XCrossAttemptModel is a deterministic-XGBoost classifier estimating P(the in-possession team attempts a cross within ~1 s of a tracking frame) — a STATE-anchored framing, reframed from the sender-level event treatment in Cao et al. (arXiv:2505.11841). It carries 7 of the paper's 8 confounders (crosser-position, #7, is omitted — no faithful tracking-only proxy) plus a novel, isolatable GK-position confounder block, which is the paper's headline gap and the reason this model exists inside the GKDV research arc (TF-17 → TF-19). - 16 features, faithful (velocity-bearing), goal-relative coordinates via the shared geometry helper - The scextended model is fit on the owner-tier corpus (IDSSE +…
Open weights
mit
silly-kicks
XShotOccurrenceModel is a deterministic-XGBoost classifier estimating P(a shot is attempted by the in-possession team within ~1 s of a tracking frame) — the xS surface of the GKDV research arc (TF-16). Paper-faithful 27-feature extractor in goal-relative coordinates via the shared geometry helper: ball r/θ/z/speed, an openGoal goal-mouth obstruction term, GK distance/bearing, and the 5 nearest defenders + 5 nearest attackers. - Trained on 964,263 rows / 182,517 positives (18.9% positive rate) scextended is HF-only for licensing, not quality: it is trained on restricted owner-tier SkillCorner data that cannot be redistributed inside the PyPI wheel (ADR-038). Only learned parameters are…
Open weights
mit
silly-kicks
Predicts where a league-average goalkeeper would position themselves given the current game state. Uses RFCDE (Random Forest Conditional Density Estimation) over HistGradientBoostingRegressor leaf assignments with weighted 2D kernel density estimation. Part of the silly-kicks soccer analytics library (GKDV research program, TF-18, Layer 2). Standard goalkeeper evaluation metrics (xGOT, save percentage, goals prevented) measure what happens after a shot is taken. Ghost-GK addresses the upstream question: given the current game state, where should the goalkeeper be standing? The model learns a league-average positional density from thousands of match frames across multiple tracking data…
Open weights
mit
silly-kicks
Predicts where a league-average outfield rearguard defender would position themselves, per tracking frame, team, and lateral slot. The outfield sibling of Ghost-GK v1: a point estimate (ghostgrx/y, goal-relative) served as the exact pickle-free boosted HistGradientBoostingRegressor mean. Part of the silly-kicks soccer analytics library (TF-60 rest-defense; ADR-087). It is the league-average baseline the rest-defense outfield counterfactual arm differences against ("how far does the actual rest-defense shape sit from average?"). For an in-possession team's rest defense (the rearguard it keeps while attacking, to blunt the counter after a loss), the model predicts the league-average position…
Open weights
mit
silly-kicks
Predicts where a league-average goalkeeper would position themselves, including the in-possession high-sweeper regime that the standard Ghost-GK v1 model cannot represent. Point-estimate (ghostgkx/y) served as the exact pickle-free boosted HistGradientBoostingRegressor mean. Part of the silly-kicks soccer analytics library (TF-60 rest-defense; ADR-083). The bundled Ghost-GK default/full variants train on a fixed goal-relative box x ∈ [0, 30] m from the defended goal: a keeper who has swept far upfield falls outside it and is dropped as a "sweeper rush". That is correct for normal in-goal positioning, but it makes the model hard-saturate at 30 m — it cannot place an in-possession keeper who…
Open weights
mit
silly-kicks
