Kylan Maloney had an assist to Steven Moodie who scored a goal to Put the Bearcats up 1-Nil. Dakota Coleman also had an assist to Josh Terry which put the Bearcats up 2-Nil. In this win Quincy Scott had 6 Saves which played a critical part in the Bearcat’s Win.
Boys Varsity Soccer ties in their first home game of the regular season vs. John Marshall in a great defensive match up. Quincy Scott had 6 saves in the tie.
End Result Forfeit.
The boys Bedford Varsity Soccer team won their game against Garfield Heights 8-0 scoring 5 goals in the first half and 3 in the second half. Collin Kennedy scored 1 and an assist, Sam Laffin scored 1, Steven Moodie scored 1 and had 2 assists, Daniel Spoto scored 1, Josh Terry scored 1, Daniel Romero scored 1 and Emiliano Cisneros scored 2. Quincy Scott played goalie in the first have and had 3 saves. Denim Whitted came in to play goalie the 2nd half and had 4 saves.
Bedford Bearcats Boys Varsity Soccer Beats Oberlin 3-1.
Quincy had 11 saves that kept us in the game along with a lot of help from Daniel Spoto and the rest of the Bearcat defense. Coming out of the half it was 0-0 and Oberlin made the first score off of a corner kick. The bearcats battled back and got a score from Kylan Maloney with a beautiful assist from Steven Moodie. Next the Bearcats got a score from Deshawn Mitchell to go up by 1. The bearcats would eventually go up by 2 with a score from Emiliano Cisneros credit the assist to Daniel Spoto.
Another great game by the defense led by Daniel Spoto and incredible goalie play by Quincy Scott. After falling behind 1-0 in the first half the Bearcats battle back as a team for the win with 1 goal by Dakota Coleman and 2 goals from Collin Kennedy.
The Bedford Seniors played their last varsity regular season soccer game against their conference rivals the Lorin Titans beating them 5-1. Freshman Denim W. had 7 saves at goalie. Emiliano Cisneros scored 1 goal on a header credit Quincy Scott with the assist.
Daniel Spoto scored on a shot that was about 50 yards out from the goal. Other goals were scored by the following: Billy Hemlinger 1goal, Damion Neal 1 goal, an Jamir Sullivan 1 goal.
From Dave Sebek - OSSCA Web Team and Statistic Lead
First off, we do not use any of those numbers for any sort of auto-ranking. In fact they are something that I used on my own personal site (www.highschoolsoccerohio.com) and the OSSCA guys ported over to their site when we combined data(bases).
I'll do my best to explain what they mean.
Pyth - is a teams pythagorean score E(Pts) - is the expected # of points a team should have (based on their Pythagorean score) D(Pts) - is the difference between the # of points they actually have and their expected points.
Some things to keep in mind for purposes of this discussion: Each game is an event worth 3 points. The total possible points a team can gain is 3 * the number of games played.
To calculate the pythagorean score, you need to know the following: Goals Scored by your team (GF) Goals Conceded by your team (GA)
To calculate the E(Pts) or expected points, take the total number of games played * 3 points/game * the Pythagorean score. Round to get a whole number. To calculate the D(Pts) take the actual points earned - E(Pts)
An example at this point may be helpful, and for that we'll look at my team, the Olentangy Braves to date, we are 4-2-2 and have scored 22 goals and given up 13 so our calculations are as follows POINTS = 14 (where points = 4 wins * 3 points/win + 2 ties * 1 point/tie = 14) GF = 22 GA = 13 PYTHAGOREAN = 0.7411 based on (22*22)/((22*22) + (13*13)) = 0.7411 E(Pts) = 18 based on 8 games * 3points/game * Pythagorean = 18 D(Pts) = -4 based on Actual Pts - E(Pts) = 14 - 18 = -4
What does it all mean? It means that based on their results, my team could be expected to "win" @74% of the points that they have played for. 74% of the points they've played for is @18. We have "won" 14 points for a difference of -4. The fun part is looking at why? In my case its pretty simple, our one win (8-0 over Big Walnut) skews are number pretty drastically.
What are the flaws or things to keep in mind?
1 - Every high school team is not created equal and every high school schedule is not created equal. If I have a good team and play in a good league/play a tough schedule, I'll most likely have a lower pythagorean score than a good team that plays in a weak league or plays a weak schedule.
2 - Incomplete results can definitely effect the pythagorean score (or your combined opponents pythagorean score)
3 - Scoring more goals and giving up less goals results in a higher pythagorean score. Period. Does that mean running up the score would result in a higher pythagorean score? in the long run, yes? in the short run a 1-0 win is the same as a 13-0 win. Both give a PYTH = 1.000. but as you can see from my results, add one 8-0 win over the course of a season and you can skew your pythagorean score.
How do I recommend you use that page? I look at two things, how a team has done and how their opponents have done. I believe that in addition to your pythagorean score, your opponents combined pythagorean scores should be displayed. Check out that number as well. In our case, our opponents Pythagorean score is 0.7560 and their Pythagorean score for their adjusted record (their combined record against everyone but me) is 0.8345.
So I would conclude that: we've done pretty well and we've done pretty well against good opponents.
Hope this helps. Feel free to respond to webmaster@ossca.org with followup questions and I'll answer as best I can.
