2.4 baseline — 0.6 × season 2.3 (12 gm) + 0.4 × last 10 2.4
−0.2 opponent leak — they concede 8.7/game vs a 9.7 league average
at this ground: too thin to count (2 gm) — shown, adds nothing
−1.5 wet forecast — averages 0.9 in the wet (9 gm)
vs them: averages 1.4 over 5 games — evidence, never summed
SignalsL10 form ▼opponent ▼wet ▼projection ▼
Most signals here point under while you're on the over — worth reading the working above before you commit.
Derived, not measured — plain arithmetic over his real games, shown in full. Adjustments can overlap (a game at this ground can also be a wet one); they add simply, and this note is the admission. Round 10: 8 — far outside his usual range; kept in the average, not smoothed away.
Line Over Under
Tap a bar for full game detail · newest on the right
Player percentile is among everyone with 5+ games this season. Opponent percentile is among the 18 clubs — p100 means they concede more of this stat than any other side.
CBR concede · Offloads
8.7per game · league avg 9.7
#13 of 17 most conceded
Stingy against this stat — the over fights uphill.
Venue split · Offloads
At GIO Stadium2.0(2)+0.7
Everywhere else1.3(54)
Only 2 games at this ground — thin evidence.
Wet vs dry · Offloads
Wet games (≥1mm)0.9(9)-0.5
Dry games1.4(47)
Weather backfilled from station data at each venue.
Similar players vs CBR · Offloads
Avg diff
-0.8
Avg diff %
-69%
Hit rate
0/8
beat their own average
DateTeamPlayerAvgResultDiff
08-09NEWDane Gagai1.00-100%
08-09NEWKalyn Ponga1.80-100%
08-09NEWTrey Mooney1.10-100%
08-01PENNathan Cleary1.10-100%
08-01PENPaul Alamoti1.21-17%
08-01PENIsaiah Papali'i1.61-37%
08-01PENLiam Martin1.010%
08-01PENIsaah Yeo1.00-100%
Similar = season average within ±1.5 of Kai's. Computed from this app's own records.