Everyone bets goalscorers. Far fewer bettors look at assists, corners won or fouls won, and bookmakers give these markets much less attention than the goalscorer market.
That doesn't make them automatically profitable, but it does mean the prices are more likely to be off. The key is matching a player's real per-game numbers against the odds.
Here's a framework for alternative player props that most bettors ignore.
Player Assists Betting
Key Assist Statistics
What to track:
| Stat | Why It Matters | Where to find it |
|---|---|---|
| Assists per game | Direct productivity | StatPair |
| Crosses per game | Delivery volume from wide areas | StatPair |
| Key passes per game | Chance creation | FotMob, SofaScore |
| Expected assists (xA) | Quality of chances created | FotMob, Understat |
Assists are rare events, so a player's assist count over a few games is mostly noise. Chance creation (key passes, xA) and role (set pieces, crossing) tell you more about what will happen next.
Best Positions for Assists
1. Wide playmakers (wingers/wing-backs)
- High crossing volume
- Cut-back opportunities
2. Central attacking midfielders
- Through balls
- Final passes
3. Full-backs in attacking systems
- Overlapping crosses
- Set-piece deliveries
Set-piece takers deserve special attention: every corner and wide free kick is an extra chance to record an assist.
Assist Bet Analysis
Player to record an assist - often priced well above evens
Who to target:
- Players who create chances regularly (check key passes on FotMob or SofaScore)
- Team facing a weak defence that concedes plenty of shots
- Home games (home teams usually attack more)
- Playing alongside a reliable finisher
- Takes corners and free kicks
Example (hypothetical):
Creative midfielder, home game against a weak defence
Stats:
- Creates several chances per home game
- Assists over a longer sample: around 0.35 per home game
- Takes the team's corners
Opponent:
- Concedes plenty of shots away from home
- His team is expected to dominate the ball
Your estimate: ~33% to assist
Fair odds: 1 / 0.33 = 3.03
Bookmaker odds: 3.50 (28.6% implied)
EV: 0.33 × 3.50 - 1 = +15.5% - but only if your 33% is realistic. Assist probabilities are hard to estimate precisely, so stake modestly.
Player Corners Won
A less-watched market
What Counts as "Corner Won"
Player wins a corner when:
- His shot is blocked or saved out for a corner
- A defender puts the ball out under pressure from him
- His cross is deflected out
Doesn't count:
- Team corners he wasn't involved in
Settlement rules differ between bookmakers, so check how they define the market.
Key Statistics
Track per player:
- Corners won per game
- Shots per game (blocked shots often become corners)
- Crosses per game (deflected crosses)
- Wide position and attacking role
Who wins the most corners:
| Player type | Why |
|---|---|
| Wingers | Crosses and take-ons near the byline |
| Strikers | Blocked shots and pressure on defenders |
| Attacking full-backs | Overlapping crosses |
Corners Won Betting Strategy
Market: Player 1+ corner won
Best opportunities:
1. Aggressive dribblers
- Take on defenders in wide areas
- Force mistakes and deflections
2. High-volume shooters
- Blocked shots often = corners
- Especially against packed defences
3. Wide players vs weak full-backs
- 1v1 mismatches
- Defenders under pressure put the ball out
Example (hypothetical):
Winger, away game
Player stats:
- Has won at least one corner in 6 of his last 10 away matches
- Takes plenty of shots and crosses
Matchup:
- Opponent's full-back struggles 1v1
- His team is expected to attack down that side
Your estimate: ~50% (6/10, adjusted down slightly for regression, up slightly for the matchup)
Odds offered: 2.50 (40% implied)
EV: 0.50 × 2.50 - 1 = +25% - a strong edge if the estimate holds. With only 10 matches of data, treat it with caution.
Fouls Won / Drawn
Underrated market with consistent patterns
Why This Market Works
Advantages:
- Very predictable - in our study of 372,650 player starts, fouls won had a split-half reliability of 0.84, one of the highest of any prop stat
- Stable in every position (0.75-0.80 within forwards, midfielders and defenders)
- Less randomness than goals or assists
Player Types to Target
Players who draw lots of fouls:
Skilful dribblers:
- Take on defenders repeatedly
- Get clipped when they beat their man
Physical target men:
- Hold-up play with their back to goal draws fouls
Quick counter-attackers:
- Fouled to stop breaks ("tactical fouls")
Fouls Won Analysis
| Player profile | Betting approach |
|---|---|
| Rarely fouled | Avoid Overs |
| Average | Only at bigger odds |
| Regularly fouled | Check the hit rate on 1+ and 2+ |
| Fouled several times most games | Consider higher lines |
Reality check on hot streaks: players who won 1+ foul in 8 or more of their last 10 starts did so again 74.4% of the time in our study, compared with the 86.4% their recent run suggested. Still well above the 53.7% base rate - but lower than it looks.
Market: Player 1+ or 2+ fouls won
Factors increasing fouls won:
- Physical or aggressive opponent (check the opponent's fouls committed)
- A referee who blows for a lot of fouls
- Counter-attacking game plan
- Cup ties against lower-level opposition
Combined Player Props
Combining multiple player outcomes = bigger odds
Understanding Combinations
1. Player 1+ shot on target + team to win
How it works:
- Positive correlation: if the star player is shooting a lot, his team is more likely to be on top
- The true joint probability is higher than simply multiplying
Example (hypothetical):
- Striker 1+ SoT: 1.40
- His team to win: 1.30
- Multiplied: 1.82
Bookmakers know these are correlated. In a bet builder, you'll usually be offered less than 1.82. Compare the offered price with your own estimate of the joint probability rather than assuming correlation makes it value.
2. Player to score + over 2.5 goals
How it works:
- If the player scores, the match is one goal closer to the Over
- High-scoring games favour strikers
- Strong positive correlation - and usually a heavily adjusted price
3. Player 1+ SoT + same player 1+ corner won
How it works:
- Active attackers often do both
- Only loosely related, so the price adjustment is usually smaller
Combinations to AVOID
❌ Player to score + under 1.5 goals
Pulls in opposite directions
❌ Defender to score + clean sheet
Possible, but the outcomes work against each other
❌ Same player assist + to score
Can happen, but the combined probability is low and the price rarely compensates
Shot + Card Combined Bets
Interesting market: Player 1+ SoT + to be booked
Can suit:
- Physical strikers (contact + shooting)
- Aggressive attacking midfielders
- Heated matches (derbies, rivalries)
Remember that player cards are close to random in our data (split-half reliability 0.35), so the card leg carries most of the uncertainty. Fouls committed is a better guide to booking risk than past cards.