[MSGB-TV] Maple Leafs vs Sabres: Live Stream (NHL Hockey Online 2019)
Bibliographic record
Abstract
The Toronto Maple Leafs need a win here after losing five of their last seven games. The Toronto Maple Leafs are averaging 3.6 goals per game and are scoring on 23.1 percent of their power play opportunities. =========================== Watch Live NOW >> https://247itv.info/ice-hockey Watch Live NOW >> https://247itv.info/ice-hockey =========================== John Tavares leads Toronto with 40 goals, Mitch Marner has 61 assists and Morgan Rielly has 197 shots on goal. Defensively, the Toronto Maple Leafs are allowing three goals per game and are killing 81 percent of their opponents power plays. Frederik Andersen has given up 141 goals on 1,725 shots faced and Garret Sparks has allowed 50 goals on 511 shots. The Toronto Maple Leafs have allowed three or more goals in their last five games. The Buffalo Sabres could use a win after losing nine of their last 11 games. The Buffalo Sabres are averaging 2.7 goals per game and are scoring on 18.2 percent of their power play opportunities. Jeff Skinner leads Buffalo with 37 goals, Jack Eichel has 47 assists and Sam Reinhart has 153 shots on goal. Defensively, the Buffalo Sabres are allowing 3.2 goals per game and are killing 81.3 percent of their opponents power plays. Carter Hutton has given up 119 goals on 1,326 shots faced and Linus Ullmark has allowed 97 goals on 1,032 shots. The Buffalo Sabres have allowed three or more goals in 10 of their last 11 games. The Maple Leafs are 54-26 in their last 80 games as a favorite, 1-5 in their last 6 games playing on 0 days rest and 2-5 in their last 7 road games. The Sabres are 1-6 in their last 7 games as an underdog, 1-4 in their last 5 games playing on 2 days rest and 8-21 in their last 29 overall. The Maple Leafs are 7-19 in the last 26 meetings in Buffalo and 4-0 in the last 4 meetings. The over is 4-0 in Maple Leafs last 4 overall. The under is 3-1-1 in Sabres last 5 overall. The Toronto Maple Leafs are back to getting torched defensively, which explains this losing skid they're currently riding. Still, the Maple Leafs have won each of the last six meetings against the Sabres and have had their way offensively in those games, including a 5-2 win a couple of weeks ago. The Buffalo Sabres look like a team that's ready for the offseason and six of their last eight losses have come by two or more goals, so they're not even competing out there most nights. The Toronto Maple Leafs should stop the bleeding and get in the win column here.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.854 | 0.713 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".