user avatar
SkillCorner
@SkillCorner
Single camera tracking data and analytics on a global scale. Powering Smarter Decisions In Sport ⚽️ 🏀 🏈
Paris, France
Joined December 2015
Posts
  • user avatar
    @Botafogo has recently become the newest addition to the list of Brazilian clubs partnering with SkillCorner 🇧🇷 The two-time Brazilian national champion will use our Physical and Game Intelligence data to enhance its scouting operation and continue the club’s excellent progress
    00:00
  • user avatar
    Nos complace anunciar la firma de nuestro primer cliente en Perú @ClubALoficial 🤝🇵🇪 Lee más aquí. skillcorner.com/es/blog/club-a…
    00:00
  • user avatar
    Sprint Distance benchmarks for 2020/21 season with both competition and team aggregation. Data shown is team level and normalised for playing time differences (P900).
  • user avatar
    #RUS #CRO #RUSCRO #WorldCup #CM2018 Dynamic heatmap of Luka #Modric during the first 90 minutes.
    00:00
  • user avatar
    Estamos felizes em anunciar que mais um clube no Brasil fechou parceria com a SkillCorner. @SCInternacional utilizará nossos Dados Físicos para apoiar suas atividades de scouting, além de nossos Dados de Tracking em Bruto XY e Game Intelligence. skillcorner.com/pt/blog/sc-int…
    00:00
  • user avatar
    Our partnerships across Europe continue to grow. Really excited to be working with @OM_Officiel for the 2020/21 season.
  • user avatar
    SkillCorner is excited to announce that full continuous player tracking is now available. The simulation option follows an extensive 12 month period of development, in order to estimate player movement off-camera, during replays and close ups. (Event sync starts at 20s)
    00:00
  • user avatar
    🔵⚪ @SCBastia adopts SkillCorner to refine its recruitment! ⚽ ️We’re excited to announce that SC Bastia will leverage our physical data to accurately assess player performance and optimize strategic decisions. A collaboration that puts data at the service of performance.
  • user avatar
    Following the recent @CIES_Football research on the relationship between high-speed running and age, we can illustrate this further by plotting sprint distance (P90) for central forwards relative to age. For context, we have revealed the statistical outliers for each age band.
  • user avatar
    Traditional football data provides information about on-the-ball events and outcomes. But on average a player is only on the ball for 3 mins per game. Can we evaluate the other 97% of a player’s contribution, at scale? Introducing Game Intelligence... #scouting #FootballData
    00:00
  • user avatar
    Here is the link of the 9 matches of broadcast tracking data, we're open sourcing today: github.com/SkillCorner/op… We'll open source soon some tooling to help visualizing the data, computing derivatives or synchronizing the data with event data.
  • user avatar
    With Game Intelligence, you can evaluate the off-ball movement of players, and how behaviours vary by position group: ➡️Dedicated forwards vs supporting wingers ➡️Midfielders need to display versatile profiles ➡️More specific runs for defenders in the build up phase
  • user avatar
    We used our tracking data to look at Peak-Sprint Velocity of players ranked by age. Last season, Victor Osimhen (24) recorded the highest PSV-99, while Kyle Walker (32) was the fastest player in Europe aged 30+. Some players can remain well above the average even aged 36 or 37.
  • user avatar
    In Game Intelligence, each run is given an xT (Expected Threat) value. xT is the probability of the team scoring a goal within 10 seconds if the pass is served to a runner. This puts all off-ball runs into context and rewards the run even if the pass isn't made. #footballdata