Match

USA vs Serbia: result 0-0 and analysis

FriendliesFriendlies 1Kick-off on January 29, 2017 at 09:00 PM (UTC)GEODIS Park, Nashville, Tennessee

USA
0-0
Serbia

Full time

What was the result of USA vs Serbia?

USA and Serbia drew 0-0 on January 29, 2017.

Official lineup for USA vs Serbia

The starting elevens fielded at kick-off.

USA

  1. 17J. Altidore
  1. 4M. Bradley
  2. 6D. Nagbe
  3. 11A. Bedoya
  4. 13J. Jones
  5. 16S. Klještan
  6. 19G. Zusi
  1. 2G. Garza
  2. 5Chad Marshall
  3. 15S. Birnbaum
  1. 1N. Rimando

Serbia

  1. 18S. Jovanović
  1. 7S. Plavšić
  2. 10A. Paločević
  3. 15S. Panić
  4. 16J. Đokić
  1. 3N. Miletić
  2. 5N. Maraš
  3. 11M. Gobeljić
  4. 13N. Ćirković
  5. 14N. Ćalasan
  1. 1F. Manojlović
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What is the recent form of both teams?

Over their last 15 matches in all competitions, USA have 7 wins, 2 draws and 6 defeats; Serbia have 3, 2 and 2.

The competition is shown for every match: in pre-season, several of these games are friendlies.

USA
DateOpponentScoreCompetition
Nov 16, 2016Costa Rica(away)0-4World Cup - Qualification CONCACAF
Nov 12, 2016Mexico(home)1-2World Cup - Qualification CONCACAF
Sep 7, 2016Trinidad and Tobago(home)4-0World Cup - Qualification CONCACAF
Sep 2, 2016St. Vincent / Grenadines(away)6-0World Cup - Qualification CONCACAF
Jun 26, 2016Colombia(home)0-1Copa America
Serbia
DateOpponentScoreCompetition
Nov 12, 2016Wales(away)1-1World Cup - Qualification Europe
Oct 9, 2016Austria(home)3-2World Cup - Qualification Europe
Oct 6, 2016Moldova(away)3-0World Cup - Qualification Europe
Sep 5, 2016Rep. Of Ireland(home)2-2World Cup - Qualification Europe
Jun 23, 2010Australia(away)1-2World Cup

How many goals should we expect?

USA score 2.0 and concede 1.3 goals per match over their last 15; Serbia score 1.6 and concede 1.1.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
USA2.01.364/1510/15
Serbia1.61.124/74/7

Over the last 15 matches in all competitions.

A question about USA vs Serbia?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

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How does Footlab AI compute this prediction?

The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy

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