0.5 baseline — 0.6 × season 0.7 (19 gm) + 0.4 × last 10 0.3
+0.0 opponent leak — they concede 38.8/game vs a 35.7 league average
−0.0 wet forecast — averages 0.5 in the wet (4 gm)
vs them: averages 0.3 over 4 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.
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.
GWS concede · Clearances
38.8per game · league avg 35.7
#2 of 18 most conceded
They leak this stat — friendly matchup for the over.
Venue split · Clearances
At Manuka Oval—(0)
Everywhere else0.4(72)
Only 0 games at this ground — thin evidence.
Wet vs dry · Clearances
Wet games (≥1mm)0.5(4)+0.1
Dry games0.4(68)
Weather backfilled from station data at each venue.
Similar players vs GWS · Clearances
Avg diff
+0.1
Avg diff %
+14%
Hit rate
4/8
beat their own average
DateTeamPlayerAvgResultDiff
08-01PORDante Visentini1.41-27%
08-01PORJack Watkins2.22-8%
08-01PORCorey Durdin1.32+60%
08-01PORWill Lorenz2.01-50%
08-01PORDarcy Byrne-Jones1.12+75%
08-01PORMiles Bergman1.92+8%
08-01PORMitch Georgiades1.32+50%
08-01PORBalyn OBrien1.010%
Similar = season average within ±1.5 of Joel's. Computed from this app's own records.