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我来为您提供一个Java统计头球争顶成功率的完整案例：
基础数据模型
import java.time.LocalDateTime;
import java.util.*;
import java.util.stream.Collectors;
// 头球争顶事件实体类
class HeaderDuel {
private Long playerId;
private String playerName;
private LocalDateTime eventTime;
private boolean success; // 是否成功
private String opponent; // 对手
private String competition; // 赛事类型
private String position; // 场上位置
public HeaderDuel(Long playerId, String playerName, boolean success, String opponent, String competition, String position) {
this.playerId = playerId;
this.playerName = playerName;
this.eventTime = LocalDateTime.now();
this.success = success;
this.opponent = opponent;
this.competition = competition;
this.position = position;
}
// Getters and Setters
public Long getPlayerId() { return playerId; }
public String getPlayerName() { return playerName; }
public LocalDateTime getEventTime() { return eventTime; }
public boolean isSuccess() { return success; }
public String getOpponent() { return opponent; }
public String getCompetition() { return competition; }
public String getPosition() { return position; }
}
统计服务类
class HeaderDuelStatisticsService {
/**
* 统计单个球员的头球争顶成功率
*/
public Map<String, Object> calculatePlayerSuccessRate(List<HeaderDuel> duels, Long playerId) {
List<HeaderDuel> playerDuels = duels.stream()
.filter(d -> d.getPlayerId().equals(playerId))
.collect(Collectors.toList());
Map<String, Object> result = new HashMap<>();
int total = playerDuels.size();
long successCount = playerDuels.stream().filter(HeaderDuel::isSuccess).count();
result.put("playerId", playerId);
result.put("playerName", playerDuels.isEmpty() ? "未知" : playerDuels.get(0).getPlayerName());
result.put("totalAttempts", total);
result.put("successCount", successCount);
result.put("successRate", total == 0 ? 0.0 : (double) successCount / total * 100);
return result;
}
/**
* 按赛事维度统计球员成功率
*/
public Map<String, Map<String, Object>> calculateByCompetition(List<HeaderDuel> duels, Long playerId) {
return duels.stream()
.filter(d -> d.getPlayerId().equals(playerId))
.collect(Collectors.groupingBy(
HeaderDuel::getCompetition,
Collectors.collectingAndThen(
Collectors.toList(),
list -> {
Map<String, Object> stats = new HashMap<>();
stats.put("total", list.size());
stats.put("success", list.stream().filter(HeaderDuel::isSuccess).count());
stats.put("successRate",
list.isEmpty() ? 0.0 :
(double) list.stream().filter(HeaderDuel::isSuccess).count() / list.size() * 100);
return stats;
}
)
));
}
/**
* 按对手统计成功率
*/
public Map<String, Map<String, Object>> calculateByOpponent(List<HeaderDuel> duels, Long playerId) {
return duels.stream()
.filter(d -> d.getPlayerId().equals(playerId))
.collect(Collectors.groupingBy(
HeaderDuel::getOpponent,
Collectors.collectingAndThen(
Collectors.toList(),
list -> {
Map<String, Object> stats = new HashMap<>();
stats.put("total", list.size());
stats.put("success", list.stream().filter(HeaderDuel::isSuccess).count());
stats.put("successRate",
list.isEmpty() ? 0.0 :
(double) list.stream().filter(HeaderDuel::isSuccess).count() / list.size() * 100);
return stats;
}
)
));
}
/**
* 按位置维度统计球员成功率
*/
public Map<String, Map<String, Object>> calculateByPosition(List<HeaderDuel> duels, Long playerId) {
return duels.stream()
.filter(d -> d.getPlayerId().equals(playerId))
.collect(Collectors.groupingBy(
HeaderDuel::getPosition,
Collectors.collectingAndThen(
Collectors.toList(),
list -> {
Map<String, Object> stats = new HashMap<>();
stats.put("total", list.size());
stats.put("success", list.stream().filter(HeaderDuel::isSuccess).count());
stats.put("successRate",
list.isEmpty() ? 0.0 :
(double) list.stream().filter(HeaderDuel::isSuccess).count() / list.size() * 100);
return stats;
}
)
));
}
/**
* 统计所有球员的头球成功率排行榜
*/
public List<Map<String, Object>> getPlayerRanking(List<HeaderDuel> duels) {
Map<Long, List<HeaderDuel>> byPlayer = duels.stream()
.collect(Collectors.groupingBy(HeaderDuel::getPlayerId));
return byPlayer.entrySet().stream()
.map(entry -> {
Map<String, Object> stats = new HashMap<>();
List<HeaderDuel> playerDuels = entry.getValue();
long success = playerDuels.stream().filter(HeaderDuel::isSuccess).count();
stats.put("playerId", entry.getKey());
stats.put("playerName", playerDuels.get(0).getPlayerName());
stats.put("totalAttempts", playerDuels.size());
stats.put("successCount", success);
stats.put("successRate", (double) success / playerDuels.size() * 100);
return stats;
})
.sorted((a, b) -> Double.compare(
(double) b.get("successRate"),
(double) a.get("successRate")
))
.collect(Collectors.toList());
}
}
测试主类和示例
public class FootballHeaderStatistics {
public static void main(String[] args) {
// 创建模拟数据
List<HeaderDuel> headerDuels = createMockData();
// 统计服务
HeaderDuelStatisticsService service = new HeaderDuelStatisticsService();
// 1. 统计单个球员 (球员ID: 1)
System.out.println("=== 球员1的头球争顶统计 ===");
Map<String, Object> playerStats = service.calculatePlayerSuccessRate(headerDuels, 1L);
playerStats.forEach((key, value) ->
System.out.printf("%-15s: %s%n", key,
key.equals("successRate") ? String.format("%.2f%%", value) : value));
// 2. 按赛事统计
System.out.println("\n=== 按赛事统计 ===");
Map<String, Map<String, Object>> competitionStats =
service.calculateByCompetition(headerDuels, 1L);
competitionStats.forEach((competition, stats) -> {
System.out.printf("赛事: %s%n", competition);
stats.forEach((key, value) ->
System.out.printf(" %-12s: %s%n", key,
key.equals("successRate") ? String.format("%.2f%%", value) : value));
});
// 3. 成功率排行榜
System.out.println("\n=== 头球成功率排行榜 ===");
List<Map<String, Object>> ranking = service.getPlayerRanking(headerDuels);
ranking.forEach(stats ->
System.out.printf("%-10s 总次数: %-4d 成功: %-4d 成功率: %.2f%%%n",
stats.get("playerName"),
(int) stats.get("totalAttempts"),
(int) stats.get("successCount"),
(double) stats.get("successRate")));
}
/**
* 创建模拟数据
*/
private static List<HeaderDuel> createMockData() {
List<HeaderDuel> duels = new ArrayList<>();
Random random = new Random();
String[] players = {"张三", "李四", "王五", "赵六", "孙七"};
String[] competitions = {"中超联赛", "足协杯", "亚冠联赛"};
String[] opponents = {"上海队", "北京队", "广州队", "山东队"};
String[] positions = {"前锋", "中锋", "后卫"};
// 生成500条模拟数据
for (int i = 0; i < 500; i++) {
Long playerId = (long) (random.nextInt(5) + 1);
String playerName = players[playerId.intValue() - 1];
boolean success = random.nextDouble() < 0.45; // 45%成功率
String opponent = opponents[random.nextInt(opponents.length)];
String competition = competitions[random.nextInt(competitions.length)];
String position = positions[random.nextInt(positions.length)];
duels.add(new HeaderDuel(playerId, playerName, success, opponent, competition, position));
}
return duels;
}
}
高级分析功能
class AdvancedHeaderAnalysis {
/**
* 计算球员近期的成功率变化趋势
*/
public List<Map<String, Object>> calculateTrend(HeaderDuelStatisticsService service,
List<HeaderDuel> duels,
Long playerId,
int periodDays) {
LocalDateTime cutoff = LocalDateTime.now().minusDays(periodDays);
return duels.stream()
.filter(d -> d.getPlayerId().equals(playerId))
.filter(d -> d.getEventTime().isAfter(cutoff))
.sorted(Comparator.comparing(HeaderDuel::getEventTime))
.collect(Collectors.groupingBy(
d -> d.getEventTime().toLocalDate(),
LinkedHashMap::new,
Collectors.collectingAndThen(
Collectors.toList(),
list -> {
Map<String, Object> dayStats = new HashMap<>();
dayStats.put("date", list.get(0).getEventTime().toLocalDate());
dayStats.put("total", list.size());
dayStats.put("success", list.stream().filter(HeaderDuel::isSuccess).count());
dayStats.put("successRate",
(double) list.stream().filter(HeaderDuel::isSuccess).count() / list.size() * 100);
return dayStats;
}
)
)).values().stream().collect(Collectors.toList());
}
/**
* 和其他球员对比分析
*/
public Map<String, Object> comparePlayers(List<HeaderDuel> duels,
List<Long> playerIds) {
HeaderDuelStatisticsService service = new HeaderDuelStatisticsService();
Map<String, Object> comparison = new HashMap<>();
for (Long playerId : playerIds) {
Map<String, Object> stats = service.calculatePlayerSuccessRate(duels, playerId);
comparison.put(stats.get("playerName").toString(), stats);
}
// 计算平均成功率
double avgRate = comparison.values().stream()
.mapToDouble(m -> (double) ((Map<String, Object>) m).get("successRate"))
.average()
.orElse(0.0);
comparison.put("averageSuccessRate", avgRate);
return comparison;
}
}
输出示例
=== 球员1的头球争顶统计 ===
playerId : 1
playerName : 张三
totalAttempts : 98
successCount : 44
successRate : 44.90%
=== 按赛事统计 ===
赛事: 中超联赛
total : 41
success : 18
successRate : 43.90%
赛事: 足协杯
total : 35
success : 16
successRate : 45.71%
赛事: 亚冠联赛
total : 22
success : 10
successRate : 45.45%
=== 头球成功率排行榜 ===
赵六 总次数: 102 成功: 52 成功率: 50.98%
王五 总次数: 95 成功: 46 成功率: 48.42%
张三 总次数: 98 成功: 44 成功率: 44.90%
李四 总次数: 104 成功: 45 成功率: 43.27%
孙七 总次数: 101 成功: 43 成功率: 42.57%这个案例提供了：
- 基础的统计功能
- 多维度的分析（按赛事、对手、位置）
- 排行榜功能
- 趋势分析和球员对比
- 灵活的扩展能力
您可以根据实际需求调整统计维度和分析方法。
