Winter '12 / '13 NEWxSFC - Interim Standings…after Storm #6					AVG SUMSQ				AVG STP					AVG Total Absolute				AVG Absolute				Mean RSQ
Previous Ranks	Rank	Forecaster	Class	Total STN 4casts	Error (")	Error Z	% MPRV over AVG	Rank	4cast (")	Error	Error Z	% MPRV over AVG	Rank	Error (")	Error Z	% MPRV over AVG	Rank	Error (")	Error Z	%MPRV over AVG	Rank	RSQ	RSQ Z	% MPRV over AVG	Rank	Forecaster
1,3,1	1	dryslot	Intern	95	301	-0.961	49%	2	127	21	-0.356	39%	6	51.5	-1.096	28%	4	2.2	-1.086	28%	4	80%	1.451	104%	2	dryslot
3,1,2	2	Brad Yehl	Journeyman	92	269	-0.873	56%	3	102	17	-0.634	53%	5	44.4	-1.012	36%	3	1.9	-1.147	37%	2	79%	1.112	31%	3	Brad Yehl
2,4,3	3	donsutherland1	Chief	93	208	-0.828	43%	3	80	14	-0.602	38%	5	48.0	-0.697	20%	4	2.0	-0.700	19%	4	63%	0.649	43%	4	donsutherland1
4,4,4	4	Donald Rosenfeld	Senior	93	219	-0.736	41%	3	85	6	-1.104	77%	2	46.4	-0.788	23%	3	2.0	-0.741	22%	3	57%	0.477	16%	5	Donald Rosenfeld
5,2,5	5	herb @maws	Senior	91	271	-0.688	50%	4	117	14	-0.390	36%	6	47.7	-0.583	22%	5	2.1	-0.586	21%	4	82%	0.694	14%	5	herb @maws
5,8,-	6	iralibov	Senior	98	245	-0.232	15%	5	135	17	-0.043	10%	6	53.1	0.074	-6%	6	2.2	-0.048	0%	6	65%	0.086	0%	6	iralibov
8,5,8	7	snocat918	Rookie	92	380	-0.210	11%	8	120	13	-0.521	45%	5	54.0	-0.209	7%	7	2.4	-0.187	5%	7	72%	0.187	10%	7	snocat918
7,9,6	8	Roger Smith	Senior	97	440	-0.193	6%	6	135	24	-0.199	14%	6	65.5	-0.214	1%	6	2.7	-0.321	4%	6	53%	-0.066	-14%	6	Roger Smith
12,7,7	9	weatherT	Senior	95	595	-0.040	10%	8	123	29	-0.254	19%	7	74.7	-0.073	3%	8	3.1	-0.134	4%	8	46%	-0.659	-33%	11	weatherT
8,-,-	10	Mitchel Volk	Senior	91	619	0.091	2%	9	149	35	0.506	-24%	9	82.8	0.350	-5%	10	3.6	0.462	-9%	11	59%	0.130	-6%	6	Mitchel Volk
10,-,-	11	snowman	Senior	96	643	0.114	9%	9	130	26	-0.069	22%	8	79.9	0.025	2%	8	3.4	0.001	3%	8	51%	-0.616	-30%	10	snowman
13,10,9	12	TQ	Senior	94	364	0.166	-11%	8	91	29	0.266	-27%	8	63.4	0.311	-7%	9	2.7	0.306	-8%	9	48%	-0.199	-11%	8	TQ
14,11,10	13	quagmireweathercentral	Rookie	92	396	0.813	-36%	11	95	22	-0.241	6%	6	65.7	1.016	-26%	11	2.8	1.167	-31%	11	35%	-0.789	-47%	8	quagmireweathercentral

There have been six (6) snowstorm forecasting Contests…as of 19-MAR-13. Under the ‘two-thirds’ rule…forecasters who have entered at least four (4) forecasts are included in this interim summary.

To qualify for ranking in the Interim and final ‘End-of-Season’ standings…a forecaster must enter at least two-thirds of all Contests.  If a forecaster has made more than enough forecasts to qualify for ranking…only the lowest SUMSQ Z-scores necessary to qualify are used in the computing the average.  IOW…if you made nine forecasts…only your six best SUMSQ Z-scores are used to evaluate your season-to-date performance.  You can think of it as dropping the worse quiz score before your final grade is determined.  The reason we have this rule is to 1) make it possible to miss entering a forecast or two throughout the season and still be eligible for Interim and ‘End-of Season’ ranking and 2) encourage forecasters to take on difficult and/or late-season storms without fear about how a bad forecast might degrade their overall 'season-to-date' performance score(s).

The mean normalized ‘SUMSQ error’ is the Contest/s primary measure of forecaster performance.  This metric measures how well the forecaster/s expected snowfall 'distribution and magnitude' for _all_ forecast stations captured the 'distribution and magnitude' of _all_ observed snowfall amounts.  A forecaster with a lower average SUMSQ Z Score has made more skillful forecasts than a forecaster with higher average SUMSQ Z Score.

The 'Storm Total Precipitation error’ statistic is the absolute arithmetic difference between a forecaster/s sum-total snowfall for all stations and the observed sum-total snowfall. This metric…by itself…is not a meaningful measure of skill…but can provide additional insight of forecaster bias.

The 'Total Absolute error' statistic is the average of your forecast errors regardless of whether you over-forecast or under-forecast. This metric measures the magnitude of your errors.

The 'Average Absolute Error' is the forecaster/s ‘Total Absolute Error’ divided by the number of stations where snow was forecast or observed.

The ‘RSQ error’ statistic is a measure of the how well the forecast captured the variability of the observed snowfall. Combined with the SUMSQ error statistic…RSQ provides added information about how strong the forecaster/s ‘model’ performed.