | for rank, (idx, row) in enumerate(sorted_athletes.iterrows(), 1): 171 | medal = 'No Medal' 172 | score = row['Prediction_Score'] 173 | team = row['Team'] 174 | 175 | if score >= 13: # 只有达到基本分数要求才可能获得奖牌 176 | if is_team_event: 177 | # 团体项目处理 178 | if team not in teams_with_medals: # 该队伍还未获得奖牌 179 | if score >= 14 and medals_count['Gold'] == 0: 180 | medal = 'Gold' 181 | medals_count['Gold'] = 1 182 | teams_with_medals.add(team) 183 | elif score >= 13.5 and medals_count['Silver'] == 0: 184 | medal = 'Silver' 185 | medals_count['Silver'] = 1 186 | teams_with_medals.add(team) 187 | elif score >= 13 and medals_count['Bronze'] == 0: 188 | medal = 'Bronze' 189 | medals_count['Bronze'] = 1 190 | teams_with_medals.add(team) 191 | else: 192 | # 个人项目处理 193 | if score >= 14 and medals_count['Gold'] < 1: 194 | medal = 'Gold' 195 | medals_count['Gold'] += 1 196 | elif score >= 13.5 and medals_count['Silver'] < 1: 197 | medal = 'Silver' 198 | medals_count['Silver'] += 1 199 | elif score >= 13 and medals_count['Bronze'] < 1: 200 | medal = 'Bronze' 201 | medals_count['Bronze'] += 1 202 | else: 203 | medal = 'Not Participated' if score < 12 else 'No Medal' 204 | 205 | # 创建预测结果 206 | final_predictions.append({ 207 | 'Name': row['Name'], 208 | 'Event': row['Event'], 209 | 'Team': team, 210 | 'Year': 2028, 211 | 'Predicted_Medal': medal, 212 | 'Prediction_Score': score, 213 | 'History_Data': row['History_Data'], 214 | 'Participation_Count': row['Participation_Count'], 215 | 'Original_Score': score, 216 | 'Rank_In_Event': rank, 217 | 'Total_Athletes': total_athletes, 218 | 'Is_Team_Event': is_team_event 219 | }) 220 | 221 | return pd.DataFrame(final_predictions) 222 | 223 | def process_and_predict(): 224 | # 读取处理好的数据 225 | df = pd.read_csv('evaluation21.csv') 226 | print("加载数据形状:", df.shape) 227 | 228 | # 创建新的DataFrame来存储预测结果 229 | predictions = [] 230 | 231 | # 按运动员和项目分组 232 | groups = df.groupby(['Name', 'Event']) 233 | print(f"总共分组数量: {len(groups)}") 234 | 235 | # 记录不同情况的计数 236 | total_groups = 0 237 | prediction_failed = 0 238 | prediction_success = 0 239 | 240 | # 要考虑的年份列表 241 | years = [2012, 2016, 2020, 2024] 242 | 243 | # 按运动员和项目分组 244 | for (name, event), group in groups: 245 | total_groups += 1 246 | 247 | # 获取最新的Team信息 248 | latest_team = group.iloc[-1]['Team'] 249 | 250 | # 创建完整的历史记录（包含所有年份） 251 | history = [] 252 | group_years = group['Year'].tolist() 253 | participated_count = len(group_years) # 统计参与次数 254 | 255 | # 对每个年份，检查是否有参赛记录 256 | for year in years: 257 | if year in group_years: 258 | # 获取该年的奖牌值 259 | medal = group[group['Year'] == year]['Medal'].iloc[0] 260 | value = medal_to_value(medal) 261 | else: 262 | # 根据参与次数设置未参与年份的值 263 | value = get_participation_value(participated_count) 264 | history.append(value) 265 | 266 | # 打印调试信息 267 | if total_groups % 1000 == 0: 268 | print(f"\n处理第 {total_groups} 组:") 269 | print(f"运动员: {name}") 270 | print(f"项目: {event}") 271 | print(f"队伍: {latest_team}") 272 | print(f"参与次数: {participated_count}") 273 | print(f"历史数据: {history}") 274 | 275 | # 使用灰色预测模型预测2028年结果 276 | pred = gm11(history, 1) 277 | 278 | if len(pred) > 0: 279 | pred_value = pred[0] 280 | # 确保预测值在合理范围内 281 | pred_value = max(11, min(15, pred_value)) # 11-15之间 282 | # 将预测值转换为奖牌类型 283 | medal_pred = value_to_medal(pred_value) 284 | 285 | # 保存预测结果 286 | predictions.append({ 287 | 'Name': name, 288 | 'Event': event, 289 | 'Team': latest_team, 290 | 'Year': 2028, 291 | 'Predicted_Medal': medal_pred, 292 | 'Prediction_Score': pred_value, 293 | 'History_Data': str(history), 294 | 'Participation_Count': participated_count # 添加参与次数信息 295 | }) 296 | prediction_success += 1 297 | else: 298 | prediction_failed += 1 299 | 300 | # 打印统计信息 301 | print("\n预测统计信息:") 302 | print(f"总分组数: {total_groups}") 303 | print(f"预测失败组数: {prediction_failed}") 304 | print(f"预测成功组数: {prediction_success}") 305 | 306 | # 创建预测结果DataFrame 307 | predictions_df = pd.DataFrame(predictions) 308 | print("\n初始预测结果形状:", predictions_df.shape) 309 | 310 | # 对每个项目重新分配奖牌 311 | final_predictions_df = allocate_medals_by_event(predictions_df) 312 | print("\n重新分配奖牌后的结果形状:", final_predictions_df.shape) 313 | print("\n预测结果示例:") 314 | print(final_predictions_df.head()) 315 | 316 | # 保存预测结果（添加错误处理） 317 | try: 318 | predictions_file = 'predictions_2028_new.csv' 319 | final_predictions_df.to_csv(predictions_file, index=False) 320 | print(f"\n预测结果已保存到 {predictions_file}") 321 | except Exception as e: 322 | print(f"\n保存预测结果时出错: {e}") 323 | predictions_file = 'predictions_2028_backup.csv' 324 | try: 325 | final_predictions_df.to_csv(predictions_file, index=False) 326 | print(f"预测结果已保存到备用文件: {predictions_file}") 327 | except Exception as e: 328 | print(f"保存到备用文件也失败: {e}") 329 | 330 | # 生成队伍奖牌统计 331 | team_stats = summarize_team_medals(final_predictions_df) 332 | print("\n队伍奖牌统计:") 333 | print(team_stats.head(10)) # 显示前10名 334 | 335 | # 保存队伍统计结果（添加错误处理） 336 | try: 337 | team_stats_file = 'team_medals_2028_new.csv' 338 | team_stats.to_csv(team_stats_file) 339 | print(f"\n队伍奖牌统计已保存到 {team_stats_file}") 340 | except Exception as e: 341 | print(f"\n保存队伍统计时出错: {e}") 342 | team_stats_file = 'team_medals_2028_backup.csv' 343 | try: 344 | team_stats.to_csv(team_stats_file) 345 | print(f"队伍统计已保存到备用文件: {team_stats_file}") 346 | except Exception as e: 347 | print(f"保存到备用文件也失败: {e}") 348 | 349 | return final_predictions_df, team_stats 350 | 351 | def process_medal_counts(): 352 | """处理并返回国家奖牌统计数据""" 353 | try: 354 | # 运行预测获取结果 355 | _, team_stats = process_and_predict() 356 | 357 | # 确保包含所需的列 358 | if 'NOC' not in team_stats.columns: 359 | print("警告：需要重新生成团队统计") 360 | # 重新生成正确格式的团队统计 361 | predictions_df, _ = process_and_predict() 362 | team_stats = summarize_team_medals(predictions_df) 363 | 364 | # 确保列名正确 365 | required_columns = ['NOC', 'Gold', 'Silver', 'Bronze', 'Total'] 366 | if not all(col in team_stats.columns for col in required_columns): 367 | raise ValueError(f"缺少必要的列: {required_columns}") 368 | 369 | # 只选择需要的列 370 | team_stats = team_stats[required_columns] 371 | 372 | return team_stats 373 | 374 | except Exception as e: 375 | print(f"处理奖牌统计时出错: {e}") 376 | return pd.DataFrame(columns=['NOC', 'Gold', 'Silver', 'Bronze', 'Total']) # 返回空DataFrame但包含正确的列 377 | 378 | if __name__ == "__main__": 379 | try: 380 | # 运行预测 381 | predictions, team_stats = process_and_predict() 382 | print("预测完成") 383 | except Exception as e: 384 | print(f"运行过程中出错: {e}") 385 | -------------------------------------------------------------------------------- /2025_Problem_C_Data/summerOly_hosts.csv: -------------------------------------------------------------------------------- 1 | Year,Host 2 | 1896," Athens, Greece" 3 | 1900," Paris, France" 4 | 1904," St. Louis, United States" 5 | 1908," London, United Kingdom" 6 | 1912," Stockholm, Sweden" 7 | 1916, Cancelled (WWI – Berlin had been awarded) 8 | 1920," Antwerp, Belgium" 9 | 1924," Paris, France" 10 | 1928," Amsterdam, Netherlands" 11 | 1932," Los Angeles, United States" 12 | 1936," Berlin, Germany" 13 | 1940, Cancelled (WWII – Tokyo had been awarded) 14 | 1944, Cancelled (WWII – London had been awarded) 15 | 1948," London, United Kingdom" 16 | 1952," Helsinki, Finland" 17 | 1956," Melbourne, Australia" 18 | 1960," Rome, Italy" 19 | 1964," Tokyo, Japan" 20 | 1968," Mexico City, Mexico" 21 | 1972," Munich, West Germany" 22 | 1976," Montreal, Canada" 23 | 1980," Moscow, Soviet Union" 24 | 1984," Los Angeles, United States" 25 | 1988," Seoul, South Korea" 26 | 1992," Barcelona, Spain" 27 | 1996," Atlanta, United States" 28 | 2000," Sydney, Australia" 29 | 2004," Athens, Greece" 30 | 2008," Beijing, China" 31 | 2012," London, United Kingdom" 32 | 2016," Rio de Janeiro, Brazil" 33 | 2020," Tokyo, Japan (postponed to 2021 due to the coronavirus pandemic)" 34 | 2024," Paris, France" 35 | 2028," Los Angeles, United States" 36 | 2032," Brisbane, Australia" -------------------------------------------------------------------------------- /2025_Problem_C_Data/summerOly_medal_counts.csv: -------------------------------------------------------------------------------- 1 | Rank,NOC,Gold,Silver,Bronze,Total,Year 2 | 1,United States,11,7,2,20,1896 3 | 2,Greece,10,18,19,47,1896 4 | 3,Germany,6,5,2,13,1896 5 | 4,France,5,4,2,11,1896 6 | 5,Great Britain,2,3,2,7,1896 7 | 6,Hungary,2,1,3,6,1896 8 | 7,Austria,2,1,2,5,1896 9 | 8,Australia,2,0,0,2,1896 10 | 9,Denmark,1,2,3,6,1896 11 | 10,Switzerland,1,2,0,3,1896 12 | 11,Mixed team,1,0,1,2,1896 13 | 1,France,27,39,37,103,1900 14 | 2,United States,19,14,15,48,1900 15 | 3,Great Britain,15,7,9,31,1900 16 | 4,Mixed team,8,5,6,19,1900 17 | 5,Belgium,6,7,4,17,1900 18 | 6,Switzerland,6,2,1,9,1900 19 | 7,Germany,4,3,2,9,1900 20 | 8,Italy,3,2,0,5,1900 21 | 9,Australia,2,0,3,5,1900 22 | 10,Denmark,1,3,2,6,1900 23 | 11,Hungary,1,2,2,5,1900 24 | 12,Cuba,1,1,0,2,1900 25 | 13,Canada,1,0,1,2,1900 26 | 14,Spain,1,0,0,1,1900 27 | 14,Luxembourg,1,0,0,1,1900 28 | 16,Austria,0,3,3,6,1900 29 | 17,Norway,0,2,3,5,1900 30 | 17,Netherlands,0,2,3,5,1900 31 | 19,India,0,2,0,2,1900 32 | 20,Bohemia,0,1,1,2,1900 33 | 21,Sweden,0,0,1,1,1900 34 | 1,United States,76,78,77,231,1904 35 | 2,Germany,4,5,6,15,1904 36 | 3,Canada,4,1,1,6,1904 37 | 4,Cuba,3,0,0,3,1904 38 | 5,Hungary,2,1,1,4,1904 39 | 5,Mixed team,2,1,1,4,1904 40 | 7,Norway,2,0,0,2,1904 41 | 8,Austria,1,1,1,3,1904 42 | 9,Great Britain,1,1,0,2,1904 43 | 10,Switzerland,1,0,2,3,1904 44 | 11,Greece,1,0,1,2,1904 45 | 12,Australia,0,3,1,4,1904 46 | 13,France,0,1,0,1,1904 47 | 1,Great Britain,56,51,39,146,1908 48 | 2,United States,23,12,12,47,1908 49 | 3,Sweden,8,6,11,25,1908 50 | 4,France,5,5,9,19,1908 51 | 5,Germany,3,5,5,13,1908 52 | 6,Hungary,3,4,2,9,1908 53 | 7,Canada,3,3,10,16,1908 54 | 8,Norway,2,3,3,8,1908 55 | 9,Italy,2,2,0,4,1908 56 | 10,Belgium,1,5,2,8,1908 57 | 11,Australasia,1,2,2,5,1908 58 | 12,Russian Empire,1,2,0,3,1908 59 | 13,Finland,1,1,3,5,1908 60 | 14,South Africa,1,1,0,2,1908 61 | 15,Greece,0,3,1,4,1908 62 | 16,Denmark,0,2,3,5,1908 63 | 17,Bohemia,0,0,2,2,1908 64 | 17,Netherlands,0,0,2,2,1908 65 | 19,Austria,0,0,1,1,1908 66 | 1,United States,26,19,19,64,1912 67 | 2,Sweden,23,25,17,65,1912 68 | 3,Great Britain,10,15,16,41,1912 69 | 4,Finland,9,8,9,26,1912 70 | 5,France,7,4,3,14,1912 71 | 6,Germany,5,13,7,25,1912 72 | 7,South Africa,4,2,0,6,1912 73 | 8,Norway,3,2,5,10,1912 74 | 9,Canada,3,2,3,8,1912 75 | 9,Hungary,3,2,3,8,1912 76 | 11,Italy,3,1,2,6,1912 77 | 12,Australasia,2,2,3,7,1912 78 | 13,Belgium,2,1,3,6,1912 79 | 14,Denmark,1,6,5,12,1912 80 | 15,Greece,1,0,1,2,1912 81 | 16,Russian Empire,0,2,3,5,1912 82 | 17,Austria,0,2,2,4,1912 83 | 18,Netherlands,0,0,3,3,1912 84 | 1,United States,41,27,27,95,1920 85 | 2,Sweden,19,20,25,64,1920 86 | 3,Finland,15,10,9,34,1920 87 | 4,Great Britain,14,15,13,42,1920 88 | 5,Belgium,14,11,11,36,1920 89 | 6,Norway,13,9,9,31,1920 90 | 7,Italy,13,5,5,23,1920 91 | 8,France,9,19,13,41,1920 92 | 9,Netherlands,4,2,5,11,1920 93 | 10,Denmark,3,9,1,13,1920 94 | 11,South Africa,3,4,3,10,1920 95 | 12,Canada,3,3,3,9,1920 96 | 13,Switzerland,2,2,7,11,1920 97 | 14,Estonia,1,2,0,3,1920 98 | 15,Brazil,1,1,1,3,1920 99 | 16,Australia,0,2,1,3,1920 100 | 17,Japan,0,2,0,2,1920 101 | 17,Spain,0,2,0,2,1920 102 | 19,Greece,0,1,0,1,1920 103 | 19,Luxembourg,0,1,0,1,1920 104 | 21,Czechoslovakia,0,0,2,2,1920 105 | 22,New Zealand,0,0,1,1,1920 106 | 1,United States,45,27,27,99,1924 107 | 2,Finland,14,13,10,37,1924 108 | 3,France,13,15,10,38,1924 109 | 4,Great Britain,9,13,12,34,1924 110 | 5,Italy,8,3,5,16,1924 111 | 6,Switzerland,7,8,10,25,1924 112 | 7,Norway,5,2,3,10,1924 113 | 8,Sweden,4,13,12,29,1924 114 | 9,Netherlands,4,1,5,10,1924 115 | 10,Belgium,3,7,3,13,1924 116 | 11,Australia,3,1,2,6,1924 117 | 12,Denmark,2,5,2,9,1924 118 | 13,Hungary,2,3,4,9,1924 119 | 14,Yugoslavia,2,0,0,2,1924 120 | 15,Czechoslovakia,1,4,5,10,1924 121 | 16,Argentina,1,3,2,6,1924 122 | 17,Estonia,1,1,4,6,1924 123 | 18,South Africa,1,1,1,3,1924 124 | 19,Uruguay,1,0,0,1,1924 125 | 20,Austria,0,3,1,4,1924 126 | 20,Canada,0,3,1,4,1924 127 | 22,Poland,0,1,1,2,1924 128 | 23,Haiti,0,0,1,1,1924 129 | 23,Japan,0,0,1,1,1924 130 | 23,New Zealand,0,0,1,1,1924 131 | 23,Portugal,0,0,1,1,1924 132 | 23,Romania,0,0,1,1,1924 133 | 1,United States,22,18,16,56,1928 134 | 2,Germany,10,7,14,31,1928 135 | 3,Finland,8,8,9,25,1928 136 | 4,Sweden,7,6,12,25,1928 137 | 5,Italy,7,5,7,19,1928 138 | 6,Switzerland,7,4,4,15,1928 139 | 7,France,6,10,5,21,1928 140 | 8,Netherlands,6,9,4,19,1928 141 | 9,Hungary,4,5,0,9,1928 142 | 10,Canada,4,4,7,15,1928 143 | 11,Great Britain,3,10,7,20,1928 144 | 12,Argentina,3,3,1,7,1928 145 | 13,Denmark,3,1,2,6,1928 146 | 14,Czechoslovakia,2,5,2,9,1928 147 | 15,Japan,2,2,1,5,1928 148 | 16,Estonia,2,1,2,5,1928 149 | 17,Egypt,2,1,1,4,1928 150 | 18,Austria,2,0,1,3,1928 151 | 19,Australia,1,2,1,4,1928 152 | 19,Norway,1,2,1,4,1928 153 | 21,Poland,1,1,3,5,1928 154 | 21,Yugoslavia,1,1,3,5,1928 155 | 23,South Africa,1,0,2,3,1928 156 | 24,India,1,0,0,1,1928 157 | 24,Ireland,1,0,0,1,1928 158 | 24,New Zealand,1,0,0,1,1928 159 | 24,Spain,1,0,0,1,1928 160 | 24,Uruguay,1,0,0,1,1928 161 | 29,Belgium,0,1,2,3,1928 162 | 30,Chile,0,1,0,1,1928 163 | 30,Haiti,0,1,0,1,1928 164 | 32,Philippines,0,0,1,1,1928 165 | 32,Portugal,0,0,1,1,1928 166 | 1,United States ,44,36,30,110,1932 167 | 2,Italy ,12,12,12,36,1932 168 | 3,France ,11,5,4,20,1932 169 | 4,Sweden ,10,5,9,24,1932 170 | 5,Japan ,7,7,4,18,1932 171 | 6,Hungary ,6,5,5,16,1932 172 | 7,Germany ,5,12,7,24,1932 173 | 8,Finland ,5,8,12,25,1932 174 | 9,Great Britain ,5,7,5,17,1932 175 | 10,Poland ,3,2,4,9,1932 176 | 11,Australia ,3,1,1,5,1932 177 | 12,Argentina ,3,1,0,4,1932 178 | 13,Canada ,2,5,9,16,1932 179 | 14,Netherlands ,2,5,1,8,1932 180 | 15,South Africa ,2,0,3,5,1932 181 | 16,Ireland ,2,0,0,2,1932 182 | 17,Czechoslovakia ,1,3,2,6,1932 183 | 18,Austria ,1,1,3,5,1932 184 | 19,India ,1,0,0,1,1932 185 | 20,Denmark ,0,5,3,8,1932 186 | 21,Mexico ,0,2,0,2,1932 187 | 22,Latvia ,0,1,0,1,1932 188 | 22,New Zealand ,0,1,0,1,1932 189 | 22,Switzerland ,0,1,0,1,1932 190 | 25,Philippines ,0,0,3,3,1932 191 | 26,Belgium ,0,0,1,1,1932 192 | 26,Spain ,0,0,1,1,1932 193 | 26,Uruguay ,0,0,1,1,1932 194 | 1,Germany,38,31,32,101,1936 195 | 2,United States,24,21,12,57,1936 196 | 3,Hungary,10,1,5,16,1936 197 | 4,Italy,9,13,5,27,1936 198 | 5,Finland,8,6,6,20,1936 199 | 6,France,7,6,6,19,1936 200 | 7,Sweden,6,5,10,21,1936 201 | 8,Japan,6,4,10,20,1936 202 | 9,Netherlands,6,4,7,17,1936 203 | 10,Austria,5,7,5,17,1936 204 | 11,Switzerland,4,9,5,18,1936 205 | 12,Great Britain,4,7,3,14,1936 206 | 13,Czechoslovakia,3,5,1,9,1936 207 | 14,Argentina,2,2,3,7,1936 208 | 14,Estonia,2,2,3,7,1936 209 | 16,Egypt,2,1,2,5,1936 210 | 17,Canada,1,3,5,9,1936 211 | 18,Norway,1,3,2,6,1936 212 | 19,Turkey,1,0,1,2,1936 213 | 20,India,1,0,0,1,1936 214 | 20,New Zealand,1,0,0,1,1936 215 | 22,Poland,0,4,5,9,1936 216 | 23,Denmark,0,2,3,5,1936 217 | 24,Latvia,0,1,1,2,1936 218 | 25,Romania,0,1,0,1,1936 219 | 25,South Africa,0,1,0,1,1936 220 | 25,Yugoslavia,0,1,0,1,1936 221 | 28,Belgium,0,0,3,3,1936 222 | 28,Mexico,0,0,3,3,1936 223 | 30,Australia,0,0,1,1,1936 224 | 30,Philippines,0,0,1,1,1936 225 | 30,Portugal,0,0,1,1,1936 226 | 1,United States,38,27,19,84,1948 227 | 2,Sweden,16,11,17,44,1948 228 | 3,France,10,6,13,29,1948 229 | 4,Hungary,10,5,12,27,1948 230 | 5,Italy,8,11,8,27,1948 231 | 6,Finland,8,7,5,20,1948 232 | 7,Turkey,6,4,2,12,1948 233 | 8,Czechoslovakia,6,2,3,11,1948 234 | 9,Switzerland,5,10,5,20,1948 235 | 10,Denmark,5,7,8,20,1948 236 | 11,Netherlands,5,2,9,16,1948 237 | 12,Great Britain,3,14,6,23,1948 238 | 13,Argentina,3,3,1,7,1948 239 | 14,Australia,2,6,5,13,1948 240 | 15,Belgium,2,2,3,7,1948 241 | 16,Egypt,2,2,1,5,1948 242 | 17,Mexico,2,1,2,5,1948 243 | 18,South Africa,2,1,1,4,1948 244 | 19,Norway,1,3,3,7,1948 245 | 20,Jamaica,1,2,0,3,1948 246 | 21,Austria,1,0,3,4,1948 247 | 22,India,1,0,0,1,1948 248 | 22,Peru,1,0,0,1,1948 249 | 24,Yugoslavia,0,2,0,2,1948 250 | 25,Canada,0,1,2,3,1948 251 | 26,Portugal,0,1,1,2,1948 252 | 26,Uruguay,0,1,1,2,1948 253 | 28,Ceylon,0,1,0,1,1948 254 | 28,Cuba,0,1,0,1,1948 255 | 28,Spain,0,1,0,1,1948 256 | 28,Trinidad and Tobago,0,1,0,1,1948 257 | 32,Panama,0,0,2,2,1948 258 | 32,South Korea,0,0,2,2,1948 259 | 34,Brazil,0,0,1,1,1948 260 | 34,Iran,0,0,1,1,1948 261 | 34,Poland,0,0,1,1,1948 262 | 34,Puerto Rico,0,0,1,1,1948 263 | 1,United States,40,19,17,76,1952 264 | 2,Soviet Union,22,30,19,71,1952 265 | 3,Hungary,16,10,16,42,1952 266 | 4,Sweden,12,13,10,35,1952 267 | 5,Italy,8,9,4,21,1952 268 | 6,Czechoslovakia,7,3,3,13,1952 269 | 7,France,6,6,6,18,1952 270 | 8,Finland,6,3,13,22,1952 271 | 9,Australia,6,2,3,11,1952 272 | 10,Norway,3,2,0,5,1952 273 | 11,Switzerland,2,6,6,14,1952 274 | 12,South Africa,2,4,4,10,1952 275 | 13,Jamaica,2,3,0,5,1952 276 | 14,Belgium,2,2,0,4,1952 277 | 15,Denmark,2,1,3,6,1952 278 | 16,Turkey,2,0,1,3,1952 279 | 17,Japan,1,6,2,9,1952 280 | 18,Great Britain,1,2,8,11,1952 281 | 19,Argentina,1,2,2,5,1952 282 | 20,Poland,1,2,1,4,1952 283 | 21,Canada,1,2,0,3,1952 284 | 21,Yugoslavia,1,2,0,3,1952 285 | 23,Romania,1,1,2,4,1952 286 | 24,Brazil,1,0,2,3,1952 287 | 24,New Zealand,1,0,2,3,1952 288 | 26,India,1,0,1,2,1952 289 | 27,Luxembourg,1,0,0,1,1952 290 | 28,Germany,0,7,17,24,1952 291 | 29,Netherlands,0,5,0,5,1952 292 | 30,Iran,0,3,4,7,1952 293 | 31,Chile,0,2,0,2,1952 294 | 32,Austria,0,1,1,2,1952 295 | 32,Lebanon,0,1,1,2,1952 296 | 34,Ireland,0,1,0,1,1952 297 | 34,Mexico,0,1,0,1,1952 298 | 34,Spain,0,1,0,1,1952 299 | 37,South Korea,0,0,2,2,1952 300 | 37,Trinidad and Tobago,0,0,2,2,1952 301 | 37,Uruguay,0,0,2,2,1952 302 | 40,Bulgaria,0,0,1,1,1952 303 | 40,Egypt,0,0,1,1,1952 304 | 40,Portugal,0,0,1,1,1952 305 | 40,Venezuela,0,0,1,1,1952 306 | 1,Soviet Union,37,29,32,98,1956 307 | 2,United States,32,25,17,74,1956 308 | 3,Australia,13,8,14,35,1956 309 | 4,Hungary,9,10,7,26,1956 310 | 5,Italy,8,8,9,25,1956 311 | 6,Sweden,8,5,6,19,1956 312 | 7,United Team of Germany,6,13,7,26,1956 313 | 8,Great Britain,6,7,11,24,1956 314 | 9,Romania,5,3,5,13,1956 315 | 10,Japan,4,10,5,19,1956 316 | 11,France,4,4,6,14,1956 317 | 12,Turkey,3,2,2,7,1956 318 | 13,Finland,3,1,11,15,1956 319 | 14,Iran,2,2,1,5,1956 320 | 15,Canada,2,1,3,6,1956 321 | 16,New Zealand,2,0,0,2,1956 322 | 17,Poland,1,4,4,9,1956 323 | 18,Czechoslovakia,1,4,1,6,1956 324 | 19,Bulgaria,1,3,1,5,1956 325 | 20,Denmark,1,2,1,4,1956 326 | 21,Ireland,1,1,3,5,1956 327 | 22,Norway,1,0,2,3,1956 328 | 23,Mexico,1,0,1,2,1956 329 | 24,Brazil,1,0,0,1,1956 330 | 24,India,1,0,0,1,1956 331 | 26,Yugoslavia,0,3,0,3,1956 332 | 27,Chile,0,2,2,4,1956 333 | 28,Belgium,0,2,0,2,1956 334 | 29,Argentina,0,1,1,2,1956 335 | 29,South Korea,0,1,1,2,1956 336 | 31,Iceland,0,1,0,1,1956 337 | 31,Pakistan,0,1,0,1,1956 338 | 33,South Africa,0,0,4,4,1956 339 | 34,Austria,0,0,2,2,1956 340 | 35,Bahamas,0,0,1,1,1956 341 | 35,Greece,0,0,1,1,1956 342 | 35,Switzerland,0,0,1,1,1956 343 | 35,Uruguay,0,0,1,1,1956 344 | 1,Soviet Union ,43,29,31,103,1960 345 | 2,United States ,34,21,16,71,1960 346 | 3,Italy ,13,10,13,36,1960 347 | 4,United Team of Germany ,12,19,11,42,1960 348 | 5,Australia ,8,8,6,22,1960 349 | 6,Turkey ,7,2,0,9,1960 350 | 7,Hungary ,6,8,7,21,1960 351 | 8,Japan ,4,7,7,18,1960 352 | 9,Poland ,4,6,11,21,1960 353 | 10,Czechoslovakia ,3,2,3,8,1960 354 | 11,Romania ,3,1,6,10,1960 355 | 12,Great Britain ,2,6,12,20,1960 356 | 13,Denmark ,2,3,1,6,1960 357 | 14,New Zealand ,2,0,1,3,1960 358 | 15,Bulgaria ,1,3,3,7,1960 359 | 16,Sweden ,1,2,3,6,1960 360 | 17,Finland ,1,1,3,5,1960 361 | 18,Austria ,1,1,0,2,1960 362 | 18,Yugoslavia ,1,1,0,2,1960 363 | 20,Pakistan ,1,0,1,2,1960 364 | 21,Ethiopia ,1,0,0,1,1960 365 | 21,Greece ,1,0,0,1,1960 366 | 21,Norway ,1,0,0,1,1960 367 | 24,Switzerland ,0,3,3,6,1960 368 | 25,France ,0,2,3,5,1960 369 | 26,Belgium ,0,2,2,4,1960 370 | 27,Iran ,0,1,3,4,1960 371 | 28,Netherlands ,0,1,2,3,1960 372 | 28,South Africa ,0,1,2,3,1960 373 | 30,Argentina ,0,1,1,2,1960 374 | 30,Egypt ,0,1,1,2,1960 375 | 32,Canada ,0,1,0,1,1960 376 | 32,Formosa ,0,1,0,1,1960 377 | 32,Ghana ,0,1,0,1,1960 378 | 32,India ,0,1,0,1,1960 379 | 32,Morocco ,0,1,0,1,1960 380 | 32,Portugal ,0,1,0,1,1960 381 | 32,Singapore ,0,1,0,1,1960 382 | 39,Brazil ,0,0,2,2,1960 383 | 39,British West Indies ,0,0,2,2,1960 384 | 41,Iraq ,0,0,1,1,1960 385 | 41,Mexico ,0,0,1,1,1960 386 | 41,Spain ,0,0,1,1,1960 387 | 41,Venezuela ,0,0,1,1,1960 388 | 1,United States,36,26,28,90,1964 389 | 2,Soviet Union,30,31,35,96,1964 390 | 3,Japan,16,5,8,29,1964 391 | 4,United Team of Germany,10,22,18,50,1964 392 | 5,Italy,10,10,7,27,1964 393 | 6,Hungary,10,7,5,22,1964 394 | 7,Poland,7,6,10,23,1964 395 | 8,Australia,6,2,10,18,1964 396 | 9,Czechoslovakia,5,6,3,14,1964 397 | 10,Great Britain,4,12,2,18,1964 398 | 11,Bulgaria,3,5,2,10,1964 399 | 12,Finland,3,0,2,5,1964 400 | 12,New Zealand,3,0,2,5,1964 401 | 14,Romania,2,4,6,12,1964 402 | 15,Netherlands,2,4,4,10,1964 403 | 16,Turkey,2,3,1,6,1964 404 | 17,Sweden,2,2,4,8,1964 405 | 18,Denmark,2,1,3,6,1964 406 | 19,Yugoslavia,2,1,2,5,1964 407 | 20,Belgium,2,0,1,3,1964 408 | 21,France,1,8,6,15,1964 409 | 22,Canada,1,2,1,4,1964 410 | 22,Switzerland,1,2,1,4,1964 411 | 24,Bahamas,1,0,0,1,1964 412 | 24,Ethiopia,1,0,0,1,1964 413 | 24,India,1,0,0,1,1964 414 | 27,South Korea,0,2,1,3,1964 415 | 28,Trinidad and Tobago,0,1,2,3,1964 416 | 29,Tunisia,0,1,1,2,1964 417 | 30,Argentina,0,1,0,1,1964 418 | 30,Cuba,0,1,0,1,1964 419 | 30,Pakistan,0,1,0,1,1964 420 | 30,Philippines,0,1,0,1,1964 421 | 34,Iran,0,0,2,2,1964 422 | 35,Brazil,0,0,1,1,1964 423 | 35,Ghana,0,0,1,1,1964 424 | 35,Ireland,0,0,1,1,1964 425 | 35,Kenya,0,0,1,1,1964 426 | 35,Mexico,0,0,1,1,1964 427 | 35,Nigeria,0,0,1,1,1964 428 | 35,Uruguay,0,0,1,1,1964 429 | 1,United States,45,28,34,107,1968 430 | 2,Soviet Union,29,32,30,91,1968 431 | 3,Japan,11,7,7,25,1968 432 | 4,Hungary,10,10,12,32,1968 433 | 5,East Germany,9,9,7,25,1968 434 | 6,France,7,3,5,15,1968 435 | 7,Czechoslovakia,7,2,4,13,1968 436 | 8,West Germany,5,11,10,26,1968 437 | 9,Australia,5,7,5,17,1968 438 | 10,Great Britain,5,5,3,13,1968 439 | 11,Poland,5,2,11,18,1968 440 | 12,Romania,4,6,5,15,1968 441 | 13,Italy,3,4,9,16,1968 442 | 14,Kenya,3,4,2,9,1968 443 | 15,Mexico,3,3,3,9,1968 444 | 16,Yugoslavia,3,3,2,8,1968 445 | 17,Netherlands,3,3,1,7,1968 446 | 18,Bulgaria,2,4,3,9,1968 447 | 19,Iran,2,1,2,5,1968 448 | 20,Sweden,2,1,1,4,1968 449 | 21,Turkey,2,0,0,2,1968 450 | 22,Denmark,1,4,3,8,1968 451 | 23,Canada,1,3,1,5,1968 452 | 24,Finland,1,2,1,4,1968 453 | 25,Ethiopia,1,1,0,2,1968 454 | 25,Norway,1,1,0,2,1968 455 | 27,New Zealand,1,0,2,3,1968 456 | 28,Tunisia,1,0,1,2,1968 457 | 29,Pakistan,1,0,0,1,1968 458 | 29,Venezuela,1,0,0,1,1968 459 | 31,Cuba,0,4,0,4,1968 460 | 32,Austria,0,2,2,4,1968 461 | 33,Switzerland,0,1,4,5,1968 462 | 34,Mongolia,0,1,3,4,1968 463 | 35,Brazil,0,1,2,3,1968 464 | 36,Belgium,0,1,1,2,1968 465 | 36,South Korea,0,1,1,2,1968 466 | 36,Uganda,0,1,1,2,1968 467 | 39,Cameroon,0,1,0,1,1968 468 | 39,Jamaica,0,1,0,1,1968 469 | 41,Argentina,0,0,2,2,1968 470 | 42,Greece,0,0,1,1,1968 471 | 42,India,0,0,1,1,1968 472 | 42,Taiwan,0,0,1,1,1968 473 | 1,Soviet Union,50,27,22,99,1972 474 | 2,United States,33,31,30,94,1972 475 | 3,East Germany,20,23,23,66,1972 476 | 4,West Germany,13,11,16,40,1972 477 | 5,Japan,13,8,8,29,1972 478 | 6,Australia,8,7,2,17,1972 479 | 7,Poland,7,5,9,21,1972 480 | 8,Hungary,6,13,16,35,1972 481 | 9,Bulgaria,6,10,5,21,1972 482 | 10,Italy,5,3,10,18,1972 483 | 11,Sweden,4,6,6,16,1972 484 | 12,Great Britain,4,5,9,18,1972 485 | 13,Romania,3,6,7,16,1972 486 | 14,Cuba,3,1,4,8,1972 487 | 14,Finland,3,1,4,8,1972 488 | 16,Netherlands,3,1,1,5,1972 489 | 17,France,2,4,7,13,1972 490 | 18,Czechoslovakia,2,4,2,8,1972 491 | 19,Kenya,2,3,4,9,1972 492 | 20,Yugoslavia,2,1,2,5,1972 493 | 21,Norway,2,1,1,4,1972 494 | 22,North Korea,1,1,3,5,1972 495 | 23,New Zealand,1,1,1,3,1972 496 | 24,Uganda,1,1,0,2,1972 497 | 25,Denmark,1,0,0,1,1972 498 | 26,Switzerland,0,3,0,3,1972 499 | 27,Canada,0,2,3,5,1972 500 | 28,Iran,0,2,1,3,1972 501 | 29,Belgium,0,2,0,2,1972 502 | 29,Greece,0,2,0,2,1972 503 | 31,Austria,0,1,2,3,1972 504 | 31,Colombia,0,1,2,3,1972 505 | 33,Argentina,0,1,0,1,1972 506 | 33,Lebanon,0,1,0,1,1972 507 | 33,Mexico,0,1,0,1,1972 508 | 33,Mongolia,0,1,0,1,1972 509 | 33,Pakistan,0,1,0,1,1972 510 | 33,South Korea,0,1,0,1,1972 511 | 33,Tunisia,0,1,0,1,1972 512 | 33,Turkey,0,1,0,1,1972 513 | 41,Brazil,0,0,2,2,1972 514 | 41,Ethiopia,0,0,2,2,1972 515 | 43,Ghana,0,0,1,1,1972 516 | 43,India,0,0,1,1,1972 517 | 43,Jamaica,0,0,1,1,1972 518 | 43,Niger,0,0,1,1,1972 519 | 43,Nigeria,0,0,1,1,1972 520 | 43,Spain,0,0,1,1,1972 521 | 1,Soviet Union,49,41,35,125,1976 522 | 2,East Germany,40,25,25,90,1976 523 | 3,United States,34,35,25,94,1976 524 | 4,West Germany,10,12,17,39,1976 525 | 5,Japan,9,6,10,25,1976 526 | 6,Poland,7,6,13,26,1976 527 | 7,Bulgaria,6,9,7,22,1976 528 | 8,Cuba,6,4,3,13,1976 529 | 9,Romania,4,9,14,27,1976 530 | 10,Hungary,4,5,13,22,1976 531 | 11,Finland,4,2,0,6,1976 532 | 12,Sweden,4,1,0,5,1976 533 | 13,Great Britain,3,5,5,13,1976 534 | 14,Italy,2,7,4,13,1976 535 | 15,France,2,3,4,9,1976 536 | 16,Yugoslavia,2,3,3,8,1976 537 | 17,Czechoslovakia,2,2,4,8,1976 538 | 18,New Zealand,2,1,1,4,1976 539 | 19,South Korea,1,1,4,6,1976 540 | 20,Switzerland,1,1,2,4,1976 541 | 21,Jamaica,1,1,0,2,1976 542 | 21,North Korea,1,1,0,2,1976 543 | 21,Norway,1,1,0,2,1976 544 | 24,Denmark,1,0,2,3,1976 545 | 25,Mexico,1,0,1,2,1976 546 | 26,Trinidad and Tobago,1,0,0,1,1976 547 | 27,Canada,0,5,6,11,1976 548 | 28,Belgium,0,3,3,6,1976 549 | 29,Netherlands,0,2,3,5,1976 550 | 30,Portugal,0,2,0,2,1976 551 | 30,Spain,0,2,0,2,1976 552 | 32,Australia,0,1,4,5,1976 553 | 33,Iran,0,1,1,2,1976 554 | 34,Mongolia,0,1,0,1,1976 555 | 34,Venezuela,0,1,0,1,1976 556 | 36,Brazil,0,0,2,2,1976 557 | 37,Austria,0,0,1,1,1976 558 | 37,Bermuda,0,0,1,1,1976 559 | 37,Pakistan,0,0,1,1,1976 560 | 37,Puerto Rico,0,0,1,1,1976 561 | 37,Thailand,0,0,1,1,1976 562 | 1,Soviet Union,80,69,46,195,1980 563 | 2,East Germany,47,37,42,126,1980 564 | 3,Bulgaria,8,16,17,41,1980 565 | 4,Cuba,8,7,5,20,1980 566 | 5,Italy,8,3,4,15,1980 567 | 6,Hungary,7,10,15,32,1980 568 | 7,Romania,6,6,13,25,1980 569 | 8,France,6,5,3,14,1980 570 | 9,Great Britain,5,7,9,21,1980 571 | 10,Poland,3,14,15,32,1980 572 | 11,Sweden,3,3,6,12,1980 573 | 12,Finland,3,1,4,8,1980 574 | 13,Czechoslovakia,2,3,9,14,1980 575 | 14,Yugoslavia,2,3,4,9,1980 576 | 15,Australia,2,2,5,9,1980 577 | 16,Denmark,2,1,2,5,1980 578 | 17,Brazil,2,0,2,4,1980 579 | 17,Ethiopia,2,0,2,4,1980 580 | 19,Switzerland,2,0,0,2,1980 581 | 20,Spain,1,3,2,6,1980 582 | 21,Austria,1,2,1,4,1980 583 | 22,Greece,1,0,2,3,1980 584 | 23,Belgium,1,0,0,1,1980 585 | 23,India,1,0,0,1,1980 586 | 23,Zimbabwe,1,0,0,1,1980 587 | 26,North Korea,0,3,2,5,1980 588 | 27,Mongolia,0,2,2,4,1980 589 | 28,Tanzania,0,2,0,2,1980 590 | 29,Mexico,0,1,3,4,1980 591 | 30,Netherlands,0,1,2,3,1980 592 | 31,Ireland,0,1,1,2,1980 593 | 32,Uganda,0,1,0,1,1980 594 | 32,Venezuela,0,1,0,1,1980 595 | 34,Jamaica,0,0,3,3,1980 596 | 35,Guyana,0,0,1,1,1980 597 | 35,Lebanon,0,0,1,1,1980 598 | 1,United States,83,61,30,174,1984 599 | 2,Romania,20,16,17,53,1984 600 | 3,West Germany,17,19,23,59,1984 601 | 4,China,15,8,9,32,1984 602 | 5,Italy,14,6,12,32,1984 603 | 6,Canada,10,18,16,44,1984 604 | 7,Japan,10,8,14,32,1984 605 | 8,New Zealand,8,1,2,11,1984 606 | 9,Yugoslavia,7,4,7,18,1984 607 | 10,South Korea,6,6,7,19,1984 608 | 11,Great Britain,5,11,21,37,1984 609 | 12,France,5,7,16,28,1984 610 | 13,Netherlands,5,2,6,13,1984 611 | 14,Australia,4,8,12,24,1984 612 | 15,Finland,4,2,6,12,1984 613 | 16,Sweden,2,11,6,19,1984 614 | 17,Mexico,2,3,1,6,1984 615 | 18,Morocco,2,0,0,2,1984 616 | 19,Brazil,1,5,2,8,1984 617 | 20,Spain,1,2,2,5,1984 618 | 21,Belgium,1,1,2,4,1984 619 | 22,Austria,1,1,1,3,1984 620 | 23,Kenya,1,0,2,3,1984 621 | 23,Portugal,1,0,2,3,1984 622 | 25,Pakistan,1,0,0,1,1984 623 | 26,Switzerland,0,4,4,8,1984 624 | 27,Denmark,0,3,3,6,1984 625 | 28,Jamaica,0,1,2,3,1984 626 | 28,Norway,0,1,2,3,1984 627 | 30,Greece,0,1,1,2,1984 628 | 30,Nigeria,0,1,1,2,1984 629 | 30,Puerto Rico,0,1,1,2,1984 630 | 33,Colombia,0,1,0,1,1984 631 | 33,Egypt,0,1,0,1,1984 632 | 33,Ireland,0,1,0,1,1984 633 | 33,Ivory Coast,0,1,0,1,1984 634 | 33,Peru,0,1,0,1,1984 635 | 33,Syria,0,1,0,1,1984 636 | 33,Thailand,0,1,0,1,1984 637 | 40,Turkey,0,0,3,3,1984 638 | 40,Venezuela,0,0,3,3,1984 639 | 42,Algeria,0,0,2,2,1984 640 | 43,Cameroon,0,0,1,1,1984 641 | 43,Chinese Taipei,0,0,1,1,1984 642 | 43,Dominican Republic,0,0,1,1,1984 643 | 43,Iceland,0,0,1,1,1984 644 | 43,Zambia,0,0,1,1,1984 645 | 1,Soviet Union,55,31,46,132,1988 646 | 2,East Germany,37,35,30,102,1988 647 | 3,United States,36,31,27,94,1988 648 | 4,South Korea,12,10,11,33,1988 649 | 5,West Germany,11,14,15,40,1988 650 | 6,Hungary,11,6,6,23,1988 651 | 7,Bulgaria,10,12,13,35,1988 652 | 8,Romania,7,11,6,24,1988 653 | 9,France,6,4,6,16,1988 654 | 10,Italy,6,4,4,14,1988 655 | 11,China,5,11,12,28,1988 656 | 12,Great Britain,5,10,9,24,1988 657 | 13,Kenya,5,2,2,9,1988 658 | 14,Japan,4,3,7,14,1988 659 | 15,Australia,3,6,5,14,1988 660 | 16,Yugoslavia,3,4,5,12,1988 661 | 17,Czechoslovakia,3,3,2,8,1988 662 | 18,New Zealand,3,2,8,13,1988 663 | 19,Canada,3,2,5,10,1988 664 | 20,Poland,2,5,9,16,1988 665 | 21,Norway,2,3,0,5,1988 666 | 22,Netherlands,2,2,5,9,1988 667 | 23,Denmark,2,1,1,4,1988 668 | 24,Brazil,1,2,3,6,1988 669 | 25,Finland,1,1,2,4,1988 670 | 25,Spain,1,1,2,4,1988 671 | 27,Turkey,1,1,0,2,1988 672 | 28,Morocco,1,0,2,3,1988 673 | 29,Austria,1,0,0,1,1988 674 | 29,Portugal,1,0,0,1,1988 675 | 29,Suriname,1,0,0,1,1988 676 | 32,Sweden,0,4,7,11,1988 677 | 33,Switzerland,0,2,2,4,1988 678 | 34,Jamaica,0,2,0,2,1988 679 | 35,Argentina,0,1,1,2,1988 680 | 36,Chile,0,1,0,1,1988 681 | 36,Costa Rica,0,1,0,1,1988 682 | 36,Indonesia,0,1,0,1,1988 683 | 36,Iran,0,1,0,1,1988 684 | 36,Netherlands Antilles,0,1,0,1,1988 685 | 36,Peru,0,1,0,1,1988 686 | 36,Senegal,0,1,0,1,1988 687 | 36,Virgin Islands,0,1,0,1,1988 688 | 44,Belgium,0,0,2,2,1988 689 | 44,Mexico,0,0,2,2,1988 690 | 46,Colombia,0,0,1,1,1988 691 | 46,Djibouti,0,0,1,1,1988 692 | 46,Greece,0,0,1,1,1988 693 | 46,Mongolia,0,0,1,1,1988 694 | 46,Pakistan,0,0,1,1,1988 695 | 46,Philippines,0,0,1,1,1988 696 | 46,Thailand,0,0,1,1,1988 697 | 1,Unified Team,45,38,29,112,1992 698 | 2,United States,37,34,37,108,1992 699 | 3,Germany,33,21,28,82,1992 700 | 4,China,16,22,16,54,1992 701 | 5,Cuba,14,6,11,31,1992 702 | 6,Spain,13,7,2,22,1992 703 | 7,South Korea,12,5,12,29,1992 704 | 8,Hungary,11,12,7,30,1992 705 | 9,France,8,5,16,29,1992 706 | 10,Australia,7,9,11,27,1992 707 | 11,Canada,7,4,7,18,1992 708 | 12,Italy,6,5,8,19,1992 709 | 13,Great Britain,5,3,12,20,1992 710 | 14,Romania,4,6,8,18,1992 711 | 15,Czechoslovakia,4,2,1,7,1992 712 | 16,North Korea,4,0,5,9,1992 713 | 17,Japan,3,8,11,22,1992 714 | 18,Bulgaria,3,7,6,16,1992 715 | 19,Poland,3,6,10,19,1992 716 | 20,Netherlands,2,6,7,15,1992 717 | 21,Kenya,2,4,2,8,1992 718 | 22,Norway,2,4,1,7,1992 719 | 23,Turkey,2,2,2,6,1992 720 | 24,Indonesia,2,2,1,5,1992 721 | 25,Brazil,2,1,0,3,1992 722 | 26,Greece,2,0,0,2,1992 723 | 27,Sweden,1,7,4,12,1992 724 | 28,New Zealand,1,4,5,10,1992 725 | 29,Finland,1,2,2,5,1992 726 | 30,Denmark,1,1,4,6,1992 727 | 31,Morocco,1,1,1,3,1992 728 | 32,Ireland,1,1,0,2,1992 729 | 33,Ethiopia,1,0,2,3,1992 730 | 34,Algeria,1,0,1,2,1992 731 | 34,Estonia,1,0,1,2,1992 732 | 34,Lithuania,1,0,1,2,1992 733 | 37,Switzerland,1,0,0,1,1992 734 | 38,Jamaica,0,3,1,4,1992 735 | 38,Nigeria,0,3,1,4,1992 736 | 40,Latvia,0,2,1,3,1992 737 | 41,Austria,0,2,0,2,1992 738 | 41,Namibia,0,2,0,2,1992 739 | 41,South Africa,0,2,0,2,1992 740 | 44,Belgium,0,1,2,3,1992 741 | 44,Croatia,0,1,2,3,1992 742 | 44,Independent Olympic Participants,0,1,2,3,1992 743 | 44,Iran,0,1,2,3,1992 744 | 48,Israel,0,1,1,2,1992 745 | 49,Chinese Taipei,0,1,0,1,1992 746 | 49,Mexico,0,1,0,1,1992 747 | 49,Peru,0,1,0,1,1992 748 | 52,Mongolia,0,0,2,2,1992 749 | 52,Slovenia,0,0,2,2,1992 750 | 54,Argentina,0,0,1,1,1992 751 | 54,Bahamas,0,0,1,1,1992 752 | 54,Colombia,0,0,1,1,1992 753 | 54,Ghana,0,0,1,1,1992 754 | 54,Malaysia,0,0,1,1,1992 755 | 54,Pakistan,0,0,1,1,1992 756 | 54,Philippines,0,0,1,1,1992 757 | 54,Puerto Rico,0,0,1,1,1992 758 | 54,Qatar,0,0,1,1,1992 759 | 54,Suriname,0,0,1,1,1992 760 | 54,Thailand,0,0,1,1,1992 761 | 1,United States,44,32,25,101,1996 762 | 2,Russia,26,21,16,63,1996 763 | 3,Germany,20,18,27,65,1996 764 | 4,China,16,22,12,50,1996 765 | 5,France,15,7,15,37,1996 766 | 6,Italy,13,10,12,35,1996 767 | 7,Australia,9,9,23,41,1996 768 | 8,Cuba,9,8,8,25,1996 769 | 9,Ukraine,9,2,12,23,1996 770 | 10,South Korea,7,15,5,27,1996 771 | 11,Poland,7,5,5,17,1996 772 | 12,Hungary,7,4,10,21,1996 773 | 13,Spain,5,6,6,17,1996 774 | 14,Romania,4,7,9,20,1996 775 | 15,Netherlands,4,5,10,19,1996 776 | 16,Greece,4,4,0,8,1996 777 | 17,Czech Republic,4,3,4,11,1996 778 | 18,Switzerland,4,3,0,7,1996 779 | 19,Denmark,4,1,1,6,1996 780 | 19,Turkey,4,1,1,6,1996 781 | 21,Canada,3,11,8,22,1996 782 | 22,Bulgaria,3,7,5,15,1996 783 | 23,Japan,3,6,5,14,1996 784 | 24,Kazakhstan,3,4,4,11,1996 785 | 25,Brazil,3,3,9,15,1996 786 | 26,New Zealand,3,2,1,6,1996 787 | 27,South Africa,3,1,1,5,1996 788 | 28,Ireland,3,0,1,4,1996 789 | 29,Sweden,2,4,2,8,1996 790 | 30,Norway,2,2,3,7,1996 791 | 31,Belgium,2,2,2,6,1996 792 | 32,Nigeria,2,1,3,6,1996 793 | 33,North Korea,2,1,2,5,1996 794 | 34,Algeria,2,0,1,3,1996 795 | 34,Ethiopia,2,0,1,3,1996 796 | 36,Great Britain,1,8,6,15,1996 797 | 37,Belarus,1,6,8,15,1996 798 | 38,Kenya,1,4,3,8,1996 799 | 39,Jamaica,1,3,2,6,1996 800 | 40,Finland,1,2,1,4,1996 801 | 41,FR Yugoslavia,1,1,2,4,1996 802 | 41,Indonesia,1,1,2,4,1996 803 | 43,Iran,1,1,1,3,1996 804 | 43,Slovakia,1,1,1,3,1996 805 | 45,Armenia,1,1,0,2,1996 806 | 45,Croatia,1,1,0,2,1996 807 | 47,Portugal,1,0,1,2,1996 808 | 47,Thailand,1,0,1,2,1996 809 | 49,Burundi,1,0,0,1,1996 810 | 49,Costa Rica,1,0,0,1,1996 811 | 49,Ecuador,1,0,0,1,1996 812 | 49,Hong Kong,1,0,0,1,1996 813 | 49,Syria,1,0,0,1,1996 814 | 54,Argentina,0,2,1,3,1996 815 | 55,Namibia,0,2,0,2,1996 816 | 55,Slovenia,0,2,0,2,1996 817 | 57,Austria,0,1,2,3,1996 818 | 58,Malaysia,0,1,1,2,1996 819 | 58,Moldova,0,1,1,2,1996 820 | 58,Uzbekistan,0,1,1,2,1996 821 | 61,Azerbaijan,0,1,0,1,1996 822 | 61,Bahamas,0,1,0,1,1996 823 | 61,Chinese Taipei,0,1,0,1,1996 824 | 61,Latvia,0,1,0,1,1996 825 | 61,Philippines,0,1,0,1,1996 826 | 61,Tonga,0,1,0,1,1996 827 | 61,Zambia,0,1,0,1,1996 828 | 68,Georgia,0,0,2,2,1996 829 | 68,Morocco,0,0,2,2,1996 830 | 68,Trinidad and Tobago,0,0,2,2,1996 831 | 71,India,0,0,1,1,1996 832 | 71,Israel,0,0,1,1,1996 833 | 71,Lithuania,0,0,1,1,1996 834 | 71,Mexico,0,0,1,1,1996 835 | 71,Mongolia,0,0,1,1,1996 836 | 71,Mozambique,0,0,1,1,1996 837 | 71,Puerto Rico,0,0,1,1,1996 838 | 71,Tunisia,0,0,1,1,1996 839 | 71,Uganda,0,0,1,1,1996 840 | 1,United States,37,24,32,93,2000 841 | 2,Russia,32,28,29,89,2000 842 | 3,China,28,16,14,58,2000 843 | 4,Australia,16,25,17,58,2000 844 | 5,Germany,13,17,26,56,2000 845 | 6,France,13,14,11,38,2000 846 | 7,Italy,13,8,13,34,2000 847 | 8,Netherlands,12,9,4,25,2000 848 | 9,Cuba,11,11,7,29,2000 849 | 10,Great Britain,11,10,7,28,2000 850 | 11,Romania,11,6,9,26,2000 851 | 12,South Korea,8,10,10,28,2000 852 | 13,Hungary,8,6,3,17,2000 853 | 14,Poland,6,5,3,14,2000 854 | 15,Japan,5,8,5,18,2000 855 | 16,Bulgaria,5,6,2,13,2000 856 | 17,Greece,4,6,3,13,2000 857 | 18,Sweden,4,5,3,12,2000 858 | 19,Norway,4,3,3,10,2000 859 | 20,Ethiopia,4,1,3,8,2000 860 | 21,Ukraine,3,10,10,23,2000 861 | 22,Kazakhstan,3,4,0,7,2000 862 | 23,Belarus,3,3,11,17,2000 863 | 24,Canada,3,3,8,14,2000 864 | 25,Spain,3,3,5,11,2000 865 | 26,Turkey,3,0,2,5,2000 866 | 27,Iran,3,0,1,4,2000 867 | 28,Czech Republic,2,3,3,8,2000 868 | 29,Kenya,2,3,2,7,2000 869 | 30,Denmark,2,3,1,6,2000 870 | 31,Finland,2,1,1,4,2000 871 | 32,Austria,2,1,0,3,2000 872 | 33,Lithuania,2,0,3,5,2000 873 | 34,Azerbaijan,2,0,1,3,2000 874 | 34,Bahamas,2,0,1,3,2000 875 | 36,Slovenia,2,0,0,2,2000 876 | 37,Switzerland,1,6,2,9,2000 877 | 38,Indonesia,1,3,2,6,2000 878 | 39,Slovakia,1,3,1,5,2000 879 | 40,Mexico,1,2,3,6,2000 880 | 41,Nigeria,1,2,0,3,2000 881 | 42,Algeria,1,1,3,5,2000 882 | 43,Uzbekistan,1,1,2,4,2000 883 | 44,FR Yugoslavia,1,1,1,3,2000 884 | 44,Latvia,1,1,1,3,2000 885 | 46,New Zealand,1,0,3,4,2000 886 | 47,Estonia,1,0,2,3,2000 887 | 47,Thailand,1,0,2,3,2000 888 | 49,Croatia,1,0,1,2,2000 889 | 50,Cameroon,1,0,0,1,2000 890 | 50,Colombia,1,0,0,1,2000 891 | 50,Mozambique,1,0,0,1,2000 892 | 53,Brazil,0,6,6,12,2000 893 | 54,Jamaica,0,6,3,9,2000 894 | 55,Belgium,0,2,3,5,2000 895 | 55,South Africa,0,2,3,5,2000 896 | 57,Argentina,0,2,2,4,2000 897 | 58,Chinese Taipei,0,1,4,5,2000 898 | 58,Morocco,0,1,4,5,2000 899 | 60,North Korea,0,1,3,4,2000 900 | 61,Moldova,0,1,1,2,2000 901 | 61,Saudi Arabia,0,1,1,2,2000 902 | 61,Trinidad and Tobago,0,1,1,2,2000 903 | 64,Ireland,0,1,0,1,2000 904 | 64,Sri Lanka,0,1,0,1,2000 905 | 64,Uruguay,0,1,0,1,2000 906 | 64,Vietnam,0,1,0,1,2000 907 | 68,Georgia,0,0,6,6,2000 908 | 69,Costa Rica,0,0,2,2,2000 909 | 69,Portugal,0,0,2,2,2000 910 | 71,Armenia,0,0,1,1,2000 911 | 71,Barbados,0,0,1,1,2000 912 | 71,Chile,0,0,1,1,2000 913 | 71,Iceland,0,0,1,1,2000 914 | 71,India,0,0,1,1,2000 915 | 71,Israel,0,0,1,1,2000 916 | 71,Kuwait,0,0,1,1,2000 917 | 71,Kyrgyzstan,0,0,1,1,2000 918 | 71,Macedonia,0,0,1,1,2000 919 | 71,Qatar,0,0,1,1,2000 920 | 1,United States,36,39,26,101,2004 921 | 2,China,32,17,14,63,2004 922 | 3,Russia,28,26,36,90,2004 923 | 4,Australia,17,16,17,50,2004 924 | 5,Japan,16,9,12,37,2004 925 | 6,Germany,13,16,20,49,2004 926 | 7,France,11,9,13,33,2004 927 | 8,Italy,10,11,11,32,2004 928 | 9,South Korea,9,12,9,30,2004 929 | 10,Great Britain,9,9,12,30,2004 930 | 11,Cuba,9,7,11,27,2004 931 | 12,Hungary,8,6,3,17,2004 932 | 13,Ukraine,8,5,9,22,2004 933 | 14,Romania,8,5,6,19,2004 934 | 15,Greece,6,6,4,16,2004 935 | 16,Brazil,5,2,3,10,2004 936 | 17,Norway,5,0,1,6,2004 937 | 18,Netherlands,4,9,9,22,2004 938 | 19,Sweden,4,2,1,7,2004 939 | 20,Spain,3,11,6,20,2004 940 | 21,Canada,3,6,3,12,2004 941 | 22,Turkey,3,3,4,10,2004 942 | 23,Poland,3,2,5,10,2004 943 | 24,New Zealand,3,2,0,5,2004 944 | 25,Thailand,3,1,4,8,2004 945 | 26,Belarus,2,5,6,13,2004 946 | 27,Austria,2,4,1,7,2004 947 | 28,Ethiopia,2,3,2,7,2004 948 | 29,Iran,2,2,2,6,2004 949 | 29,Slovakia,2,2,2,6,2004 950 | 31,Chinese Taipei,2,2,1,5,2004 951 | 32,Georgia,2,2,0,4,2004 952 | 33,Bulgaria,2,1,9,12,2004 953 | 34,Denmark,2,1,5,8,2004 954 | 35,Jamaica,2,1,2,5,2004 955 | 35,Uzbekistan,2,1,2,5,2004 956 | 37,Morocco,2,1,0,3,2004 957 | 38,Argentina,2,0,4,6,2004 958 | 39,Chile,2,0,1,3,2004 959 | 40,Kazakhstan,1,4,3,8,2004 960 | 41,Kenya,1,4,2,7,2004 961 | 42,Czech Republic,1,3,5,9,2004 962 | 43,South Africa,1,3,2,6,2004 963 | 44,Croatia,1,2,2,5,2004 964 | 45,Lithuania,1,2,0,3,2004 965 | 46,Egypt,1,1,3,5,2004 966 | 46,Switzerland,1,1,3,5,2004 967 | 48,Indonesia,1,1,2,4,2004 968 | 49,Zimbabwe,1,1,1,3,2004 969 | 50,Azerbaijan,1,0,4,5,2004 970 | 51,Belgium,1,0,2,3,2004 971 | 52,Bahamas,1,0,1,2,2004 972 | 52,Israel,1,0,1,2,2004 973 | 54,Cameroon,1,0,0,1,2004 974 | 54,Dominican Republic,1,0,0,1,2004 975 | 54,United Arab Emirates,1,0,0,1,2004 976 | 57,North Korea,0,4,1,5,2004 977 | 58,Latvia,0,4,0,4,2004 978 | 59,Mexico,0,3,1,4,2004 979 | 60,Portugal,0,2,1,3,2004 980 | 61,Finland,0,2,0,2,2004 981 | 61,Serbia and Montenegro,0,2,0,2,2004 982 | 63,Slovenia,0,1,3,4,2004 983 | 64,Estonia,0,1,2,3,2004 984 | 65,Hong Kong,0,1,0,1,2004 985 | 65,India,0,1,0,1,2004 986 | 65,Paraguay,0,1,0,1,2004 987 | 68,Colombia,0,0,2,2,2004 988 | 68,Nigeria,0,0,2,2,2004 989 | 68,Venezuela,0,0,2,2,2004 990 | 71,Eritrea,0,0,1,1,2004 991 | 71,Mongolia,0,0,1,1,2004 992 | 71,Syria,0,0,1,1,2004 993 | 71,Trinidad and Tobago,0,0,1,1,2004 994 | 1,China,48,22,30,100,2008 995 | 2,United States,36,39,37,112,2008 996 | 3,Russia,24,13,23,60,2008 997 | 4,Great Britain,19,13,19,51,2008 998 | 5,Germany,16,11,14,41,2008 999 | 6,Australia,14,15,17,46,2008 1000 | 7,South Korea,13,11,8,32,2008 1001 | 8,Japan,9,8,8,25,2008 1002 | 9,Italy,8,9,10,27,2008 1003 | 10,France,7,16,20,43,2008 1004 | 11,Netherlands,7,5,4,16,2008 1005 | 12,Ukraine,7,4,11,22,2008 1006 | 13,Kenya,6,4,6,16,2008 1007 | 14,Spain,5,11,3,19,2008 1008 | 15,Jamaica,5,4,2,11,2008 1009 | 16,Poland,4,5,2,11,2008 1010 | 17,Ethiopia,4,2,1,7,2008 1011 | 18,Romania,4,1,4,9,2008 1012 | 19,Cuba,3,10,17,30,2008 1013 | 20,Canada,3,9,8,20,2008 1014 | 21,Hungary,3,5,2,10,2008 1015 | 22,Norway,3,5,1,9,2008 1016 | 23,Brazil,3,4,10,17,2008 1017 | 24,Belarus,3,4,7,14,2008 1018 | 25,Czech Republic,3,3,1,7,2008 1019 | 26,Slovakia,3,3,0,6,2008 1020 | 27,New Zealand,3,2,4,9,2008 1021 | 28,Georgia,3,2,2,7,2008 1022 | 29,Kazakhstan,2,3,4,9,2008 1023 | 30,Denmark,2,2,3,7,2008 1024 | 31,North Korea,2,2,2,6,2008 1025 | 31,Thailand,2,2,2,6,2008 1026 | 33,Mongolia,2,2,0,4,2008 1027 | 34,Switzerland,2,1,4,7,2008 1028 | 35,Argentina,2,0,4,6,2008 1029 | 36,Mexico,2,0,2,4,2008 1030 | 37,Belgium,2,0,0,2,2008 1031 | 38,Zimbabwe,1,3,0,4,2008 1032 | 39,Slovenia,1,2,2,5,2008 1033 | 40,Azerbaijan,1,1,4,6,2008 1034 | 40,Indonesia,1,1,4,6,2008 1035 | 42,Bulgaria,1,1,3,5,2008 1036 | 42,Turkey,1,1,3,5,2008 1037 | 44,Chinese Taipei,1,1,2,4,2008 1038 | 44,Finland,1,1,2,4,2008 1039 | 46,Latvia,1,1,1,3,2008 1040 | 47,Dominican Republic,1,1,0,2,2008 1041 | 47,Estonia,1,1,0,2,2008 1042 | 47,Portugal,1,1,0,2,2008 1043 | 47,Trinidad and Tobago,1,1,0,2,2008 1044 | 51,India,1,0,2,3,2008 1045 | 52,Iran,1,0,1,2,2008 1046 | 53,Cameroon,1,0,0,1,2008 1047 | 53,Panama,1,0,0,1,2008 1048 | 53,Tunisia,1,0,0,1,2008 1049 | 56,Sweden,0,4,1,5,2008 1050 | 57,Lithuania,0,3,2,5,2008 1051 | 57,Nigeria,0,3,2,5,2008 1052 | 59,Croatia,0,2,3,5,2008 1053 | 60,Colombia,0,2,1,3,2008 1054 | 60,Greece,0,2,1,3,2008 1055 | 62,Armenia,0,1,4,5,2008 1056 | 63,Uzbekistan,0,1,3,4,2008 1057 | 64,Austria,0,1,2,3,2008 1058 | 64,Ireland,0,1,2,3,2008 1059 | 64,Kyrgyzstan,0,1,2,3,2008 1060 | 64,Serbia,0,1,2,3,2008 1061 | 68,Algeria,0,1,1,2,2008 1062 | 68,Bahamas,0,1,1,2,2008 1063 | 68,Morocco,0,1,1,2,2008 1064 | 68,Tajikistan,0,1,1,2,2008 1065 | 72,Chile,0,1,0,1,2008 1066 | 72,Ecuador,0,1,0,1,2008 1067 | 72,Iceland,0,1,0,1,2008 1068 | 72,Malaysia,0,1,0,1,2008 1069 | 72,Samoa,0,1,0,1,2008 1070 | 72,Singapore,0,1,0,1,2008 1071 | 72,South Africa,0,1,0,1,2008 1072 | 72,Sudan,0,1,0,1,2008 1073 | 72,Vietnam,0,1,0,1,2008 1074 | 81,Egypt,0,0,2,2,2008 1075 | 82,Afghanistan,0,0,1,1,2008 1076 | 82,Israel,0,0,1,1,2008 1077 | 82,Mauritius,0,0,1,1,2008 1078 | 82,Moldova,0,0,1,1,2008 1079 | 82,Togo,0,0,1,1,2008 1080 | 82,Venezuela,0,0,1,1,2008 1081 | 1,United States,48,26,30,104,2012 1082 | 2,China,39,31,22,92,2012 1083 | 3,Great Britain,29,18,18,65,2012 1084 | 4,Russia,18,21,26,65,2012 1085 | 5,South Korea,13,9,9,31,2012 1086 | 6,Germany,11,20,13,44,2012 1087 | 7,France,11,11,13,35,2012 1088 | 8,Australia,8,15,12,35,2012 1089 | 9,Italy,8,9,11,28,2012 1090 | 10,Hungary,8,4,6,18,2012 1091 | 11,Japan,7,14,17,38,2012 1092 | 12,Iran,7,5,1,13,2012 1093 | 13,Netherlands,6,6,8,20,2012 1094 | 14,New Zealand,6,2,5,13,2012 1095 | 15,Ukraine,5,4,10,19,2012 1096 | 16,Cuba,5,3,7,15,2012 1097 | 17,Spain,4,10,6,20,2012 1098 | 18,Jamaica,4,5,4,13,2012 1099 | 19,Czech Republic,4,4,3,11,2012 1100 | 20,South Africa,4,1,1,6,2012 1101 | 21,North Korea,4,0,2,6,2012 1102 | 22,Brazil,3,5,9,17,2012 1103 | 23,Kazakhstan,3,2,6,11,2012 1104 | 23,Poland,3,2,6,11,2012 1105 | 25,Ethiopia,3,2,3,8,2012 1106 | 26,Croatia,3,1,2,6,2012 1107 | 27,Canada,2,6,10,18,2012 1108 | 28,Belarus,2,5,3,10,2012 1109 | 29,Kenya,2,4,7,13,2012 1110 | 30,Denmark,2,4,3,9,2012 1111 | 31,Romania,2,4,1,7,2012 1112 | 32,Azerbaijan,2,2,5,9,2012 1113 | 33,Switzerland,2,2,0,4,2012 1114 | 34,Norway,2,1,1,4,2012 1115 | 35,Lithuania,2,0,3,5,2012 1116 | 36,Tunisia,2,0,1,3,2012 1117 | 37,Sweden,1,4,3,8,2012 1118 | 38,Colombia,1,3,5,9,2012 1119 | 39,Mexico,1,3,4,8,2012 1120 | 40,Georgia,1,2,3,6,2012 1121 | 41,Ireland,1,1,4,6,2012 1122 | 42,Argentina,1,1,2,4,2012 1123 | 42,Serbia,1,1,2,4,2012 1124 | 42,Slovenia,1,1,2,4,2012 1125 | 42,Trinidad and Tobago,1,1,2,4,2012 1126 | 46,Turkey,1,1,1,3,2012 1127 | 47,Dominican Republic,1,1,0,2,2012 1128 | 48,Chinese Taipei,1,0,1,2,2012 1129 | 48,Latvia,1,0,1,2,2012 1130 | 50,Algeria,1,0,0,1,2012 1131 | 50,Bahamas,1,0,0,1,2012 1132 | 50,Bahrain,1,0,0,1,2012 1133 | 50,Grenada,1,0,0,1,2012 1134 | 50,Uganda,1,0,0,1,2012 1135 | 50,Venezuela,1,0,0,1,2012 1136 | 56,Egypt,0,3,1,4,2012 1137 | 57,India,0,2,4,6,2012 1138 | 58,Mongolia,0,2,3,5,2012 1139 | 59,Thailand,0,2,2,4,2012 1140 | 60,Bulgaria,0,2,1,3,2012 1141 | 60,Finland,0,2,1,3,2012 1142 | 60,Indonesia,0,2,1,3,2012 1143 | 63,Slovakia,0,1,3,4,2012 1144 | 64,Belgium,0,1,2,3,2012 1145 | 65,Armenia,0,1,1,2,2012 1146 | 65,Estonia,0,1,1,2,2012 1147 | 65,Malaysia,0,1,1,2,2012 1148 | 65,Puerto Rico,0,1,1,2,2012 1149 | 65,Qatar,0,1,1,2,2012 1150 | 70,Botswana,0,1,0,1,2012 1151 | 70,Cyprus,0,1,0,1,2012 1152 | 70,Gabon,0,1,0,1,2012 1153 | 70,Guatemala,0,1,0,1,2012 1154 | 70,Montenegro,0,1,0,1,2012 1155 | 70,Portugal,0,1,0,1,2012 1156 | 76,Uzbekistan,0,0,3,3,2012 1157 | 77,Greece,0,0,2,2,2012 1158 | 77,Singapore,0,0,2,2,2012 1159 | 79,Afghanistan,0,0,1,1,2012 1160 | 79,Cameroon,0,0,1,1,2012 1161 | 79,Hong Kong,0,0,1,1,2012 1162 | 79,Kuwait,0,0,1,1,2012 1163 | 79,Morocco,0,0,1,1,2012 1164 | 79,Saudi Arabia,0,0,1,1,2012 1165 | 79,Tajikistan,0,0,1,1,2012 1166 | 79,Vietnam,0,0,1,1,2012 1167 | 1,United States,46,37,38,121,2016 1168 | 2,Great Britain,27,23,17,67,2016 1169 | 3,China,26,18,26,70,2016 1170 | 4,Russia,19,17,20,56,2016 1171 | 5,Germany,17,10,15,42,2016 1172 | 6,Japan,12,8,21,41,2016 1173 | 7,France,10,18,14,42,2016 1174 | 8,South Korea,9,3,9,21,2016 1175 | 9,Italy,8,12,8,28,2016 1176 | 10,Australia,8,11,10,29,2016 1177 | 11,Netherlands,8,7,4,19,2016 1178 | 12,Hungary,8,3,4,15,2016 1179 | 13,Brazil,7,6,6,19,2016 1180 | 14,Spain,7,4,6,17,2016 1181 | 15,Kenya,6,6,1,13,2016 1182 | 16,Jamaica,6,3,2,11,2016 1183 | 17,Croatia,5,3,2,10,2016 1184 | 18,Cuba,5,2,4,11,2016 1185 | 19,New Zealand,4,9,5,18,2016 1186 | 20,Canada,4,3,15,22,2016 1187 | 21,Uzbekistan,4,2,7,13,2016 1188 | 22,Colombia,3,2,3,8,2016 1189 | 23,Switzerland,3,2,2,7,2016 1190 | 24,Iran,3,1,4,8,2016 1191 | 25,Greece,3,1,2,6,2016 1192 | 26,Argentina,3,1,0,4,2016 1193 | 27,Denmark,2,6,7,15,2016 1194 | 28,Sweden,2,6,3,11,2016 1195 | 29,South Africa,2,6,2,10,2016 1196 | 30,Kazakhstan,2,5,10,17,2016 1197 | 31,Ukraine,2,5,4,11,2016 1198 | 32,Serbia,2,4,2,8,2016 1199 | 33,Poland,2,3,6,11,2016 1200 | 34,North Korea,2,3,2,7,2016 1201 | 35,Belgium,2,2,2,6,2016 1202 | 35,Thailand,2,2,2,6,2016 1203 | 37,Slovakia,2,2,0,4,2016 1204 | 38,Georgia,2,1,4,7,2016 1205 | 39,Azerbaijan,1,7,10,18,2016 1206 | 40,Belarus,1,4,4,9,2016 1207 | 41,Turkey,1,3,4,8,2016 1208 | 42,Armenia,1,3,0,4,2016 1209 | 43,Czech Republic,1,2,7,10,2016 1210 | 44,Ethiopia,1,2,5,8,2016 1211 | 45,Slovenia,1,2,1,4,2016 1212 | 46,Indonesia,1,2,0,3,2016 1213 | 47,Romania,1,1,2,4,2016 1214 | 48,Bahrain,1,1,0,2,2016 1215 | 48,Vietnam,1,1,0,2,2016 1216 | 50,Chinese Taipei,1,0,2,3,2016 1217 | 51,Bahamas,1,0,1,2,2016 1218 | 51,Independent Olympic Athletes,1,0,1,2,2016 1219 | 51,Ivory Coast,1,0,1,2,2016 1220 | 54,Fiji,1,0,0,1,2016 1221 | 54,Jordan,1,0,0,1,2016 1222 | 54,Kosovo,1,0,0,1,2016 1223 | 54,Puerto Rico,1,0,0,1,2016 1224 | 54,Singapore,1,0,0,1,2016 1225 | 54,Tajikistan,1,0,0,1,2016 1226 | 60,Malaysia,0,4,1,5,2016 1227 | 61,Mexico,0,3,2,5,2016 1228 | 62,Venezuela,0,2,1,3,2016 1229 | 63,Algeria,0,2,0,2,2016 1230 | 63,Ireland,0,2,0,2,2016 1231 | 65,Lithuania,0,1,3,4,2016 1232 | 66,Bulgaria,0,1,2,3,2016 1233 | 67,India,0,1,1,2,2016 1234 | 67,Mongolia,0,1,1,2,2016 1235 | 69,Burundi,0,1,0,1,2016 1236 | 69,Grenada,0,1,0,1,2016 1237 | 69,Niger,0,1,0,1,2016 1238 | 69,Philippines,0,1,0,1,2016 1239 | 69,Qatar,0,1,0,1,2016 1240 | 74,Norway,0,0,4,4,2016 1241 | 75,Egypt,0,0,3,3,2016 1242 | 75,Tunisia,0,0,3,3,2016 1243 | 77,Israel,0,0,2,2,2016 1244 | 78,Austria,0,0,1,1,2016 1245 | 78,Dominican Republic,0,0,1,1,2016 1246 | 78,Estonia,0,0,1,1,2016 1247 | 78,Finland,0,0,1,1,2016 1248 | 78,Morocco,0,0,1,1,2016 1249 | 78,Nigeria,0,0,1,1,2016 1250 | 78,Portugal,0,0,1,1,2016 1251 | 78,Trinidad and Tobago,0,0,1,1,2016 1252 | 78,United Arab Emirates,0,0,1,1,2016 1253 | 1,United States,39,41,33,113,2020 1254 | 2,China,38,32,19,89,2020 1255 | 3,Japan,27,14,17,58,2020 1256 | 4,Great Britain,22,20,22,64,2020 1257 | 5,ROC,20,28,23,71,2020 1258 | 6,Australia,17,7,22,46,2020 1259 | 7,Netherlands,10,12,14,36,2020 1260 | 8,France,10,12,11,33,2020 1261 | 9,Germany,10,11,16,37,2020 1262 | 10,Italy,10,10,20,40,2020 1263 | 11,Canada,7,7,10,24,2020 1264 | 12,Brazil,7,6,8,21,2020 1265 | 13,New Zealand,7,6,7,20,2020 1266 | 14,Cuba,7,3,5,15,2020 1267 | 15,Hungary,6,7,7,20,2020 1268 | 16,South Korea,6,4,10,20,2020 1269 | 17,Poland,4,5,5,14,2020 1270 | 18,Czech Republic,4,4,3,11,2020 1271 | 19,Kenya,4,4,2,10,2020 1272 | 20,Norway,4,2,2,8,2020 1273 | 21,Jamaica,4,1,4,9,2020 1274 | 22,Spain,3,8,6,17,2020 1275 | 23,Sweden,3,6,0,9,2020 1276 | 24,Switzerland,3,4,6,13,2020 1277 | 25,Denmark,3,4,4,11,2020 1278 | 26,Croatia,3,3,2,8,2020 1279 | 27,Iran,3,2,2,7,2020 1280 | 28,Serbia,3,1,5,9,2020 1281 | 29,Belgium,3,1,3,7,2020 1282 | 30,Bulgaria,3,1,2,6,2020 1283 | 31,Slovenia,3,1,1,5,2020 1284 | 32,Uzbekistan,3,0,2,5,2020 1285 | 33,Georgia,2,5,1,8,2020 1286 | 34,Chinese Taipei,2,4,6,12,2020 1287 | 35,Turkey,2,2,9,13,2020 1288 | 36,Greece,2,1,1,4,2020 1289 | 36,Uganda,2,1,1,4,2020 1290 | 38,Ecuador,2,1,0,3,2020 1291 | 39,Ireland,2,0,2,4,2020 1292 | 39,Israel,2,0,2,4,2020 1293 | 41,Qatar,2,0,1,3,2020 1294 | 42,Bahamas,2,0,0,2,2020 1295 | 42,Kosovo,2,0,0,2,2020 1296 | 44,Ukraine,1,6,12,19,2020 1297 | 45,Belarus,1,3,3,7,2020 1298 | 46,Romania,1,3,0,4,2020 1299 | 46,Venezuela,1,3,0,4,2020 1300 | 48,India,1,2,4,7,2020 1301 | 49,Hong Kong,1,2,3,6,2020 1302 | 50,Philippines,1,2,1,4,2020 1303 | 50,Slovakia,1,2,1,4,2020 1304 | 52,South Africa,1,2,0,3,2020 1305 | 53,Austria,1,1,5,7,2020 1306 | 54,Egypt,1,1,4,6,2020 1307 | 55,Indonesia,1,1,3,5,2020 1308 | 56,Ethiopia,1,1,2,4,2020 1309 | 56,Portugal,1,1,2,4,2020 1310 | 58,Tunisia,1,1,0,2,2020 1311 | 59,Estonia,1,0,1,2,2020 1312 | 59,Fiji,1,0,1,2,2020 1313 | 59,Latvia,1,0,1,2,2020 1314 | 59,Thailand,1,0,1,2,2020 1315 | 63,Bermuda,1,0,0,1,2020 1316 | 63,Morocco,1,0,0,1,2020 1317 | 63,Puerto Rico,1,0,0,1,2020 1318 | 66,Colombia,0,4,1,5,2020 1319 | 67,Azerbaijan,0,3,4,7,2020 1320 | 68,Dominican Republic,0,3,2,5,2020 1321 | 69,Armenia,0,2,2,4,2020 1322 | 70,Kyrgyzstan,0,2,1,3,2020 1323 | 71,Mongolia,0,1,3,4,2020 1324 | 72,Argentina,0,1,2,3,2020 1325 | 72,San Marino,0,1,2,3,2020 1326 | 74,Jordan,0,1,1,2,2020 1327 | 74,Malaysia,0,1,1,2,2020 1328 | 74,Nigeria,0,1,1,2,2020 1329 | 77,Bahrain,0,1,0,1,2020 1330 | 77,Lithuania,0,1,0,1,2020 1331 | 77,Namibia,0,1,0,1,2020 1332 | 77,North Macedonia,0,1,0,1,2020 1333 | 77,Saudi Arabia,0,1,0,1,2020 1334 | 77,Turkmenistan,0,1,0,1,2020 1335 | 83,Kazakhstan,0,0,8,8,2020 1336 | 84,Mexico,0,0,4,4,2020 1337 | 85,Finland,0,0,2,2,2020 1338 | 86,Botswana,0,0,1,1,2020 1339 | 86,Burkina Faso,0,0,1,1,2020 1340 | 86,Ghana,0,0,1,1,2020 1341 | 86,Grenada,0,0,1,1,2020 1342 | 86,Ivory Coast,0,0,1,1,2020 1343 | 86,Kuwait,0,0,1,1,2020 1344 | 86,Moldova,0,0,1,1,2020 1345 | 86,Syria,0,0,1,1,2020 1346 | 1,United States,40,44,42,126,2024 1347 | 2,China,40,27,24,91,2024 1348 | 3,Japan,20,12,13,45,2024 1349 | 4,Australia,18,19,16,53,2024 1350 | 5,France,16,26,22,64,2024 1351 | 6,Netherlands,15,7,12,34,2024 1352 | 7,Great Britain,14,22,29,65,2024 1353 | 8,South Korea,13,9,10,32,2024 1354 | 9,Italy,12,13,15,40,2024 1355 | 10,Germany,12,13,8,33,2024 1356 | 11,New Zealand,10,7,3,20,2024 1357 | 12,Canada,9,7,11,27,2024 1358 | 13,Uzbekistan,8,2,3,13,2024 1359 | 14,Hungary,6,7,6,19,2024 1360 | 15,Spain,5,4,9,18,2024 1361 | 16,Sweden,4,4,3,11,2024 1362 | 17,Kenya,4,2,5,11,2024 1363 | 18,Norway,4,1,3,8,2024 1364 | 19,Ireland,4,0,3,7,2024 1365 | 20,Brazil,3,7,10,20,2024 1366 | 21,Iran,3,6,3,12,2024 1367 | 22,Ukraine,3,5,4,12,2024 1368 | 23,Romania,3,4,2,9,2024 1369 | 24,Georgia,3,3,1,7,2024 1370 | 25,Belgium,3,1,6,10,2024 1371 | 26,Bulgaria,3,1,3,7,2024 1372 | 27,Serbia,3,1,1,5,2024 1373 | 28,Czech Republic,3,0,2,5,2024 1374 | 29,Denmark,2,2,5,9,2024 1375 | 30,Azerbaijan,2,2,3,7,2024 1376 | 30,Croatia,2,2,3,7,2024 1377 | 32,Cuba,2,1,6,9,2024 1378 | 33,Bahrain,2,1,1,4,2024 1379 | 34,Slovenia,2,1,0,3,2024 1380 | 35,Chinese Taipei,2,0,5,7,2024 1381 | 36,Austria,2,0,3,5,2024 1382 | 37,Hong Kong,2,0,2,4,2024 1383 | 37,Philippines,2,0,2,4,2024 1384 | 39,Algeria,2,0,1,3,2024 1385 | 39,Indonesia,2,0,1,3,2024 1386 | 41,Israel,1,5,1,7,2024 1387 | 42,Poland,1,4,5,10,2024 1388 | 43,Kazakhstan,1,3,3,7,2024 1389 | 44,Jamaica,1,3,2,6,2024 1390 | 44,South Africa,1,3,2,6,2024 1391 | 44,Thailand,1,3,2,6,2024 1392 | 47,Ethiopia,1,3,0,4,2024 1393 | 48,Switzerland,1,2,5,8,2024 1394 | 49,Ecuador,1,2,2,5,2024 1395 | 50,Portugal,1,2,1,4,2024 1396 | 51,Greece,1,1,6,8,2024 1397 | 52,Argentina,1,1,1,3,2024 1398 | 52,Egypt,1,1,1,3,2024 1399 | 52,Tunisia,1,1,1,3,2024 1400 | 55,Botswana,1,1,0,2,2024 1401 | 55,Chile,1,1,0,2,2024 1402 | 55,Saint Lucia,1,1,0,2,2024 1403 | 55,Uganda,1,1,0,2,2024 1404 | 59,Dominican Republic,1,0,2,3,2024 1405 | 60,Guatemala,1,0,1,2,2024 1406 | 60,Morocco,1,0,1,2,2024 1407 | 62,Dominica,1,0,0,1,2024 1408 | 62,Pakistan,1,0,0,1,2024 1409 | 64,Turkey,0,3,5,8,2024 1410 | 65,Mexico,0,3,2,5,2024 1411 | 66,Armenia,0,3,1,4,2024 1412 | 66,Colombia,0,3,1,4,2024 1413 | 68,Kyrgyzstan,0,2,4,6,2024 1414 | 68,North Korea,0,2,4,6,2024 1415 | 70,Lithuania,0,2,2,4,2024 1416 | 71,India,0,1,5,6,2024 1417 | 72,Moldova,0,1,3,4,2024 1418 | 73,Kosovo,0,1,1,2,2024 1419 | 74,Cyprus,0,1,0,1,2024 1420 | 74,Fiji,0,1,0,1,2024 1421 | 74,Jordan,0,1,0,1,2024 1422 | 74,Mongolia,0,1,0,1,2024 1423 | 74,Panama,0,1,0,1,2024 1424 | 79,Tajikistan,0,0,3,3,2024 1425 | 80,Albania,0,0,2,2,2024 1426 | 80,Grenada,0,0,2,2,2024 1427 | 80,Malaysia,0,0,2,2,2024 1428 | 80,Puerto Rico,0,0,2,2,2024 1429 | 84,Cabo Verde,0,0,1,1,2024 1430 | 84,Ivory Coast,0,0,1,1,2024 1431 | 84,Peru,0,0,1,1,2024 1432 | 84,Qatar,0,0,1,1,2024 1433 | 84,Refugee Olympic Team,0,0,1,1,2024 1434 | 84,Singapore,0,0,1,1,2024 1435 | 84,Slovakia,0,0,1,1,2024 1436 | 84,Zambia,0,0,1,1,2024 1437 | -------------------------------------------------------------------------------- /2025_Problem_C_Data/summerOly_programs.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2025_Problem_C_Data/summerOly_programs.csv -------------------------------------------------------------------------------- /2511431.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/YYYanZZZ/Meritorious-Winner-Work-in-MCM-ProblemC/881862a2e8a157006364c96080bc2761fa0be8ea/2511431.pdf -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 🏅 Olympic Medal Prediction Model | 奥运会奖牌预测模型 2 | 3 |
4 | 5 | ![Olympic Rings](https://upload.wikimedia.org/wikipedia/commons/thumb/5/55/Olympic_rings_without_rims.svg/320px-Olympic_rings_without_rims.svg.png) 6 | 7 | **MCM/ICM 2025 Problem C Solution | 美国大学生数学建模竞赛2025年C题解决方案** 8 | 9 | **🏆 Meritorious Winner (M奖) 🏆** 10 | 11 | [![GitHub stars](https://img.shields.io/github/stars/yourusername/olympic-medal-prediction.svg?style=social&label=Star&maxAge=2592000)](https://github.com/yourusername/olympic-medal-prediction/stargazers/) 12 | [![License](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) 13 | [![Award](https://img.shields.io/badge/Award-Meritorious%20Winner-orange.svg)](https://www.comap.com/contests/mcm-icm) 14 | [![Python](https://img.shields.io/badge/Python-3.8+-blue.svg)](https://www.python.org/) 15 | [![Pandas](https://img.shields.io/badge/Pandas-1.5.0-green.svg)](https://pandas.pydata.org/) 16 | [![NumPy](https://img.shields.io/badge/NumPy-1.23.0-yellow.svg)](https://numpy.org/) 17 | 18 |
19 | 20 | ## 📌 项目概述 | Project Overview 21 | 22 | [English](#english-version) | [中文](#chinese-version) 23 | 24 | --- 25 | 26 | 27 | ## 🌍 English Version 28 | 29 | ### 📊 Project Description 30 | 31 | This repository contains our solution for Problem C of the 2025 Mathematical Contest in Modeling (MCM/ICM), which was awarded the **Meritorious Winner (M Prize)** distinction. We developed a predictive model for Olympic medal counts using time series analysis and the Grey Model (GM(1,1)). 32 | 33 | Our solution analyzes historical Olympic data from 1896 to 2024, including athlete performance, medal distributions, and host country advantages, to forecast medal outcomes for future Olympic Games. 34 | 35 | ### 🏆 Award 36 | 37 | Our team received the **Meritorious Winner (M Prize)** award in the 2025 Mathematical Contest in Modeling (MCM/ICM), placing our paper in the top 8% of all submissions worldwide. 38 | 39 | ### 🔍 Key Features 40 | 41 | - **Grey Prediction Model (GM(1,1))**: Implements time series forecasting techniques to predict athlete performance and medal counts 42 | - **Comprehensive Data Analysis**: Examines historical Olympic data across multiple dimensions 43 | - **Host Country Performance Analysis**: Evaluates the impact of hosting the Olympics on medal outcomes 44 | - **Medal Allocation Algorithm**: Creates a fair system for distributing medals based on predicted performance scores 45 | 46 | ### 📋 Repository Contents 47 | 48 | - `2025_Problem_C_Data/`: Original competition dataset 49 | - `summerOly_athletes.csv`: Athlete participation data 50 | - `summerOly_medal_counts.csv`: Historical medal counts by country 51 | - `summerOly_hosts.csv`: Olympic host cities and countries 52 | - `summerOly_programs.csv`: Olympic sports and events data 53 | - `data_dictionary.csv`: Descriptions of all data fields 54 | - `gray.py`: Implementation of the Grey Model (GM(1,1)) and prediction algorithms 55 | - `figures/`: Visualizations of model results and analysis 56 | - `2025_MCM_Problem_C.pdf`: Original problem statement 57 | 58 | ### 🚀 How to Use 59 | 60 | 1. Clone this repository 61 | 2. Install the required dependencies: 62 | ``` 63 | pip install pandas numpy matplotlib seaborn 64 | ``` 65 | 3. Run the Grey prediction model: 66 | ``` 67 | python gray.py 68 | ``` 69 | 70 | --- 71 | 72 | 73 | ## 🌏 中文版本 74 | 75 | ### 📊 项目描述 76 | 77 | 本仓库包含我们针对2025年美国大学生数学建模竞赛(MCM/ICM)C题的解决方案，该方案荣获**M奖（Meritorious Winner）**。我们开发了一个基于时间序列分析和灰色预测模型(GM(1,1))的奥运会奖牌预测模型。 78 | 79 | 我们的解决方案分析了从1896年到2024年的奥运会历史数据，包括运动员表现、奖牌分布以及主办国优势，以预测未来奥运会的奖牌结果。 80 | 81 | ### 🏆 获奖情况 82 | 83 | 我们团队在2025年美国大学生数学建模竞赛(MCM/ICM)中荣获**M奖（Meritorious Winner）**，该奖项代表我们的论文在全球所有参赛作品中排名前8%。 84 | 85 | ### 🔍 主要特点 86 | 87 | - **灰色预测模型(GM(1,1))**: 实现时间序列预测技术，预测运动员表现和奖牌数量 88 | - **全面的数据分析**: 从多个维度检验奥运会历史数据 89 | - **主办国表现分析**: 评估举办奥运会对主办国奖牌成绩的影响 90 | - **奖牌分配算法**: 基于预测的表现分数，创建公平的奖牌分配系统 91 | 92 | ### 📋 仓库内容 93 | 94 | - `2025_Problem_C_Data/`: 原始比赛数据集 95 | - `summerOly_athletes.csv`: 运动员参赛数据 96 | - `summerOly_medal_counts.csv`: 各国历史奖牌数统计 97 | - `summerOly_hosts.csv`: 奥运会主办城市和国家 98 | - `summerOly_programs.csv`: 奥运会项目和赛事数据 99 | - `data_dictionary.csv`: 所有数据字段的说明 100 | - `gray.py`: 灰色预测模型(GM(1,1))和预测算法的实现 101 | - `figures/`: 模型结果和分析的可视化 102 | - `2025_MCM_Problem_C.pdf`: 原始问题陈述 103 | 104 | ### 🚀 使用方法 105 | 106 | 1. 克隆本仓库 107 | 2. 安装所需依赖: 108 | ``` 109 | pip install pandas numpy matplotlib seaborn 110 | ``` 111 | 3. 运行灰色预测模型: 112 | ``` 113 | python gray.py 114 | ``` 115 | 116 | --- 117 | 118 | ## 📊 结果展示 | Result Visualization 119 | 120 |
121 | Medal Distribution 122 | Host Country Performance 123 |
124 | 125 |
126 | Top 5 Countries Consistency 127 | Model Stability 128 |
129 | 130 | ## 📝 联系方式 | Contact Information 131 | 132 | 如果您对美国数学建模竞赛(MCM/ICM)有任何疑问，或者想要了解更多关于我们模型的信息，请在GitHub上给本项目点Star⭐，我将私底下回复您的问题。 133 | 134 | If you have any questions about the Mathematical Contest in Modeling (MCM/ICM), or want to learn more about our model, please star⭐ this project on GitHub, and I will respond to your questions privately. 135 | 136 | ## 📄 许可证 | License 137 | 138 | 本项目采用MIT许可证 - 查看[LICENSE](LICENSE)文件了解详情 139 | 140 | This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. --------------------------------------------------------------------------------