Mit dem Guide verknüpftes Quiz · Mittel Ebene

KI im Sportanalyse-Quiz

Verstehen Sie erwartete Ziele, optisches Spieler-Tracking und Daten zur Athletenbelastung als eindeutige Quellen für die Analyse der sportlichen Leistung.

Verwandte FührungspfadeKI in der Sportanalyse
Frage 1 von 8

Was schätzt die Kennzahl „erwartete Tore“ (xG) im Fußball?

Sehen Sie sich jede Frage in der Vorschau an8 Fragen

Während Sie am Quiz teilnehmen, werden Antworten und Erklärungen angezeigt.

  1. Was schätzt die Kennzahl „erwartete Tore“ (xG) im Fußball?
    • Die Wahrscheinlichkeit, dass ein bestimmter Schuss aufgrund seiner Eigenschaften zu einem Tor führt
    • Die Anzahl der Tore, die eine Mannschaft in dieser Saison tatsächlich geschossen hat
    • Das Gehalt, das ein Stürmer zahlen sollte
    • Die Gesamtdistanz, die ein Spieler in einem Spiel zurücklegt
  2. Which company did the NBA announce as its official optical-tracking technology partner in its Hawk-Eye partnership?
    • Catapult Sports
    • Hawk-Eye Innovations, part of Sony Group
    • StatsBomb
    • The U.S. Department of Agriculture
  3. Which sensor inputs does Catapult describe in its athlete-monitoring system?
    • Only jersey color and player name
    • Only event logs such as passes and shots
    • GPS or local-positioning data, inertial sensors and heart-rate data
    • Only the final score of a match
  4. What does the NBA’s Defensive Pressure Score use optical tracking data to estimate?
    • The probability a soccer shot becomes a goal
    • The athlete’s blood oxygen level during training
    • A team’s future draft position
    • The defensive pressure an opponent places on an offensive player
  5. What modeling idea did Skinner and Guy propose for learning basketball player skills from tracking data?
    • An offensive network model relating player skills to play success and lineup performance
    • A soccer shot-conversion model using only shot location
    • A biometric wearable classifier for injury diagnosis
    • A contract-value model based only on box scores
  6. What did a study of more than 50,000 NBA shot trajectories report about tight contests?
    • Contest level has no relationship to shot trajectory
    • Shooters tend to miss more often when their shots are tightly contested
    • Every contested shot is automatically blocked
    • Three-point shots never change under defensive pressure
  7. Which contextual factors does the StatsBomb xG description say may inform a shot’s expected-goal value?
    • Only the player’s jersey number
    • Only the final score of the match
    • Distance, angle, body part and contextual factors such as goalkeeper and defender positions
    • The team’s season budget
  8. What can optical tracking data provide beyond event records such as passes and shots?
    • Only the final match score
    • A medical diagnosis for each athlete
    • A guaranteed explanation for every tactical decision
    • Continuous player and ball positions over time