CBS Sports did a pretty good power ranking with their league bot this week. You can see it here. I don't really have a big issue with the bot's rankings. I am a bit uncomfortable with my #2 ranking, but I do have the longest win streak right now. Rather than re-invent the blog wheel, I'll try to do something different this week.
Most of you look at your scoring preview after setting your lineup. I hope. I was curious how accurate those scoring forecasts have been for us so far this season. So I created a spreadsheet that tracks the variance between actual scoring and the forecast scoring. With about 2 exceptions, how a team over or under deliver to their predicted points is highly correlated to the coaching / managerial efficiency ranking.
Some surprising findings:
Here are the results (sorry for the plain formatting, looks nicer on the spreadsheet).
Most of you look at your scoring preview after setting your lineup. I hope. I was curious how accurate those scoring forecasts have been for us so far this season. So I created a spreadsheet that tracks the variance between actual scoring and the forecast scoring. With about 2 exceptions, how a team over or under deliver to their predicted points is highly correlated to the coaching / managerial efficiency ranking.
Some surprising findings:
- Tuna has over-performed EVERY week so far compared to his forecast. He's beating his predicted score by 15 points on average. He's indeed a juggernaut hot stock.
- Hai matches the forecast expectations the best, with an average close to zero and a relatively low standard deviation score of 14.6. Hai is the closest match to an index fund in this group.
- On the opposite side, despite having a variance close to zero, Vu and Matt have wild scoring swings as shown by their high std dev scores and thus are the most unpredictable to predict each week.
- Victor has overachieved in the past 4 weeks, helping him outdo his predicted score by more than 10 points each week on average.
- Kevin and Byron have very close performances, doing about 5 points better than expected to the preview scores with a middle of the road standard deviations.
- Donny would be underachieving if not for one monster week 4 where he out-kicked his coverage by almost 45 points. That was the best case of exceeding expectations so far this year.
- Justin either outperforms or underperform by more than 10 points each week. Not sure what to make of this for the future, however.
- When PJ does badly, he really, really, really sucks. All his negative variances are over 20 points under the forecast. Yeah, I can see why the league bot is shorting on him.
Here are the results (sorry for the plain formatting, looks nicer on the spreadsheet).
| Total | Average | Std Dev | ||
| Tuna | Forecast | 522.6 | 87.1 | |
| Actual | 618.0 | 103.0 | ||
| Variance | 95.4 | 15.9 | 11.6 | |
| Victor | Forecast | 452.6 | 75.4 | |
| Actual | 515.0 | 85.8 | ||
| Variance | 62.4 | 10.4 | 12.8 | |
| Justin | Forecast | 497.2 | 82.9 | |
| Actual | 519.0 | 86.5 | ||
| Variance | 21.8 | 3.6 | 18.3 | |
| Byron | Forecast | 427.7 | 71.3 | |
| Actual | 461.0 | 76.8 | ||
| Variance | 33.3 | 5.6 | 19.1 | |
| Kevin | Forecast | 491.4 | 81.9 | |
| Actual | 526.0 | 87.7 | ||
| Variance | 34.6 | 5.8 | 19.3 | |
| Hai | Forecast | 479.1 | 79.9 | |
| Actual | 462.0 | 77.0 | ||
| Variance | -17.1 | -2.9 | 14.6 | |
| Donny | Forecast | 465.0 | 77.5 | |
| Actual | 485.0 | 80.8 | ||
| Variance | 20.0 | 3.3 | 20.9 | |
| Vu | Forecast | 463.8 | 77.3 | |
| Actual | 445.0 | 74.2 | ||
| Variance | -18.8 | -3.1 | 31.7 | |
| Matt | Forecast | 467.1 | 77.8 | |
| Actual | 448.0 | 74.7 | ||
| Variance | -19.1 | -3.2 | 30.5 | |
| PJ | Forecast | 430.3 | 71.7 | |
| Actual | 390.0 | 65.0 | ||
| Variance | -40.3 | -6.7 | 21.7 |
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