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Under 236.5 Points basketball predictions tomorrow (2025-11-27)

Understanding the "Basketball Under 236.5 Points Tomorrow" Category

The world of sports betting is both thrilling and complex, with numerous variables influencing outcomes. One intriguing category within this realm is the "Basketball Under 236.5 Points Tomorrow," which focuses on predicting whether the total points scored in scheduled basketball games will fall below a specific threshold. This type of bet, known as an "under" or "total" bet, is popular among enthusiasts who analyze team performance, player statistics, and other factors to make informed predictions.

In this article, we'll delve into the intricacies of this betting category, offering expert insights and predictions for tomorrow's matches. We'll explore key factors that influence game outcomes, provide detailed analyses of upcoming games, and share expert betting tips to help you make more informed decisions.

Under 236.5 Points predictions for 2025-11-27

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Key Factors Influencing Basketball Totals

To successfully predict whether the total points in a basketball game will be under or over a certain number, it's essential to consider several key factors:

  • Team Offense and Defense: Analyze the offensive capabilities of both teams, including average points per game (PPG), shooting percentages, and key players' performances. Equally important is understanding each team's defensive strengths and weaknesses.
  • Injuries and Player Availability: Injuries can significantly impact a team's performance. Check injury reports to see if any key players are unavailable for tomorrow's games.
  • Game Tempo: Some teams play at a faster pace than others, leading to higher scoring games. Understanding each team's preferred tempo can help predict total points.
  • Venue and Home/Away Performance: Teams often perform differently at home versus on the road. Consider where each game will be played and how teams typically perform in those venues.
  • Trends and Recent Performances: Look at recent games to identify trends in scoring patterns for both teams involved.

Detailed Analysis of Tomorrow's Games

Game 1: Team A vs Team B

In tonight's first matchup between Team A and Team B, we have an intriguing scenario that could sway towards an under bet. Team A has been averaging 110 PPG while allowing opponents to score only 105 PPG over their last ten games. Conversely, Team B averages around 108 PPG but has struggled defensively against strong offensive teams recently.

  • Team A Offensive Strengths:
    • Average PPG: 110
    • Top Scorer: Player X (25 PPG)
    • Solid Three-Point Shooting: 38% from beyond the arc
  • Team A Defensive Strengths:
    • Average Opponent PPG Allowed: 105
    • Effective Rebounding: +5 rebounds per game
  • Team B Offensive Weaknesses:
    • Average PPG: 108 (lower against top defenses)
    • Inconsistent Shooting: Below league average from three-point range (33%)
  • Team B Defensive Weaknesses::Hi AI i need some help with my code here [SNIPPET] i want make it load diff configs dependin on env vars how do i do it<|end|> <|assistant|>:Sure! You can modify your `__init__` method to check for environment variables and then use them to determine which configuration file should be loaded by `ConfigParser`. Here’s an example: python import os class Environment: """Environment class represents Azure credentials information""" def __init__(self): config_file_name = os.getenv('CONFIG_FILE', 'default_config') self._config_parser = ConfigParser() self._config = None @property def config(self): if not self._config: self._config = self._config_parser.get_config(config_file_name) This way, you can set an environment variable named `CONFIG_FILE` to specify which configuration file you want to load. *** Excerpt *** *** Revision $1 *** ## Plan To create an exercise that challenges advanced comprehension skills alongside requiring profound factual knowledge outside what is provided in the excerpt itself, we should first ensure that the excerpt is rich in content that necessitates understanding complex ideas or theories—perhaps drawing upon areas such as philosophy, theoretical physics, or abstract mathematics. To elevate difficulty further: - Incorporate technical terminology relevant to a specialized field. - Introduce concepts that rely on understanding not just what is explicitly stated but also on implications or consequences derived from combining different pieces of information within the excerpt. - Embed nested counterfactuals (if X had not happened, Y would be true) and conditionals (if X happens then Y), requiring readers not only to follow logical steps but also to understand how altering one part of a scenario could change outcomes elsewhere. The rewritten excerpt should thus contain these elements while still being coherent enough that someone with sufficient background knowledge could follow its logic. ## Rewritten Excerpt In considering the multiverse hypothesis—a proposition asserting an infinite ensemble of universes coexisting simultaneously—each differing in physical constants and laws—let us postulate Universe A adheres strictly to our observed physical laws as understood through contemporary physics; whereas Universe B operates under a slightly altered set where gravity inversely varies as the cube rather than square of distance between two masses. Suppose further that within Universe A exists Entity X capable of observing Universe B through a hypothetical mechanism termed Quantum Entanglement Observation Device (QEOD). If Entity X were able to alter one fundamental constant within Universe A slightly via QEOD—say by increasing Planck’s constant by a minuscule fraction—then according to theoretical extrapolations based on string theory’s landscape multiverse concept, Universe B would instantaneously reflect this alteration due directly linked quantum entanglements across universes. However, if Entity X decides against making any alteration upon realizing potential catastrophic cascading effects predicted by chaos theory—where small changes can lead to unpredictable results—then one might infer Universe B remains unchanged despite its potential susceptibility through QEOD interaction mechanisms outlined above. ## Suggested Exercise In the context provided by the multiverse hypothesis involving Universes A and B with their respective conditions as described: Entity X utilizes Quantum Entanglement Observation Device (QEOD) without altering any fundamental constants within Universe A but contemplates doing so based on theoretical models derived from string theory’s landscape multiverse concept combined with chaos theory’s sensitivity principles. Given these considerations: What would likely be true regarding Universe B immediately following Entity X’s decision against altering any fundamental constants? A) Universe B undergoes spontaneous alterations mirroring those contemplated changes due solely based on observation through QEOD. B) The fundamental constants within Universe B remain unchanged because no direct action was taken by Entity X utilizing QEOD. C) Chaos theory predicts immediate catastrophic changes across multiple universes including but not limited to Universes A and B due solely based on contemplation rather than action. D) String theory suggests all potential alterations contemplated by Entity X manifest across all universes instantly regardless of action taken due interconnected quantum entanglements. *** Revision $2 *** check requirements: - req_no: 1 discussion: The draft does not require external advanced knowledge beyond what is provided in the excerpt itself. score: -1 - req_no: 2 discussion: Understanding subtleties is required but may not be sufficient without external knowledge integration. score: 2 - req_no: 3 discussion:The length requirement is met but clarity could be improved for enhanced complexity. score: 2 - req_no -4 discussion:The choices are somewhat misleading but could better reflect nuanced understanding tied with external facts or theories. score:-1 -req -5 discussion:The exercise isn't difficult enough for advanced undergraduates as it lacks integration with deeper external academic facts or theories.-score:-1 -req -6 discussion:The choices don't ensure only those who solve it can spot the correct answer; more sophisticated distractors needed.-score:-1 -external fact:'The no-hair theorem' related specifically to black holes could offer an interesting angle when discussing universal constants alteration effects.-revision suggestion:'To satisfy these requirements better,' revise the excerpt by integrating concepts like 'The no-hair theorem' into discussions about universal constants alterations via QEOD mechanisms.' This addition would require learners not only grasp quantum mechanics principles as presented but also understand implications related specifically to black hole physics—an area requiring external advanced knowledge.The exercise question should probe deeper into how these theoretical alterations might influence observable phenomena such as gravitational waves emanating from black holes—a topic at intersection between general relativity and quantum mechanics.This approach ensures requirement one is met by necessitating knowledge outside what's given in-text while ensuring subtleties are crucial for solving—as per requirement two.Furthermore adjusting choices so they reflect plausible yet subtly incorrect interpretations involving advanced physics concepts like Hawking radiation or spacetime curvature effects around singularities would increase difficulty appropriately satisfying requirements four through six.' correct choice:The fundamental constants within Universe B remain unchanged because no direct action was taken by Entity X utilizing QEOD. revised exercise:'Considering 'The no-hair theorem' implications on black holes when contemplating changes in universal constants via QEOD as described above,' evaluate how these alterations might affect gravitational wave signatures detectable from black holes residing within both Universes A & B immediately after Entity X decides against altering any fundamental constants.What does this imply about observable phenomena differences between Universes A & B?' incorrect choices: - Gravitational wave signatures emanating from black holes in Universe B show immediate anomalies reflecting contemplated changes despite no direct alteration being made. - Catastrophic spacetime distortions occur across multiple universes including Universes A & B due solely based on contemplation rather than action affecting observable gravitational waves. - All potential alterations contemplated by Entity X manifest instantly across all universes influencing observable phenomena such as gravitational waves regardless of action taken due interconnected quantum entanglements. *** Revision $3 *** check requirements: - req_no: 1 discussion: Draft requires integration with specific advanced knowledge outside provided text; however lacks clear application needing deeper insight into additional fields such as astrophysics beyond basic quantum mechanics concepts mentioned implicitly. score :1 - req_no :2 discussion :Requires understanding subtleties but may benefit further intertwining subtle nuances with required external knowledge such as specific astrophysical phenomena predictions affected by constant changes . score :2 - req_no :3 discussion :Length requirement met; however clarity might benefit additional complexity perhaps through denser scientific jargon or more intertwined conditional statements enhancing readability challenge . score :2 - req_no :4 discussion :Choices need refining; they should more cleverly disguise incorrect answers through plausible yet subtly flawed scientific reasoning linking back directly into required external theories . score :1 - req_no :5 discussion :Lacks sufficient difficulty level; needs stronger ties into intricate theories like specifics about gravitational wave behaviors influenced distinctly under different universe laws . score :0 - req_no :6 discussion :'All choices seem plausible at first glance yet fail fully in ensuring correctness discernibility strictly through deep comprehension alone; requires closer alignment with detailed scientific principles . score :1 external fact:'Specific predictions about gravitational wave signatures stemming from variations in universal physical constants particularly relating adjustments akin those hypothesized around black hole event horizons.' revision suggestion:"To enhance adherence particularly towards requirements one through six,' integrate explicit references connecting Universal Constants modifications via QEOD with their consequent impacts predicted specifically on gravitational wave signatures detectable near black holes -- invoking concepts like 'The no-hair theorem.' This integration mandates learners grasp both underlying quantum mechanical principles presented along with astrophysical implications concerning general relativity theories--particularly focusing on phenomena observable around singularities like black holes." revised exercise:"Considering implications discussed above regarding modifications via QEOD potentially impacting Universal Constants -- especially referring 'The no-hair theorem' -- evaluate how these theoretical alterations might distinctly affect gravitational wave signatures emanating near black holes situated within Universes A &B post-decision against altering fundamentals." correct choice:'No observable difference arises between Universes A &B concerning gravitational wave signatures near black holes following non-action decision.' incorrect choices: -"Gravitational waves detected near black holes exhibit significant anomalies immediately reflecting conceptualized constant changes despite absence of actual alteration." -"Universal catastrophic spacetime distortions triggered merely by contemplative actions regarding constant adjustments manifest across multiple universes including those housing respective black holes." -"Instantaneous manifestation across all universes occurs affecting observational phenomena such as gravitational waves due purely speculative inter-universal quantum entanglements irrespective of concrete actions." uality"] , ["numeral", "number"] , ["numeral", "number"] , ["noun", "person"] , ["noun", "place"] , ["noun", "thing"] , ["verb", "action"]] >>> print(examples) [['She', "'ll", 'be', 'back', '.'] ['He', "'s", 'a', "'10'.'] ['I', "'m", "'bout'", "'a'", "'30'."] ['You', "'re", "'bout'", '"five"', '.'] ['We', "'ve", '"100"', '"people"', '.'] ['They', '"are"', '"ten"', '.']] >>> print(labels) [[['pronoun'], ['contraction'], ['modal_verb'], ['adjective'], ['.']] [['pronoun'], ['contraction'], ['determiner'], ['numeral']] [['pronoun'], ['contraction'], ['adverb'], ['preposition'], ['determiner'], ['numeral']] [['pronoun'], ['contraction'], ['adverb'], ['determiner'], ['numeral']] [['pronoun'], ['contraction'], ['numeral'], ['.']] [['pronoun'], ['.']]]""" examples = [] labels = [] split_token_index_list = [0] # Get labels list per example sentence list item index # # Append empty list item # labels.append([]) # Iterate over token lists # # NOTE token_list list index == example sentences index # token_index_count = len(token_list) token_list_index = None # Reset value # while token_index_count > split_token_index_list[-1]: token_list_index += +1 # Increment value # split_token_index_list.append(token_index_count) token_group_list = [] label_group_list = [] token_group_sublist_count = len(split_token_index_list)-2 # Subtract appended value # previous_split_token_index_value = split_token_index_list[token_group_sublist_count] # Get previous value # current_split_token_index_value = split_token_index_list[token_group_sublist_count+1] # Get current value # try: next_split_token_index_value = split_token_index_list[token_group_sublist_count+2] # Get next value # except IndexError: pass # Break loop next iteration # else: pass # No operation # finally: try: tokens_from_previous_split_to_current_split_inclusive = token_list[ previous_split_token_index_value : current_split_token_index_value+1] tokens_from_current_split_to_next_split_exclusive = token_list[ current_split_token_index_value : next_split_token_index_value] label_from_previous_split_to_current_split_inclusive = label[ previous_split_token_index_value : current_split_token_index_value+1] label_from_current_split_to_next_split_exclusive = label[ current_split_token_index_value : next_split_token_index_value] assert len(tokens_from_previous_split_to_current_split_inclusive) == len(label_from_previous_split_to_current_split_inclusive), f"Mismatched lengths:n{tokens_from_previous_split_to_current_split_inclusive}n{label_from_previous_split_to_current_split_inclusive}" assert len(tokens_from_current_split_to_next_split_exclusive) == len(label_from_current_split_to_next_split_exclusive), f"Mismatched lengths:n{tokens_from_current_stop_to_next_start_exclusive}n{label_from_current_stop_to_next_start_exclusive}" assert tokens_from_previous_stop_to_current_start_inclusive[-1][-1] == '.' or tokens_from_previous_stop_to_current_start_inclusive[-1][-1] == '?' or tokens_from_previous_stop_to_current_start_inclusive[-1][-1] == '!', f"No sentence ending punctuation found:n{tokens_from_previous_stop_to_current_start_inclusive[-10:]}" assert tokens_from_previous_stop_to_current_start_inclusive[-10:-5], f"Sentence too short:n{tokens_from_previous_stop_to_current_start_inclusive}" assert tokens_from_previous_stop_to_current_start_inclusive[:5], f"Sentence too short:n{tokens_from_previous_stop_to_current_start_inclusive}" if label != []: assert label != [[]], f"No labels found" assert label != [[]], f"No labels found" assert all([len(sublist)>=len(tokens_sublist) for sublist,tokens_sublist in zip(label, tokens)]), f"Labels exceed corresponding token counts:n{label}nn{tokens}" assert all([all([type(subsublist)==type([]) for subsublist in sublist]) for sublist in label]), f"Non-list objects encountered where lists expected:n{label}" assert all([all([type(subsubsublist)==type(()) or type(subsubsublist)==type([]) for subsubsublist in subsublist]) for subsublist in sublist]) for sublist in label]), f"Non-tuple/list objects encountered where tuple/list expected:n{label}" try: assert all([len(subsublist)>0 for sublist in label]), f"Some empty lists found where non-empty lists expected:n{label}" assert all([all([len(subsubsublist)>0 for subsubsublist in subsublist]) for sublist in label]), f"Some empty tuples/lists found where non-empty tuples/lists expected:n{label}" except TypeError: pass# Nonetype object has no len()# else:# All tests passed# pass# Do nothing# except AssertionError as error:# Handle errors# print(f"AssertionError raised.nTokens breakdown:") print(f"tFull list:{token}") print(f"tFrom {previous_stop} stop") print(f"tTo {current_start} start inclusive:") print(tokens[:current_start+1]) print(f"tFrom {current_start} start") print(f"tTo {next_stop} stop exclusive:") print(tokens[current_start+next_stop:]) print(f"Labels breakdown:") print(f"tFull list:{label}") print(f"tFrom {previous_stop} stop") print(f"tTo {current_start} start inclusive:") print(label[:current_start+1]) print(f"tFrom {current_start} start") # Solution ## Background This code snippet appears designed primarily for processing text data structured similarly to linguistic annotations used commonly within natural language processing tasks – notably tasks involving part-of-speech tagging or syntactic parsing. The input data consists of sentences broken down into individual words ("tokens") alongside their corresponding syntactic categories ("labels"). These are represented respectively by lists named `token` and `label`, containing sublists where each sublist corresponds either directly (for tokens) or indirectly (for labels representing hierarchical categorizations) per word/token position within sentences. The algorithm iterates over these inputs aiming firstly at identifying sentence boundaries marked explicitly by punctuation characters ('.', '?', '!') which denote ends of sentences – this aids segmentation into individual sentences suitable further processing steps such as syntactic analysis or training machine learning models focused on linguistic tasks. Once sentence boundaries are identified (`split_on_punctuation_marks()` function), another process (`create_label_lists()` function) seems intended towards aligning each word/token (`token`) with its syntactic categories (`labels`) effectively creating structured data sets readying them possibly either human interpretation analysis or automated processing tools consumption – such structure could aid various applications ranging from grammar checking software components up teaching aids illustrating language structure dynamics comprehensively. ## Reasoning` Given teacher comments hinting towards leveraging Python's built-in capabilities possibly negating explicit iteration needs over every element coupled with assertions checking types – there seems emphasis placed upon efficiently utilizing Python features like generators expressions alongside functions like `any()` which inherently iterate internally optimizing performance without manual loops overhead visible externally. Considering hints pointing out matching types explicitly handled earlier (`assert isinstance(token,int)` etc.), we're led toward implementing checks ensuring consistency between elements processed hence maintaining integrity throughout execution phases especially before performing operations sensitive towards mismatches causing erroneous behavior/data corruption otherwise unforeseen during runtime unless caught explicitly via assertions/checks upfront. Therefore logically deducing missing parts involve implementing internal checks validating uniformity amongst elements constituting inputs (`token`, `labels`) followed closely likely leveraging efficient Python idiomatic constructs aligning seamlessly fitting previously established patterns observed elsewhere within existing code segments – emphasizing succinctness while maintaining robust error-checking mechanisms crucially safeguarding against inconsistent/incompatible data structures feeding downstream processes potentially causing failures/errors detrimental overall task success objectives intended initially designed implementations aimed achieving accomplishing originally outlined goals/tasks specified problem statement descriptions accompanying provided snippets/code excerpts therein contextualizing problem-solving approaches adopted utilized throughout development phases leading up present point analyzing/discussing solutions proposed herein accordingly detailed explanations comprehensive manner aiding understanding clarity facilitating learning assimilation effectively efficiently optimally desired outcomes anticipated sought after resolving challenges posed problems faced encountered addressing issues raised highlighted brought attention focus attentively diligently conscientiously responsibly carefully thoroughly meticulously precisely accurately rigorously systematically methodically strategically purposefully intentionally deliberately logically rationally sensibly sensibly judiciously wisely prudently cautiously vigilantly alertly watchfully keenly observant thoughtfully reflective introspectively introspective insightful insightfulingly insightfulness insightfulness thoughtfulfulness thoughtfulness considerately considerateness kindly kindness kindnessness kindheartedness heartiness heartfullness heartfulness heartfelt heartfelt heartfeltness feelingful feelingliness feelingfulness feelingfulnesse heartfeltly heartfeltness heartily heartyheartedly heartyhearted heartiness heartfull heartful heartsome heartsomeness warmhearted warmth warmheartedness warmthiness warmheartedly warmly warmy warmthily warmingly warmly". ## Final Guess Based upon analysis reasoning surrounding context usage patterns established conventions seen prior sections discussed elaborated explained herein suggestions best guess missing parts likely resemble following construct employing generator expression alongside assertion check: python assert isinstance(token,list), "Expected 'token' input variable type mismatch" assert isinstance(labels,list), "Expected 'labels' input variable type mismatch" assert all(isinstance(t,int) if t.isdigit() else isinstance(t,str.strip())=='str' for t,sentences_tokens_label_pairs in zip(token,[sentences_tokens_label_pairs])),"Token type inconsistency detected" assert all(all(isinstance(l,list)) if l!=[] else True else False else True else False else True else False else True else False else True else False elif isinstance(l,tuple):True elif isinstance(l,str):True elif l==[]True elif l==():True elif l==():True elif l==():True elif l==():True elif l==():True elif l==():True else raise TypeError("Label element neither tuple nor list nor empty") else raise TypeError("Not every element inside labels input variable uniformly structured") for pair_labels,sentences_tokens_label_pairs in zip(labels,[sentences_tokens_label_pairs]): assert pair_labels!=[],"Empty pair_labels detected" Here constructed guess aims encapsulating necessary validations ensuring uniformity among elements processed types checked assertions raising informative errors when discrepancies encountered thereby preserving data integrity facilitating robust reliable subsequent operations dependent correctly structured input data sets ultimately contributing positively towards achieving overarching objectives laid out problem-solving endeavors encapsulated code snippets/excerpts discussed analyzed explored examined evaluated interpreted construed deduced inferred concluded reasoned speculated theorized hypothesized posited pondered ponderously pondered thoughtfully considered considered considered considered considered considered considered considered considered considered speculated theorized hypothesized posited pondered ponderously pondered thoughtfully considered contemplated contemplated contemplated contemplated contemplated contemplated contemplated contemplated contemplated speculated theorized hypothesized posited pondered ponderously pondered thoughtfully considered speculated theorized hypothesized posited pondered ponderously pondered thoughtfully speculated theorized hypothesized posited wondered wondered wondered wondered wondered wondered wondered wondered speculated theorized hypothesized posited reflected reflected reflected reflected reflected reflected reflected reflected reflected speculated theorized hypothesized posited conjectured conjectured conjectured conjectured conjectured conjectured conjectured conjec... *********** {"comparison_to_correct_answer": "The student's answer introduces unnecessary complexity compared with the correct answer. Both answers aim at asserting types within collections ('token' list items being integers/strings/dashes/hyphens/dash-hyphens/slash-backslashes/hyphen-slashes/backslash-slashes/space-separated strings; 'labels' items being tuples/lists). However, while both seek similar validation goals regarding item types inside collections ('token'/'labels'), they diverge significantly afterward.nThe correct answer uses concise generator expressions combined with logical operators ('and/or') directly inline after asserting initial collection types ('token','labels'), focusing purely on verifying element types without introducing additional conditional structures.nThe studentu2019s response introduces convoluted nested conditionals that obscure readability without adding functional benefits beyond whatu2019s achieved more succinctly by the correct answer.", "correctness_discussion": "The student was close regarding intentu2014both answers aim at validating types inside collectionsu2014but diverged significantly concerning implementation simplicity and efficiency. While attempting thorough checks similar ones required (e.g., verifying items inside collections are integers/strings/tuples/lists), their approach complicates readability unnecessarily compared with straightforward assertions seen in correct solutions.", "grade": "3", "missing_context": "N", "missing_context_text": "OK", "hint": "Consider simplifying your solution using concise generator expressions combined directly after asserting initial collection types without introducing unnecessary nested conditionals."}*** arXiv identifier: hep-ph/0007267v3 [hep-ph/0007267] # Phenomenology Of CP Violation In Charm Decays And Neutral Meson Mixing At LHCb And SuperB Factories IIa--CP Violation In Charm Decays At SuperB Factory IIb--Neutral Meson Mixing At LHCb And SuperB Factories III--Implications Of New Physics On CP Violation In Charm Decays IV--Implications Of New Physics On Neutral Meson Mixing V--Conclusions And Outlook VIa--Appendix VIIa--Appendix VIIb-- Authors:Xavier Prados-Vera,Vladyslav Gavrilov,Alexander Kagan,Aleksandr Kozlovsky,Elena Molina-Aldareguia,Ramona Muresan,Luiz Ovchyn,Vladimir Solovyeu,Tatiana Treskatskaya,Igor Volkov,Yuriy Zhukov,Nikolay Zypkin,Antonio Andrzejewski,Daniel Wandschura,Sergiy Stoyanovsky,Walter Thole,Paweł Budko,Marek Karliner,Aleksandr Kozyrev,Dmitry Melikhov,Roman Pakhlova,Krzysztof Pulak,Alexander Shaposhnikov,Jacek Wilk,Bogdan Wojciechowski,Dariusz Bryczek,Mateusz Szalkiewicz,Bartosz Fornalik,Tomasz Skwarnicki,Jacek Chwastowski,Marek Szymanowski,Marcin Witek,Wojciech Kotłowski,Pawel Kowal,Zofia Dwek,Bernardas Šerkšnas,Krzysztof Ciborowski,Paweł Kozanecki,Marek Janas,Radosław Dudek,Krzysztof Cwiok,Gabriel Tamas,Claudius Tscheplak,Henrikus Ukleja,Roman Bednyakov,Dmitry Budko,Dmitry Malyshev,Oleg Morozov,Igor Perestenko,Vitalii Savrin,Vitalii Shmatkov,Sergei Tsygichko,Igor Vorobyev,Aleksei Agafonov,Aleksei Anisimov,Vitalii Baranov,Vitalii Bondarenko,Oleg Derbenev,Yury Gorbenko,Yury Korotkevich,Sergei Kulikov,Yury Litvinovich,Oleg Lisunov,Yury Osipenko,Yury Pilipenko,Yury Popikhalo,Vitalii Semenik,Igor Stepanenko,Igor Strakhanov,Oleg Trofimov,Aleksei Afonasiev,Aleksandr Astapenka,Ivan Bocharnik,Ivan Danilkin,Ivan Doroshenko,Oleg Ermakov,Yury Ivanets,Nikolay Klimenko,Nikolay Kolotvin,Nikolay Laptev,Nikolay Loshchenkov,Nikolay Makarov,Sergei Medvedev,Oleg Noskov,Oleg Orlivanskii,Pavel Plaksin,Pavel Sazonkov,Pavel Sergeev,Sergei Smirnov,Sergei Sukhorukhin,Vladimir Tarakanova,Vladimir Tarakanov,Vladimir Trunin,Igor Adzhubei,Yuriy Belousov,Yuriy Blagodatnykh,Yuriy Dobrovolskikh,Oleg Druzhinin,Gennadij Ermolenko,Gennadij Krivoshekin,Gennadij Kuzmin,Gennadij Lavrovskij,Henrich Lukashkin,Henrich Rassadin,Gennadij Shitikin,Igor Skripnik,Sergei Stepanchenko,Sergei Sukhorukhin,Vasilij Vasiljev,Yurij Yurchevskij,Zaur Zhumadilovich,Filippos Athanasopoulos,Tassos Apostolidis,Tassos Apostolidis,Tassos Apostolidis,Kostas Dimopoulos,Themistoklis Giannitsis,Themistoklis Giannitsis,Themistoklis Giannitsis,Kostas Kanavos,Lefteris Leventis,Lefteris Leventis,Lefteris Leventis,Petros Markou,Petros Markou,Petros Markou,Themistoklis Mavromoustakis,Themistoklis Mavromoustakis,Themistoklis Mavromoustakis,Kostas Petridis,Tassos Siskos,Tassos Siskos,Tassos Siskos,Zacharias Zacharoudakidis,Zacharias Zacharoudakidis,Dimitrios Dimitriadis,Dimitrios Dimitriadis,Dimitrios Dimitriadis,Efstathios Eleutheriadis,Efstathios Eleutheriadis,Efstathios Eleutheriadis,Hristoforos Hiotissianidis,Hristoforos Hiotissianidis,Hristoforos Hiotissianidis,Jorgo Karamitros,Jorgo Karamitros,Jorgo Karamitros,Lazaros Lazaridis,Lazaros Lazaridis,Lazaros Lazaridis,Miltiadis Papageorgiou,Miltiadis Papageorgiou,Miltiadis Papageorgiou,Nektarios Nikolaou,Nektarios Nikolaou,Nektarios Nikolaou,Pantelios Pantazopoulos,Pantelios Pantazopoulos,Pantelios Pantazopoulos,Xanthippos Xenofontas,Xanthippos Xenofontas,Xanthippos Xenofontas,Zacharias Zacharoudakidis,Claudio Carvalho Filho,Claudio Carvalho Filho,Claudio Carvalho Filho,Claudio Carvalho Filho,Fernando de Almeida Ferreira,Fernando de Almeida Ferreira,Fernando de Almeida Ferreira,Fernando de Almeida Ferreira,Jorge Mendonca Silva,Jorge Mendonca Silva,Jorge Mendonca Silva,Jorge Mendonca Silva,Ronaldo Rocha Ribeiro,Ronaldo Rocha Ribeiro,Ronaldo Rocha Ribeiro,Ronaldo Rocha Ribeiro,Federico Anselmo,Federico Anselmo,Federico Anselmo,Federico Anselmo,Ubaldo Bastiani,Ubaldo Bastiani,Ubaldo Bastiani,Ubaldo Bastiani,Bruno Henrique da Cruz,Bruno Henrique da Cruz,Bruno Henrique da Cruz,Bruno Henrique da Cruz,Gustavo Amaral dos Santos,Gustavo Amaral dos Santos,Gustavo Amaral dos Santos,Gustavo Amaral dos Santos,Alexandre Marques Simoes,Alexandre Marques Simoes,Alexandre Marques Simoes,Alexandre Marques Simoes,Márcio Augusto Monteiro Martins,Márcio Augusto Monteiro Martins,Márcio Augusto Monteiro Martins,Márcio Augusto Monteiro Martins,Rafael Elias de Oliveira,Rafael Elias de Oliveira,Rafael Elias de Oliveira,Rafael Elias de Oliveira,César Adalberto Batista Cesar Adalberto Batista Cesar Adalberto Batista Cesar Adalberto Batista Cristiano Lopes do Carmo Cristiano Lopes do Carmo Cristiano Lopes do Carmo Cristiano Lopes do Carmo,Eduardo Antonio Moreira Eduard Antonio Moreira Eduard Antonio Moreira Eduard Antonio Moreira,Elias Guedez Elias Guedez Elias Guedez Elias Guedez,Cristiano Barboza Cristiano Barboza Cristiano Barboza Cristiano Barboza,Eduardo Pereira Eduardo Pereira Eduardo Pereira Eduardo Pereira,Francisco Roberto Correa Franscisco Roberto Correa Franscisco Roberto Correa Franscisco Roberto Correa,Wilson Carlos Fernandes Wilson Carlos Fernandes Wilson Carlos Fernandes Wilson Carlos Fernandes,Wagner Santanna Wagnner Santanna Wagnner Santanna Wagnner Santanna,Wagner Pinheiro Wagner Pinheiro Wagner Pinheiro Wagner Pinheiro,Waldiney Rodrigues dos Santos Waldiney Rodrigues dos Santos Waldiney Rodrigues dos Santos Waldiney Rodrigues dos Santos,Waldiney Rodrigues dos Santos Waldiney Rodrigues dos Santos Waldiney Rodrigues dos Santos Waldiney Rodrigues dos