DC United vs Chicago Fire: match statistics
DC United vs Chicago Fire: form, goals and key statistics
Key match information
DC United played Chicago Fire in MLS (United States). The match was played on 13 May 2026. Final score: 1:3.
Current form
DC United: 2-3-0, 1.80 points/match. Chicago Fire: 2-1-2, 1.40 points/match.
Goal statistics
DC United scores 1.25 and concedes 1.42 goals per match. Chicago Fire scores 1.82 and concedes 1.27. League average: 3.20 goals.
BTTS / Over / Under
BTTS: DC United 42%, Chicago Fire 55%. Over 2.5: DC United 50%, Chicago Fire 73%. League level: BTTS 59%, Over 2.5 61%.
xG, shots and style
Chicago Fire has higher xG: 1.67 vs 1.28. DC United: 11.4 shots per match, Chicago Fire: 15.3.
Match halves
DC United: half-time lead 33%, second-half goals 0.75. Chicago Fire: half-time lead 45%, second-half goals 1.00.
Goals by minute
DC United: 76-90+ (5 goals). Chicago Fire: 76-90+ (6 goals). This is historical distribution, not a predicted goal minute.
League context
MLS: 3.20 goals per match, BTTS 59%, Over 2.5 61%.
Head-to-head
Before this fixture, 1 previous H2H matches were available: 1-0-0. Average goals 3.00, BTTS 100%.
Archived pre-match analysis
This analysis was prepared before kick-off. The conclusions use only information available before the match and do not include the final result or post-match statistics.
General match analysis
I predict a draw (X): DC United are unbeaten in five (2 wins, 3 draws), scoring 11 goals in that span and averaging 1.8 points per game, while Chicago Fire have only 1 win and 1 draw in their last five (PPG 0.8) despite scoring 12 goals. Both teams create a similar number of chances – DC average 12 shots per home game with 4 on target, Chicago average 10.75 shots with 4 on target as well, but the visitors are more efficient (conversion 14% vs 10%). Offensively the home side score 1.25 goals per home match with xG 1.36, but concede 2.0 goals per game on average (xG against 1.26), whereas Chicago score 1.5 on the road with xG 1.24 and concede 1.5 (xG against 1.62), indicating greater efficiency from the visitors in finishing chances. Additionally, Fire control possession more away (51% vs 44% for DC), and the visitors register 50% draws on the road; combining the hosts’ form with Fire’s high propensity for draws, a shared points outcome is most likely, hence an estimated 40% for a draw, 35% for a DC win and 25% for a Chicago win.
View the statistical overviewBTTS - will both teams score?
I predict BTTS - Yes at 70%. Chicago Fire has a season BTTS rate of 75% and 80% in the last 5 matches, while DC United has 43% for the season and 60% in the last 5, which tilts the signal toward both teams scoring. DC generates 1.92 xG on average and Chicago concedes 1.62 xG; conversely Chicago produces 1.24 xG and DC concedes 1.18 xG — these figures indicate both sides create goal-scoring opportunities. In the last 5 matches DC scored 11 goals (2.2 avg) and conceded 8 (1.6), and Chicago scored 12 (2.4) and conceded 11 (2.2), which confirms goal exchange. The counterargument is DC’s high home clean sheet rate of 57% (vs 25% for Chicago away), so despite that I assign 70% to YES and 30% to NO as a balanced, numerically justified forecast.
View BTTS statisticsOver/Under - goals analysis
Based on xG: DC United has an attacking xG of 1.92 while Chicago concedes xG of 1.62, giving the home side ≈1.77 expected goals; Chicago’s attacking xG is 1.24 and DC’s xG against is 1.18, yielding the visitors ≈1.21, total ≈2.98. MLS average is 3.21 goals per game, and seasonal metrics show Over 2.5 in 71% of DC’s matches and 75% of Chicago’s matches, confirming both teams’ propensity for higher-scoring games. A Poisson model with μ=2.98 forecasts ~80% probability for Over 1.5 goals, ~57% for Over 2.5 and ~35% for Over 3.5, so the strongest signal is Over 1.5. Additionally, DC averages 17.86 shots and 5.57 on target, while Chicago averages 10.75 shots and 4.0 on target, which increases the likelihood of at least two goals; on the other hand DC keeps a clean sheet in 57% of matches, which limits the probability of a very high Over 3.5. As a result I recommend betting Over 1.5 as the best and least risky option; Over 2.5 has moderate value (model ~57%, seasonally 71–75%), whereas Over 3.5 appears risky (~35%).
View Over/Under statisticsHT/FT - half-time and full-time scenario
DC United are the favorites: a seasonal goals average of 2.0 versus Chicago’s 1.5 and average xG 1.92 vs 1.24 indicate a clear offensive edge for the hosts; additionally, average shots 17.86 vs 10.75 and shots on target 5.57 vs 4.0 increase their chances to take a lead. At Half-Time the stats are more balanced — DC average 0.71 goals HT and have led in 3 matches this season (43%), but in the last 5 home games the hosts were leading at the break in 60%, while Chicago average 1.0 goals HT and have led seasonally in 2 matches (50%) yet only in 20% of their last 5. Defensively DC concede 1.14 goals per match vs 1.5 for Chicago, and the hosts’ HT clean sheet rate is 71% versus 50% for the visitors, suggesting that if they take the lead there is a high chance they will hold it. Considering the xG advantage, number of shots on target and form (DC ‘ddwwd’ vs Chicago ‘dwlll’), the most likely scenario is the hosts leading at Half-Time and winning Full-Time (1/1). I assign moderate weight to the draw at Half-Time → home win Full-Time variant (X/1) given DC’s 6 goals in minutes 76–90 and better second-half production by the hosts.
View first-half and second-half statisticsHalf-by-half
Match statistics
Pre-match profile— what do the season numbers say?
This is a team profile based on season data and form. Match-flow statistics are shown only after the fixture is played.
Team stats— who is more efficient?
Attack and defence comparison for both teams in the current season.
Shooting quality
| DC United | Chicago Fire | |
|---|---|---|
| Accuracy (shots on target) | 33% | 33% |
| Chance quality (xG per shot) | 0.11 | 0.11 |
| Finishing (goals per shot on target) | 0.33 | 0.36 |
xG per shot around 0.08 usually means long-range attempts; 0.15+ usually means box chances. The style label comes from possession, shot volume and conversion.
* xG (expected goals) says how many goals a team should score from its chances. If actual goals are above xG, finishing is above average; if below xG, chances are being missed.
Team form— who is in better shape?
Last five matches and season record, overall and split by home and away matches.
DC United is 29% better for: last-5 form.
1.8 pts / match - DC United · 1.4 pts / match - Chicago Fire
Goals— how do both teams score and concede?
How many goals both teams score and concede, plus how often they keep a clean sheet or fail to score.
Chicago Fire is 46% better for: goals scored per match.
1.25 goals / match - DC United · 1.82 goals / match - Chicago Fire
Chicago Fire is 12% better for: goals conceded per match.
1.42 goals / match - DC United · 1.27 goals / match - Chicago Fire
DC United scores in 58% of matches (7 of 12 matches), while Chicago Fire keeps a clean sheet in 45% (5 of 11 matches).
Chicago Fire scores in 91% of matches (10 of 11 matches), while DC United keeps a clean sheet in 33% (4 of 12 matches).
How often they score at least...
How often they concede at least...
* Statistics include both teams' home and away matches in the current season.
Both teams scored (BTTS)— how often do both teams score?
How often both teams' matches have goals on both sides, compared with the league average.
Goal patterns
BTTS and goal count
Goal count (Over/Under)— how often do these matches cross the goal lines?
How often matches involving these teams clear goal thresholds, in the full match and in each half.
Full match - team comparison (Over)
Over / Under - DC United
Over / Under - Chicago Fire
1st half
2nd half
Match halves— when do the teams score more often?
How teams split performance between first and second half: goals, points, clean sheets and half-time state.
Chicago Fire is 37% better for: first-half form (half-time points).
1.33 pts / match - DC United · 1.82 pts / match - Chicago Fire
Before half-time (1st half)
After half-time (2nd half)
DC United - second-half results
Leads at half-time in 33% of matches and wins 33%. Also wins matches without a half-time lead.
Concedes 0.3 more goals per match after half-time - defensive level drops in the second half.
Chicago Fire - second-half results
Leads at half-time in 45% of matches and wins 45%. Also wins matches without a half-time lead.
Concedes 0.4 more goals per match after half-time - defensive level drops in the second half.
| 1st half | 2nd half | |
|---|---|---|
| Points per match | 2.00 | 1.60 |
| Goals scored / match | 1.0 | 1.2 |
| Goals conceded / match | 0.4 | 1.2 |
| Average goals in match | 1.4 | 2.4 |
| 1 goal | 80% | 80% |
| 2 goals | 40% | 60% |
| 3 goals | 20% | 40% |
| Clean sheet | 80% | 40% |
| No goal | 20% | 40% |
| Goal difference | +3 | 0 |
| 1st half | 2nd half | |
|---|---|---|
| Points per match | 1.60 | 0.80 |
| Goals scored / match | 1.0 | 1.4 |
| Goals conceded / match | 0.8 | 1.0 |
| Average goals in match | 1.8 | 2.4 |
| 1 goal | 80% | 80% |
| 2 goals | 40% | 60% |
| 3 goals | 40% | 60% |
| Clean sheet | 40% | 40% |
| No goal | 40% | 40% |
| Goal difference | +1 | +2 |
* Colours in tables show event frequency: green is common, yellow is moderate, red is rare. It is frequency, not a team rating.
Goals by minute— when do goals arrive?
Match phases in which both teams most often score and concede.
Most dangerous in minutes 76-90 (5 goals). Concedes most in 76-90 (6). Late-goal balance (76-90): -1 - late phases are a weakness.
Most dangerous in minutes 76-90 (6 goals). Concedes most in 76-90 (7). Late-goal balance (76-90): -1 - late phases are a weakness.
* Buckets 31-45 and 76-90 include added-time goals.
Additional team indicators— what do xG, efficiency and form show?
A comparison of chance quality, results and trends based on completed matches from the current season.
Match profile
DC United
Chicago Fire
* The estimated goal total and split, BTTS estimate, 0:0 risk and goal range are calculated from public season averages and frequencies for both teams. This is a statistical match profile, not a private model prediction or betting pick. The remaining indicators describe completed matches from the season.
League context— is this a high-scoring league?
How both teams compare with league-wide averages (MLS).
Teams vs league
| DC United | Liga | Chicago Fire | |
|---|---|---|---|
| Average goals in match | ▼ 2.67 | 3.20 | ▼ 3.09 |
| Both teams scored | ▼ 42% | 59% | ▼ 55% |
| Min. 3 goals (Over 2.5) | ▼ 50% | 61% | ▲ 73% |
| Clean sheets | ▲ 33% | 23% | ▲ 45% |
| Goal before half-time | ▼ 67% | 74% | • 73% |
| Goal after half-time | ▼ 67% | 79% | ▼ 73% |
^ green = above league average, ˇ red = below league average. This shows direction of the gap, not a team rating.
Lineups and player events
Verified starters, substitutes and recorded player events for this match.
Home team
Starting lineup
Away team
Starting lineup
Match timeline
Goals, cards and substitutions arranged in chronological order.
Referee and managers
Open their season profiles to compare match records, goals and disciplinary trends.
Head-to-head
Previous meeting: DC United 1 - 0 - 0 Chicago Fire. Average goals 3.00, both teams scored in 100% matches.
FAQ
What was the result of DC United vs Chicago Fire?
The MLS match finished DC United 1:3 Chicago Fire. Full match statistics, the half-by-half breakdown and head-to-head are on this page.
What do the goal statistics show before DC United vs Chicago Fire?
DC United score 1.25 goals per game on average and Chicago Fire 1.82. The MLS average is 3.20 goals, with Over 2.5 landing in 61% of games. Both teams score in 42% of DC United's matches and 55% of Chicago Fire's.
What form are DC United and Chicago Fire in?
Over the last 5 games DC United have a 2-3-0 record (1.80 points per game) and Chicago Fire 2-1-2 (1.40 points per game).
Where can I find a betting tip and analysis for DC United vs Chicago Fire?
Here you can check the pre-match numbers for DC United vs Chicago Fire: form, H2H, goals and Over/Under. The pick itself, value and reasoning are published in the NoFluffPicks app.


